Article

A Comparison of ligand based virtual screening methods and application to corticotropin releasing factor 1 receptor

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

Ligand based virtual screening approaches were applied to the CRF1 receptor. We compared ECFP6 fingerprints, FTrees, Topomers, Cresset FieldScreen, ROCS OpenEye shape Tanimoto, OpenEye combo-score and OpenEye electrostatics. The 3D methods OpenEye Shape Tanimoto, combo-score and Topomers performed the best at separating actives from inactives in retrospective experiments. By virtue of their higher enrichment the same methods identified more active scaffolds. However, amongst a given number of active compounds the Cresset and OpenEye electrostatic methods contained more scaffolds and returned ranked compounds with greater diversity. A selection of the methods were employed to recommend compounds for screening in a prospective experiment. New CRF1 actives antagonists were found. The new actives contained different underlying chemical architecture to the query molecules, results indicative of successful scaffold-hopping.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... Contrary to what happens when VS is applied to select the most similar compounds in shape or pharmacophore properties, where the tools base their predictions on scoring functions that measure these particular features, 7,13,14 the predictions in this field are not exclusively based on this descriptor, but on both the similarity of the three dimensional shape and electrostatic similarity. [15][16][17][18][19][20][21][22][23][24][25][26][27] Broadly speaking, all the previous works follow the same methodology, although they may differ in the selection procedure used to determine the compounds proposed as best predictions. Essentially, they initially optimize the compounds in the database against the query in terms of shape by using ROCS, 28 they prioritize the top N compounds with the highest shape similarity values and then evaluate them in terms of electrostatic similarity. ...
... The ZAP Toolkit has been widely used in the literature to calculate the electrostatic similarity score for two compounds. 2,[15][16][17][18][19][20][21][22][23][24][25][26][27]50 In this subsection we would like to remark that the ZAP Toolkit can return an erroneous value, which was discovered when using Optipharm. During the optimization procedure, Optipharm can progressively separate two input compounds aimed to escape from local optima and explore the searching space in depth. ...
Preprint
Full-text available
div>Ligand Based Virtual Screening (LBVS) methods are widely used in drug discovery as filters for subsequent in-vitro and in-vivo characterization. This means, increasing accuracy of LBVS approaches may have a huge impact on increasing chances of success. Since the databases processed in drug discovery campaigns are enormously large, this pre-selection process requires the use of fast and precise methodologies. The similarity between compounds can be measured using different descriptors such as shape, pharmacophore or electrostatic similarity. The latter is the goal of this work, i.e., we want to improve the process of obtaining the compounds most similar to a query in terms of electrostatic similarity. To do so, the current and widely proposed methodology in the literature is based on the use of ROCS to assess the similarity of compounds in terms of shape and then evaluate a small subset of them with ZAP for prioritization regarding electrostatic similarity. This paper proposes an alternative methodology that consists of directly optimizing electrostatic similarity and works with the entire database of compounds without using shape cut-offs. For this purpose, a new and improved version of the OptiPharm software has been developed. OptiPharm implements a parameterizable metaheuristic algorithm able to solve any optimization problems directly related to the involved molecular conformations. We show that our new method completely outperforms the classical proposal widely used in the literature. Accordingly, we are able to conclude that many of the compounds proposed with our novel approach could not be discovered with the classical one. As a result, this methodology opens up new horizons in Drug Discovery.</div
... VS applied to the electrostatic similarity of compounds is a clear example of this. Contrary to what happens when VS is applied to select the most similar compounds in shape or pharmacophore properties, where the tools base their predictions on scoring functions that measure these particular features (Lešnik et al., 2015;Puertas-Martín et al., 2019;Yan et al., 2013), the predictions in this field are not exclusively based on this descriptor, but on both the similarity of the three dimensional shape and electrostatic similarity (Tresadern et al., 2009;Chu and Gochin, 2013;Kim et al., 2015;Kossmann et al., 2016;Woodring et al., 2017;Maccari et al., 2011;Kim et al., 2016;López-Ramos and Perruccio, 2010;Hevener et al., 2012;Kaoud et al., 2012;Tiikkainen et al., 2009;Massarotti et al., 2014;Oyarzabal et al., 2009). ...
... The ZAP Toolkit has been widely used in the literature to calculate the electrostatic similarity score for two compounds (Boström et al., 2013;Tresadern et al., 2009;Chu and Gochin, 2013;Kim et al., 2015;Kossmann et al., 2016;Woodring et al., 2017;Maccari et al., 2011;Kim et al., 2016;López-Ramos and Perruccio, 2010;Hevener et al., 2012;Fig. 6. Compound DB01365 is printed green. ...
... Ligand-based virtual screening uses the information of known active ligand for prediction. It does not require the knowledge of target protein structure for screening [18]. The ligand-based tool known as LiSiCA was used to screen all 5 sets of ligands retrieved from the previous step. ...
Preprint
Full-text available
Background: Development of carbapenem resistance against Klebsiella pneumoniae is a situation of grave concern and require urgent attention. Among the KPC produced by K. pneumoniae, KPC-3 and KPC-15 play a major role in development of resistance to carbapenems. Materials and methods: KPC-2 structure was taken and then mutated to obtain the structure of KPC-3 and KPC-15. The binding sites of KPC-3 and KPC-15 were predicted by the COACH server. Drug like ligands from ZINC were then screened by ligand-based drug screening (LBVS) by keeping Relebactam as template. The top 50,000 selected ligands were then screened by structure based virtual screening (SBVS) using idock. The consensus weighted rank was computed for identifying ligands with dual inhibitory property. Relebactum was kept as a comparator for SBVS and the similarity search was conducted between the identified top 3 ligands against Relebactam. The ADMET properties were explored using admetSAR. Results: Based on consensus weighted ranks, top 3 ligands with dual inhibitory property are- ZINC76060350 (consensus weighted rank - 1.5), ZINC05528590 (2), ZINC72290395 (3.5). All the top 3 dual inhibitor have a good probability of passing through the blood brain barrier. The RDKit and Morgan fingerprint scores between Relebactam and top three ligands were 0.24, 0.22, 0.23 and 0.26, 0.19, 0.25 respectively (showing only 20% similarity). Therefore, the three identified ligands may independently be effective in inhibiting the activity of KPC-3 and KPC-15. Conclusion: The suggested ligands could be taken forward for the development of new drug against a multi-resistant- Klebsiella pneumoniae infections.
... The methodological part will focus on pre-screening, docking, and post-docking methods. While an extensive comparison of the various existing (ligand-based and structure-based) virtual screening methods is outside the scope of this review, we refer the reader to a few representative works on this topic [107][108][109][110]. ...
Article
Protein kinases are one of the most targeted protein families in current drug discovery pipelines. They are implicated in many oncological, inflammatory, CNS-related and other clinical indications. Virtual screening is a computational technique with a diverse set of available tools that has been shown many times to provide novel starting points for kinase-directed drug discovery. This review starts with a concise overview of the function, structural features and inhibitory mechanisms of protein kinases. In addition to briefly reviewing practical aspects of structure-based virtual screenings, we discuss several case studies to illustrate the state of the art in the virtual screening for type I, type II, allosteric (type III-V) and covalent (type VI) kinase inhibitors. With this review, we strive to provide a summary of the latest advances in the structure-based discovery of novel kinase inhibitors, as well as a practical tool to anyone who wishes to embark on such an endeavor.
... 88 (Although the latter issue can be addressed with data fusion techniques 89 , which we cover in more detail in subchapter 5.) Fingerprint similarity searching was compared to other virtual screening methods (such as shape similarity searching and ligand docking) in several works, with varying conclusions, but such comparisons are out of the focus of the present work. [90][91][92] This subchapter is dedicated to a thorough overview of current fingerprinting methods. Before moving on to an itemized description however, we highlight some recent, well-written reviews of this field 86,93 , as well as some detailed, in-depth analyses of molecular fingerprints, dealing primarily with the similarities and differences among the fingerprinting methods themselves 88 , and the effects of various parameters (such as the addressable space, atom typing schemes and bit scaling rules) on fingerprints and their virtual screening performances (in particular on hashed fingerprints implemented in Schrödinger's Canvas). ...
Chapter
Full-text available
In this chapter we strive to provide a comprehensive but reasonably compact overview of the various possibilities for the computational representation of molecules. This includes a detailed introduction to the most commonly used chemical file formats (complemented with a few novel or more specific representations), a thorough overview of the theoretical backgrounds of various molecular fingerprints and descriptors, and a complete section devoted to similarity measures and data fusion approaches. Finally, we provide a list of the most important online chemical databases and conclude the chapter with a short outlook on present trends and future expectations.
... As mentioned above, amidine and/or guanidine chemistry is characteristic of BACE1 inhibition, but not widely represented in HTS decks; hence, novel exploratory chemistry assisted with computational prioritization provided multiple lead series that could not be identified from high-throughput methods [76]. We routinely use ligand-based virtual screening methods to identify analogs that otherwise would not be included in HTS [77]; this has delivered important hits for several programs. More recently, we have moved into exploring molecular dynamics methods for drug discovery applications [78]. ...
Article
The role of medicinal chemistry has changed over the past 10 years. Chemistry had become one step in a process; funneling the output of high-throughput screening (HTS) on to the next stage. The goal to identify the ideal clinical compound remains, but the means to achieve this have changed. Modern medicinal chemistry is responsible for integrating innovation throughout early drug discovery, including new screening paradigms, computational approaches, novel synthetic chemistry, gene-family screening, investigating routes of delivery, and so on. In this Foundation Review, we show how a successful medicinal chemistry team has a broad impact and requires multidisciplinary expertise in these areas.
... Machine learning (ML) algorithms adopt a different approach from classical virtual screening (VS) [21] approaches. In the case of ligand-based virtual screening (LBVS), it utilizes the active ligand's information and similarity between candidate ligands and the known active compounds to find new ligands [22]. As a result, these methods are useful when there is no 3-dimensional structure of the target protein available. ...
Article
Full-text available
New drug production, from target identification to marketing approval, takes over 12 years and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the urgent need for more powerful computational methods for drug discovery. Here, we review the computational approaches to predicting protein–ligand interactions in the context of drug discovery, focusing on methods using artificial intelligence (AI). We begin with a brief introduction to proteins (targets), ligands (e.g. drugs) and their interactions for nonexperts. Next, we review databases that are commonly used in the domain of protein–ligand interactions. Finally, we survey and analyze the machine learning (ML) approaches implemented to predict protein–ligand binding sites, ligand-binding affinity and binding pose (conformation) including both classical ML algorithms and recent deep learning methods. After exploring the correlation between these three aspects of protein–ligand interaction, it has been proposed that they should be studied in unison. We anticipate that our review will aid exploration and development of more accurate ML-based prediction strategies for studying protein–ligand interactions.
... As the docking simulations consider both structures (ligands and targets), its calculations are more computationally expensive. Considering these aspects, similarity searches and pharmacophore modeling are alternatives to faster calculations (Brogi et al., 2009;Tresadern et al., 2009) and are defined as ligandbased drug design (LBDD) strategies since they do not require the biological target structure (Turki et al., 2017). Figure 1 illustrates the main steps in a drug design process, including the use of computational tools. ...
Article
Full-text available
Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR) involve the construction of predictive models that relate a set of descriptors of a chemical compound series and its biological activities with respect to one or more targets in the human body. Datasets used to perform QSAR analyses are generally characterized by a small number of samples and this makes them more complex to build accurate predictive models. In this context, transfer and multi-task learning techniques are very suitable since they take information from other QSAR models to the same biological target, reducing efforts and costs for generating new chemical compounds. Therefore, this review will present the main features of transfer and multi-task learning studies, as well as some applications and its potentiality in drug design projects.
... However, the prospective aspect only comprised Topomers, Cresset, OEST, and OECS. Pharmacophore modeling and docking were missing in this study [28]. In 2010, Krüger and Evers retrospectively compared the enrichment factors of several docking protocols, ROCS, Feature Trees, and Scitegic Functional Fingerprints and investigated the hitlist complementarity. ...
Article
Full-text available
Computational methods can be applied in drug development for the identification of novel lead candidates, but also for the prediction of pharmacokinetic properties and potential adverse effects, thereby aiding to prioritize and identify the most promising compounds. In principle, several techniques are available for this purpose, however, which one is the most suitable for a specific research objective still requires further investigation. Within this study, the performance of several programs, representing common virtual screening methods, was compared in a prospective manner. First, we selected top-ranked virtual screening hits from the three methods pharmacophore modeling, shape-based modeling, and docking. For comparison, these hits were then additionally predicted by external pharmacophore- and 2D similarity-based bioactivity profiling tools. Subsequently, the biological activities of the selected hits were assessed in vitro, which allowed for evaluating and comparing the prospective performance of the applied tools. Although all methods performed well, considerable differences were observed concerning hit rates, true positive and true negative hits, and hitlist composition. Our results suggest that a rational selection of the applied method represents a powerful strategy to maximize the success of a research project, tightly linked to its aims. We employed cyclooxygenase as application example, however, the focus of this study lied on highlighting the differences in the virtual screening tool performances and not in the identification of novel COX-inhibitors. Copyright © 2015 The Authors. Published by Elsevier Masson SAS.. All rights reserved.
... According to criterion (5), this equation identified molecules in prediction set having high values of MG-CA inhibitory activity ''suggested for synthesis''. In Table 1, the predicted values of not yet synthesized compounds 29-51 were identified by the program as high have been marked in bold letters, while the values identified as low have been underlined. ...
Article
A quantitative structure–activity relationship (QSAR) study of sulfonamide inhibitors targeting the β-carbonic anhydrase (CA, EC 4.2.1.1) from the fungus Malassezia globosa is reported. A large set of PRECLAV descriptors has been used to obtain four parametric models. This study presents QSAR data on a pool of 28 compounds. The quality of prediction is high enough (SE = 0.3446, r2 = 0.8687, F = 39.6921, Q = 0.7446). A heuristic algorithm selected the best multiple linear regression (MLR) equation which showed the correlation between the observed values and the calculated values of activity. The proposed prediction set included new, not yet synthesized, 23 molecules having various structures. Many compounds in the prediction set seem to possess higher computed activity compared to the presently available M. globosa β-CA inhibitors. Read More: http://informahealthcare.com/doi/abs/10.3109/14756366.2015.1031127
... Virtual screening was initially performing in six commercial compounds databases based on similarity (shape and electrostatics) of reported active ones. For this step, a dihydropyridine was used as template and the ROCS and EON softwares were used to access shape and electrostatic similarities, respectively [13][14][15]. The ROCS and EON softwares from the OpenEye Company were used in the LBDD studies. ...
Article
Calcium channel blockage as a therapeutic strategy for treatment of leishmaniasis has demonstrated a promising pathway of treatment for this pathology. In this work, virtual screening approaches have been performed in several databases of commercially available compounds in order to design novel leishmanicidal compounds with potential L-type calcium channel blockage. Several compounds were tested against Leishmania intracellular parasites, using High-Content Analyses Assays. Results have indicated two compounds with new chemotypes, which were able to kill the parasite, with moderate activity and high efficacy, without toxicity for the host. Compounds here discovered represent a very useful molecular simplification compared to the reference or control compound, amphotericin B, with suitable ADME/Tox properties and synthetic accessibility.
... Em um estudo para a seleção de moléculas baseado na similaridade de forma e na similaridade eletrostática, Tresadern e colaboradores123 fizeram uma comparação de métodos de triagem virtual baseado no ligante e suas aplicações para o receptor do fator 1 de liberação da corticotrofina (do inglês Corticotrofin Releasing Factor 1 Receptor, CRF1) 120 . Empregando em seus estudos, programas que adotam o uso de fingerprints 3D como o programa ROCS (do inglês, Rapid Overlay of Chemical Structures) que usa o coeficiente de Tanimoto para calcular similaridade por forma, 124 e outro grupo, com o programa OpenEye Combo-Score e o programa EON que usam o coeficiente de Tanimoto para cálculo de similaridade eletrostática. ...
Article
Full-text available
The development of virtual screening techniques represents a major advance in the current drug design era. Through several strategies, virtual screening is able to facilitate the selection of molecules with the desired chemical features to modulate the biological activity of the most attractive molecular targets currently available. From the simplest techniques, as the similarity search or molecular docking, to more complex strategies, including statistical methods and machine learning, the main goal of virtual screening is to improve the searching for molecules with the desired features required for becoming drug candidates, thus accelerating the continuous process of drug design. The aim of this review is to discuss the main virtual screening strategies and how they relate to the drug design process.
... And the standard error of pIC 50 taken from 144 predictions followed by synthesis and testing in four different discovery organizations, was reported with extraordinarily low 0.6 value (or, expressed as an error in predicted potency ratios, 4x). [65][66][67] The practice of 3D QSAR is inherently limited to local models (as herein defined elsewhere). However, it can be expected, that with the latest explosive expansion of public databases such as ChEMBL and PubChem and with further evolution of alignment protocols, that limitation will slowly recede. ...
Article
Full-text available
Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss: (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists towards collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.
... Structure-based virtual screening methods offer a means to directly identify novel inhibitory compounds that complement the target protein surface 20 ; these methods are not limited by the requirement for template compound(s) implicit to ligand-centric (mimicry) approaches 21 . In the simplest terms, virtual screening requires some method for sequentially positioning each candidate compound from a library at its most likely position on the protein surface (i.e., "docking"), followed by a subsequent discrimination step (i.e., "scoring") to rank each of the resulting complexes based on their likelihood of showing the desired activity. ...
Article
Traditional drug targets have historically included signaling proteins that respond to small-molecules and enzymes that use small-molecules as substrates. Increasing attention is now being directed towards other types of protein targets, in particular those that exert their function by interacting with nucleic acids or other proteins rather than small-molecule ligands. Here, we systematically compare existing examples of inhibitors of protein-protein interactions to inhibitors of traditional drug targets. While both sets of inhibitors bind with similar potency, we find that the inhibitors of protein-protein interactions typically bury a smaller fraction of their surface area upon binding to their protein targets. The fact that an average atom is less buried suggests that more atoms are needed to achieve a given potency, explaining the observation that ligand efficiency is typically poor for inhibitors of protein-protein interactions. We then carried out a series of docking experiments, and found a further consequence of these relatively exposed binding modes is that structure-based virtual screening may be more difficult: such binding modes do not provide sufficient clues to pick out active compounds from decoy compounds. Collectively, these results suggest that the challenges associated with such non traditional drug targets may not lie with identifying compounds that potently bind to the target protein surface, but rather with identifying compounds that bind in a sufficiently buried manner to achieve good ligand efficiency, and thus good oral bioavailability. While the number of available crystal structures of distinct protein interaction sites bound to small-molecule inhibitors is relatively small at present (only 21 such complexes were included in this study), these are sufficient to draw conclusions based on the current state of the field; as additional data accumulate it will be exciting to refine the viewpoint presented here. Even with this limited perspective however, we anticipate that these insights, together with new methods for exploring protein conformational fluctuations, may prove useful for identifying the "low-hanging fruit" amongst non-traditional targets for therapeutic intervention.
... Dye structures were, also, modelled by the conformational search ability of the Omega v.2.4.3 (OpenEye Scientific Software, Santa Fe, NM 87507) software. Omega employs a rule-based algorithm [48] in combination with variants of the Merck force field 94 [49]. The following parameters were used for the conformer generation with Omega v.2.4.3: a maximum of 200 conformers per compound and an energy cut-off of 10 kcal/mol relative to the 8 global minimum identified from the search. ...
Article
Textile dyeing has economical and ecological implications. Our application of QSAR techniques to dye -cellulose binding is based on the hypothesis of specific dye-fibre interactions. As an alternative to classical QSAR studies, comparative molecular field analysis was previously used to predict technical dye adsorption properties. This paper presents a structure-affinity study of heterocyclic azo dye adsorption on cellulose fibre by multiple linear regression (MLR), comparative molecular field (CoMFA) and comparative molecular similarity index (CoMSIA) analysis. Structural descriptors, derived from the minimum energy conformers, obtained by molecular mechanics and semiempirical level quantum chemical calculations, were correlated with dye affinity for cellulose by MLR. Models with predictive power were obtained. Despite these good results 3D-QSAR CoMFA and CoMSIA approaches gave a deeper insight into dye-cellulose interactions. Dye conformers obtained by the AM1 and ab initio approaches were aligned using atom per atom superposition of a common frame. A comparative analysis on statistic performances and predictive model power was performed for the AM1 and DFT variants of CoMFA and CoMSIA models. Statistically significant models were established for 16 molecules and validated by an external test set of 5 compounds, yielding the best predictive DFT CoMFA model [r(2) = 0.960, with 4 components, q(2) = 0.707 and SEE = 1.12] and several CoMSIA models for AM1 and ab initio cases [r(2) = 0.935 / 0.947, q(2) = 0.688 / 0.739 and SEE = 1.32 / 1.46]. The contour maps obtained from 3D-QSAR studies were appraised for affinity trends for the investigated dye molecules. Results indicate a predominant hydrogen donor ability of the dye molecules for both AM1 and ab initio variants to play a significant role in dye binding to cellulose. Electrostatic interactions derived from DFT charges bring an important contribution to dye affinity, too. The information obtained from both CoMFA and CoMSIA 3D contour maps may be used in the design of new heterocyclic azo dyes. (C) 2012 Elsevier Ltd. All rights reserved.
... Despite the availability of X-ray crystal structure data for several members of the GPCR superfamily, structure-based discovery of GPCR ligands has until recently been restricted to the TM domain of class A (rhodopsin-like) receptors, and the N-terminal domain of class C GPCRs (glutamate-like receptors). Prospective ligand-based virtual screening studies to identify new ligand of class B GPCR ligands have been described (in particular, for CRFR1) (Tresadern, Bemporad, & Howe, 2009;Ye, Liao, Wei, & Gao, 2010), but only recently the first structure-based identification of noncompetitive ligands for two related class B (secretin-like) GPCRs, the GLR and the glucagon-like peptide 1 receptor (GLP-1R), was reported (de Graaf, Rein, et al., 2011). A knowledge-based homology model of GLR was constructed based on a validated structural model of the CRFR1 receptor, as for this representative class B, GPCR numerous experimental data on both the ligand and receptor side were available to guide the modeling procedure (see Sections 2.1 and 2.2) ( de Graaf, Rein, et al., 2011). ...
Article
This review will focus on the construction, refinement, and validation of G-protein-coupled receptor (GPCR) structural models for the purpose of structure-based virtual screening (SBVS) and ligand design. The review will present a comparative analysis of GPCR crystal structures and their implication on GPCR (homology) modeling. The challenges associated with steps along the modeling workflow will be discussed: the use of experimental anchors to steer the modeling procedure, amino acid sequence alignment and template selection, receptor structure refinement, loop modeling, ligand-binding mode prediction, and virtual screening for novel ligands. An overview of several successful structure-based ligand discovery and design studies shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands for GPCRs. Moreover, the recently solved GPCR crystal structures have further increased the opportunities in structure-based ligand discovery for this pharmaceutically important protein family.
... It is used with ROCS to sort and rank compounds according to their electrostatic similarity. 47,48 Compounds having an EON score .0.85 were considered to best match the template or antagonist, and separated 271 compounds. 46,49 To obtain the best results from the docking experiment, conformers of compounds were generated. ...
Article
Full-text available
Wnt-4 (wingless mouse mammary tumor virus integration site-4) protein is involved in many crucial embryonic pathways regulating essential processes. Aberrant Wnt-4 activity causes various anomalies leading to gastric, colon, or breast cancer. Wnt-4 is a conserved protein in structure and sequence. All Wnt proteins contain an unusual fold comprising of a thumb (or N-terminal domain) and index finger (or C-terminal domain) bifurcated by a palm domain. The aim of this study was to identify the best inhibitors of Wnt-4 that not only interact with Wnt-4 protein but also with the covalently bound acyl group to inhibit aberrant Wnt-4 activity. A systematic computational approach was used to analyze inhibition of Wnt-4. Palmitoleic acid was docked into Wnt-4 protein, followed by ligand-based virtual screening of nearly 209,847 compounds; conformer generation of 271 compounds resulted from extensive virtual screening and comparative docking of 10,531 conformers of 271 unique compounds through GOLD (Genetic Optimization for Ligand Docking), AutoDock-Vina, and FRED (Fast Rigid Exhaustive Docking) was subsequently performed. Linux scripts was used to handle the libraries of compounds. The best compounds were selected on the basis of having maximum interactions to protein with bound palmitoleic acid. These represented lead inhibitors in further experiments. Palmitoleic acid is important for efficient Wnt activity, but aberrant Wnt-4 expression can be inhibited by designing inhibitors interacting with both protein and palmitoleic acid.
... These methods are suitable for scaffold hopping because they assess properties important for biological recognition and not just underlying atom connectivity. We have previously developed optimal implementations of these approaches 19 and applied them to identify mGlu2 PAM scaffolds. 14,18 Here, our approach was similar and aimed at replacing the central scaffold, the triazolopyridine in 2a, with alternative heterocyclic ring systems. ...
Article
Full-text available
Glutamate hyperfunction is implicated in multiple neurological and psychiatric diseases. Activation of the mGlu2 receptor results in reduced glutamate release and decreased excitability representing a promising novel therapeutic agent for the treatment of disorders such as epilepsy, schizophrenia, mood, anxiety, and other neuropsychiatric disorders. We have previously reported substantial efforts leading to potent and selective mGlu2 PAMs from different chemical series. Herein, the discovery and optimization of a novel series of imidazopyrazinone mGlu2 PAMs are reported. This new scaffold originated from computational searching of fragment databases and comparison with our previously explored scaffolds. Optimization guided by our robust understanding of SAR from former series led to potent, selective, and brain-penetrant compounds.
... In a comparison by Tresadern et al [65], ECFP6 fingerprints were compared to several other virtual screening methods: feature trees, topomers, ROCS shape Tanimoto, EON electrostatic Tanimoto, OpenEye ComboScore (a combination of shape Tanimoto and color-score), and ...
Article
Molecular fingerprints have been used for a long time now in drug discovery and virtual screening. Their ease of use (requiring little to no configuration) and the speed at which substructure and similarity searches can be performed with them -paired with a virtual screening performance similar to other more complex methods- is the reason for their popularity. However, there are many types of fingerprints, each representing a different aspect of the molecule, which can greatly affect search performance. This review focuses on commonly used fingerprint algorithms, their usage in virtual screening, and the software packages and online tools that provide these algorithms.
Article
It is not uncommon in drug discovery that the core fragment, typically called scaffold, of a molecule with an interesting biological activity cannot be developed further because of issues related to intellectual property, physicochemical properties, metabolic stability, or toxicity, to name only a few reasons. In this situation, it is desirable to replace this molecule with another having a different chemical connectivity, but similar shape and pharmacophore features enabling it to interact in the same way with the target as the original molecule. Such a replacement is called scaffold hopping. Several ligand-based virtual screening and scoring methods supporting the identification of novel ligands starting from known ligands and, if known, their bound conformation, are available. Scaffold hopping capability has been demonstrated for pharmacophore searches, field- and shape-based similarity searches, alignment free similarity searches using three-dimensional (3D)- or connectivity-based descriptors, and fragment-based methods. Although for many methods successful prospective uses have been reported, rigorous systematic benchmarking of scaffold hopping is still challenging due to the lacking consensus in the definition of a scaffold. Despite their drawbacks, computational scaffold extraction methods have been frequently used in approximate benchmarks for scaffold hopping. In many systematic retrospective studies, connectivity-based methods were shown to be at least equally effective as 3D methods, especially when the conformations of the reference structures were generated with a conformer generator. However, in prospective comparison studies, especially when a hypothesis of the 3D binding conformation was available and used, often 3D methods were found to give superior results. © 2012 John Wiley & Sons, Ltd.
Article
Full-text available
The aromatic/heterocyclic sulfonamides possessing a large diversity of scaffolds are the most important class of Plasmodium falciparum carbonic anhydrase (pfCA) inhibitors. Sulfonamide inhibitors of the protozoanCAs may have potential for the development of novel therapies of human malaria. I have attempted to build QSAR models using the OMEGA, MOPAC, PRECLAV, DRAGON and BROOD software to explore the correlations between the calculated molecular descriptors on the pool of 27 compounds and their experimental pfCA inhibitory activities. The novelty of this work consists in not only exploring the structural attributes of bioactive molecules but in predicting in silico the structures of new compounds which may show antimalarial activity. The analogs of the lead molecule are generated by replacing selected fragments that have similar shape and electrostatics. The various pharmacokinetic evaluations and synthetic accessibility test were also carried out to search more suitable compounds. The molecules of the prediction set include many molecules having high computed activity compared to the reported such derivatives.
Article
Fire retardant materials diminish the hazard to life from fire. Polyphosphonates and polyphosphates display good flame retardancy and attractive plasticizing properties, being an important class of organophosphorus based polymer additives. Properties of previously synthesized polyphosphoesters are presented here, being simulated as monomers. In this quantitative structure-property relationship work, the flammability was expressed by limiting oxygen index (LOI) values, which were determined experimentally. Two types of chiral structures were found by molecular mechanics calculations using the MMFF94s force field for half of the monomers, consequently, two datasets were built. Structural parameters were calculated for the minimum energy structures and were related to the LOI values by multiple linear regression (MLR), artificial neural networks (ANNs), and support vector machines (SVMs). MLR calculations were combined with a genetic algorithm for variable selection. Stable and predictive MLR models in terms of 2D autocorrelation parameters weighed by atomic polarizabilities and of 3D-Morse descriptors were obtained. Somewhat inferior fits were found in the nonlinear modeling by ANNs and SVMs with the same set of descriptors. Monomers including R chiral structures gave more stable and predictive models compared to the S isomers in all approaches. Monomer geometry influences the flame retardancy, being favorable for R isomers.
Article
Full-text available
Ligand Based Virtual Screening methods are used to screen molecule databases to select the most promising compounds for a query. This is performed by decision-makers based on the information of the descriptors, which are usually processed individually. This methodology leads to a lack of information and hard post-processing dependent on the expert’s knowledge that can end up in the discarding of promising compounds. Consequently, in this work, we propose a new multi-objective methodology called MultiPharm-DT where several descriptors are considered simultaneously and whose results are offered to the decision-maker without effort on their part and without relying on their expertise.
Article
Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.
Chapter
Africa disproportionately bears the brunt of the global disease burden. It has the highest prevalence of infectious diseases and some of them are unique to the continent, such as tsetse-transmitted trypanosomosis. Consequently, it is imperative for Africa to find therapies to such diseases. In spite of the intellectual and scientific capacity on the continent, as well as the rich natural resources it possesses, Africa is yet to supply a drug on the market. This chapter discusses some of the platforms that will enable Africa to effectively participate in the discovery of new drug entities. The application of these technologies to natural products is explored in detail and their relevance to Africa highlighted.
Article
The single-layered gut epithelium represents the primary line of defense against environmental stressors. Thereby monolayer integrity and tightness are essentially required to maintain gut health and function. To date only a few plant-derived phytochemicals have been described as affecting intestinal barrier function. We investigated the impact of 28 secondary plant compounds on the barrier function of intestinal epithelial CaCo-2/TC-7 cells via transepithelial electrical resistance measurements (TEER). Apart from genistein, the compounds that had the biggest effect in the TEER measurements were biochanin A and prunetin. These isoflavones improved barrier tightness by 36% and 60%, respectively, compared to the non-treated control. Furthermore, both isoflavones significantly attenuated TNFα-dependent barrier disruption, thereby maintaining a high barrier resistance comparable to non-stressed cells. In docking analyses exploring the putative interaction with the tyrosine kinase EGFR, these novel modulators of barrier tightness showed very similar values as compared to the known tyrosine kinase inhibitor genistein. Both biochanin A and prunetin were also identified as potent reducers of NFκB and ERK activation, zonula occludens 1 tyrosine phosphorylation as well as metalloproteinase-mediated shedding activity, which may account for the barrier-improving ability of these isoflavones.
Article
Template CoMFA, a novel alignment methodology for training or test set structures in 3D-QSAR, is introduced. Its two most significant advantages are its complete automation and its ability to derive a single combined model from multiple structural series affecting a biological target. Its only two inputs are: one or more "template" structures having 3D coordinates that share some Cartesian space, as may result from X-ray crystallography or pharmacophoric hypothesis; and one or more connectivity-only SAR tables associated with a common target. Template CoMFA also overcomes the major disadvantages of both existing 3D-QSAR alignment methodologies, specifically the tedium and subjectivity of familiar ad hoc approaches, and the awkwardness, occasional physicochemical heresies, and structural scope limitations of the purely topomer approach. The template CoMFA algorithms are described, and two of its application classes are presented. The first class, general models of binding to factorXa and P38 map kinase, use crystallographic structures as templates, with the encouraging result that the statistical qualities of each of these two combined models are equivalent to those of their constituent individual series models. The second, fifteen datasets originally collected for validation of topomer CoMFA, with arbitrary structures as templates, confirms that the modeling power of template CoMFA resembles that of its predecessors.
Article
A Quantitative Structure–Activity Relationship (QSAR) is a linear or non-linear model, which relates variations in molecular descriptors to variations in the biological activity of a series of active and/or inactive molecules. For this article, different feature-selection or reduction methods were all coupled with Partial Least Squares (PLS) modeling during the selection of features. A PLS model was also built with the entire set of molecular descriptors and was used as a reference to check the reliability and the performance of the different feature-selection methods. To evaluate the ability of the different feature-selection methods, they were performed on two data sets.
Article
Full-text available
A series of novel reversible inhibitors of the dual-specificity phosphatase Cdc25 was discovered using a two-stage molecular field-based similarity analysis. This method compares molecules on the basis of electrostatic and steric features, rather than their underlying structures, facilitating scaffold-hopping to new chemotypes. In this prospective study, a field point pharmacophore model was generated from three structurally diverse, reversible Cdc25 inhibitors and used in field-based virtual screening of 3.7 million commercially available compounds. Seven thiazoles, from the small set of 35 compounds selected for testing, showed reversible inhibition of activity at all three isoforms of Cdc25 (Cdc25A, B and C) at micromolar concentrations. The new series are not structurally related to the initial three starting points, but share their biological properties. Substructure searching rapidly identified additional thiazoles with modest (10-fold) increases in activity equivalent to those of the initial three starting points. This study demonstrates the effectiveness of this ligand-based method to both define a pharmacophore and effect virtual screening resulting in rapid and efficient identification of chemical starting points for development of novel therapeutic agents.
Article
Abstract Ureido-substituted benzene sulfonamides are the most important class of CA inhibitors which significantly inhibited the formation of primary tumors and metastases. Here, we present quantitative structure activity relationships (QSAR) study on a pool of 27 such inhibitors. A heuristic algorithm selected the best multiple linear regression (MLR) equation, showing the correlation between the observed values and the calculated values of activity. The calculated values of activity were in good agreement with the experimental values. The novelty of this work consists in not only exploring the structural attributes of bioactive molecules but also in predicting in silico the structures of new compounds which may show antimetastatic activity. The not yet synthesized such molecules (i.e. the prediction set) included many compounds showing a higher computed activity compared to the reported such derivatives, but they have been however not yet assayed.
Chapter
Factor Xa (FXa) is recognized as an attractive target for the design and development of new anticoagulant agents for combating the thromboembolic diseases. Recently, in silico prediction and screening approaches have been adopted as effective paradigms to complement high-throughput screening (HTS) for the identification of novel lead compounds of a specific biological target. In this work, we integrated the ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches for prediction and screening of the potentially potent FXa inhibitors from large chemical libraries. The state-of-the-art machine learning methods, including support vector machine and random forest, were firstly employed as the LBVS approach to develop the prediction models to rapidly narrow large chemical libraries to just hundreds of enriched hits or more. The VS performance of the developed models was evaluated by using the annotated MDL Drug Data Report (MDDR) database, achieving substantial yields and comparable hit rates and enrichment factors. The better performing random forest model was subsequently used to perform VS against the “fragment-like” subset of ZINC database to enrich the potential actives. These potentially enriched actives were further docked to the target protein human FXa using AutoDock4 of the SBVS approach, so as to examine their binding affinities, thereby obtaining 27 most potent candidates.
Article
Full-text available
The toxicity of chemicals greatly depends on their interaction with macromolecular targets. The main goal of this study was to develop an approach for predicting protein targets for chemical toxins using a molecular similarity search of toxin-target information collected in the Toxin and Toxin-Target Database. The developed method was used to identify new targets for toluene which could predict potential cellular toxicity and to validate the approach with in vitro laboratory studies. We obtained 124 potential targets for toluene from a molecular similarity search. Results were further analysed using in silico molecular docking methods. The binding of toluene to two proteins, hemoglobin and serum albumin, was validated by the measurement of binding using microscale thermophoresis. The measured binding constant between toluene and hemoglobin was 1.9 μM, while albumin demonstrated toluene-induced aggregation. These results demonstrate the applicability of an exploratory in silico toxicity tool, based on a molecular similarity search and protein-ligand docking for identification of potential targets for chemical toxins.
Article
Protein arginine methyltransferases (PRMTs) are essential epigenetic and post-translational regulators in eukaryotic organisms. Dysregulation of PRMTs is intimately related to multiple types of human diseases, particularly cancer. Based on the previously reported PRMT1 inhibitors bearing the diamidine pharmacophore, we performed virtual screening to identify additional amidine-associated structural analogs. Subsequent enzymatic tests and characterization led to the discovery of a top lead K313 (2-(4-((4-carbamimidoylphenyl)amino)phenyl)-1H-indole-6-carboximidamide), which possessed low-micromolar potency with biochemical IC50 of 2.6 μM for human PRMT1. Limited selectivity was observed over some other PRMT isoforms such as CARM1 and PRMT7. Molecular modeling and inhibition pattern studies suggest that K313 is a nonclassic noncompetitive inhibitor to PRMT1. K313 significantly inhibited cell proliferation and reduced the arginine asymmetric dimethylation level in the leukaemia cancer cells.
Chapter
Parkinson’s Disease (PD) is a neurodegenerative disease that causes damage to the cognitive and motor system due to the death of dopaminergic neurons, which are responsible for the synthesis of the neurotransmitter dopamine. The study aimed to compare the monoamine oxidase B (MAO-B) inhibitory activity of natural molecules described in the literature with Selegiline, as potential drugs for the treatment of PD through molecular modeling, molecular docking and prediction of ADME/Tox properties. Thus, it was found the structure of the four natural molecules, Amburoside A, Harman, Harmaline and Harmalol, showed antiparkinsonian biological activity. Maps Electrostatic Potential showed similar regions between the molecules, except for Amburoside A, and Harmaline had a greater similarity in the positive potential with Selegiline. Molecular docking demonstrated that the studied molecules interact with 4–6 amino acids from the active site of the MAO-B enzyme, indicating that it has an inhibitory action on the enzyme, through hydrogen bonding and hydrophobic interactions. For ADME property predictions, most of the molecules showed good human oral absorption, all showed average permeability in Caco-2 cells, most showed average permeability in MDCK cells, showed low binding to plasma proteins, and for permeability in the blood-brain barrier, they were between good and medium. Overall, Harmaline has more properties similar to Selegiline. For toxicological properties, all molecules including Selegiline showed a positive result for the possibility of mutagenicity, whereas for the parameter of carcinogenicity in rats only the molecules Harmaline and Harmalol were positive, but no molecule was positive for carcinogenicity in mice. Therefore, the molecule that presented the best results was Harmaline, opening perspectives for the execution of in vitro studies.
Chapter
Myrciaria cauliflora (jabuticaba) is a Brazilian native species of the Atlantic forest region that produces fruits enriched with outstanding antioxidant content, such as anthocyanins, polyphenols, tannins and flavonoids. It additionally is known that jabuticaba fruits are attractive sources of bioactive molecules that drive phytotechnological research worldwide. Several works with jabuticaba were developed in last years covering mainly the agricultural, pharmaceutical and food science fields. However, there is still a gap regarding technological development. Here, we make an approach over the technological products obtained form jabuticaba fruits, their biological potential, the drug-like properties of chemical markers and the main techniques that would be employed in future development of other products with commercial value.
Chapter
Since the industrial revolution from century XIX, the global environment has received a charge of each more pollutant. Even with filters and catalysts to minimize some industrial residues is necessary more caution and research treat waste and other products. In such a perspective, water clean and environmental remediation are some of the most important themes for humanity. The chemical treatment for a large quantity of generated pollutant residues by industry is a great challenge. Such pollutants are in molecules or materials forms. In particular, a molecule group denominated dyes is the focus. Heterogeneous catalysis based on semiconductor oxides is a widely investigated topic as a broad and potential technology for clean water treatment. Then, we present a chapter with a comprehensive perspective of the modifications applied in CuO and ZnO to improve the efficiency in heterogeneous photocatalysis processes. The DFT approaches ally to experimental evidence showed that doping and heterojunctions are efficient tools to maximize the discovery of the advanced materials directed to water clean and environmental remediation. Mn-doped ZnO presented an exciting performance for photocatalysis on methylene blue dye from defects connected to intermediary electronic levels. Heterojunction made from CuO/ZnO is a putative candidate for photodegradation in two ways: (i) generation in situ of oxidizing molecules; and (ii) the sunlight wavelength range as an energy source. Such molecular mechanism is possible from the generation, stability, and control on the charges carriers diffusion inside semiconductor oxides. How to understand and influence the creation of the electron–hole pair is the fundamental step to establish the heterogeneous photocatalysis based on semiconductor oxides as one of the essential applications of the advanced materials in environmental remediation.
Chapter
Alkaline earth stannates with perovskite structure (ASnO3, A = Ca, Sr, Ba) have been studied for a long time due to their unique structure and physicochemical properties, but few works in literature have been devoted to their thin films. The technology of thin films makes structuring materials in fettered dimensions very simple, making them useful in electronic devices. Moreover, the possibility of oriented and epitaxial growth allows a better understanding of the surface and interface properties of the films to tailor their functionalities. In this chapter, recent findings on photoluminescent properties of ASnO3-type perovskites are discussed and results on polycrystalline and epitaxial thin films deposited using a physical deposition method (pulsed laser deposition, PLD) and a chemical one (chemical solution deposition, CSD) are presented. In this context, two different series were carefully investigated considering the Sr-site substitution in SrSnO3 perovskite to form the Ca1−xSrxSnO3 solid solution, and the Sn-site substitution giving origin to SrSn1−xTixO3 (x = 0, 0.25, 0.5, 0.75 and 1). The structural and microstructural characteristics of all films are first presented. Then, discussion about the influence of composition, method of deposition, type of growth and short-range order/disorder related to photoluminescence properties are shown.
Chapter
Virtual screening studies consists of applying successive filters to large groups of molecules, called virtual libraries, in order to obtain a small number of hits. These hits, after going through activity-proving studies, generally in vitro enzymatic activity assays, can be followed by optimization studies aiming to increase activity and generating lead compounds. Computational approaches used in virtual screening studies are based on previously reported information about ligand or macromolecular receptor structures, and thus are called Ligand or Structure-Based Drug Design, respectively. The starting point for a virtual screening study is to obtain and prepare the virtual library to be used. The number of compounds present in virtual libraries, which can reach hundreds of thousands, have different characteristics, and depend on the study to be performed. In order to have a good efficiency of a virtual screening study, the compounds of a library must follow the criteria of representativeness and diversity, since these studies aim not only to obtain compounds with biological activity, but also to broaden the knowledge of different chemical classes of compounds able of interacting with a given target. In this chapter, we will address the fundaments of virtual screening studies, as well as the emergence and how these studies are currently conducted. From the initial choice of strategies that can be adopted, followed by the choice and preparation of databases, techniques that can be adopted, and ending with studies of hits optimization.
Chapter
One of the important steps in the enzyme catalyzed reaction is the binding of ligand or substrate to an enzyme (target or macromolecule). The study of their interactions using molecular docking methods to explore the ligand conformations adopted within the binding sites of macromolecular targets forms the basis for a rational drug design strategy. This approach is used in drug discovery and medicinal chemistry to identify or design small molecules against specific targets, for therapeutic interventions, for infectious diseases, antibiotic resistance, cancer, or cardiovascular diseases, and many more. Huge amounts of money and many years are spent to introduce a medicine into the commercial market; hence, it becomes necessary for a scientist to explore new cost and time saving ways to launch a drug into the market. The use of molecular docking approach to identify drug candidate against infectious diseases has now become one of the important steps in drug designing. This chapter highlights five aspects of the use of molecular docking for drug design: structure-based drug design (multiple molecules docked against a target), ligand-based drug design (exploration of molecular descriptors), fragment-based drug design (expansion or linkage of small fragments identified against a target to generate lead molecule), reverse or inverse drug designing (screening of potential interacting proteins against a compound of interest), and drug repurposing (identification of new uses for approved drugs). We would further discuss several successful cases of molecular docking and drug design studies including drugs for the treatment of HIV, tuberculosis, influenza, malaria, antibiotic resistance, and other prevalent diseases such as cancer.
Article
Full-text available
The drug development process is a major challenge in the pharmaceutical industry since it takes a substantial amount of time and money to move through all the phases of developing of a new drug. One extensively used method to minimize the cost and time for the drug development process is computer-aided drug design (CADD). CADD allows better focusing on experiments, which can reduce the time and cost involved in researching new drugs. In this context, structure-based virtual screening (SBVS) is robust and useful and is one of the most promising in silico techniques for drug design. SBVS attempts to predict the best interaction mode between two molecules to form a stable complex, and it uses scoring functions to estimate the force of non-covalent interactions between a ligand and molecular target. Thus, scoring functions are the main reason for the success or failure of SBVS software. Many software programs are used to perform SBVS, and since they use different algorithms, it is possible to obtain different results from different software using the same input. In the last decade, a new technique of SBVS called consensus virtual screening (CVS) has been used in some studies to increase the accuracy of SBVS and to reduce the false positives obtained in these experiments. An indispensable condition to be able to utilize SBVS is the availability of a 3D structure of the target protein. Some virtual databases, such as the Protein Data Bank, have been created to store the 3D structures of molecules. However, sometimes it is not possible to experimentally obtain the 3D structure. In this situation, the homology modeling methodology allows the prediction of the 3D structure of a protein from its amino acid sequence. This review presents an overview of the challenges involved in the use of CADD to perform SBVS, the areas where CADD tools support SBVS, a comparison between the most commonly used tools, and the techniques currently used in an attempt to reduce the time and cost in the drug development process. Finally, the final considerations demonstrate the importance of using SBVS in the drug development process.
Chapter
This chapter provides a brief introduction to fingerprint-based similarity searching in chemical databases, and the use of fingerprints for scaffold-hopping applications in both simulated and operational virtual screening environments.
Article
Starting from two weak mGlu2 receptor positive allosteric modulator (PAM) HTS hits (4 and 5) a molecular hybridization strategy resulted in the identification of a novel spiro-oxindole piperidine series with improved activity and metabolic stability. Scaffold hopping around the spiro-oxindole core identified the 3-(azetidin-3-yl)-1H-benzimidazol-2-one as bioisoster. Medicinal chemistry optimization of these two novel chemotypes resulted in the identification of potent, selective, orally bioavailable and brain penetrant mGluR2 PAMs
Article
Full-text available
Background: Armed with the digital availability of two natural products libraries, amounting to some 195,885 molecular entities, we ask the question of how we can best sample from them to maximise their 'representativeness' in smaller and more usable libraries of 96, 384, 1152 and 1920 molecules. Purpose and scope. The term 'representativeness' is intended to include diversity, but for numerical reasons (and the likelihood of being able to perform a QSAR) it is necessary to focus on areas of chemical space that are more highly populated. New synthesis. Encoding chemical structures as fingerprints using the RDKit 'patterned' algorithm, we first assess the granularity of the natural products space using a simple clustering algorithm, showing that there are major regions of 'denseness' but also a great many very sparsely populated areas. We then apply a 'hybrid' hierarchical K-means clustering algorithm to the data to produce more statistically robust clusters from which representative and appropriate numbers of samples may be chosen. There is necessarily again a trade-off between cluster size and cluster number, but within these constraints, libraries containing 384 or 1152 molecules can be found that come from clusters that represent some 18 and 30% of the whole chemical space, with cluster sizes of, respectively, 50 and 27 or above, just about sufficient to perform a QSAR. By using the online availability of molecules via the Molport system (www.molport.com), we were also able to construct (and, for the first time, provide the contents of) a small virtual library of available molecules that provided effective coverage of the chemical space described. Consistent with this, the average molecular similarities of the contents of the libraries developed is considerably smaller than was that of the original libraries. Conclusion: The suggested libraries may have use in molecular or phenotypic screening, including for determining possible transporter substrates.
Article
This paper presents result of quantitative structure-activity relationships (QSAR) study realized with the PRECLAV, omega, brood and MOPAC software. The dependent property is the inhibitory activity against human carbonic anhydrase mitochondrial isoforms VA. The calibration set includes 12 2-substituted-1,3,4-thiadiazole-5-sulfamides heterocyclic with two clinically used CA inhibitors namely AZA, and ZNS molecules. The prediction set contains nine others not yet synthesized substituted heterocyclic sulphonamides having unknown observed values of activity. In the presence of prediction set, the predictive quality of QSAR of hCA VA (r(2) = 0.9528, F = 60.5698, r(CV)(2) = 0.9052) is large. The obtained models suggest a slightly different inhibition mechanism for the isoforms. Large percentage, in weight, of C2HN3 molecular fragments seems to be not favorable to inhibitory activity of VA.
Article
Full-text available
The peroxisome proliferator-activated receptor (PPAR) γ regulates the expression of genes involved in adipogenesis, lipid homeostasis, and glucose metabolism, making it a valuable drug target. However, full activation of the nuclear receptor is associated with unwanted side effects. Research therefore focuses on the discovery of novel partial agonists, which show a distinct protein-ligand interaction pattern compared to full agonists. Within this study, we employed pharmacophore- and shape-based virtual screening and docking independently and in parallel for the identification of novel PPARγ ligands. The ten top-ranked hits retrieved with every method were further investigated with external in silico bioactivity profiling tools. Subsequent biological testing not only confirmed the binding of nine out of the 29 selected test compounds, but enabled the direct comparison of the method performances in a prospective manner. Although all three methods successfully identified novel ligands, they varied in the numbers of active compounds ranked among the top-ten in the virtual hit list. In addition, these compounds were in most cases exclusively predicted as active by the method which initially identified them. This suggests, that the applied programs and methods are highly complementary and cover a distinct chemical space of PPARγ ligands. Further analyses revealed that eight out of the nine active molecules represent novel chemical scaffolds for PPARγ, which can serve as promising starting points for further chemical optimization. In addition, two novel compounds, identified with docking, proved to be partial agonists in the experimental testing.
Article
Full-text available
Tyrosyl-DNA phosphodiesterase 2 (TDP2) processes protein/DNA adducts resulting from abortive DNA topoisomerase II (Top2) activity. TDP2 inhibition could provide synergism with the Top2 poison class of chemotherapeutics. By virtual screening of the NCI diversity small molecule database, we identified selective TDP2 inhibitors and experimentally verified their selective inhibitory activity. Three inhibitors exhibited low-micromolar IC50 values. Molecular dynamics simulations revealed a common binding mode for these inhibitors, involving association to the TDP2 DNA-binding cleft. MM-PBSA per-residue energy decomposition identified important interactions of the compounds with specific TDP2 residues. These interactions could provide new avenues for synthetic optimization of these scaffolds.
Article
Leishmaniasis is prevalent in tropical and subtropical regions of the world. About 12 million people in 88 countries are already affected by Leishmaniasis. Cutaneous leishmaniasis is a common form of leishmaniasis most commonly caused by L. major. There are several medications are available for the treatment of Leishmaniasis but they are highly toxic and the problem of resistance persists. Inositol phosphosphingolipid phospholipase C-like (ISCL) protein belonging to the sphingolipid metabolism of Leishmania is an important target protein as it is essential for the parasite survival and metacyclogenesis. Recent studies have shown that benzimidazole derivatives have antiprotozoan, antifungal antimicrobial, antiviral and anticancer activities. In the present study, we have screened certain benzimidazole derivatives for their potential to act as inhibitors of target protein ISCL. A ligand based screening approach was used for the inhibitor design. Virtual screening of the ligands was done using similarity searches, pharmacophore prediction and 2D fingerprinting approaches. Docking of the inhibitors with the binding site of ISCL resulted in the identification of one of the compounds (C4) which interacted with some of the key residues of the ISCL protein which are responsible for catalytic activity as well as tethering of the ISCL with the membrane.
Article
The quantitative structure activity relationships (QSAR) study on the activation of the human secretary isoform of the metalloenzyme carbonic anhydrase hCA III (cytosolic) and IV (membrane-associated) with a series of natural and non-natural amino acids and aromatic/heterocyclic amines are reported. A large set of MOPAC, PRECLAV and DRAGON descriptors have been used to obtain tri parametric models. A heuristic algorithm selects the best multiple linear regression (MLR) equation showed the correlation between the observed values and the calculated values of activity is very good. The obtained models are discussed using a variety of statistical parameters. This work is exploring the structural attributes of bioactive molecules.
Article
Scleractinian coral stylophora pistillata carbonic anhydrase (STPCA) enzyme is a secreted isoform, plays a direct role in bio-mineralization. Sulfonamides, including some clinically used derivatives are the most important class of STPCA inhibitors. In order to search for efficient STPCA inhibitors molecules, the present work deals with quantitative structure-activity relationship (QSAR) studies of a series of 36 bioactive molecules. A heuristic algorithm selects the best multiple linear regression (MLR) equation showed the correlation between the observed values and the calculated values of activity is very good (N=36, Se=0.1683, r(2)=0.9158, F=54.3809, r(cv)(2)=0.8569). The novelty of this work is not only to explore the structural attributes of bioactive molecules but also to design and predict in silico the STPCA inhibitory activity of new not yet synthesized compounds. The analyzed prediction set includes many molecules having greater computed activity than observed value of inhibitory activity.
Article
Full-text available
The possibility that hypersecretion of corticotropin-releasing factor (CRF) contributes to the hyperactivity of the hypothalamo-pituitary-adrenal axis observed in patients with major depression was investigated by measuring the concentration of this peptide in cerebrospinal fluid of normal healthy volunteers and in drug-free patients with DSM-III diagnoses of major depression, schizophrenia, or dementia. When compared to the controls and the other diagnostic groups, the patients with major depression showed significantly increased cerebrospinal fluid concentrations of CRF-like immunoreactivity; in 11 of the 23 depressed patients this immunoreactivity was greater than the highest value in the normal controls. These findings are concordant with the hypothesis that CRF hypersecretion is, at least in part, responsible for the hyperactivity of the hypothalamo-pituitary-adrenal axis characteristic of major depression.
Article
Full-text available
Four small, targeted libraries of differentially substituted amino pyrimidines were synthesized in moderate to good yields. Excellent regiochemistry was observed for substitution at C2/C4 with selectivity > 50:1 noted. All analogues were screened for their ability to interact with CRH1 and CRH2 receptors. In all instances only poor agonistic and/or antagonistic behaviour was noted at CRH2. However, several compounds were potent and selective CRH1 antagonists, most notably 13a Ki = 39 nM. Additionally we have utilized these data and that recently reported by others to refine our original CRH1 pharmacophore (J Med. Chem., 1999, 42, 2351-2357).
Article
A chemically advanced template search (CATS) based on topological pharmacophore models has been developed as a technique for virtual screening. This technique has successfully identified novel potent Ca²⁺ antagonists (such as 2) that have a similar activity to 1 (a known T-channel blocking agent) in a library of several hundred thousand compounds on the basis of a correlation vector representation.
Article
A Gaussian description of molecular shape is used to compare the shapes of two molecules by analytically optimizing their volume intersection. The method is applied to predict the relative orientation of ligand series binding to the proteins, thrombin, HIV protease, and thermolysin. The method is also used to quantify the degree of chirality of asymmetric molecules and to investigate the chirality of biphenyl and the amino acids. The shape comparison method uses the newly described shape multipoles that can also be used to describe the inherent shape of molecules. Some results of calculated shape quadrupoles are given for the ligands used in this work. © 1996 by John Wiley & Sons, Inc.
Article
A method for the determination of the convulsive threshold by means of graded electrical stimulation has been described by Spiegel¹ and has been employed for comparing the action of certain drugs. The apparatus used in this investigation represents a simplification of that devised by Spiegel and embodies also the arrangement of electrodes employed by Krasnogorski.² A description and diagram have been published.³ The point of departure for the investigation was the fact that although phenobarbital is one of the most efficient anticonvulsant drugs in common use, other barbiturates are comparatively ineffective, a fact that is often observed clinically and is strikingly demonstrated by the apparatus employed. For this reason and from certain theoretical considerations,³ a search was made among phenyl derivatives of the general type of phenobarbital, including phenyl, cresyl and tolyl sulfonates, benzoates, ketones and esters, with such radicals as carbamic, barbituric and malic acid,
Article
The nonpeptide CRH antagonist antalarmin has been shown to block both behavioral and endocrine responses to CRH. However, it’s potential activity in blunting behavioral and endocrine sequelae of stressor exposure has not been assessed. Because antagonism of central CRH by α-helical CRH attenuates conditioned fear responses, we sought to test antalarmin in this regard. In addition, it remains unclear as to whether this is a result of receptor blockade during conditioning or during testing. Thus, we explored whether CRH mediates the induction or expression of conditioned fear (freezing in a context previously associated with 2 footshocks; 1.0 mA, 5 sec each). Furthermore, because rats previously exposed to inescapable shock (IS; 100 shocks, 1.6 mA, 5 sec each), demonstrate enhanced fear conditioning, we investigated whether this effect would be blocked by antalarmin. Antalarmin (20 mg/kg·2 ml ip) impaired both the induction and expression of conditioned fear. In addition, antalarmin blocked the enhancement of fear conditioning produced by prior exposure to IS. Despite the marked behavioral effects observed in antalarmin-treated rats, antalarmin had no effect on IS-induced rises in ACTH or corticosterone. However, antalarmin did block the ACTH response produced by exposure to 2 footshocks.
Article
This chapter provides a background, describes various methods, performance measurements, evaluations, post-processing, and the future directions of high throughput docking methods for pharmaceutical lead finding. The docking programs generate poses for each candidate ligand, a pose being defined by the ligand conformation plus orientation within the binding site. Selecting among available software for high throughput docking (HTD) is a challenging problem. HTD studies usually assume a rigid protein because allowing for a flexible protein would be too computationally expensive. Cole et al suggest that the statistical significance of HTD results must be established if the data are to be interpreted with any certainty. It is clear that a significant amount of time has gone into this recent round of HTD evaluations, on the part of both the industrial practitioners and also the academic and commercial developers, who understandably wanted to ensure that their programs are deployed in optimal fashion. In the interest of reducing time spent on future evaluations, it would be useful to establish a standardized set of benchmarks, such as the ones employed by computer hardware vendors.
Article
Corticotropin-releasing factor (CRF) is a 41-amino acid peptide neurohormone that plays a major role in the body’s response to stress by modulating the endocrine, autonomic, behavioural and immune systems. The peptide interacts with two known receptors, CRF1 and CRF2, which belong to class B (secretin-like) G-protein-coupled receptors. Over the past ten years, a number of small molecule antagonists have been published in the patent literature. The present review covers recent patent literature (since 2000) where low molecular weight, non-peptide CRF antagonists are disclosed. These can be divided into four main classes of molecules: monocyclic, bicyclic and tricyclic compounds as well as a miscellaneous category, which include compounds that are unlike the traditional small molecule CRF1 antagonists.
Article
Corticotropin-releasing hormone (CRH) is an endogenous 41-amino acid peptide involved in a wide ranging series of systems including the brain, the coordination of the body's overall response to stress, and more recently as a crucial initiator in the onset of labor, also known as the placental clock. Although more physiological data on CRH is emerging shedding more light on the processes involved and their integration, the mode of action of the hormone and the postulated binding site(s) remain unknown. Recently, a number of small-molecular-weight ligands have emerged as potent antagonists but, as therapeutics, suffer from a lack of solubility. Additionally, despite a number of exhaustively large patents, the lack of structural diversity with these antagonists has enabled little scope for comprehensive and wide ranging studies into the structure of the binding sites of this hormone. As part of a program investigating new, structurally diverse antagonists and agonists of CRH, we have developed a preliminary pharmacophore based on the known small-molecular-weight ligands as an initial step in our program. This pharmacophore was validated by comparison with some of the compounds we postulated to be active.
Article
A Gaussian description of molecular shape is used to compare the shapes of two molecules by analytically optimizing their volume intersection. The method is applied to predict the relative orientation of ligand series binding to the proteins, thrombin, HIV protease, and thermolysin. The method is also used to quantify the degree of chirality of asymmetric molecules and to investigate the chirality of biphenyl and the amino acids. The shape comparison method uses the newly described shape multipoles that can also be used to describe the inherent shape of molecules. Some results of calculated shape quadrupoles are given for the ligands used in this work. © 1996 by John Wiley & Sons, Inc.
Article
Although the concept of similarity is a convenient for humans, a formal definition of similarity between chemical compounds is needed to enable automatic decision-making. The objective of similarity measures in toxicology and drug design is to allow assessment of chemical activities. The ideal similarity measure should be relevant to the activity of interest. The relevance could be established by exploiting the knowledge about fundamental chemical and biological processes responsible for the activity. Unfortunately, this knowledge is rarely available and therefore different approximations have been developed based on similarity between structures or descriptor values. Various methods are reviewed, ranging from two-dimensional, three-dimensional and field approaches to recent methods based on “Atoms in Molecules” theory. All these methods attempt to describe chemical compounds by a set of numerical values and define some means for comparison between them. The review provides analysis of potential pitfalls of this methodology – loss of information in the representations of molecular structures – the relevance of a particular representation and chosen similarity measure to the activity. A brief review of known methods for descriptor selection is also provided. The popular “neighborhood behavior” principle is criticized, since proximity with respect to descriptors does not necessarily mean proximity with respect to activity. Structural similarity should also be used with care, as it does not always imply similar activity, as shown by examples. We remind that similarity measures and classification techniques based on distances rely on certain data distribution assumptions. If these assumptions are not satisfied for a given dataset, the results could be misleading. A discussion on similarity in descriptor space in the context of applicability domain assessment of QSAR models is also provided. Finally, it is shown that descriptor based similarity analysis is prone to errors if the relationship between the activity and the descriptors has not been previously established. A justification for the usage of a particular similarity measure should be provided for every specific activity by expert knowledge or derived by data modeling techniques.
Article
Similarity searches based on chemical descriptors have proven extremely useful in aiding large-scale drug screening. Typically an investigator starts with a “probe”, a drug-like molecule with an interesting biological activity, and searches a database to find similar compounds. In some projects, however, the only known actives are peptides, and the investigator needs to identify drug-like actives. 3D similarity methods are able to help in this endeavor but suffer from the necessity of having to specify the active conformation of the probe, something that is not always possible at the beginning of a project. Also, 3D methods are slow and are complicated by the need to generate low-energy conformations. In contrast, topological methods are relatively rapid and do not depend on conformation. However, unmodified topological similarity methods, given a peptide probe, will preferentially select other peptides from a database. In this paper we show some simple protocols that, if used with a standard topological similarity search method, are sufficient to select nonpeptide actives given a peptide probe. We demonstrate these protocols by using 10 peptide-like probes to select appropriate nonpeptide actives from the MDDR database.
Article
Similarity searches using topological descriptors have proved extremely useful in aiding large-scale screening. We describe alternative forms of the atom pair (Carhart et al. J. Chem. Inf. Comput. Sci. 1985, 25, 64-73.) and topological torsion (Nilakantan et al. J. Chem. Inf. Comput. Sci. 1987, 27, 82-85.) descriptors that use physiochemical atom types. These types are based on binding property class, atomic log P contribution, and partial atomic charges. The new descriptors are meant to be more ''fuzzy'' than the original descriptors. We propose objective criteria for determining how effective one descriptor is versus another in selecting active compounds from large databases. Using these criteria, we run similarity searches over the Derwent Standard Drug File with ten typical druglike probes. The new descriptors are not as good as the original descriptors in selecting actives if one considers the average over all probes, but the new descriptors do better for several individual probes. Generally we find that whether one descriptor does better than another varies from probe to probe in a way almost impossible to predict a priori. Most importantly, we find that different descriptors typically select very different sets of actives. Thus it is advantageous to run similarity probes with several types of descriptors.
Article
One of the most commonly used clustering algorithms within the worldwide pharmaceutical industry is Jarvis-Patrick's (J -P) (Jarvis, R. A. IEEE Trans. Comput. 1973, C-22, 1025-1034). The implementation of J-P under Daylight software, using Daylight's fingerprints and the Tanimoto similarity index, can deal with sets of 100 k molecules in a matter of a few hours. However, the J-P clustering algorithm has several associated problems which make it difficult to cluster large data sets in a consistent and timely manner. The clusters produced are greatly dependent on the choice of the two parameters needed to run J-P clustering, such that this method tends to produce clusters which are either very large and heterogeneous or homogeneous but too small. In any case, J-P always requires time-consuming manual tuning. This paper describes an algorithm which will identify dense clusters where similarity within each cluster reflects the Tanimoto value used for the clustering, and, more importantly, where the cluster centroid will be at least similar, at the given Tanimoto value, to every other molecule within the cluster in a consistent and automated manner. The similarity term used throughout this paper reflects the oVerall similarity between two given molecules, as defined by Daylight's fingerprints and the Tanimoto similarity index.
Article
A simple type of substructure called an atom pair is defined in terms of the atomic environments of, and shortest path separations between, all pairs of atoms in the topological representation of a chemical structure. An algorithm is presented for computing atom pairs from such a representation. Two applications of atom pairs to structure-activity problems are described. In the first, a measure of similarity between compounds is defined, and the use of this measure in probing large databases of structures is discussed. In the second, a heuristic technique called trend vector analysis is described. The trend vector summarizes the correlation, within a set of structures, of the occurrence of atom pairs of different types with measured biological activity. These correlations can be used to estimate the biological activity of new compounds. A comparison of trend vector analysis with discriminant plane analysis is presented for one series of compounds.
Article
In this paper, we present a reassessment of the sampling properties of the metric matrix distance geometry algorithm, which is in wide-spread use in the determination of three-dimensional structures from nuclear magnetic resonance (NMR) data. To this end, we compare the conformational space sampled by structures generated with a variety of metric matrix distance geometry protocols. As test systems we use an unconstrained polypeptide, and a small protein (rabbit neutrophil defensin peptide 5) for which only few tertiary distances had been derived from the NMR data, allowing several possible folds of the polypeptide chain. A process called metrization in the preparation of a trial distance matrix has a very large effect on the sampling properties of the algorithm. It is shown that, depending on the metrization protocol used, metric matrix distance geometry can have very good sampling properties'indeed, both for the unconstrained model system and the NMR-structure case. We show that the sampling properties are to a great degree determined by the way in which the first few distances are chosen within their bounds. Further, we present a new protocol (partial metrization) that is computationally more efficient but has the same excellent sampling properties. This novel protocol has been implemented in an expanded new release of the program X-PLOR with distance geometry capabilities.
Article
The rise in circulating ACTH levels after adrenalectomy in the rat is associated with a decrease in CRF receptor-binding capacity in the anterior pituitary. To investigate the role of increased hypothalamic CRF release on pituitary CRF receptor regulation after withdrawal of glucocorticoid feedback by adrenalectomy, the effects of chronic CRF infusion and lesions in the medial basal hypothalamus were studied in the rat. Subcutaneous infusion of CRF at 10, 25, 50, and 100 ng/min for 48 h in intact rats caused dose-dependent increases in plasma ACTH levels from the control value of 32.1 +/- 4.3 to 58.0 +/- 4.9, 82.0 +/- 7.1, 135.5 +/- 11.6, and 149.2 +/- 13.2 pg/ml, respectively. In contrast, the pituitary CRF receptor concentration was reduced by 25.3 +/- 4.5%, 38.3 +/- 2.5%, 43.8 +/- 0.9%, and 45.8 +/- 2.0%, respectively. Intravenous infusion of increasing doses of CRF caused a similar increase in plasma ACTH levels, which became maximum at the lowest infusion dose (32.4 +/- 5.4, 138.5 +/- 12.3, 162.0 +/- 18.3, and 167 +/- 19.1 pg/ml for control and 10, 50, and 100 ng/min CRF, respectively). Pituitary CRF receptor concentration was again decreased after iv CRF infusion [by 42 +/- 6.2% with the lowest dose (10 ng/min)], with no further reduction after infusion of 50 and 100 ng/min (49.0 +/- 6.8% and 26.0 +/- 6.2%, respectively)]. The decrease in pituitary CRF receptors after CRF infusion was accompanied by a decrease in CRF-stimulated adenylate cyclase activity, with a 10- to 100-fold increase in the concentration of CRF required for threshold stimulation. In cultured pituitary cells prepared from animals infused with 50 ng/min CRF for 48 h, maximum CRF-stimulated ACTH release was reduced by 29 +/- 3.2% (P less than 0.01; n = 3), with no significant change in sensitivity to CRF (ED50, 0.6 +/- 0.5 and 1.0 +/- 0.5 nM CRF for control and CRF infusion, respectively). The role of endogenous CRF in adrenalectomy-induced pituitary CRF receptor down-regulation was also studied in rats with medial basal hypothalamic deafferentation. The marked loss of pituitary CRF receptors after adrenalectomy was completely prevented by such hypothalamic lesioning, indicating that receptor down-regulation was dependent on the release of CRF or/and other hypothalamic factors. The data demonstrate that while increased CRF levels result in down-regulation and desensitization of pituitary CRF receptors, the differences between adrenalectomy and CRF infusion indicate that additional regulatory factors are involved in the modulation of CRF receptor content and activity after adrenalectomy.
Article
This article has no abstract; the first 100 words appear below. To the Editor: The recent availability of the newly sequenced human corticotropin-releasing factor holds promise in furthering the understanding of the pathophysiology underlying hypercortisolism linked to depression.¹ Current research suggests that corticotropin-releasing factor is not only a key hormone in the regulation of corticotropin but may also act in the brain to initiate a variety of physiologic responses characteristic for stress.² We have compared the secretory patterns of cortisol with the corticotropin and Cortisol responses to human corticotropin-releasing factor in 12 unmedicated patients (aged 36 to 69) with a major depressive disorder (primary and endogenous) and 9 healthy controls (aged . . .
Article
In 33 cats the projections of different parts of the mesencephalon to the facial nucleus were studied with the aid of the autoradiographical tracing method. The results indicate the existence of many different mesencephalo-facial pathways. The dorsomedial facial subnucleus, containing motoneurons innervating ear muscles, receives afferents from 4 different mesencephalic areas: a, the most rostral mesencephalic reticular formation; b, the nucleus of Darkschewitsch and/or the ventral part of the rostral PAG; c, the interstitial nucleus of Cajal and/or the mesencephalic tegmentum dorsomedial to the red nucleus. These areas project bilaterally by way of an ipsilateral medial tegmental pathway. The medial part of the deep tectum. This area projects bilaterally by way of the tecto-spinal tract. The lateral mesencephalic tegmentum close to the parabigeminal nucleus. This area projects mainly contralaterally by way of a separate contralateral lateral tegmental fiber bundle. The mesencephalic tegmentum just dorsolateral to the red nucleus and perhaps from the dorsolateral red nucleus itself. This area projects contralaterally by way of the rubrospinal tract. The intermediate facial subnucleus containing motoneurons innervating the muscle around the eye, receives afferents from two different mesencephalic areas: The dorsal part of the rostral as well as caudal red nucleus (but not from its caudal pole) and from the dorsally adjoining mesencephalic tegmentum including the area of the nucleus of Darkschewitsch and the interstitial nucleus of Cajal. These areas project contralaterally by way of the contralateral rubrospinal tract. The nucleus of the optic tract and/or the olivary pretectal nucleus. This area projects contralaterally by way of a contralateral medial tegmental pathway. The lateral and ventrolateral facial subnuclei containing motoneurons innervating the muscles around the mouth receive afferents from two different mesencephalic areas: The lateral part of the deep tectal layers. This area projects contralaterally by way of the tecto-spinal tract. The nucleus raphe dorsalis and perhaps the nucleus centralis superior. This area projects by way of the lateral tegmentum of caudal pons and medulla.
Article
Extended electron distributions (XEDs) have been added to the molecular mechanics Coulombic term and applied to a selection of intermolecular interactions. The results from this approach have been compared with the commonly used atom-centred charges and more rigorous AM1-derived natural atom orbital point densities. The use of XEDs generally improves the simulation of experimental and ab initio results over the other two charge allocations and corrects geometries in those cases for which the others yield wrong results.
Article
Specially expanded databases containing three-dimensional structures are created to enhance the utility of docking methods to find new leads, i.e., active compounds of pharmacological interest. The expansion is based on the automatic generation of a set of maximally dissimilar conformations. The ligand receptor system of methotrexate and dihydrofolate reductase is used to demonstrate the feasibility of creating flexibases and their utility in docking studies.
Article
The quality of molecular electrostatic maps generated by non-quantum mechanical methods has been improved using extended electron distributions. Further simplification has been achieved by distilling these maps down to their energy extrema. A new means of defining surface interaction has been added and the resulting composite map has been plotted for a limited number of low-lying conformers of a series of agonists and antagonists of the H2 and H3 receptors and 5-HT1A and 5-HT1D receptors. The results from the cross-comparison of these maps indicate their ability to distinguish the specific receptor. Interesting consequences of the method are that structural overlay is irrelevant, that several conformations may contribute to the overall binding pattern and that lesser pharmacological activities may be deduced from the results.
Article
The comparative molecular field analysis steric field of a single "topomeric" conformer is introduced as a molecular diversity descriptor particularly useful for combinatorial chemistry involving variations around a fixed "core". Using this new descriptor, 736 commercially available thiols are divided into 231 bioisosteric clusters, whose compositions agree at least as well with medicinal chemical experience and intuition as do clusters derived from Tanimoto differences between 2D fragment occurrences. However, in practice topomeric steric fields complement 2D fingerprints, being the two most frequently useful descriptors yet found for neighborhood-based design of combinatorial libraries.
Article
Corticotrophin-releasing factor (CRF) acts within both the brain and the periphery to coordinate the overall response of the body to stress. The involvement of the CRF systems in a variety of both CNS and peripheral disease states has stimulated great interest in this peptide as a potential site of therapeutic intervention. The recent cloning of multiple CRF receptor subtypes has precipitated a new era in CRF research that has allowed precise molecular, pharmacological and anatomical examination of mammalian CRF receptors. In this article, Derek Chalmers and colleagues highlight the major differences between the two classes of CRF receptors, CRF1 and CRF2, and a functionally related CRF-binding protein, and discuss the relevance of these sites to the ongoing development of CRF-based therapeutics.
Article
The syntheses of a centrally active nonpeptide CRF1 receptor antagonist 2, butylethyl[2,5-dimethyl-7-(2,4,6-trimethylphenyl)-7H-pyrrolo [2,3-d]pyrimidin-4-yl]amine (CP-154,526), and its analogs 11-14 and [3H]-2 are reported. The in vitro CRF1 receptor binding affinity in the series 2, the pharmacokinetic properties of 2 in rats, and the anxiolytic-like effects of orally administered 2 are presented.
Article
Two CRF receptors, CRFR1 and CRFR2, have recently been cloned and characterized. CRFR1 shares 70% sequence identity with CRFR2, yet has much higher affinity for rat/human CRF (r/hCRF) than CRFR2. As a first step toward understanding the interactions between rat/human CRF and its receptor, the regions that are involved in receptor-ligand binding and/or receptor activation were determined by using chimeric receptor constructs of the two human CRFR subtypes, CRFR1 and CRFR2, followed by generating point mutations of the receptor. The EC50 values in stimulation of intracellular cAMP of the chimeric and mutant receptors for the peptide ligand were determined using a cAMP-dependent reporter system. Three regions of the receptor were found to be important for optimal binding of r/hCRF and/or receptor activation. The first region was mapped to the junction of the third extracellular domain and the fifth transmembrane domain; substitution of three amino acids of CRFR1 in this region (Val266, Tyr267, and Thr268) by the corresponding CRFR2 amino acids (Asp266, Leu267, and Val268) increased the EC50 value by approximately 10-fold. The other two regions were localized to the second extracellular domain of the CRFR1 involving amino acids 175-178 and His189 residue. Substitutions in these two regions each increased the EC50 value for r/hCRF by approximately 7- to 8-fold only in the presence of the amino acid 266-268 mutation involving the first region, suggesting that their roles in peptide ligand binding might be secondary.
Article
In this paper we present a new method for evaluating molecular similarity between small organic compounds. Instead of a linear representation like fingerprints, a more complex description, a feature tree, is calculated for a molecule. A feature tree represents hydrophobic fragments and functional groups of the molecule and the way these groups are linked together. Each node in the tree is labeled with a set of features representing chemical properties of the part of the molecule corresponding to the node. The comparison of feature trees is based on matching subtrees of two feature trees onto each other. Two algorithms for tackling the matching problem are described throughout this paper. On a dataset of about 1000 molecules, we demonstrate the ability of our approach to identify molecules belonging to the same class of inhibitors. With a second dataset of 58 molecules with known binding modes taken from the Brookhaven Protein Data Bank, we show that the matchings produced by our algorithms are compatible with the relative orientation of the molecules in the active site in 61% of the test cases. The average computation time for a pair comparison is about 50 ms on a current workstation.
Article
A new method SQ has been developed to provide fast, automatic, and objective pairwise three-dimensional molecular alignments. SQ uses an atom-based clique-matching step followed by an alignment scoring function that has been parametrized to recognize pharmacologically relevant atomic properties. Molecular alignments from SQ are consistent with known drug-receptor interactions. We demonstrate this with six pairs of receptor-ligand complexes from the Brookhaven Protein Data Bank. The SQ-generated alignment of one isolated ligand onto another is shown to approximate the alignment of the ligands when the receptors are superimposed. SQ appears to be better than its predecessor SEAL (Kearsley and Smith, Tetrahedron Comput. Methodol. 1990, 3, 615-633) in this regard. SQ has been tailored so that, given one molecule as a probe, it can be used to routinely scan large chemical databases for which precomputed conformations have been stored. The SQ score, a measure of 3D similarity of each candidate molecule to the probe, can be used to rank compounds for the purposes of chemical screening. We demonstrate this with three probes (a thrombin inhibitor, an HIV protease inhibitor, and a model for angiotensin II). In each case SQ can preferentially select from the MDDR database other compounds with the same activity as the probe. We further show, using the angiotensin example, how SQ can identify topologically diverse compounds with the same activity.
Article
The principle of bioisosterism-similarly shaped molecules are more likely to share biological properties than are other molecules-has long helped to guide drug discovery. An algorithmic implementation of this principle, based on shape comparisons of a single rule-generated "topomer" conformation per molecule, had been found to be the descriptor most consistently predictive of similar biological properties, in retrospective studies, and also to be well-suited for searching large (>10(12)) "virtual libraries" of potential reaction products. Therefore a prospective trial of this shape similarity searching method was carried out, with synthesis of 425 compounds and testing of them for inhibition of binding of angiotensin II (A-II). The 63 compounds that were identified by shape searching as most similar to any of four query structures included all of the seven compounds found to be highly active, with none of the other 362 structures being highly active (p < 0.001). Additional consistent relations (p < 0.05) were found, among all 425 compounds, between the degree of shape similarity to the nearest query structure and the frequency of various levels of observed activity. Known "SAR" (rules specifying structural features required for A-II antagonism) were also regenerated within the biological data for the 63 shape similar structures.
Article
A chemically advanced template search (CATS) based on topological pharmacophore models has been developed as a technique for virtual screening. This technique has successfully identified novel potent Ca(2+) antagonists (such as 2) that have a similar activity to 1 (a known T-channel blocking agent) in a library of several hundred thousand compounds on the basis of a correlation vector representation.
Article
Flexible database docking with DOCK 4.0 has been evaluated for its ability to retrieve biologically active molecules from a database of approximately 1,000 compounds with known activities against thrombin and the progesterone receptor. The retrieval of known actives and chemically similar but inactive molecules was monitored as a function of conformational and orientational sampling. The largest enrichment of actives among the 10% highest ranking molecules is obtained when only five conformations are used to seed the next round of ligand reconstruction and limited sampling is applied to place the base fragment in the binding site. The performance of energy and chemical scoring, as implemented in DOCK 4.0, was found to depend on the protein used for docking. For the progesterone receptor, energy scoring yields the largest enrichments (64%) in terms of actives retrieved among the 10% top scoring molecules, while chemical scoring performs best for thrombin (94%). With the exception of the application of energy scoring to the progesterone receptor, both energy-based scoring schemes applied in this study do not discriminate well between true actives and chemically similar but inactive compounds. In conclusion, flexible docking is able to effectively prioritize high-throughput screening databases, using less conformational sampling than normally required for appropriate reconstruction of protein-ligand complexes. The more subtle discrimination between chemically similar classes of active and inactive compounds remains, however, problematic.
Article
Clinical and preclinical data suggest that unrestrained secretion of corticoctropin-releasing hormone (CRH) in the CNS produces several signs and symptoms of depression and anxiety disorders through continuous activation of CRH(1) receptors. This led to the development of drugs that selectively antagonize CRH(1) receptors suppressing anxiety-like behavior in rats and also in monkey models of anxiety. These findings led to a clinical development program exploring the antidepressive potential of R121919, a water-soluble pyrrolopyrimidine that binds with high affinity to human CRH(1) receptors and is well absorbed in humans. This compound was administered to 24 patients with a major depressive episode primarily in order to investigate whether its endocrine mode of action compromises the stress-hormone system or whether other safety and tolerability issues exist. The patients were enrolled in two dose-escalation panels: one group (n=10) where the dose range increased from 5-40 mg and another group (n=10) where the dose escalated from 40 to 80 mg within 30 days each. Four patients dropped out because of withdrawal of consent to participate (three cases) or worsening of depressive symptomatoloy in one case. We found that R121919 was safe and well tolerated by the patients during the observation period. Moreover, the data suggested that CRH(1)-receptor blockade does not impair the corticotropin and cortisol secretory activity either at baseline or following an exogenous CRH challenge. We also observed significant reductions in depression and anxiety scores using both, patient and clinician ratings. These findings, along with the observed worsening of affective symptomatology after drug discontinuation, suggests that the pharmacological principle of CRH(1)-receptor antagonism has considerable therapeutic potential in the treatment and the prevention of diseases where exaggerated central CRH activity is present at baseline or following stress exposure.
Article
Corticotropin releasing hormone (CRH, sometimes known as CRF) is an endogenous 41 amino acid peptide that has been implicated in the onset of pregnancy, the 'fight or flight' response, in addition to a large number of physiological disorders. Recently, medicinal chemists have developed a number of potent and selective compounds that show promise in a vast array of therapeutic uses. Herein we review the current status of research.
A knowledge-based approach for generating conformations of molecules has been developed. The method described here provides a good sampling of the molecule's conformational space by restricting the generated conformations to those consistent with the reference database. The present approach, internally named et for enumerate torsions, differs from previous database-mining approaches by employing a library of much larger substructures while treating open chains, rings, and combinations of chains and rings in the same manner. In addition to knowledge in the form of observed torsion angles, some knowledge from the medicinal chemist is captured in the form of which substructures are identified. The knowledge-based approach is compared to Blaney et al.'s distance geometry (DG) algorithm for sampling the conformational space of molecules. The structures of 113 protein-bound molecules, determined by X-ray crystallography, were used to compare the methods. The present knowledge-based approach (i) generates conformations closer to the experimentally determined conformation, (ii) generates them sooner, and (iii) is significantly faster than the DG method.