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Identification of Covalent Binding Sites Targeting Cysteines Based on Computational Approaches
Abstract
Covalent drugs have attracted increasing attention in recent years due to good inhibitory activity and selectivity. Targeting noncatalytic cysteines with irreversible inhibitors is a powerful approach for enhancing pharmacological potency and selectivity because cysteines can form covalent bonds with inhibitors through their nucleophilic thiol groups. Most human kinases have multiple noncatalytic cysteines within the active site. Thus, it will be very useful if we could predict the cysteines that are likely to form covalent bonds when designing irreversible inhibitors. In this work, FTMap was firstly applied to check its ability in predicting covalent binding site defined as the region where covalent bonds are formed between cysteines and irreversible inhibitors. However, even though it has excellent performance in detecting the hot spots within the binding pocket and its hydrogen bond interaction frequency analysis could give us some interesting instructions, FTMap's ability in predicting covalent binding pockets is still limited. Thus, we proposed a simple but useful covalent fragment probing approach and showed that it successfully predicted the covalent binding site of seven targets. By adopting a distance-based method, we observed that the closer the nucleophiles of covalent warheads are to the thiol group of a cysteine, the higher possibility a cysteine is prone to form a covalent bond. The results may provide insights into designing irreversible inhibitors against this kind of targets.
... Theoretically and experimentally, it has been proposed that covalent systems with no direct covalent bonds could have the potential to induce covalent linkage if the electrophilic warhead group and the side chain of the nucleophilic receptor target are found in close proximity (Fig. 4) [32,[100][101][102]. While there have been developments of covalent-docking protocols to simulate a covalent biomolecular system, some conventional noncovalent-docking programs/ protocols have also been employed in the modeling of covalent binders that involves assessing the bond distance between the pre-reactive covalent warhead of the compound and the nucleophilic protein group. ...
... Following that, flexible docking investigations were conducted on a targeted approved covalent drug library consisting of 32 compounds with a variety of electrophilic functional groups. Among them, the calculations identified four compounds capable of interacting with the protein's binding site and, secondly, their potential to act as covalent inhibitors, as the distance between the sulfur and the electrophilic center varied between 2.98 and 3.78 Å (values less than 4 Å indicating a complex capable of forming a covalent bond) [101]. ...
The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for
covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular
docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation
of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug
discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking
community about the realization of covalent docking and the existence of suitable programs to make their future virtualscreening
events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical
description of the functionality of covalent-docking programs down to selecting the ‘best’ program to consult with during
a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on
how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the
growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking
pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their
work for translational research.
... Theoretically and experimentally, it has been proposed that covalent systems with no direct covalent bonds could have the potential to induce covalent linkage if the electrophilic warhead group and the side chain of the nucleophilic receptor target are found in close proximity (Fig. 4) [32,[100][101][102]. While there have been developments of covalent-docking protocols to simulate a covalent biomolecular system, some conventional noncovalent-docking programs/ protocols have also been employed in the modeling of covalent binders that involves assessing the bond distance between the pre-reactive covalent warhead of the compound and the nucleophilic protein group. ...
... Following that, flexible docking investigations were conducted on a targeted approved covalent drug library consisting of 32 compounds with a variety of electrophilic functional groups. Among them, the calculations identified four compounds capable of interacting with the protein's binding site and, secondly, their potential to act as covalent inhibitors, as the distance between the sulfur and the electrophilic center varied between 2.98 and 3.78 Å (values less than 4 Å indicating a complex capable of forming a covalent bond) [101]. ...
The continuous approval of covalent drugs in recent years for the treatment of diseases has led to an increased search for covalent agents by medicinal chemists and computational scientists worldwide. In the computational parlance, molecular docking which is a popular tool to investigate the interaction of a ligand and a protein target, does not account for the formation of covalent bond, and the increasing application of these conventional programs to covalent targets in early drug discovery practice is a matter of utmost concern. Thus, in this comprehensive review, we sought to educate the docking community about the realization of covalent docking and the existence of suitable programs to make their future virtual-screening events on covalent targets worthwhile and scientifically rational. More interestingly, we went beyond the classical description of the functionality of covalent-docking programs down to selecting the ‘best’ program to consult with during a virtual-screening campaign based on receptor class and covalent warhead chemistry. In addition, we made a highlight on how covalent docking could be achieved using random conventional docking software. And lastly, we raised an alert on the growing erroneous molecular docking practices with covalent targets. Our aim is to guide scientists in the rational docking pursuit when dealing with covalent targets, as this will reduce false-positive results and also increase the reliability of their work for translational research.
Graphical abstract
... Therefore, reactive cysteine residues at the PPI site are considered as a common characteristic for the design of covalent PPI inhibitors. Computational tools can detect covalent binding site through several methods: (1) binding site prediction, (2) hydrogen bond frequency analysis, and (3) covalent binding site detection [55]. Meanwhile, comprehensive databases including targetable cysteine and known covalent inhibitors can be manually curated [54][55][56][57]. ...
... Computational tools can detect covalent binding site through several methods: (1) binding site prediction, (2) hydrogen bond frequency analysis, and (3) covalent binding site detection [55]. Meanwhile, comprehensive databases including targetable cysteine and known covalent inhibitors can be manually curated [54][55][56][57]. However, it should be noted that covalent inhibitors may modify many available residues in a target, and some proteins may be more susceptible to this than others. ...
Protein-protein interactions (PPIs) are central to a variety of biological processes, and their dysfunction is implicated in the pathogenesis of a range of human diseases, including cancer. Hence, the inhibition of PPIs has attracted significant attention in drug discovery. Covalent inhibitors have been reported to achieve high efficiency through forming covalent bonds with cysteine or other nucleophilic residues in the target protein. Evidence suggests that there is a reduced risk for the development of drug resistance against covalent drugs, which is a major challenge in areas such as oncology and infectious diseases. Recent improvements in structural biology and chemical reactivity have enabled the design and development of potent and selective covalent PPI inhibitors. In this review, we will highlight the design and development of therapeutic agents targeting PPIs for cancer therapy.
... A ligand can form a covalent bond with target residues (commonly Cys, Ser, and Lys, but there are other cases as well) upon binding, which imposes strict constraints on the binding site detection problem. There are several databases of covalent agents, including Cova-lentInDB (Du et al., 2021) and CovPDB (Gao et al., 2022), and there are methods for predicting the ability of cysteines to form a covalent bond with ligands ( Zhang et al., 2016( Zhang et al., , 2017Zhao et al., 2017;Du et al., 2022;Gao and Günther, 2023). Other examples include methods to predict macromolecular binding sites, such as protein-nucleic acids ( Hendrix et al., 2021;Wei et al., 2022;Yuan et al., 2022a;Liu and Tian, 2023;Roche et al., 2023;Song et al., 2023;Zhu and Yu, 2023) or protein-protein (Fout et al., 2017;Gainza et al., 2020;Dai and Bailey-Kellogg, 2021;Renaud et al., 2021;Sverrisson et al., 2021;Tubiana et al., 2022;Gao et al., 2023;Jha et al., 2023;Krapp et al., 2023). ...
Binding sites are key components of biomolecular structures, such as proteins and RNAs, serving as hubs for interactions with other molecules. Identification of the binding sites in macromolecules is essential for structure-based molecular and drug design. However, experimental methods for binding site identification are resource-intensive and time-consuming. In contrast, computational methods enable large-scale binding site identification, structure flexibility analysis, as well as assessment of intermolecular interactions within the binding sites. In this review, we describe recent advances in binding site identification using machine learning methods; we classify the approaches based on the encoding of the macromolecule information about its sequence, structure, template knowledge, geometry, and energetic characteristics. Importantly, we categorize the methods based on the type of the interacting molecule, namely, small molecules, peptides, and ions. Finally, we describe perspectives, limitations, and challenges of the state-of-the-art methods with an emphasis on deep learning-based approaches. These computational approaches aim to advance drug discovery by expanding the druggable genome through the identification of novel binding sites in pharmacological targets and facilitating structure-based hit identification and lead optimization.
... Covalent bonding imparts an inherent irreversibility, enhancing inhibitory activity and selectivity [22][23][24][25][26]. This study aims to discover and characterize covalent smallmolecule stabilizers for the clinically significant p53 Y220C mutation. ...
The p53 Y220C mutation, a prevalent structural variant in human cancers, compromises DNA binding and tumor suppressor functions by destabilizing the protein structure. Leveraging a combined approach of structure-based virtual screening, molecular dynamics simulations, and in vitro assays, we have identified C8, a racemic compound with an indole core and α, β-unsaturated carbonyl groups, as a covalent stabilizer for p53 Y220C. Protein thermal shift and homogeneous time-resolved fluorescence assays confirmed that C8 and its analogs selectively bind to p53 Y220C and restore its DNA binding ability. Subsequent molecular dynamics simulations and structure–activity relationship analyses showed that both enantiomers of C8 form covalent bonds with Cys124 and Cys220, stabilizing the mutant structure. C8 and its analogs emerge as promising lead candidates for restoring the Y220C mutant's transcriptional function, highlights the potential of this scaffold for further optimization into p53 Y220C-targeted therapeutics.
Graphical abstract
... Despite this fact, protein targets can have multiple Cys residues, or even more than one Cys within the protein active site. Computational approaches to identify accessible Cys residues with appropriate reactivities for covalent inhibition have been published [21,22]. ...
Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism. However, the models from these studies are often linear regression equations and can have limitations associated with their usage. Applications of machine learning (ML) models to predict covalent warhead reactivities with QM descriptors are not extensively seen in the literature. This study uses QM descriptors, calculated at different levels of theory, to train ML models to predict reactivities of covalent acrylamide warheads. The QM/ML models are compared with linear regression models built upon the same QM descriptors and with ML models trained on structure-based features like Morgan fingerprints and RDKit descriptors. Experiments show that the QM/ML models outperform the linear regression models and the structure-based ML models, and literature test sets demonstrate the power of the QM/ML models to predict reactivities of unseen acrylamide warhead scaffolds. Ultimately, these QM/ML models are effective, computationally feasible tools that can expedite the design of new covalent inhibitors.
... Most of the work on covalent kinase inhibitors has focused on cysteine targeting covalency, and as such there is a large and growing body of work aimed at mapping the 'cysteineome'identifying which kinases within the kinome have a cysteine which is likely to be targetable [216][217][218][219][220] (Supplementary Figure S9). The identification of the location of these cysteines (Supplementary Table S9) has made it possible to make informed choices for the development of cysteine targeting covalent inhibitors (Supplementary Table S9). ...
There are over 500 human kinases ranging from very well-studied to almost completely ignored. Kinases are tractable and implicated in many diseases, making them ideal targets for medicinal chemistry campaigns, but is it possible to discover a drug for each individual kinase? For every human kinase, we gathered data on their citation count, availability of chemical probes, approved and investigational drugs, PDB structures, and biochemical and cellular assays. Analysis of these factors highlights which kinase groups have a wealth of information available, and which groups still have room for progress. The data suggest a disproportionate focus on the more well characterized kinases while much of the kinome remains comparatively understudied. It is noteworthy that tool compounds for understudied kinases have already been developed, and there is still untapped potential for further development in this chemical space. Finally, this review discusses many of the different strategies employed to generate selectivity between kinases. Given the large volume of information available and the progress made over the past 20 years when it comes to drugging kinases, we believe it is possible to develop a tool compound for every human kinase. We hope this review will prove to be both a useful resource as well as inspire the discovery of a tool for every kinase.
... According to the Swiss ADME website, online physicochemical descriptions of substances, including their absorption, distribution, metabolism, elimination, and toxicity, are predicted. To increase the success rate of medication research and lessen the issue of money being lost in the later stages of drug development, these virtual screening and compound optimization filtering tools are required[13][14][15]. Virtual screening is done with different softwares that is represented infigure 6. ...
... Usually, the ability to detect protein− ligand pockets does not extend beyond 40% for most methods. 8 Modern approaches do not increase the prediction accuracy significantly compared with nonmachine learning algorithms, especially for the identification of previously uncharacterized, shallow solvent-exposed, 9 and allosteric binding sites 10 as well as sites of covalent inhibitors binding 11 and cavities within protein−protein interface (PPI) regions. 12 SiteRadar is a graph neural network (GNN)-based approach for identifying protein−ligand-binding sites. ...
Identifying ligand-binding sites on the protein surface is a crucial step in the structure-based drug design. Although multiple techniques have been proposed, including those using machine learning algorithms, the existing solutions do not provide significant advantages over nonmachine learning approaches and there is still a big room for improvement. The low ability to identify protein-ligand-binding sites makes available approaches inapplicable to automated drug design. Here, we present SiteRadar, a new algorithm for mapping cavities that are likely to bind a small-molecule ligand. SiteRadar shows higher accuracy in binding site identification compared with FPocket and PUResNet. SiteRadar demonstrates an ability to detect up to 74% of true ligand-binding sites according to the top N + 2 metric and usually covers approximately 80% of ligand atoms. Therefore, SiteRadar can be regarded as a promising solution for implementation into algorithms for automated drug design.
... An intrinsic limitation of ligand-based methods is represented (by definition) by the absence of the receptor. As previously stated, the reaction partner (the targeted amino acid together with its environment in the binding pocket) and mechanism can significantly affect covalent bond formation [87]. Structure-based approaches can address this aspect. ...
Fragment based drug discovery has long been used for the identification of new ligands and interest in targeted covalent inhibitors has continued to grow in recent years, with high profile drugs such as osimertinib and sotorasib gaining FDA approval. It is therefore unsurprising that covalent fragment-based approaches have become popular and have recently led to the identification of novel targets and binding sites, as well as ligands for targets previously thought to be ‘undruggable’. Understanding the properties of such covalent fragments is important, and characterizing and/or predicting reactivity can be highly useful. This review aims to discuss the requirements for an electrophilic fragment library and the importance of differing warhead reactivity. Successful case studies from the world of drug discovery are then be examined.
... Binding site identification of the target protein helps in determination of proteinligand interaction, hydrogen bond formation, post docking dynamics, complex free energy determination, etc. that will lead to identify the best pharmacophore of the ligand. X-ray crystallography helps in determination of binding site in the target protein [26,27]. The information regarding the binding site can be obtained from co-crystallized proteins with their substrates or known inhibitors [28]. ...
Various challenges such as cost and time consumption problems associated with traditional drug design and development process have been overcome with in silico approaches known as computer-aided drug design (CADD). It involves the use of various structure-based or ligand-based computational drug designing approaches to invent, modify, and analyse various biologically active molecules or drugs. CADD approaches can speed up the possibilities of identifying molecules with desirable characteristics and features, propel hit-to-lead development, and reduce the chances of failure over the many obstacles of early preclinical studies. The two types of computational drug designing approaches are structure-based drug design (SBDD) and ligand-based drug design (LBDD). The information generated through these approaches provides an idea of the electronic properties (electrostatic potential, polarizability, etc.) required in desired molecule that will influence binding affinity and helps in optimization of known ligands for designing and development of new molecules with improved activity and safety profiles. This chapter focuses on the different computational approaches such as molecular docking, virtual screening, homology modelling, pharmacophore development, and quantitative structure-activity relationship (QSAR) as well as new developments in practical aspects and their role in pharmaceutical applications. This chapter also highlights the clinically approved drugs developed using CADD strategies.KeywordsComputer-Aided Drug DesignMolecular ModellingQSARHomology modellingStructure-based drug designLigand-based drug design
... In a second time, examination of the potentialities of the covalent inhibition of this protein due to the formation of a covalent adduct M Pro -I can be examined. For this, the location of the electrophilic moiety of compounds, in particular the distance between the electrophilic center and the thiol of Cys145 has to be adequate (Zhang et al., 2016) (Fig. 2). As a consequence, we used standard docking experiments targeting Cys145 with a cutoff of 4Å as a theoretical study (Choi et al., 2016;Lin et al., 2011). ...
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 which has infected millions of people worldwide. The main protease of SARS-CoV-2 (MPro) has been recognized as a key target for the development of antiviral compounds. Taking advantage of the X-ray crystal complex with reversible covalent inhibitors interacting with the catalytic cysteine 145 (Cys145), we explored flexible docking studies to select alternative compounds able to target this residue as covalent inhibitors. First, docking studies of three known electrophilic compounds led to results consistent with co-crystallized data validating the method for SARS-CoV-2 MPro covalent inhibition. Then, libraries of soft electrophiles (overall 41 757 compounds) were submitted to docking-based virtual screening resulting in the identification of 17 molecules having their electrophilic group close to the Cys145 residue. We also investigated flexible docking studies of a focused approved covalent drugs library including 32 compounds with various electrophilic functional groups. Among them, the calculations resulted in the identification of four compounds, namely dimethylfumarate, fosfomycin, ibrutinib and saxagliptin, able first, to bind to the active site of the protein and second, to form a covalent bond with the catalytic cysteine.
... Nevertheless, selection of promising covalent hits from large libraries has been achieved with immense reduction in wet lab costs, as evidenced by numerous recent publications [120][121][122]. Moreover, in silico prediction tools represent a straightforward means to detect potential pseudopockets on a protein of interest; hence the increasing number of works relying on these calculations [123,124] and the appearance of free web servers such as the FTMap family [125]. Previously undruggable protein sites are now being reconsidered for TCI if they lie in the vicinity of a nucleophilic amino acid, and virtual interrogation is not uncommonly the first step in this re-evaluation process. ...
In the first decade of targeted covalent inhibition, scientists have successfully reversed the previous trend that had impeded the use of covalent inhibition in drug development. Successes in the clinic, mainly in the field of kinase inhibitors, are existing proof that safe covalent inhibitors can be designed and employed to develop effective treatments. The case of KRAS G12C covalent inhibitors entering clinical trials in 2019 has been among the hottest topics discussed in drug discovery, raising expectations for the future of the field. In this perspective, an overview of the milestones hit with targeted covalent inhibitors, as well as the promise and the needs of current research, are presented. While recent results have confirmed the potential that was foreseen, many questions remain unexplored in this branch of precision medicine.
... The determination of the architecture of the active site of the macromolecule can provide clear information about the protein-ligand interaction phenomenon, post-docking dynamics, hydrogen bond formation, and free energies of the complex [12]. ...
Cancers are the leading cause of deaths worldwide. In 2018, an estimated 18.1 million new cancer cases and 9.6 million cancer-related deaths occurred globally. Several previous studies have shown that the enzyme, leucine aminopeptidase is involved in pathological conditions such as cancer. On the basis of the knowledge that isoquinoline alkaloids have antiproliferative activity and inhibitory activity towards leucine aminopeptidase, the present study was conducted a study which involved database search, virtual screening, and design of new potential leucine aminopeptidase inhibitors with a scaffold based on 3,4-dihydroisoquinoline. These compounds were then filtered through Lipinski’s “rule of five,” and 25 081 of them were then subjected to molecular docking. Next, three-dimensional quantitative structure-activity relationship (3D-QSAR) study was performed for the selected group of compounds with the best binding score results. The developed model, calculated by leave-one-out method, showed acceptable predictive and descriptive capability as represented by standard statistical parameters r² (0.997) and q² (0.717). Further, 35 compounds were identified to have an excellent predictive reliability. Finally, nine selected compounds were evaluated for drug-likeness and different pharmacokinetics parameters such as absorption, distribution, metabolism, excretion, and toxicity. Our methodology suggested that compounds with 3,4-dihydroisoquinoline moiety were potentially active in inhibiting leucine aminopeptidase and could be used for further in-depth in vitro and in vivo studies.
... The determination of the binding site of target macromolecular can provide clear information about the proteinligand interaction phenomenon, post-docking dynamics, hydrogen bond formation, free energies of the complex, and so on, which in turn can calculate the best pharmacophores of the novel ligand [43]. Binding sites in the target macromolecular can be experimentally determined, for example using site-directed mutagenesis or X-ray crystallography [44]. ...
Over the past ten years, the number of three-dimensional protein structures identified by advanced science and technology increases, and the gene information becomes more available than ever before as well. The development of computing science becomes another driving force which makes it possible to use computational methods effectively in various phases of the drug design and research. Now Structure-based drug design (SBDD) tools are widely used to help researchers to predict the position of small molecules within a three-dimensional representation of the protein structure and estimate the affinity of ligands to target protein with considerable accuracy and efficiency. They also accelerate discovery speed of potent drug and reduce the cost and times for drug research. Here we present an overview of SBDD used in drug discovery and highlight its recent successes and major challenges to current SBDD methodologies.
... This is the extended crucial step to the previous step in this approach, because the binding site has a major part in deciding the fate of the result and is playing the exclusive role in PTP targeting. In SBVS, the binding site projects the protein-ligand interaction phenomenon, post-docking dynamics, hydrogen bond formation, and free energies of the complex [108]. The best calculated pharmacophores of the binding site determine the fate of the novel inhibitor. ...
Phosphorylation is a critical mechanism in biological systems and it is estimated that phosphorylation is indispensable for about 30% of key biological activities such as cell cycle progression, migration, and division. It is synergistically balanced by kinases and phosphatases, and any deviation from this balance leads to diseased conditions. Pathway or biological activity based abnormalities in phosphorylation and the type of involved phosphatase influence the outcome and cause diverse diseases ranging from diabetes, rheumatoid arthritis, and numerous cancers. Protein tyrosine phosphatases (PTPs) are of prime importance in the process of dephosphorylation and catalyze several biological functions. Abnormal protein tyrosine phosphatase (PTP) activities are reported to result in several diseases in humans. Consequently, there is an increased demand for potential PTP inhibitory small molecules. Several strategies in structure-based drug designing techniques for potential inhibitory small molecules of PTPs have been explored along with traditional drug designing methods in order to overcome the hurdles in PTP inhibitor discovery. In this review, we discuss druggable PTPs and structure based virtual screening efforts for successful inhibitor designing of them.
Human Papillomavirus (HPV) is linked to multiple cancers, most significantly cervical cancer, for which HPV infection is associated with nearly all cases. Essential to the oncogenesis of HPV is the function of the viral protein E6 and its role in degrading the cell cycle regulator p53. Degradation of p53, and the resultant loss of cell cycle control, is mediated by E6 recruitment of the E3 ubiquitin ligase E6AP and subsequent ubiquitination of p53. Here, we report the design of a stapled peptide that mimics the LxxLL α-helical domain of E6AP to bind and covalently label a cysteine residue specific to HPV-16 E6. Several acrylamide- and haloacetamide-based warheads were evaluated for reactivity and specificity, and a panel of hydrocarbon-stapled peptides was evaluated for enhanced binding affinity and increased proteolytic stability. Structure-based modeling was used to rationalize the observed trends in the reactivity of the warheads and the impact of the hydrocarbon staple position on the binding affinity of the stapled peptides. The development of a proteolytically stable and reactive peptide represents a new class of peptide-based inhibitors of protein–protein interactions with a potential therapeutic value toward HPV-derived cancers.
Fluorophore integration into proteins within living cells is essential for exploring proteins in their natural environment. Bruton's tyrosine kinase (BTK), is a validated oncology target and is crucial for B...
Covalent inhibitors have been a rapidly growing field in drug discovery due to their therapeutic potential and unique advantages in cancer therapy. As opposed to noncovalent inhibitory drugs, covalent inhibitors reversibly or irreversibly modify proximal nucleophilic amino acid residues on proteins, aiming to selectively recognize and bind to protein targets and addressing some of the challenges faced by noncovalent drugs. Most successful targeted covalent inhibitors depend primarily on binding‐site cysteine residues, but this has limitations for certain protein targets that lack targetable cysteine residues. Recently, the rational design of covalent inhibitors or covalent probes targeting other nucleophilic residues, such as lysine, tyrosine, serine, has turned out to be another promising strategy for cancer therapy. Thus, the development of novel strategies to extend the scope of covalent binding and improve the binding properties is required. This review gives a summary of the development of covalent inhibitors targeting noncysteine from different aspects, including target identification, structure–activity relationships, drug discovery strategies, and binding properties, in the hope of providing a scientific reference for future covalent drug discovery as a means of expanding research in cancer therapy.
Molecular docking is an in silico method that involves positioning 3D structure of ligand and target (derived from the databases) in different orientations. Thousands of molecules that can be natural products, synthetic compounds, or often the approved drugs available in the databases can be used for virtual screening, a process where the ligand molecules are docked against the target to look for optimal conformation. It is a crucial step in the computer-aided drug designing process, as following this step, further screening and development of the desired molecule can be performed. The prerequisite for the development of new drug molecule is a known structure of target against which the drug is to be developed. After the screening process for optimal conformation, a potent lead compound can be identified through the scoring function. A significant concept termed as structure-ctivity relationship (SAR) provides a clue of properties of a molecule based on its structure. It enables the identification of the desired positions on a molecule for modification in order to improve the pharmacological properties of the molecule such as efficacy, potency, solubility, and pharmacokinetics etc. Lead discovery ensues a process that involves the development of a drug candidate that once tested through bioinformatics tools can be further taken for preclinical studies, followed by clinical trials. The results of clinical trials are crucial in making decision on whether to release the drug into the market. Moreover, once hit compounds are identified, lead molecules can be chosen to perform lead optimization, which involves maximizing the interactions between the ligand and selected target molecule to enhance its pharmacological activity and reduce the side effects.KeywordsLigandTargetReceptorLeadDrugIn silico
KRASG12C is the most prevalent KRAS mutation in non-small cell lung cancer (NSCLC) and has emerged as a promising therapeutic target. Herein, two series of novel 4(1H)-quinolinone and urea compounds were designed based on the reported KRASG12C inhibitor SH-9. Many compounds showed significantly growth inhibitory activity against human NSCLC cells with KRASG12C mutation in cell viability assays. Compound 20a exhibited an IC50 value of 0.5 μM in KRASG12C-mutant NCI–H358 cells with 21-fold selectivity over KRASWT NCI–H2228 cells. LC-MS analysis indicated that compounds 14c, 14h and 20a covalently bound to KRASG12C rather than KRASWT. Moreover, these compounds could remarkably trap KRASG12C in its inactive state by blocking SOS1-mediated GDP/GTP exchange. Furthermore, treatment of NCI–H358 but not NCI–H2228 cells with 20a dose-dependently reduced the phosphorylation of KRAS downstream effectors ERK and AKT. Importantly, 20a significantly inhibited tumor growth in NCI–H358 xenograft models by suppressing KRASG12C signalling. These results indicate that 20a is a promising candidate worthy of further investigation.
Computer-based modeling and simulation is emerging as a useful tool to complement the analysis and interpretation of biological data. The large volume, scale, and complexity of data generated from in vitro, in vivo, and ex vivo data cannot be analyzed and interpreted by conventional data analysis tools. So, various in silico computational e-resources, databases, and simulation softwares are being used for the determination of pharmacokinetic (PK) and pharmacodynamic (PD) parameters for the management of diseases. These tools help in providing multiscale representation of the biological processes in the order of increasing complexity from that of protein and genes, cells, isolated tissues and organs, and the whole organism. The United States Food and Drug Administration (USFDA) has also directed the use of PK/PD simulation for the evaluation of drugs during the clinical phase, in which the primary focus is on the establishment of relationship between therapeutic drug concentration and patient response. The aim of this chapter is to discuss the role, advancement, and development of biocomputational tools used in research and development in the pharmaceutical industry, wherein the number of experimental studies is exponentially growing. Furthermore, application of these studies to optimize the dosing regimens, dose-response relationship, etc. will be discussed.KeywordsBiomolecular simulationIn silico modelingPharmacokineticPharmacodynamic simulation
Computational approaches in drug style, discovery and admiration. Generally, drug discovery takes an extended Duration of your time amount Ni twelve year and billon of capital. It includes the making of recent molecules, docking Molecules to focus on macromolecule, analyzing molecular interaction, estimating binding strength and drug properties. Computer power-assisted Drug planning (CADD) is value effective and freed from some biological trials. It mainly consists of 2 styles of drug style that’s structure -based drug style and ligand-based drug style. Through it we are able to comprehend the drug receptor interaction. Structure primarily based Drug style includes binding Site identification, arrival and stocking, virtual screening, compound choice, lead optimization. Ligand Based Drug style includes quantitative structure activity relationship, medicine modelling and steps Followed as structure- primarily based drug style. As we are able to see CADD facilitate to acknowledge appropriate characteristics of a Drug and its compatibility to induce a straightforward hand in pre- clinical trials.
The development of a covalent inhibitor requires the incorporation of an appropriate warhead into the chemical structure of the inhibitor and the selection of an appropriate nucleophilic amino acid to react with the warhead. Prediction of the reactivity of new warheads and the degree to which an amino acid is susceptible to covalent modification are critical goals of computer-aided design of covalent inhibitors. The warhead must be reactive toward its target, but its susceptibility to metabolism and off-target reactions are also important criteria. The atomic charges, Natural Bond Orbitals (NBO), electrophilicity index, and Fukui function have all been explored as predictive descriptors of warhead reactivity with significant success. Alternatively, the direct ab initio calculation of barrier heights and reaction energies of model reactions have also been employed as descriptors for predicting the reactivity of a warhead with a model side-chain. The second component is the reactivity of the targeted amino acid, which can also vary because the probability if being deprotonated into its reactive state depends on the local environment of the amino acid. The calculated pKa of the residue is commonly used as a descriptor of side-chain reactivity. Predicting these pKa's computationally is challenging, but new simulation-based methods have demonstrated improved accuracy.
As an effective target in abnormal angiogenesis-related tumor treatment, VEGFR-2 has small-molecule inhibitors of various scaffolds being approved for treating diseases such as renal carcinoma, non-small cell lung cancer, etc. However, endogenous and acquired drug resistance are still considered to be the main contributors for the failure of VEGFR-2 clinical candidates. Therefore, development of novel VEGFR-2 inhibitors is still urgently needed in the market but also challenging. In this work, residues including Asp1046, Ile1025, HIS1026, Cys919 and Lys868 were identified as the most important residues for Hbonded interaction, while His1026, Asp1046, Glu885, Ile1025 and Leu840 exhibited critical role for the nonbonded interactions through a comprehensive analysis of protein–ligand interactions, which plays critical roles in the binding of compounds and targets. Guided by the analysis of binding interactions, a total of 10 novel VEGFR-2 inhibitors based on N-methyl-4-oxo-N-propyl-1,4-dihydroquinoline-2-carboxamide scaffold were discovered through fragment-based drug design and structure-based virtual screening, which expands the chemical space of current VEGFR-2 inhibitors. Biological activity evaluation showed that even though the enzymatic activity of these compounds against VEGFR-2 were inferior to that of the positive controls sorafenib and motesanib, compound I-10 showed moderate HepG2 cell inhibitory activity with an IC50 value of 33.65 μM and eight compounds exhibited moderate or higher HUVEC inhibitory activity in the range of 19.54–57.98 μM compared to the controls. Particularly, the HUVEC inhibitory activity of compound I-6 (IC50 = 19.54 μM) outperformed motesanib and can be used as starting points for further optimization and development for cancer treatment.
Communicated by Ramaswamy H. Sarma
Drug innovation is not only reflected in the discovery of new chemotypes of active compounds against existing targets but also more dependent on the innovation of drug targets. Currently, a number of attractive and validated targets could not be targeted pharmacologically. Some have been described as “undruggable”. In this review, we summarized the current situation of “undruggable” targets, and the design strategies for “undruggable” targets, hoping to provide references for the development of innovative drugs.
This article is protected by copyright. All rights reserved.
Targeted covalent-inhibitors (TCIs) have been successfully developed as high-affinity and selective inhibitors of enzymes of the protein kinase family. These drugs typically act by undergoing an electrophilic addition with an active site cysteine residue, so design of a TCI begins with the identification of a “druggable” cysteine. These electrophilic additions generally require the deprotonation of the thiol to form a reactive anionic thiolate, so the acidity of the residue is a critical factor. Few experimental measurements of the pKa’s of druggable cysteines have been reported, so computational prediction could prove to be very important in selecting reactive cysteine targets. Here, we report the computed pKa’s of druggable cysteines in select protein kinases which are of clinical relevance for targeted therapies. The pKa’s of the cysteines were calculated using advanced computational methods based on all-atom replica-exchange thermodynamic integration molecular dynamics simulations in explicit solvent. We found that the acidities of druggable cysteines within protein kinases are diverse and elevated, indicating enormous differences in their reactivity. Constant pH molecular dynamics simulations were also performed on select protein kinases, with results confirming this varied range in the acidities of druggable cysteines. Many of these active-site cysteines have low exposure to solvent molecules, elevating their pKa. Electrostatic interactions with nearby anionic residues also elevate the pKa’s of cysteine residues in the active site. The results suggest that some cysteine residues within kinase binding sites will be slow to react with a TCI due to their low acidity. Several oncogenic kinase mutations were also modeled and found to have similar pKa’s to the wild-type.
Hybrid molecules have been developed which are comprised of a tyrosine kinase-targeted, quinazoline-based scaffold and a flexibly linked dia(m)minechloridoPt(II) moiety. The target compounds maintain high affinity and selectivity for ErbB...
Covalent inhibition is a rapidly growing discipline within drug discovery. Many historical covalent inhibitors were discovered by serendipity, with such a mechanism of action often regarded as undesirable due to potential toxicity issues. Recent progress has seen a major shift in this outlook, as covalent inhibition shows promise for targets where previous efforts to identify non-covalent small molecule inhibitors have failed. Targeted covalent inhibitors (TCIs) can offer drug discovery scientists the ability to increase the potency and/or selectivity of small molecule inhibitors, by attachment of reactive functional groups designed to covalently bind to specific sites in a target. In this tutorial review we introduce the broader concept of covalent inhibition, discuss the potential benefits and challenges of such an approach, and provide an overview of the current status of the field. We also describe some strategies and computational tools to enable successful covalent drug discovery.
We demonstrate that the Knoevenagel condensation can be exploited in combinatorial synthesis on the solid phase. Condensation products from such reactions were structurally characterized, and their Michael reactivity with thiol and phosphine nucleophiles is described. Cyanoacrylamides were previously reported to react reversibly with thiols, and notably, we show that dilution into low pH buffer can trap covalent adducts which are isolable via chromatography. Finally, we synthesized both traditional and DNA-encoded one-bead, one-compound libraries containing cyanoacrylamides as a source of cysteine-reactive, reversibly covalent protein ligands.
Computational and experimental studies were applied to the discovery of a series of novel vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors. Eight compounds exhibited nanomolar IC50 values against VEGFR-2 and compounds 1, 3, 8 and 9 showed potent antiproliferative effects against several cell lines. Particularly, compound 9 behaved better than FDA approved drugs, sorafenib and sunitinib, in antiproliferative activity against cell lines related to all nine tumor types tested (GI50 values), and it was better or comparable in safety (LC50 values). Compound 9 even demonstrated high potency on one of the drug-resistant cell lines (NCI/ADR-RES) responsible for ovarian cancer and cell lines contributing to prostate cancer, regarded as one of the VEFG/VEGFR pathway drug-resistant tumors. This compound is likely a promising candidate for the treatment of leukemia, non-small cell lung cancer (NSCLC), colon cancer, ovarian cancer and breast cancer with a suitable balance of both efficacy and safety.
Targeted covalent compounds or drugs have good potency as they can bind to a specific target for a long time with low doses. Most currently known covalent ligands were discovered by chance or by modifying existing non-covalent compounds to make them covalently attached to a nearby reactive residue. Computational methods for novel covalent ligand binding prediction are highly demanded. We performed statistical analysis on protein complexes with covalent ligands attached to cysteine residues. We found that covalent modified cysteine residues have unique features compared to those not attached to covalent ligands, including lower pKa, higher exposure and higher ligand binding affinity. SVM models were built to predict cysteine residues suitable for covalent ligand design with prediction accuracy of 0.73. Given a protein structure, our method can be used to automatically detect druggable Cys residues for covalent ligand design, which is especially useful for identifying novel binding sites for covalent allosteric regulating ligand design.
The present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i) covalent interactions in biomolecular systems; (ii) the mathematical framework of covalent molecular docking; (iii) implementation of covalent docking protocol in drug design workflows; (iv) applications covalent docking: case studies and (v) shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.
Significance
Inhibitors of the FGF receptors (FGFRs) are currently under clinical investigation for the treatment of various cancers. All currently approved kinase inhibitors eventually are rendered useless by the emergence of drug-resistant tumors. We used structure-based drug design to develop the first, to our knowledge, selective, next-generation covalent FGFR inhibitors that can overcome the most common form of kinase inhibitor resistance, the mutation of the so-called “gatekeeper” residue located in the ATP-binding pocket. We also describe a novel kinase inhibitor design strategy that uses a single electrophile to target covalently cysteines that are located in different positions within the ATP-binding pocket. These results have important implications for the design of covalent FGFR inhibitors that can overcome clinical resistance.
Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1 and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including what are to our knowledge the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org/).
Bruton's tyrosine kinase (Btk) is an attractive drug target for treating several B-cell lineage cancers. Ibrutinib is a first-in-class covalent irreversible Btk inhibitor and has demonstrated impressive effects in multiple clinical trials. Herein, we present a series of novel 2,5-diaminopyrimidine covalent irreversible inhibitors of Btk. Compared with ibrutinib, these inhibitors exhibited a different selectivity profile for the analyzed kinases as well as a dual-action mode of inhibition of both Btk activation and catalytic activity, which counteracts a negative regulation loop for Btk. Two compounds from this series, 31 and 38, showed potent antiproliferative activities toward multiple B-cell lymphoma cell lines, including germinal center B-cell-like diffuse large B cell lymphoma (GCB-DLBCL) cells. In addition, compound 31 significantly prevented tumor growth in a mouse xenograft model.
Significance
Covalent kinase inhibition strategies are reemerging, but critical gaps in the understanding of molecular determinants of potency still persist. A kinetic approach is developed to describe the components of overall inhibitor potency (reversible binding and chemical reactivity). Detailed kinetic descriptions of EGFR covalent drugs are provided. Reversible interactions of covalent inhibitors are found to be essential to biochemical and cellular potency. A dynamic linkage between available affinity and necessary reactivity is proposed. Cysteine oxidation is an emerging type of posttranslational modification. Specific oxidation of the EGF receptor cysteine nucleophile causes highly variable effects on inhibitor potency. Two mechanisms of drug resistance are identified (reversible cysteine–inhibitor warhead interactions and specific cysteine oxidation) as well as a rational framework for understanding and designing covalent inhibitors.
BTK and ITK are cytoplasmic tyrosine kinases of crucial importance for B- and T-cell development, with loss-of-function mutations causing X-linked agammaglobuinemia and susceptibility to severe, frequently lethal, Epstein-Barr virus infection, respectively. Over the last few years, considerable efforts have been made in order to develop small molecule inhibitors for these kinases to treat lymphocyte malignancies, autoimmunity or allergy/hypersensitivity. The rationale is that even if complete lack of BTK or ITK during development causes severe immunodeficiency, inactivation after birth may result in a less severe phenotype. Moreover, therapy can be transient or only partially block the activity of BTK or ITK. Furthermore, a drug-induced B-cell deficiency is treatable by gamma globulin substitution therapy. The newly developed BTK inhibitor PCI-32765, recently renamed Ibrutinib, has already entered several clinical trials for various forms of non-Hodgkin lymphoma as well as for multiple myeloma. Experimental animal studies have demonstrated highly promising treatment effects also in autoimmunity. ITK inhibitors are still under the early developmental phase, but it can be expected that such drugs will also become very useful. In this manuscript we present BTK and ITK with their signaling pathways and review the development of the corresponding inhibitors. This article is protected by copyright. All rights reserved.
The high frequency of activating RAS or BRAF mutations in cancer provides strong rationale for targeting the mitogen-activated protein kinase (MAPK) pathway. Selective BRAF and MAP-ERK kinase (MEK) inhibitors have shown clinical efficacy in patients with melanoma. However, the majority of responses are transient, and resistance is often associated with pathway reactivation of the extracellular signal-regulated kinase (ERK) signaling pathway. Here, we describe the identification and characterization of SCH772984, a novel and selective inhibitor of ERK1/2 that displays behaviors of both type I and type II kinase inhibitors. SCH772984 has nanomolar cellular potency in tumor cells with mutations in BRAF, NRAS, or KRAS and induces tumor regressions in xenograft models at tolerated doses. Importantly, SCH772984 effectively inhibited MAPK signaling and cell proliferation in BRAF or MEK inhibitor–resistant models as well as in tumor cells resistant to concurrent treatment with BRAF and MEK inhibitors. These data support the clinical development of ERK inhibitors for tumors refractory to MAPK inhibitors.
Significance: BRAF and MEK inhibitors have activity in MAPK-dependent cancers with BRAF or RAS mutations. However, resistance is associated with pathway alterations resulting in phospho-ERK reactivation. Here, we describe a novel ERK1/2 kinase inhibitor that has antitumor activity in MAPK inhibitor-naïve and MAPK inhibitor-resistant cells containing BRAF or RAS mutations. Cancer Discov; 3(7); 742–50. ©2013 AACR.
See related commentary by Nissan et al., p. 719
This article is highlighted in the In This Issue feature, p. 705
Structure-based virtual screening plays an important role in drug discovery and complements other screening approaches. In general, protein crystal structures are prepared prior to docking in order to add hydrogen atoms, optimize hydrogen bonds, remove atomic clashes, and perform other operations that are not part of the x-ray crystal structure refinement process. In addition, ligands must be prepared to create 3-dimensional geometries, assign proper bond orders, and generate accessible tautomer and ionization states prior to virtual screening. While the prerequisite for proper system preparation is generally accepted in the field, an extensive study of the preparation steps and their effect on virtual screening enrichments has not been performed. In this work, we systematically explore each of the steps involved in preparing a system for virtual screening. We first explore a large number of parameters using the Glide validation set of 36 crystal structures and 1,000 decoys. We then apply a subset of protocols to the DUD database. We show that database enrichment is improved with proper preparation and that neglecting certain steps of the preparation process produces a systematic degradation in enrichments, which can be large for some targets. We provide examples illustrating the structural changes introduced by the preparation that impact database enrichment. While the work presented here was performed with the Protein Preparation Wizard and Glide, the insights and guidance are expected to be generalizable to structure-based virtual screening with other docking methods.
Binding hot spots, protein sites with high-binding affinity, can be identified using X-ray crystallography or NMR by screening
libraries of small organic molecules that tend to cluster at such regions. FTMAP, a direct computational analog of the experimental
screening approaches, globally samples the surface of a target protein using small organic molecules as probes, finds favorable
positions, clusters the conformations and ranks the clusters on the basis of the average energy. The regions that bind several
probe clusters predict the binding hot spots, in good agreement with experimental results. Small molecules discovered by fragment-based
approaches to drug design also bind at the hot spot regions. To identify such molecules and their most likely bound positions,
we extend the functionality of FTMAP (http://ftmap.bu.edu/param) to accept any small molecule as an additional probe. In its updated form, FTMAP identifies the hot spots based on a standard
set of probes, and for each additional probe shows representative structures of nearby low energy clusters. This approach
helps to predict bound poses of the user-selected molecules, detects if a compound is not likely to bind in the hot spot region,
and provides input for the design of larger ligands.
Targeting noncatalytic cysteine residues with irreversible acrylamide-based inhibitors is a powerful approach for enhancing pharmacological potency and selectivity. Nevertheless, concerns about off-target modification motivate the development of reversible cysteine-targeting strategies. Here we show that electron-deficient olefins, including acrylamides, can be tuned to react with cysteine thiols in a rapidly reversible manner. Installation of a nitrile group increased the olefins' intrinsic reactivity, but, paradoxically, eliminated the formation of irreversible adducts. Incorporation of these electrophiles into a noncovalent kinase-recognition scaffold produced slowly dissociating, covalent inhibitors of the p90 ribosomal protein S6 kinase RSK2. A cocrystal structure revealed specific noncovalent interactions that stabilize the complex by positioning the electrophilic carbon near the targeted cysteine. Disruption of these interactions by protein unfolding or proteolysis promoted instantaneous cleavage of the covalent bond. Our results establish a chemistry-based framework for engineering sustained covalent inhibition without accumulating permanently modified proteins and peptides.
The mitogen-activated kinases JNK1/2/3 are key enzymes in signaling modules that transduce and integrate extracellular stimuli into coordinated cellular response. Here, we report the discovery of irreversible inhibitors of JNK1/2/3. We describe two JNK3 cocrystal structures at 2.60 and 2.97 Å resolution that show the compounds form covalent bonds with a conserved cysteine residue. JNK-IN-8 is a selective JNK inhibitor that inhibits phosphorylation of c-Jun, a direct substrate of JNK, in cells exposed to submicromolar drug in a manner that depends on covalent modification of the conserved cysteine residue. Extensive biochemical, cellular, and pathway-based profiling establish the selectivity of JNK-IN-8 for JNK and suggests that the compound will be broadly useful as a pharmacological probe of JNK-dependent signal transduction. Potential lead compounds have also been identified for kinases, including IRAK1, PIK3C3, PIP4K2C, and PIP5K3.
Cys is much different from other common amino acids in proteins. Being one of the least abundant residues, Cys is often observed in functional sites in proteins. This residue is reactive, polarizable, and redox-active; has high affinity for metals; and is particularly responsive to the local environment. A better understanding of the basic properties of Cys is essential for interpretation of high-throughput data sets and for prediction and classification of functional Cys residues. We provide an overview of approaches used to study Cys residues, from methods for investigation of their basic properties, such as exposure and pK(a), to algorithms for functional prediction of different types of Cys in proteins.
Despite the growing number of examples of small-molecule inhibitors that disrupt protein-protein interactions (PPIs), the origin of druggability of such targets is poorly understood. To identify druggable sites in protein-protein interfaces we combine computational solvent mapping, which explores the protein surface using a variety of small "probe" molecules, with a conformer generator to account for side-chain flexibility. Applications to unliganded structures of 15 PPI target proteins show that the druggable sites comprise a cluster of binding hot spots, distinguishable from other regions of the protein due to their concave topology combined with a pattern of hydrophobic and polar functionality. This combination of properties confers on the hot spots a tendency to bind organic species possessing some polar groups decorating largely hydrophobic scaffolds. Thus, druggable sites at PPI are not simply sites that are complementary to particular organic functionality, but rather possess a general tendency to bind organic compounds with a variety of structures, including key side chains of the partner protein. Results also highlight the importance of conformational adaptivity at the binding site to allow the hot spots to expand to accommodate a ligand of drug-like dimensions. The critical components of this adaptivity are largely local, involving primarily low energy side-chain motions within 6 Å of a hot spot. The structural and physicochemical signature of druggable sites at PPI interfaces is sufficiently robust to be detectable from the structure of the unliganded protein, even when substantial conformational adaptation is required for optimal ligand binding.
Covalent drugs have proved to be successful therapies for various indications, but largely owing to safety concerns, they are rarely considered when initiating a target-directed drug discovery project. There is a need to reassess this important class of drugs, and to reconcile the discordance between the historic success of covalent drugs and the reluctance of most drug discovery teams to include them in their armamentarium. This review surveys the prevalence and pharmacological advantages of covalent drugs, discusses how potential risks and challenges may be addressed through innovative design, and presents the broad opportunities provided by targeted covalent inhibitors.
Cysteine is the most intrinsically nucleophilic amino acid in proteins, where its reactivity is tuned to perform diverse biochemical functions. The absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here we describe a proteomics method to profile quantitatively the intrinsic reactivity of cysteine residues en masse directly in native biological systems. Hyper-reactivity was a rare feature among cysteines and it was found to specify a wide range of activities, including nucleophilic and reductive catalysis and sites of oxidative modification. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotic phylogeny that we show is required for yeast viability and is involved in iron-sulphur protein biogenesis. We also demonstrate that quantitative reactivity profiling can form the basis for screening and functional assignment of cysteines in computationally designed proteins, where it discriminated catalytically active from inactive cysteine hydrolase designs.
The binding sites of proteins generally contain smaller regions that provide major contributions to the binding free energy and hence are the prime targets in drug design. Screening libraries of fragment-sized compounds by NMR or X-ray crystallography demonstrates that such 'hot spot' regions bind a large variety of small organic molecules, and that a relatively high 'hit rate' is predictive of target sites that are likely to bind drug-like ligands with high affinity. Our goal is to determine the 'hot spots' computationally rather than experimentally.
We have developed the FTMAP algorithm that performs global search of the entire protein surface for regions that bind a number of small organic probe molecules. The search is based on the extremely efficient fast Fourier transform (FFT) correlation approach which can sample billions of probe positions on dense translational and rotational grids, but can use only sums of correlation functions for scoring and hence is generally restricted to very simple energy expressions. The novelty of FTMAP is that we were able to incorporate and represent on grids a detailed energy expression, resulting in a very accurate identification of low-energy probe clusters. Overlapping clusters of different probes are defined as consensus sites (CSs). We show that the largest CS is generally located at the most important subsite of the protein binding site, and the nearby smaller CSs identify other important subsites. Mapping results are presented for elastase whose structure has been solved in aqueous solutions of eight organic solvents, and we show that FTMAP provides very similar information. The second application is to renin, a long-standing pharmaceutical target for the treatment of hypertension, and we show that the major CSs trace out the shape of the first approved renin inhibitor, aliskiren.
FTMAP is available as a server at http://ftmap.bu.edu/.
Deregulation of kinase activity has emerged as a major mechanism by which cancer cells evade normal physiological constraints on growth and survival. To date, 11 kinase inhibitors have received US Food and Drug Administration approval as cancer treatments, and there are considerable efforts to develop selective small molecule inhibitors for a host of other kinases that are implicated in cancer and other diseases. Herein we discuss the current challenges in the field, such as designing selective inhibitors and developing strategies to overcome resistance mutations. This Review provides a broad overview of some of the approaches currently used to discover and characterize new kinase inhibitors.
Computational mapping places molecular probes--small molecules or functional groups--on a protein surface to identify the most favorable binding positions. Although x-ray crystallography and NMR show that organic solvents bind to a limited number of sites on a protein, current mapping methods result in hundreds of energy minima and do not reveal why some sites bind molecules with different sizes and polarities. We describe a mapping algorithm that explains the origin of this phenomenon. The algorithm has been applied to hen egg-white lysozyme and to thermolysin, interacting with eight and four different ligands, respectively. In both cases the search finds the consensus site to which all molecules bind, whereas other positions that bind only certain ligands are not necessarily found. The consensus sites are pockets of the active site, lined with partially exposed hydrophobic residues and with a number of polar residues toward the edge. These sites can accommodate each ligand in a number of rotational states, some with a hydrogen bond to one of the nearby donor/acceptor groups. Specific substrates and/or inhibitors of hen egg-white lysozyme and thermolysin interact with the same side chains identified by the mapping, but form several hydrogen bonds and bind in unique orientations.
We have catalogued the protein kinase complement of the human genome (the "kinome") using public and proprietary genomic, complementary DNA, and expressed sequence tag (EST) sequences. This provides a starting point for comprehensive analysis of protein phosphorylation in normal and disease states, as well as a detailed view of the current state of human genome analysis through a focus on one large gene family. We identify 518 putative protein kinase genes, of which 71 have not previously been reported or described as kinases, and we extend or correct the protein sequences of 56 more kinases. New genes include members of well-studied families as well as previously unidentified families, some of which are conserved in model organisms. Classification and comparison with model organism kinomes identified orthologous groups and highlighted expansions specific to human and other lineages. We also identified 106 protein kinase pseudogenes. Chromosomal mapping revealed several small clusters of kinase genes and revealed that 244 kinases map to disease loci or cancer amplicons.
The mitogen-activated protein (MAP) kinases p44ERK1 and p42ERK2 are crucial components of the regulatory machinery underlying normal and malignant cell proliferation. A currently accepted model maintains that ERK1 and ERK2 are regulated similarly and contribute to intracellular signaling by phosphorylating a largely common subset of substrates, both in the cytosol and in the nucleus.
Here, we show that ablation of ERK1 in mouse embryo fibroblasts and NIH 3T3 cells by gene targeting and RNA interference results in an enhancement of ERK2-dependent signaling and in a significant growth advantage. By contrast, knockdown of ERK2 almost completely abolishes normal and Ras-dependent cell proliferation. Ectopic expression of ERK1 but not of ERK2 in NIH 3T3 cells inhibits oncogenic Ras-mediated proliferation and colony formation. These phenotypes are independent of the kinase activity of ERK1, as expression of a catalytically inactive form of ERK1 is equally effective. Finally, ectopic expression of ERK1 but not ERK2 is sufficient to attenuate Ras-dependent tumor formation in nude mice.
These results reveal an unexpected interplay between ERK1 and ERK2 in transducing Ras-dependent cell signaling and proliferation. Whereas ERK2 seems to have a positive role in controlling normal and Ras-dependent cell proliferation, ERK1 probably affects the overall signaling output of the cell by antagonizing ERK2 activity.
Much of drug discovery today is predicated on the concept of selective targeting of particular bioactive macromolecules by low-molecular-mass drugs. The binding of drugs to their macromolecular targets is therefore seen as paramount for pharmacological activity. In vitro assessment of drug-target interactions is classically quantified in terms of binding parameters such as IC(50) or K(d). This article presents an alternative perspective on drug optimization in terms of drug-target binary complex residence time, as quantified by the dissociative half-life of the drug-target binary complex. We describe the potential advantages of long residence time in terms of duration of pharmacological effect and target selectivity.
Small-molecule kinase inhibitors (SMKIs), 28 of which are approved by the US Food and Drug Administration (FDA), have been actively pursued as promising targeted therapeutics. Here, we assess the key structural and physicochemical properties, target selectivity and mechanism of function, and therapeutic indications of these approved inhibitors. Our analysis showed that >30% of approved SMKIs have a molecule weight (MW) exceeding 500 and all have a total ring count of between three and five. The assumption that type II inhibitors tend to be more selective than type I inhibitors has been proved to be unreliable. Although previous SMKI research was concentrated on tyrosine kinase inhibitors for cancer treatment, recent progress indicates diversification of SMKI research in terms of new targets, mechanistic types, and therapeutic indications.
Copyright © 2015. Published by Elsevier Ltd.
The discovery of novel scaffolds against a specific target has long been one of the most significant but challengeable goals in discovering lead compounds. A scaffold that binds in important regions of the active pocket is more favorable as a starting point because scaffolds generally possess greater optimization possibilities. However, due to the lack of sufficient chemical space diversity of the databases and the ineffectiveness of the screening methods, it still remains a great challenge to discover novel active scaffolds. Since the strengths and weaknesses of both fragment-based drug design and traditional virtual screening (VS), we proposed a fragment VS concept based on Bayesian categorization for the discovery of novel scaffolds. This work investigated the proposal through an application on VEGFR-2 target. Firstly, scaffold and structural diversity of chemical space for 10 compound databases were explicitly evaluated. Simultaneously, a robust Bayesian classification model was constructed for screening not only compound databases but also their corresponding fragment databases. Although analysis of the scaffold diversity demonstrated a very unevenly distribution of scaffolds over molecules, results showed that our Bayesian model behaved better in screening fragments than molecules. Through a literature retrospective research, several generated fragments with relatively high Bayesian scores indeed exhibit VEGFR-2 biological activity, which strongly proved the effectiveness of fragment VS based on Bayesian categorization models. This investigation of Bayesian-based fragment VS can further emphasize the necessity for enrichment of compound databases employed in lead discovery by amplifying the diversity of databases with novel structures.
The high frequency of activating BRAFV600E mutations in melanoma (40-70%), thyroid (50%) and colorectal cancer (10%), or KRAS/NRAS mutations in melanoma (20%), pancreatic (90%), colorectal (50%) and non-small cell lung cancer (30%), provides strong rationale for targeting the MAPK pathway as a therapeutic strategy ¹⁻⁶. Vemurafenib (PLX4032) and dabrafenib (GSK2118436), selective BRAF inhibitors, and trametinib (GSK1120212), an allosteric MEK inhibitor, have shown robust clinical efficacy in melanoma patients ⁷⁻¹⁰. However, the majority of responses are transient and cellular resistance is often associated with pathway reactivation involving the downstream extracellular-signal-regulated kinases 1 and 2 (ERK1/2) (reviewed in ¹¹). We hypothesized that pathway blockade at ERK, the last signaling node prior to MAPK transcriptional programming, would not only be efficacious in MAPK-activated tumors but would also have utility in BRAF or MEK inhibitor resistant settings. We therefore sought to identify small molecule inhibitors of ERK. This report describes the identification and characterization of SCH772984, a potent and selective ATP competitive inhibitor of ERK1/2 which displays behaviors of both type I and type II kinase inhibitors. SCH772984 has nanomolar cellular potency on tumor cells with mutations in BRAF, NRAS, or KRAS and induces tumor regressions in xenograft models at tolerated doses. Importantly, SCH772984 effectively inhibited MAPK signaling and cell proliferation in BRAF or MEK inhibitor resistant models as well as in the context of BRAF/MEK combination resistance. Together these data support the clinical development of ERK inhibitors, not only in patients with MAPK activated tumors, but also in patients who have developed acquired resistance to BRAF or MEK inhibitors or resistance to the recently described combination of these agents.
Citation Format: Ahmed A. Samatar, Erick J. Morris, Sharda Jha, Restaino R. Clifford, Bart Luttrerbach, Marc Pelletier, Ulrike Philippar, Lata Jayaraman, Leigh Zawel, Steve Fawell, Gary Gilliland. A novel ERK inhibitor is active in models of acquired resistance to BRAF and MEK inhibitors. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2343. doi:10.1158/1538-7445.AM2013-2343
Kinases have emerged as one of the most intensively pursued targets in current pharmacological research, especially for cancer, due to their critical roles in cellular signaling. To date, the US FDA has approved 28 small-molecule kinase inhibitors, half of which were approved in the past 3 years. While the clinical data of these approved molecules are widely presented and structure-activity relationship (SAR) has been reported for individual molecules, an updated review that analyzes all approved molecules and summarizes current achievements and trends in the field has yet to be found. Here we present all approved small-molecule kinase inhibitors with an emphasis on binding mechanism and structural features, summarize current challenges, and discuss future directions in this field.
Copyright © 2015 Elsevier Ltd. All rights reserved.
(Free access of full paper until August 14, 2015: http://authors.elsevier.com/a/1RFq0bg0kGTV4)
Aberrant signaling through the fibroblast growth factor 19 (FGF19)/fibroblast growth factor receptor 4 (FGFR 4) signaling complex has been shown to cause hepatocellular carcinoma (HCC) in mice and has been implicated to play a similar role in humans. We have developed BLU9931, a potent and irreversible small-molecule inhibitor of FGFR4, as a targeted therapy to treat patients with HCC whose tumors have an activated FGFR4 signaling pathway. BLU9931 is exquisitely selective for FGFR4 versus other FGFR family members and all other kinases. BLU9931 shows remarkable antitumor activity in mice bearing an HCC tumor xenograft that overexpresses FGF19 due to amplification as well as a liver tumor xenograft that overexpresses FGF19 mRNA but lacks FGF19 amplification. Approximately one third of patients with HCC whose tumors express FGF19 together with FGFR4 and its coreceptor klotho β (KLB) could potentially respond to treatment with an FGFR4 inhibitor. These findings are the first demonstration of a therapeutic strategy that targets a subset of patients with HCC.
This article documents the discovery of BLU9931, a novel irreversible kinase inhibitor that specifically targets FGFR4 while sparing all other FGFR paralogs and demonstrates exquisite kinome selectivity. BLU9931 is efficacious in tumors with an intact FGFR4 signaling pathway that includes FGF19, FGFR4, and KLB. BLU9931 is the first FGFR4-selective molecule for the treatment of patients with HCC with aberrant FGFR4 signaling. Cancer Discov; 5(4); 1-14. ©2015 AACR.
©2015 American Association for Cancer Research.
The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
Interest in drugs that covalently modify their target is driven by the desire for enhanced efficacy that can result from the silencing of enzymatic activity until protein re-synthesis can occur, along with the potential for increased selectivity by targeting uniquely positioned nucleophilic residues in the protein. However, covalent approaches carry additional risk for toxicities or hypersensitivity reactions that can result from covalent modification of unintended targets. Here we describe methods for measuring the reactivity of covalent reactive groups (CRGs) with a biologically relevant nucleophile, glutathione (GSH), along with kinetic data for a broad array of electrophiles. We also describe a computational method for predicting electrophilic reactivity, which taken together can be applied to the prospective design of thiol-reactive covalent inhibitors.
Covalent ligand-target interactions offer significant pharmacological advantages. However, off-target reactivity of the reactive groups, which usually have electrophilic properties, must be minimized and the selectivity of irreversible inhibitors is a crucial requirement. We therefore performed a systematic study to determine the selectivity of several electrophilic groups that can be used as building blocks for covalently binding ligands. Six reactive groups with modulated electrophilicity were combined with eleven non-reactive moieties, resulting in a small combinatorial library of 72 fragment-like compounds. These compounds were screened against a group of eleven enzyme targets to assess their selectivity and their potential for promiscuous binding to proteins. The assay results showed a considerably lower degree of promiscuity than initially expected, even for those members of the screening collection that contain supposedly highly reactive electrophiles.
Although many popular docking programs include a facility to account for covalent ligands, large-scale systematic docking validation studies of covalent inhibitors have been sparse. In this paper, we present the development and validation of a novel approach for docking and scoring covalent inhibitors, which consists of conventional non-covalent docking, heuristic formation of the covalent attachment point and structural refinement of the protein-ligand complex. This approach combines the strengths of the docking program Glide and the protein structure modeling program Prime, and does not require any parameter fitting for the study of additional covalent reaction types. We first test this method by predicting the native binding geometry of 38 covalently bound complexes. The average RMSD of the predicted poses is 1.52 Å and 76% of test set inhibitors have an RMSD of less than 2.0 Å. In addition, the apparent affinity score constructed herein, is tested on a virtual screening study and the characterization of the SAR properties of two different series of congeneric compounds with satisfactory success.
Protein-protein interactions are implicated in the pathogenesis of many diseases and are therefore attractive but challenging targets for drug design. One of the challenges in development is the identification of potential druggable binding sites in protein interacting interfaces. Identification of interface surfaces can greatly aid rational drug design of small molecules inhibiting protein-protein interactions. In this work, starting from the structure of a free monomer, we have developed a ligand docking based method, called "FindBindSite" (FBS) to locate protein-protein interacting interface regions and potential druggable sites in this interface. FindBindSite utilizes the results from docking a small and diverse library of small molecules to the entire protein structure. By clustering regions with the highest docked ligand density from FBS, we have shown that these high ligand density regions strongly correlate with the known protein-protein interacting surfaces. We have further predicted potential druggable binding sites on the protein surface using FBS, with druggability being defined as the site with high density of ligands docked. FBS shows a hit rate of 71% with high confidence, and 93% with lower confidence for the 41 proteins for predicting druggable binding sites on the protein-protein interface. Mining the regions of lower ligand density that are contiguous with the high scoring high ligand density regions from FBS, we were able to map 70% of the protein-protein interacting surface in 24 out of 41 structures tested. We also observed that FBS has limited sensitivity to the size and nature of the small molecule library used for docking. The experimentally determined hotspot residues for each protein-protein complex, cluster near the best scoring druggable binding sites identified by FBS. These results validate the ability of our technique to identify druggable sites within protein-protein interface regions that have the maximal possibility of interface disruption.
The function and role of Bruton's tyrosine kinase (BTK) in human B cell development was demonstrated by its association with X-linked agammaglobulinemia (XLA) manifested by a substantial reduction in immunoglobulins and B cells. BTK has a crucial role in pre-B cell receptor (BCR) and BCR signaling during normal B cell development and activation. Aberrant BCR signaling is associated with autoimmune diseases, such as rheumatoid arthritis (RA). In addition, BTK is also expressed in myeloid cell populations, including monocytes, macrophages, neutrophils and mast cells. These innate cells infiltrate the synovial cavity and produce inflammatory cytokines, aggravating arthritic symptoms. In myeloid cell populations, BTK functions downstream of the Fcγ receptors (FcγR) and Fcɛ receptors (FcɛR) [1,2]. In the absence of BTK, FcR-mediated functions, such as cytokine production, are impaired. In addition, Xid mice, which have a mutation in BTK, have decreased susceptibility to developing collagen-induced arthritis (CIA) [3]. Given that BTK is involved in multiple signaling pathways downstream of the BCR and FcR, it is an attractive therapeutic target for RA.
In recent years, the number of drug candidates with a covalent mechanism of action progressing through clinical trials or being approved by the FDA has increased significantly. And as interest in covalent inhibitors has increased, the technical challenges for characterizing and optimizing these inhibitors have become evident. A number of new tools have been developed to aid this process, but these have not gained wide-spread use. This review will highlight a number of methods and tools useful for prosecuting covalent inhibitor drug discovery programs.
In recent years, various virtual screening (VS) tools have been developed and many successful screening campaigns have been showcased. However, no matter by conventional molecular docking or pharmacophore screening, the selection of virtual hits is based on the ranking of compounds by scoring functions or fit values, which remains the bottleneck of VS due to insufficient accuracy. As the limitations of individual methods persist, a comprehensive comparison and integration of different methods may provide insights into selecting suitable methods for VS. Here, we evaluated the performance of molecular docking, fingerprint-based 2D similarity and multicomplex pharmacophore in an individual and a combined manner, through a retrospective VS study on VEGFR-2 inhibitors. An integrated two-layer workflow was developed and validated through VS of VEGFR-2 inhibitors against the DUD-E database, which demonstrated improved VS performance through a ligand-based method ECFP_4, followed by molecular docking, and then a strict multicomplex pharmacophore. Through a retrospective comparison with six formerly published papers, this integrated approach outperformed 43 out of 45 methods, indicating a great effectiveness. This kind of integrated VS approach can be extended to other targets for the screening and discovery of inhibitors.
A novel class of furo[2,3-d]pyrimidines has been discovered as potent dual inhibitors of Tie-2 and VEGFR2 receptor tyrosine kinases (TK) and a diarylurea moiety at 5-position shows remarkably enhanced activity against both enzymes. One of the most active compounds, 4-amino-3-(4-((2-fluoro-5-(trifluoromethyl)phenyl)amino-carbonylamino)phenyl)-2-(4-methoxyphenyl)furo[2,3-d]pyrimidine (7k) is < 3 nM on both TK receptors and the activity is rationalized based on the X-ray crystal structure. © 2005 Elsevier Ltd. All rights reserved.
Protein kinases are a large family of approximately 530 highly conserved enzymes that transfer a γ-phosphate group from ATP to a variety of amino acid residues, such as tyrosine, serine, and threonine, that serves as a ubiquitous mechanism for cellular signal transduction. The clinical success of a number of kinase-directed drugs and the frequent observation of disease causing mutations in protein kinases suggest that a large number of kinases may represent therapeutically relevant targets. To date, the majority of clinical and preclinical kinase inhibitors are ATP competitive, noncovalent inhibitors that achieve selectivity through recognition of unique features of particular protein kinases. Recently, there has been renewed interest in the development of irreversible inhibitors that form covalent bonds with cysteine or other nucleophilic residues in the ATP-binding pocket. Irreversible kinase inhibitors have a number of potential advantages including prolonged pharmacodynamics, suitability for rational design, high potency, and ability to validate pharmacological specificity through mutation of the reactive cysteine residue. Here, we review recent efforts to develop cysteine-targeted irreversible protein kinase inhibitors and discuss their modes of recognizing the ATP-binding pocket and their biological activity profiles. In addition, we provided an informatics assessment of the potential "kinase cysteinome" and discuss strategies for the efficient development of new covalent inhibitors.
VEGF is an important signaling protein involved in both vasculogenesis and angiogenesis. As an essential receptor protein tyrosine kinase propagating cellular signal transduction processes, VEGFR-2 is a central target for drug discovery against tumor-associated angiogenesis. Since the autophosphorylation of VEGFR-2 represents a key step in this signal pathway that contributes to angiogenesis, the discovery of small molecule inhibitors that block this reaction has attracted great interest for novel drugs research and development. Advances in the understanding of catalytic cleft and the conformational changes of DFG motif have resulted in the development of small molecule inhibitors known as type I and type II. High-resolution crystal structures of various inhibitors in complex with the receptor offer an insight into the relationship among binding modes, inhibition mechanisms, activity, selectivity and resistance. To control selectivity, improve activity and introduce intellectual property novelty, the strategies for the further development are discussed through structural and conformational analysis in this review.
In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
Not applicable for a Perspective.
c-Src and Bcr-Abl are two cytoplasmatic tyrosine kinases (TKs) involved in the development of malignancies. In particular, Bcr-Abl is the etiologic agent of chronic myeloid leukemia, where Src is also involved; the latter is hyperactivated in several solid tumors. Because of the structural homology between Src and Abl, several compounds originally synthesized as Src inhibitors have also been shown to be Abl inhibitors, useful in overcoming the onset of some types of chronic myeloid leukemia resistances, which frequently appear in the advanced phases of pathology. In recent years, the development of such compounds has been promoted by both excellent preclinical and clinical results, and by the theory that dual or multi-targeted inhibitors might be more effective than selective inhibitors. This review is an update on the most important dual inhibitors already in clinical trials and includes information regarding compounds that have appeared in the literature in recent years.
Kinases have emerged as one of the most prolific therapeutic targets. An important criterion in the therapeutic success of inhibitors targeting the nucleotide binding pocket of kinases is the inhibitor residence time. Recently, covalent kinase inhibitors have attracted attention since they confer terminal inhibition and should thus be more effective than reversible inhibitors with transient inhibition. The most robust approach to design irreversible inhibitors is to capitalize on the nucleophilicity of a cysteine thiol group present in the target protein. Herein, we report a systematic analysis of cysteine residues present in the nucleotide binding site of kinases, which could be harnessed for irreversible inhibition, taking into consideration the different kinase conformations. We demonstrate the predictive power of this analysis with the design and validation of an irreversible inhibitor of KIT/PDGFR kinases. This is the first example of a covalent kinase inhibitor that combines a pharmacophore addressing the DFG-out conformation with a covalent trap.
In the past decade tremendous progress has been made toward a new class of therapeutics termed 'targeted covalent drugs', in which structure-based approaches are employed to create small molecules that inactivate their protein target through targeted covalent attachment to a specific cysteine. In the kinase field, this approach is demonstrating promise in overcoming the potency, selectivity, and efficacy challenges currently faced by reversible kinase inhibitors, with several advancing into late stage clinical testing. This design paradigm has been successfully applied to making drug candidates for epidermal growth factor receptor (EGFR), Her2, and Bruton's tyrosine kinase (Btk). Here we review recent pre-clinical and clinical advances with targeted covalent kinase inhibitors, and the potential for broader application of the approach.
Bruton's tyrosine kinase (BTK), a member of the TEC family of kinases, plays a crucial role in B-cell maturation and mast cell activation. Although the structures of the unphosphorylated mouse BTK kinase domain and the unphosphorylated and phosphorylated kinase domains of human ITK are known, understanding the kinase selectivity profiles of BTK inhibitors has been hampered by the lack of availability of a high resolution, ligand-bound BTK structure. Here, we report the crystal structures of the human BTK kinase domain bound to either Dasatinib (BMS-354825) at 1.9 A resolution or to 4-amino-5-(4-phenoxyphenyl)-7H-pyrrolospyrimidin- 7-yl-cyclopentane at 1.6 A resolution. This data provides information relevant to the development of small molecule inhibitors targeting BTK and the TEC family of nonreceptor tyrosine kinases. Analysis of the structural differences between the TEC and Src families of kinases near the Trp-Glu-Ile motif in the N-terminal region of the kinase domain suggests a mechanism of regulation of the TEC family members.
c-Jun N-terminal kinases (JNKs), first characterized as stress-activated members of the mitogen-activated protein kinase (MAPK) family, have become a focus of inhibitor screening strategies following studies that have shown their critical roles in the development of a number of diseases, such as diabetes, neurodegeneration and liver disease. We discuss recent advances in the discovery and development of ATP-competitive and ATP-noncompetitive JNK inhibitors. Because understanding the modes of actions of these inhibitors and improving their properties will rely on a better understanding of JNK structure, JNK catalytic mechanisms and substrates, recent advances in these areas of JNK biochemistry are also considered. In addition, the use of JNK gene knockout animals is continuing to reveal in vivo functions for these kinases, with tissue-specific roles now being dissected with tissue-specific knockouts. These latest advances highlight the many challenges now faced, particularly in the directed targeting of the JNK isoforms in specific tissues.
Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.
A series of 2-(quinazolin-4-ylamino)-[1,4] benzoquinone derivatives that function as potent covalent-binding, irreversible inhibitors of the kinase domain of vascular endothelial growth factor receptor-2 (VEGFR-2) has been prepared by ceric ammonium nitrate oxidation of substituted (2,5-dimethoxyphenyl)(6,7-disubstituted-quinazolin-4-yl)amines and by displacement of the chlorine atom of substituted 2-chloro-5-(6,7-disubstituted-quinazolin-4-ylamino)-[1,4]benzoquinones with various amines, anilines, phenols, and alcohols. Enzyme studies were conducted in the absence and presence of glutathione and plasma. Several of the compounds inhibit VEGF-stimulated autophosphorylation in intact cells. Kinetic experiments were performed to study the reactivity of selected inhibitors toward glutathione. Reactivities correlated with LUMO energies calculated as averages of those of individual conformers weighted by the Boltzmann distribution. These results and molecular modeling were used to rationalize the biological observations. The compounds behave as non-ATP-competitive inhibitors. Unequivocal evidence, from mass spectral studies, indicates that these inhibitors form a covalent interaction with Cys-1045. One member of this series displays antitumor activity in an in vivo model.
(Chemical Equation Presented) A series of highly selective irreversible inhibitors for Bruton's tyrosine kinase (Btk) was developed using a structural bioinformatics approach. Their capabilities to modulate Btk's activity were characterized both in vitro and in vivo. Oral treatment with once-a-day dosing of compound 4 greatly inhibited disease development in a rodent rheumatoid arthritis (RA) model.