[Show abstract][Hide abstract] ABSTRACT: Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the twelve isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.
Journal of Chemical Information and Modeling 01/2015; · 4.07 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: It is widely accepted that protein receptors exist as an ensemble of conformations in solution. How best to incorporate receptor flexibility into virtual screening protocols used for drug discovery remains a significant challenge. Here, stepwise methodologies are described to generate and select relevant protein conformations for virtual screening in the context of the relaxed complex scheme (RCS), to design small molecule libraries for docking, and to perform statistical analyses on the virtual screening results. Methods include equidistant spacing, RMSD-based clustering, and QR factorization protocols for ensemble generation and ROC analysis for ensemble selection.
Methods in Molecular Biology 01/2015; 1215:445-69. · 1.29 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The emergence of drug-resistant bacteria threatens to revert humanity back to the preantibiotic era. Even now, multidrug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, tens of thousands of lives lost. As many pharmaceutical companies have abandoned antibiotic development in search of more lucrative therapeutics, academic researchers are uniquely positioned to fill the pipeline. Traditional high-throughput screens and lead-optimization efforts are expensive and labor intensive. Computer-aided drug-discovery techniques, which are cheaper and faster, can accelerate the identification of novel antibiotics, leading to improved hit rates and faster transitions to preclinical and clinical testing. The current review describes two machine-learning techniques, neural networks and decision trees, that have been used to identify experimentally validated antibiotics. We conclude by describing the future directions of this exciting field.
Chemical Biology & Drug Design 01/2015; 85(1). · 2.51 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Analysis of macromolecular/small-molecule binding pockets can provide important insights into molecular recognition and receptor dynamics. Since its release in 2011, the POVME (POcket Volume MEasurer) algorithm has been widely adopted as a simple-to-use tool for measuring and characterizing pocket volumes and shapes. We here present POVME 2.0, which is an order of magnitude faster, has improved accuracy, includes a graphical user interface, and can produce volumetric density maps for improved pocket analysis. To demonstrate the utility of the algorithm, we use it to analyze the binding pocket of RNA editing ligase 1 from the unicellular parasite Trypanosoma brucei, the etiological agent of African sleeping sickness. The POVME analysis characterizes the full dynamics of a potentially druggable transient binding pocket and so may guide future antitrypanosomal drug-discovery efforts. We are hopeful that this new version will be a useful tool for the computational- and medicinal-chemist community.
Journal of Chemical Theory and Computation 11/2014; 10(11):5047-5056. · 5.39 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Owing to recent developments in computational algorithms and architectures, it is now computationally tractable to explore biologically relevant, equilibrium dynamics of realistically-sized functional proteins using all-atom molecular dynamics simulations. Molecular dynamics simulations coupled with Markov state models is a nascent but rapidly growing technology that is enabling robust exploration of equilibrium dynamics. The objective of this work is to explore the challenges of coupling molecular dynamics simulations and Markov state models in the study of functional proteins. Using recent studies as a framework, we explore progress in sampling, model building, model selection, and coarse-grained analysis of models. Our goal is to highlight some of the current challenges in applying Markov state models to realistically-sized proteins and spur discussion on advances in the field.
Journal of Chemical Theory and Computation 07/2014; 10(7):2648-2657. · 5.31 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: As ever larger and more complex biological systems are modeled in silico, approximating physiological lipid bilayers with simple planar models becomes increasingly unrealistic. In order to build accurate large-scale models of subcellular environments, models of lipid membranes with carefully considered, biologically relevant curvature will be essential. In the current work, we present a multi-scale utility called LipidWrapper capable of creating curved membrane models with geometries derived from various sources, both experimental and theoretical. To demonstrate its utility, we use LipidWrapper to examine an important mechanism of influenza virulence. A copy of the program can be downloaded free of charge under the terms of the open-source FreeBSD License from http://nbcr.ucsd.edu/lipidwrapper. LipidWrapper has been tested on all major computer operating systems.
[Show abstract][Hide abstract] ABSTRACT: Sharing sets of chemical data (e.g., chemical properties, docking scores, etc.) among collaborators with diverse skill sets is a common task in computer-aided drug design and medicinal chemistry. The ability to associate this data with images of the relevant molecular structures greatly facilitates scientific communication. There is a need for a simple, free, open-source program that can automatically export aggregated reports of entire chemical data sets to files viewable on any computer, regardless of the operating system and without requiring the installation of additional software.
[Show abstract][Hide abstract] ABSTRACT: RNA editing is essential for mitochondrial gene expression in all trypanosomatids but absent from the host and therefore a potentially powerful drug target. The process is catalyzed by multiprotein complexes, the editosomes, and involves several enzymatic steps. A key component of editosomes is RNA editing ligase 1 (REL1). The crystal structure of this enzyme revealed a deep pocket that serves to bind and orient the essential ATP cofactor. Using a virtual drug screening strategy we had previously identified compounds that inhibit TbREL1 with micromolar IC50 values (Amaro, R., Schnaufer A. et al., 2008).
To identify additional hits for drug discovery efforts we generated a library of compounds similar to the known TbREL1 inhibitors by performing a substructure search against several databases of commercially available compounds. Top compounds, judged by their predicted binding energies, were docked against molecular dynamics snapshots to account for molecular flexibility. After further refinement, 34 top candidates were tested in biochemical assays. Four compounds inhibited REL1 with IC50 values between 1 and 10 μM. Efforts are under way to improve the in vitro activity and selectivity of these compounds and to establish their effect on trypanosomes
[Show abstract][Hide abstract] ABSTRACT: P116 RNA editing as a drug target in trypanosomes: development of a high throughput screening assay for RNA editing ligase 1
Laurence Hall & Achim Schnaufer
Institute of Immunology & Infection Research and Centre of Immunity, Infection & Evolution, University of Edinburgh, EH9 3J, UK
RNA editing is essential for mitochondrial gene expression in all trypanosomatids but absent from the host and potentially therefore a powerful drug target. The process is catalyzed by multiprotein complexes, the editosomes, and involves several enzymatic steps. Using a virtual drug screening strategy followed by biochemical validation we had previously identified compounds that inhibit TbREL1 with single-digit micromolar IC50 values (Amaro, R., Schnaufer A. et al., 2008). A further eight compounds with low-micromolar IC50 values were identified by substructure screening (Durrant, Hall et al. 2010, PLoS, Neglected Tropical Diseases 4(8): e803).
Our current efforts are focused on expediting compound library screens by developing a high throughput fluorescence-based (FRET) REL1 assay. We have systematically optimized the assay with respect to reaction chemistry; recombinant enzyme production; fluorophores and enzyme kinetics. This has significantly improved reaction rate, sensitivity and dynamic range. We will implement large scale compound library screens utilizing this improved FRET assay in association with the Drug Discovery Unity at the University of Dundee
[Show abstract][Hide abstract] ABSTRACT: Allosteric signaling occurs when chemical and/or physical changes at an allosteric site alter the activity of a primary orthosteric site often many Ångströms distant. A number of recently developed computational techniques, including dynamical network analysis, novel topological and molecular dynamics methods, and hybrids of these methods, are useful for elucidating allosteric signaling pathways at the atomistic level. No single method prevails as best to identify allosteric signal propagation path(s), rather each has particular strengths in characterizing signals that occur over specific timescale ranges and magnitudes of conformational fluctuation. With continued improvement in accuracy and predictive power, these computational techniques aim to become useful drug discovery tools that will allow researchers to identify allostery critical residues for subsequent pharmacological targeting.
Current Opinion in Structural Biology 03/2014; 25C:98-103. · 8.75 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Human African trypanosomiasis (HAT) is a major health problem in sub-Saharan Africa caused by Trypanosoma brucei infection. Current HAT drugs are difficult to administer and not effective against all parasite species at different stages of the disease which indicates an unmet pharmaceutical need. TbRET2 is an indispensable enzyme for the parasite and is targeted here using a computational approach that combines molecular dynamics simulations and virtual screening. The compounds prioritized are then tested in T. brucei via Alamar blue cell viability assays. This work identified 20 drug-like compounds which are candidates for further testing in the drug discovery process.
Chemical Biology & Drug Design 02/2014; · 2.51 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site many ångstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. Aside from providing signal redundancy, suboptimal paths traverse residues that, if disrupted through pharmacological or mutational means, could modulate the allosteric regulation of important drug targets. To demonstrate the utility of our program, we present a case study describing the allostery of HisH-HisF, an amidotransferase from T. maritima thermotiga. WISP and its VMD-based graphical user interface (GUI) can be downloaded from http://nbcr.ucsd.edu/wisp.
Journal of Chemical Theory and Computation 02/2014; 10(2):511-517. · 5.31 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Influenza is a global human health threat, and there is an immediate need for new antiviral therapies to circumvent the limitations of vaccination and current small molecule therapies. During viral transcription, influenza incorporates the 5'-end of the host cell's mRNA in a process that requires the influenza endonuclease. Based on recently published endonuclease crystalized structures, a three-dimensional pharmacophore was developed and used to virtually screen 450,000 compounds for influenza endonuclease inhibitors. Of 264 compounds tested in a FRET-based endonuclease-inhibition assay, 16 inhibitors (IC50 <50 μM) that span 5 molecular classes novel to this endonuclease were found (6.1% hit rate). To determine cytotoxicity and antiviral activity, subsequent cellular assays were performed. Two compounds suppress viral replication with negligible cell toxicity.
[Show abstract][Hide abstract] ABSTRACT: CYP19A1, also known as aromatase or estrogen synthetase, is the rate-limiting enzyme in the biosynthesis of estrogens from their corresponding androgens. Several clinically used breast cancer therapies target aromatase. In this work, explicitly solvated all-atom molecular dynamics simulations of aromatase with a model of the lipid bilayer and the transmembrane helix are performed. The dynamics of aromatase and the role of titration of an important amino acid residue involved in aromatization of androgens are investigated via two 250-ns long simulations. One simulation treats the protonated form of the catalytic aspartate 309, which appears more consistent with crystallographic data for the active site, while the simulation of the deprotonated form shows some notable conformational shifts. Ensemble-based computational solvent mapping experiments indicate possible novel druggable binding sites that could be utilized by next-generation inhibitors. In addition, the effects of protonation on the ligand positioning and channel dynamics are investigated using geometrical models that estimate the opening width of critical channels. Significant differences in channel dynamics between the protonated and deprotonated trajectories are exhibited, suggesting that the mechanism for substrate and product entry and the aromatization process may be coupled to a "locking" mechanism and channel opening. Our results may be particularly relevant in the design of novel drugs, which may be useful therapeutic treatments of cancers such as those of the breast and prostate.
Journal of Chemical Information and Modeling 08/2013; · 4.30 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: APOBEC3A and APOBEC3G are DNA cytosine deaminases with biological functions in foreign DNA and retrovirus restriction, respectively. APOBEC3A has an intrinsic preference for cytosine preceded by thymine (5'-TC) in single-stranded DNA substrates, whereas APOBEC3G prefers the target cytosine to be preceded by another cytosine (5'-CC). To determine the amino acids responsible for these strong dinucleotide preferences, we analyzed a series of chimeras in which putative DNA binding loop regions of APOBEC3G were replaced with the corresponding regions from APOBEC3A. Loop 3 replacement enhanced APOBEC3G catalytic activity but did not alter its intrinsic 5'-CC dinucleotide substrate preference. Loop 7 replacement caused APOBEC3G to become APOBEC3A-like and strongly prefer 5'-TC substrates. Simultaneous loop 3/7 replacement resulted in a hyperactive APOBEC3G variant that also preferred 5'-TC dinucleotides. Single amino acid exchanges revealed D317 as a critical determinant of dinucleotide substrate specificity. Multi-copy explicitly solvated all-atom molecular dynamics simulations suggested a model in which D317 acts as a helix-capping residue by constraining the mobility of loop 7, forming a novel binding pocket that favorably accommodates cytosine. All catalytically active APOBEC3G variants, regardless of dinucleotide preference, retained HIV-1 restriction activity. These data support a model in which the loop 7 region governs the selection of local dinucleotide substrates for deamination but is unlikely to be part of the higher level targeting mechanisms that direct these enzymes to biological substrates such as HIV-1 cDNA.
Journal of Molecular Biology 08/2013; · 3.91 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Chlamydia trachomatis is the most prevalent cause of bacterial sexually transmitted diseases and the leading cause of preventable blindness worldwide. Global control of Chlamydia will best be achieved with a vaccine, a primary target for which is the major outer membrane protein, MOMP, which comprises ∼60% of the outer membrane protein mass of this bacterium. In the absence of experimental structural information on MOMP, three previously published topology models presumed a16-stranded barrel architecture. Here, we use the latest β-barrel prediction algorithms, previous 2D topology modeling results, and comparative modeling methodology to build a 3D model based on the 16-stranded, trimeric assumption. We find that while a 3D MOMP model captures many structural hallmarks of a trimeric 16-stranded β-barrel porin, and is consistent with most of the experimental evidence for MOMP, MOMP residues 320-334 cannot be modeled as β-strands that span the entire membrane, as is consistently observed in published 16-stranded β-barrel crystal structures. Given the ambiguous results for β-strand delineation found in this study, recent publications of membrane β-barrel structures breaking with the canonical rule for an even number of β-strands, findings of β-barrels with strand-exchanged oligomeric conformations, and alternate folds dependent upon the lifecycle of the bacterium, we suggest that although the MOMP porin structure incorporates canonical 16-stranded conformations, it may have novel oligomeric or dynamic structural changes accounting for the discrepancies observed.
PLoS ONE 07/2013; 8(7):e68934. · 3.53 Impact Factor