First steps in the direction of synthetic,allosteric, direct inhibitors of thrombin and factor Xa

Designing non-saccharide functional mimics of heparin is a major challenge. In this work, a library of small, aromatic molecules based on the sulfated DHP scaffold was synthesized and screened against thrombin and factor Xa. The results reveal that (i) selected monomeric benzofuran derivatives inhibit the two enzymes, albeit weakly; (ii) the two enzymes recognize different structural features in the benzofurans studied suggesting significant selectivity of recognition; and (iii) the mechanism of inhibition is allosteric. The molecules represent the first allosteric small molecule inhibitors of the two enzymes.     

Fpocket: An open source platform for ligand pocket detection

Background  

Virtual screening methods start to be well established as effective approaches to identify hits, candidates and leads for drug discovery research. Among those, structure based virtual screening (SBVS) approaches aim at docking collections of small compounds in the target structure to identify potent compounds. For SBVS, the identification of candidate pockets in protein structures is a key feature, and the recent years have seen increasing interest in developing methods for pocket and cavity detection on protein surfaces.     

Identification and Validation of a Potent Dual Inhibitor of the P. falciparum M1 and M17 Aminopeptidases Using Virtual Screening

The Plasmodium falciparum PfA-M1 and PfA-M17 metalloaminopeptidases are validated drug targets for the discovery of antimalarial agents. In order to identify dual inhibitors of both proteins, we developed a hierarchical virtual screening approach, followed by in vitro evaluation of the highest scoring hits. Starting from the ZINC database of purchasable compounds, sequential 3D-pharmacophore and molecular docking steps were applied to filter the virtual ‘hits’. At the end of virtual screening, 12 compounds were chosen and tested against the in vitro aminopeptidase activity of both PfA-M1 and PfA-M17. Two molecules showed significant inhibitory activity (low micromolar/nanomolar range) against both proteins. Finally, the crystal structure of the most potent compound in complex with both PfA-M1 and PfA-M17 was solved, revealing the binding mode and validating our computational approach.     

Virtual screening against metalloenzymes for inhibitors and substrates

Molecular docking uses the three-dimensional structure of a receptor to screen databases of small molecules for potential ligands, often based on energetic complementarity. For many docking scoring functions, which calculate nonbonded interactions, metalloenzymes are challenging because of the partial covalent nature of metal-ligand interactions. To investigate how well molecular docking can identify potential ligands of metalloenzymes using a "standard" scoring function, we have docked the MDL Drug Data Report (MDDR), a functionally annotated database of 95,000 small molecules, against the X-ray crystal structures of five metalloenzymes. These enzymes included three zinc proteases, the nickel analogue of an iron enzyme, and a molybdenum metalloenzyme. The ability of the docking program to retrospectively enrich the annotated ligands as high-scoring hits for each enzyme and to calculate proper geometries was evaluated. In all five systems, the annotated ligands within the MDDR were enriched at least 20 times over random. To test the approach prospectively, a sixth target, the zinc beta-lactamase from Bacteroides fragilis, was screened against the fragment-like subset of the ZINC database. We purchased and tested 15 compounds from among the top 50 top-ranked ligands from docking, and found 5 inhibitors with apparent K(i) values less than 120 microM, the best of which was 2 microM. A more ambitious test still was predicting actual substrates for a seventh target, a Zn-dependent phosphotriesterase from Pseudomonas diminuta. Screening the Available Chemicals Directory (ACD) identified 25 thiophosphate esters as potential substrates within the top 100 ranked compounds. Eight of these, all previously uncharacterized for this enzyme, were acquired and tested, and all were confirmed experimentally as substrates. These results suggest that a simple, noncovalent scoring function may be used to identify inhibitors of at least some metalloenzymes.     

3-D clustering: a tool for high throughput docking

This report describes a computer program for clustering docking poses based on their 3-dimensional (3D) coordinates as well as on their chemical structures. This is chiefly intended for reducing a set of hits coming from high throughput docking, since the capacity to prepare and biologically test such molecules is generally far more limited than the capacity to generate such hits. The advantage of clustering molecules based on 3D, rather than 2D, criteria is that small variations on a scaffold may bring about different binding modes for molecules that would not be predicted by 2D similarity alone. The program does a pose-by-pose/atom-by-atom comparison of a set of docking hits (poses), scoring both spatial and chemical similarity. Using these pair-wise similarities, the whole set is clustered based on a user-supplied similarity threshold. An output coordinate file is created that mirrors the input coordinate file, but contains two new properties: a cluster number and similarity to the cluster center. Poses in this output file can easily be sorted by cluster and displayed together for visual inspection with any standard molecular viewing program, and decisions made about which molecule should be selected for biological testing as the best representative of this group of similar molecules with similar binding modes.     

Compound prioritization from inverse docking experiment using receptor‐centric and ligand‐centric methods: a case study on Plasmodium falciparum Fab enzymes

Prioritization of compounds using inverse docking approach is limited owing to potential drawbacks in its scoring functions. Classically, molecules ranked by best or lowest binding energies and clustering methods have been considered as probable hits. Mining probable hits from an inverse docking approach is very complicated given the closely related protein targets and the chemically similar ligand data set. To overcome this problem, we present here a computational approach using receptor‐centric and ligand‐centric methods to infer the reliability of the inverse docking approach and to recognize probable hits. This knowledge‐driven approach takes advantage of experimentally identified inhibitors against a particular protein target of interest to delineate shape and molecular field properties and use a multilayer perceptron model to predict the biological activity of the test molecules. The approach was validated using flavone derivatives possessing inhibitory activities against principal antimalarial molecular targets of fatty acid biosynthetic pathway, FabG, FabI and FabZ, respectively. We propose that probable hits can be retrieved by comparing the rank list of docking, quantitative‐structure activity relationship and multilayer perceptron models. Copyright © 2014 John Wiley & Sons, Ltd.     

Novel allosteric sites on Ras for lead generation

Aberrant Ras activity is a hallmark of diverse cancers and developmental diseases. Unfortunately, conventional efforts to develop effective small molecule Ras inhibitors have met with limited success. We have developed a novel multi-level computational approach to discover potential inhibitors of previously uncharacterized allosteric sites. Our approach couples bioinformatics analysis, advanced molecular simulations, ensemble docking and initial experimental testing of potential inhibitors. Molecular dynamics simulation highlighted conserved allosteric coupling of the nucleotide-binding switch region with distal regions, including loop 7 and helix 5. Bioinformatics methods identified novel transient small molecule binding pockets close to these regions and in the vicinity of the conformationally responsive switch region. Candidate binders for these pockets were selected through ensemble docking of ZINC and NCI compound libraries. Finally, cell-based assays confirmed our hypothesis that the chosen binders can inhibit the downstream signaling activity of Ras. We thus propose that the predicted allosteric sites are viable targets for the development and optimization of new drugs.     

Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K_i value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development.     

Synthesis and SAR of novel,non-MPEP chemotype mGluR5 NAMs identified by functional HTS

This Letter describes the discovery and SAR of three novel series of mGluR5 non-competitive antagonists/negative allosteric modulators (NAMs) not based on manipulation of an MPEP/MTEP chemotype identified by a functional HTS approach. This work demonstrates fundamentally new mGluR5 NAM chemotypes with submicromolar potencies, and further examples of a mode of pharmacology ‘switch’ to provide PAMs with a non-MPEP scaffold.     

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer’s disease

Alzheimer’s disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.     

Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies

c-Met receptor tyrosine kinase is a proto-oncogene whose aberrant activation is attributed to a lower rate of survival in most cancers. Natural product-derived inhibitors known as “fourth generation inhibitors” constitute more than 60% of anticancer drugs. Furthermore, consensus docking approach has recently been introduced to augment docking accuracy and reduce false positives during a virtual screening. In order to obtain novel small-molecule Met inhibitors, consensus docking approach was performed using Autodock Vina and Autodock 4.2 to virtual screen Naturally Occurring Plant-based Anti-cancer Compound–Activity–Target database against active and inactive conformation of c-Met kinase domain structure. Two hit molecules that were in line with drug-likeness criteria, desired docking score, and binding pose were subjected to molecular dynamics simulations to elucidate intermolecular contacts in protein–ligand complexes. Analysis of molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area studies showed that ZINC08234189 is a plausible inhibitor for the active state of c-Met, whereas ZINC03871891 may be more effective toward active c-Met kinase domain compared to the inactive form due to higher binding energy. Our analysis showed that both the hit molecules formed hydrogen bonds with key residues of the hinge region (P1158, M1160) in the active form, which is a hallmark of kinase domain inhibitors. Considering the pivotal role of HGF/c-Met signaling in carcinogenesis, our results propose ZINC08234189 and ZINC03871891 as the therapeutic options to surmount Met-dependent cancers.     

Protein Allostery and Ligand Design: Computational Design Meets Experiments to Discover Novel Chemical Probes

Herein we examine the determinants of the allosteric inhibition of the mitochondrial chaperone TRAP1 by a small molecule ligand. The knowledge generated is harnessed into the design of novel derivatives with interesting biological properties.TRAP1 is a member of the Hsp90 family of proteins, which work through sequential steps of ATP processing coupled to client-protein remodeling. Isoform selective inhibition of TRAP1 can provide novel information on the biomolecular mechanisms of molecular chaperones, as well as new insights into the development of small molecules with therapeutic potential.Our analysis of the interactions between an active first-generation allosteric ligand and TRAP1 shows how the small molecule induces long-range perturbations that influence the attainment of reactive poses in the active site. At the same time, the dynamic adaptation of the allosteric binding pocket to the presence of the first-generation compound sets the stage for the design of a set of second-generation ligands: the characterization of the formation/disappearance of pockets around the allosteric site that is used to guide optimize the ligands’ fit for the allosteric site and improve inhibitory activities. The effects of the newly designed molecules are validated experimentally in vitro and in vivo. We discuss the implications of our approach as a promising strategy towards understanding the molecular determinants of allosteric regulation in chemical and molecular biology, and towards speeding up the design of allosteric small molecule modulators.     

Virtual screening for novel COX-2 inhibitors using the ZINC database

Cyclooxygenase-2 (COX-2) enzyme binds to arachidonic acid and releases metabolites that are used to induce pain and inflammation. COX-2 selective inhibitors such as celecoxib, rofecoxib and valdecoxib are currently used to reduce inflammatory response. However, they lack anti-thrombotic activity and hence lead to cardiovascular and renal liabilities apart from gastrointestinal irritation. Therefore, there is still a need to develop more potent COX-2 inhibitors. In this paper, we report the screening of various compounds from the ZINC database (contains 4.6 million small molecule compounds) using the eHiTS (electronic High Throughput Screening) software tool against the COX-2 protein. The strategy employed can be conveniently split into two categories, viz. screening and docking, respectively. Screening was performed using molecular constraints tool to filter compounds with physico-chemical properties similar to the 6COX bound ligand SC-558. The analysis resulted in 1042 Lipinski compliant hits which are docked and scored to identify structurally novel ligands that make similar interactions to those of known ligands or may have different interactions with other parts of the binding site. Our screening approach identified two molecules ZINC00663976 (eHITS score of -7.135 kcal/mol) and ZINC02062094 (eHITS score of -7.242 kcal/mol) from the ZINC database. Their energy scores are better than the 6COX bound co-crystallized ligand SC-558 with an eHiTS score of -6.559 kcal/mol. Both the ligands were docked within the binding pocket forming interactions with Leu352, Phe518, Met522, Val523, Ala527 and Ser353. Visual inspection suggested similar orientation and binding mode for ZINC02062094 with SC-558 ligand. The NH group of the ligand formed hydrogen bond interactions with the backbone NH of Ala527.     

Proposed lead molecules against Hemagglutinin of avian influenza virus (H5N1)

Human infection with avian influenza H5N1 is an emerging infectious disease characterized by respiratory symptoms and a high fatality rate. Hemagglutinin and neuraminidase are the two surface proteins responsible for infection by influenza virus. Till date, neuraminidase has been the major target for antiviral drugs. In the present study we chose hemagglutinin protein as it mediates the binding of the virus to target cells through sialic acid residues on the host cell-surface. Hemagglutinin of H5 avian influenza (PDB ID: 1JSN) was used as the receptor protein. Ligands were generated by structure-based de novo approach and virtual screening of ZINC database. A total of 11,104 conformers were generated and docked into the receptor binding site using 'High Throughput Virtual Screening'. We proposed potential lead molecules against the receptor binding site of hemagglutinin based on the results obtained from in silico docking and hydrogen bond interaction between the ligand and the 1JSN protein molecule. We found sialic acid derivative 1 to be the lead molecules amongst the ligands generated by structure based de novo approach. However the molecules obtained from ZINC database were showing better docking scores as well as conserved hydrogen bond interactions. Thus we proposed ZINC00487720 and ZINC00046810 as potential lead molecules that could be used as an inhibitor to the receptor binding site of hemagglutinin. They could now be studied in vivo to validate the in silico results.     

Discovery of novel MDR-Mycobacterium tuberculosis inhibitor by new FRIGATE computational screen

With 1.6 million casualties annually and 2 billion people being infected, tuberculosis is still one of the most pressing healthcare challenges. Here we report on the new computational docking algorithm FRIGATE which unites continuous local optimization techniques (conjugate gradient method) with an inherently discrete computational approach in forcefield computation, resulting in equal or better scoring accuracies than several benchmark docking programs. By utilizing FRIGATE for a virtual screen of the ZINC library against the Mycobacterium tuberculosis (Mtb) enzyme antigen 85C, we identified novel small molecule inhibitors of multiple drug-resistant Mtb, which bind in vitro to the catalytic site of antigen 85C.     

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with ?96.462, ?143.549, and ?122.526 kJ mol^?1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.     

The impact of cryo-EM on determining allosteric modulator-bound structures of G protein-coupled receptors

G-protein coupled receptors (GPCRs) are important therapeutic targets for the treatment of human disease. Although GPCRs are highly successful drug targets, there are many challenges associated with the discovery and translation of small molecule ligands that target the endogenous ligand-binding site for GPCRs. Allosteric modulators are a class of ligands that target alternative binding sites known as allosteric sites and offer fresh opportunities for the development of new therapeutics. However, only a few allosteric modulators have been approved as drugs. Advances in GPCR structural biology enabled by the cryogenic electron microscopy (cryo-EM) revolution have provided new insights into the molecular mechanism and binding location of small molecule allosteric modulators. This review highlights the latest findings from allosteric modulator-bound structures of Class A, B, and C GPCRs with a focus on small molecule ligands. Emerging methods that will facilitate cryo-EM structures of more difficult ligand-bound GPCR complexes are also discussed. The results of these studies are anticipated to aid future structure-based drug discovery efforts across many different GPCRs.     

Negative allosteric modulators of cannabinoid receptor 2: protein modeling,binding site identification and molecular dynamics simulations in the presence of an orthosteric agonist

Abstract

Selective activation of the cannabinoid receptor subtype 2 (CB2) shows promise for treating pain, inflammation, multiple sclerosis, cancer, ischemic/reperfusion injury and osteoporosis. Target selectivity and off-target side effects are two major limiting factors for orthosteric ligands, and therefore, the search for allosteric modulators (AMs) is a widely used drug discovery approach. To date, only a limited number of negative CB2 AMs have been identified, possessing only micromolar activity at best, and the CB2 receptor’s allosteric site(s) are not well characterized. Herein, we used computational approaches including receptor modeling, site mapping, docking, molecular dynamics (MD) simulations and binding free energy calculations to predict, characterize and validate allosteric sites within the complex of the CB2 receptor with bound orthosteric agonist CP55,940. After docking of known negative CB2 allosteric modulators (NAMs), dihydro-gambogic acid (DHGA) and trans-β-caryophyllene (TBC) (note that TBC also shows agonist activity), at the predicted allosteric sites, the best total complex with CB2, CP55,940 and NAM was embedded into a hydrated lipid bilayer and subjected to a 200 ns MD simulation. The presence of an AM affected the CB2–CP55,940 complex, altering the relative positioning of the toggle switch residues and promoting a strong π–π interaction between Phe117^3.36 and Trp258^6.48. Binding of either TBC or DHGA to a putative allosteric pocket directly adjacent to the orthosteric ligand reduced the binding free energy of CP55,940, which is consistent with the expected effect of a negative AM. The identified allosteric sites present immense scope for the discovery of novel classes of CB2 AMs.