Identification of potential inhibitors for HCV NS5b of genotype 4a by combining dynamic simulation,protein–ligand interaction fingerprint, 3D pharmacophore,docking and 3D QSAR

Abstract

HCV NS5B polymerase has been one of the most attractive targets for developing new drugs for HCV infection and many drugs were successfully developed, but all of them were designed for targeting Hepatitis C Virus genotype 1 (HCV GT1). Hepatitis C virus genotype 4a (HCV GT4a) dominant in Egypt has paid less attention. Here, we describe our protocol of virtual screening in identification of novel potential potent inhibitors for HCV NS5B polymerase of GT4a using homology modeling, protein–ligand interaction fingerprint (PLIF), docking, pharmacophore, and 3D CoMFA quantitative structure activity relationship (QSAR). Firstly, a high-quality 3D model of HCV NS5B polymerase of GT4a was constructed using crystal structure of HCV NS5B polymerase of GT1 (PDB ID: 3hkw) as a template. Then, both the model and the template were simulated to compare conformational stability. PLIF was generated using five crystal structures of HCV NS5B (PDB ID: 4mia, 4mib, 4mk9, 4mka, and 4mkb), which revealed the most important residues and their interactions with the co-crystalized ligands. After that, a 3D pharmacophore model was developed from the generated PLIF data and then used as a screening filter for 17000328 drug-like zinc database compounds. 900 compounds passed the pharmacophore filter and entered the docking-based virtual screening stage. Finally, a 3D CoMFA QSAR was developed using 42 compounds as a training and 19 compounds as a test set. The 3D CoMFA QSAR was used to design and screen some potential inhibitors, these compounds were further evaluated by the docking stage. The highest ranked five hits from docking result (compounds (p1–p4) and compound q1) were selected for further analysis.

Communicated by Ramaswamy H. Sarma     

Identification of Pak1 inhibitors using water thermodynamic analysis

Abstract

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.     

Identification of novel inhibitors of HCV RNA-dependent RNA polymerase by pharmacophore-based virtual screening and in vitro evaluation

Hepatitis C virus (HCV) is the major etiological agent of non-A, non-B hepatitis where no effective treatment is available. The HCV NS5B with RNA-dependent RNA polymerase (RdRp) activity is a key target for the treatment of HCV infection. Here we report novel NS5B polymerase inhibitors identified by virtual screening and in vitro evaluation of their inhibitory activities. On the basis of a newly identified binding pocket of NS5B, distinct from the nucleotide binding site but highly conserved among various HCV isolates, we performed virtual screening of compounds that fit this binding pocket from the available chemical database of 3.5 million compounds. The inhibitory activities of the in silico selected 119 compounds were estimated with in vitro RdRp assay. Three compounds with IC50 values of about 20 μM were identified, and their kinetic analyses suggest that these compounds are noncompetitive inhibitors with respect to the ribonucleotide substrate. Furthermore, the single-point mutations of the conserved residues in the binding pocket of NS5B resulted in the significant decrease of the RdRp activity, indicating that the binding pocket presented here might be important for the therapeutic intervention of HCV. These novel inhibitors would be useful for the development of effective anti-HCV agents.     

Structure-based virtual screening,synthesis and SAR of novel inhibitors of hepatitis C virus NS5B polymerase

Hepatitis C virus (HCV) NS5B polymerase is a key target for the development of therapeutic agents aimed at the treatment of HCV infections. Here we report on the identification of novel allosteric inhibitors of HCV NS5B through a combination of structure-based virtual screening, synthesis and structure–activity relationship (SAR) optimization approach. Virtual screening of 260,000 compounds from the ChemBridge database against the tetracyclic indole inhibitor binding pocket of NS5B (allosteric pocket-1, AP-1), sequentially down-sized the library by 4 orders of magnitude to yield 23 candidates. In vitro evaluation of the NS5B inhibitory activity of the in-silico selected compounds resulted in 17% hit rate, identifying two novel chemotypes. Of these, compound 3, bearing the rhodanine scaffold, proved amenable for productive SAR exploration and synthetic modification. As a result, 25 derivatives that exhibited IC₅₀ values ranging from 7.7 to 68.0 μM were developed. Docking analysis of lead compound 28 within the tetracyclic indole- and benzylidene-binding allosteric pockets (AP-1 and AP-3, respectively) of NS5B revealed topological similarities between these two pockets. Compound 28, a novel rhodanine analog with NS5B inhibitory potency in the low micromolar level range may be a promising lead for future development of more potent NS5B inhibitors.     

New molecular scaffolds for the design of Mycobacterium tuberculosis type II dehydroquinase inhibitors identified using ligand and receptor based virtual screening

Using ligand and receptor based virtual screening approaches we have identified potential virtual screening hits targeting type II dehydroquinase from Mycobacterium tuberculosis, an effective and validated anti-mycobacterial target. Initially, we applied a virtual screening workflow based on a combination of 2D structural fingerprints, 3D pharmacophore and molecular docking to identify compounds that rigidly match specific aspects of ligand bioactive conformation. Subsequently, the resulting compounds were ranked and prioritized using receptor interaction fingerprint based scoring and quantitative structure activity relationship model developed using already known actives. The virtual screening hits prioritized belong to several classes of molecular scaffolds with several available substitution positions that could allow chemical modification to enhance binding affinity. Finally, identified hits may be useful to a medicinal chemist or combinatorial chemist to pick up the new molecular starting points for medicinal chemistry optimization for the design of novel type II dehydroquinase inhibitors.     

Computationally guided identification of Akt-3, a serine/threonine kinase inhibitors: Insights from homology modelling,structure-based screening,molecular dynamics and quantum mechanical calculations

Abstract

Chemical entities targeting kinase signalling pathways serve as a potential strategy to combat malignancies. Protein Kinase B or Akt is a validated target for various malignancies and Akt3 remains the least explored isoform among all its isoforms. Initially, homology modelling technique was used for generating protein structure and further validation was performed using molecular dynamics simulation and Ramachandran plot. The validated protein structure was then subjected for active site analysis which led to identification of active site residues based on metrics provided by site score. The important residues in binding site were identified as Thr81, Asp271 and Asp289 for binding energetics and inhibition. Subsequently, virtual screening methodologies were used for identification of novel hits for inhibition of Protein Kinase B or Akt3. This led to the identification of two hits, i.e. thiophene derivative and thieno-pyridine derivative which were selected on the basis of their binding affinity and drug likeliness. These identified hits were subjected for molecular dynamics simulations, quantum mechanical and synthetic accessibility studies. The role of crucial residues in binding site stood validated as suggested by molecular dynamics simulations studies.

Communicated by Ramaswamy H. Sarma     

Fragment-based discovery of hepatitis C virus NS5b RNA polymerase inhibitors

Non-nucleoside inhibitors of HCV NS5b RNA polymerase were discovered by a fragment-based lead discovery approach, beginning with crystallographic fragment screening. The NS5b binding affinity and biochemical activity of fragment hits and inhibitors was determined by surface plasmon resonance (Biacore) and an enzyme inhibition assay, respectively. Crystallographic fragment screening hits with 1–10 mM binding affinity (K_D) were iteratively optimized to give leads with 200 nM biochemical activity and low μM cellular activity in a Replicon assay.     

Discovery of novel small-molecule Src kinase inhibitors via a kinase-focused druglikeness rule and structure-based virtual screening

Overexpression of the non-receptor tyrosine kinase Src is implicated in the development and progression of various human cancers. Blocking signalling pathways mediated by Src is believed to be a promising anticancer strategy. We report herein the discovery of novel small-molecule Src inhibitors by crystal structure-based virtual screening. A kinase-focused druglikeness rule was proposed and used in the design of compound library. Combination of large-scale docking with DOCK and rescoring with GOLD resulted in 6 hits with moderate to potent inhibitory activity against Src. Among them, compound 1 with an IC₅₀ of 1.2 μM shows the most potent inhibitory activity. By using molecular docking, binding models of the top 3 hits (ranked by potency and ligand efficiency) with Src were constructed to provide a rational strategy that simultaneously exploits hydrogen bonding interaction in the hinge region and hydrophobic stacking in the back pocket. This approach is instructive and meaningful to further structure-based drug design of Src inhibitors.     

Identification of plasmepsin inhibitors as selective anti-malarial agents using ligand based drug design

We describe the application of ligand based virtual screening technologies towards the discovery of novel plasmepsin (PM) inhibitors, a family of malarial parasitic aspartyl proteases. Pharmacophore queries were used to screen vendor libraries in search of active and selective compounds. The virtual hits were biologically assessed for activity and selectivity using whole cell Plasmodium falciparum parasites and on target in PM II, PM IV and the closely related human homologue, Cathepsin D assays. Here we report the virtual screening highlights, structures of the hits and their demonstrated biological activity.     

Discovery of novel HCV polymerase inhibitors using pharmacophore-based virtual screening

We report the use of pharmacophore-based virtual screening as an efficient tool for the discovery of novel HCV polymerase inhibitors. A three-dimensional pharmacophore model for the HCV-796 binding site, NNI site IV inhibitor, to the enzyme was built by means of the structure-based focusing module in Cerius2 program. Using these models as a query for virtual screening, we produced a successful example of using pharmacophore-based virtual screening to identify novel compounds with HCV replicon assay through inhibition of HCV polymerization. Among the hit compounds, compounds 1 and 2 showed 56% and 48% inhibition of NS5B polymerization activity at 20 μM, respectively. In addition, compound 1 also exhibited replicon activity with EC₅₀ value of 2.16 μM. Following up the initial hit, we obtained derivatives of compound 1 and evaluated polymerization inhibition activity and HCV replicon assay. These results provide information necessary for the development of more potent NS5B inhibitors.     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Discovery of potent apoptosis signal-regulating kinase 1 inhibitors via integrated computational strategy and biological evaluation

Abstract

Apoptosis signal-regulating Kinase 1 (ASK1) has been confirmed as a potential therapeutic target for the treatment of non-alcoholic steatohepatitis (NASH) disorder and the discovery of ASK1 inhibitors has attracted increasing attention. In this work, a series of in silico methods including pharmacophore screening, docking binding site analysis, protein-ligand interaction fingerprint (PLIF) similarity investigation and molecular docking were applied to find the potential hits from commercial compound databases. Five compounds with potential inhibitory activity were purchased and submitted to biological activity validation. Thus, one hit compound was discovered with micromolar IC₅₀ value (10.59?μM) against ASK1. Results demonstrated that the integration of computation methods and biological test was quite reliable for the discovery of potent ASK1 inhibitors and the strategy could be extended to other similar targets of interest.     

Identification of novel small molecule non-peptidomimetic inhibitor for prolyl oligopeptidase through in silico and in vitro approaches

Abstract

Prolyl oligopeptidase (POP) enzyme has been studied for various disorders, viz. Schizophrenia, Alzheimer’s, Parkinson’s, Depression, Inflammation, etc., for three decades, but no drug has passed through the clinical trials, possibly because of indigent pharmacokinetics. This might have been a result of similar structures of drug candidates. This study aimed at identifying novel small non-peptidomimetic inhibitors for POP enzyme that could serve as a lead for developing newer drugs. Structure-based virtual screening of molecules of MolMall database was conducted on the POP enzyme (PDB ID 3DDU) to identify potential hits. The hits identified were subjected to computational pharmacokinetic screening followed by molecular mechanics/generalized Born and surface area studies to estimate the binding free energy of the docked complexes. After that, nine hits were selected and tested for POP inhibitory activity, among which one compound MM 4 was found to be most potent with EC₅₀ of 100 µM. Compound MM 4 was further subjected to molecular dynamics simulations to study the overall stability of the ligand–protein complex. The compound interacted strongly with catalytic amino acid Arg643 by forming salt and water bridges; it also interacted well with amino acids Phe173, Arg252 and Met235. This study provides a lead molecule for further development of POP inhibitors.

Communicated by Ramaswamy H. Sarma     

Screening of hepatitis C NS5B polymerase inhibitors containing benzothiadiazine core: a steered molecular dynamics

Hepatic C virus (HCV) is a global health problem, resulting in liver cirrhosis and inflammation that can develop to hepatocellular carcinoma and fatality. The NS5B polymerase of HCV plays an important role in viral RNA replication process, making it an attractive therapeutic target for design and development of anti-HCV drugs. To search new potent compounds against the HCV NS5B polymerase, the molecular docking and the steered molecular dynamics (SMD) simulation techniques were performed. The potential potent inhibitors of the NS5B polymerase were screened out from the ZINC database using structural similarity search and molecular docking technique. Five top-hit compounds (the ZINC compounds 49888724, 49054741, 49777239, 49793673, and 49780355) were then studied by the SMD simulations based on the hypothesis that a high rupture force relates to a high binding efficiency. The results demonstrated that the ZINC compound 49888724 had a greater maximum rupture force, reflecting a good binding strength and inhibitory potency than known inhibitors and the rest four ZINC compounds. Therefore, our finding indicated that the ZINC compound 49888724 is a potential candidate to be a novel NS5B inhibitor for further design. Besides, the van der Waals interaction could be considered as the main contribution for stabilizing the NS5B-ligand complex.     

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

Receptor based 3D-QSAR to identify putative binders of Mycobacterium tuberculosis Enoyl acyl carrier protein reductase

In the current study, the applicability and scope of 3D-QSAR models (CoMFA and CoMSIA) to complement virtual screening using 3D pharmacophore and molecular docking is examined and applied to identify potential hits against Mycobacterium tuberculosis Enoyl acyl carrier protein reductase (MtENR). Initially CoMFA and CoMSIA models were developed using series of structurally related arylamides as MtENR inhibitors. Docking studies were employed to position the inhibitors into MtENR active site to derive receptor based 3D-QSAR models. Both CoMFA and CoMSIA yielded significant cross validated q² values of 0.663 and 0.639 and r² values of 0.989 and 0.963, respectively. The statistically significant models were validated by a test set of eight compounds with predictive r² value of 0.882 and 0.875 for CoMFA and CoMSIA. The contour maps from 3D-QSAR models in combination with docked binding structures help to better interpret the structure activity relationship. Integrated with CoMFA and CoMSIA predictive models structure based (3D-pharmacophore and molecular docking) virtual screening have been employed to explore potential hits against MtENR. A representative set of 20 compounds with high predicted IC₅₀ values were sorted out in the present study.     

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.