A profound computational study to prioritize the natural compound inhibitors against the P. falciparum orotidine-5-monophosphate decarboxylase enzyme

Abstract

In the current contribution, a multicomplex-based pharmacophore modeling approach was employed on the structural proteome of Plasmodium falciparum orotidine-5-monophosphate decarboxylase enzyme (PfOMPDC). Among the constructed pharmacophore models, the representative hypotheses were selected as the primary filter to screen the molecules with the complementary features responsible for showing inhibition. Thereafter, auxiliary evaluations were performed on the screened candidates via drug-likeness and molecular docking studies. Subsequently, the stability of the docked protein-ligand complexes was scrutinized by employing molecular dynamics simulations and molecular mechanics-Poisson Boltzmann surface area based free binding energy calculations. The stability the docked candidates was compared with the highly active crystallized inhibitor (3S9Y-FNU) to seek more potential candidates. All the docked molecules displayed stable dynamic behavior and high binding free energy in comparison to 3S9Y-FNU. The employed workflow resulted in the retrieval of five drug-like candidates with diverse scaffolds that may show inhibitory activity against PfOMPDC and could be further used as the novel scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

3D-QSAR pharmacophore-based virtual screening,molecular docking and molecular dynamics simulation toward identifying lead compounds for NS2B–NS3 protease inhibitors

NS2B–NS3 protease has been identified to serve as lead drug design target due to its significant role in West Nile viral (WNV) and dengue virus (DENV) reproduction and replication. There are currently no approved chemotherapeutic drugs and effective vaccines to inhibit DENV and WNV infections. In this work, 3D-QSAR pharmacophore model has been developed to discover potential inhibitory candidates. Validation through Fischer’s model and decoy test indicate that the developed 3D pharmacophore model is highly predictive for DENV inhibitors, which was then employed to screen ZINC chemical library to obtain reasonable hits. Following ADMET filtering, 15 hits were subjected to further filter through molecular docking and CoMFA modeling. Finally, top three hits were identified as lead compounds or potential inhibitory candidates with IC₅₀ values of ～0.4637?µM and fitness of ～57.73. It is implied from CoMFA modeling that substituents at the side site of benzotriazole such as a p-nitro group (e.g. biphenyl head) and a carbonyl (e.g. carboxylate function) at the side site of furan or amino group may improve bioactivity of ZINC85645245, respectively. Molecular dynamics simulations (MDS) were performed to discover new interactions and reinforce the binding modes from docking for the hits also. The QSAR and MDS results obtained from this work should be useful in determining structural requirements for inhibitor development as well as in designing more potential inhibitors for NS2B–NS3 protease.     

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM,pharmacophore and docking model

Abstract

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.     

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.     

Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing

Abstract

Histone deacetylases (HDACs), a critical family of epigenetic enzymes, has emerged as a promising target for antitumor drugs. Here, we describe our protocol of virtual screening in identification of novel potential HDAC inhibitors through pharmacophore modeling, 3D-QSAR, molecular docking and molecular dynamics (MD) simulation. Considering the limitation of current virtual screening works, drug repurposing strategy was applied to discover druggable HDAC inhibitor. The ligand-based pharmacophore and 3D-QSAR models were established, and their reliability was validated by different methods. Then, the DrugBank database was screened, followed by molecular docking. MD simulation (100?ns) was performed to further study the stability of ligand binding modes. Finally, results indicated the hit DB03889 with high in silico inhibitory potency was suitable for further experimental analysis.

Communicated by Ramaswamy H. Sarma     

Reliable structural information for rational design of benzoxazole type potential cholesteryl ester transfer protein (CETP) inhibitors through multiple validated modeling techniques

Abstract

The drug design and discovery of lipid modulators is very demanding as no new molecule has entered into the market in the last 35 years. Cholesteryl ester transfer protein (CETP) is a promising target as lipid modulators. Inhibition of the CETP enzyme reduces the risk of cardiovascular events. The first CETP inhibitor torcetrapib and related drug candidates failed in the clinical trial due to the off-target effects leading to high toxicity. Thus, newer CETP inhibitors have now paramount importance to accelerate the drug discovery efforts in the field of cardiovascular disease (CVD). In the present study, 140 benzoxazole compounds were studied by using different chemometric techniques, for example, pharmacophore mapping, molecular docking, three-dimensional quantitative structure–activity relationship comparative molecular field analysis (3D-QSAR CoMFA), topomer CoMFA and Bayesian classification, in order to generate complete and reliable information regarding the structural requirements for the CETP inhibition. The best pharmacophore hypothesis was statistically significant (regression coefficient of 0.957 and a lower root mean square of 0.890). Molecular docking study revealed that cyano-substituted compounds form hydrogen bond with targeted macromolecule. The 3D-QSAR CoMFA model also produced a leave-one-out (LOO) cross-validated Q² of 0.527, an R² of 0.853 and an R²_Pred of 0.603. Similarly, two topomer CoMFA models were also statistically significant and reliable in terms of their Q², R² and R²_Pred values. The Bayesian classification study also provided the excellent ROC values of 0.919 and 0.939 for training and test sets, respectively. Overall, this study may help in the rational design of newer benzoxazole type compounds with higher CETP inhibition.

Communicated by Ramaswamy H. Sarma     

Identification of potential leukocyte antigen-related protein (PTP-LAR) inhibitors through 3D QSAR pharmacophore-based virtual screening and molecular dynamics simulation

Abstract

Owing to its negative regulatory role in insulin signaling, protein tyrosine phosphatase of leukocyte antigen-related protein (PTP-LAR) was widely thought as a potential drug target for diabetes. Now, it was urgent to search for potential LAR inhibitors targeting diabetes. Initially, the pharmacophore models of LAR inhibitors were established with the application of the HypoGen module. The cost analysis, test set validation, as well as Fischer’s test was used to verify the efficiency of pharmacophore model. Then, the best pharmacophore model (Hypo-1-LAR) was applied for the virtual screening of the ZINC database. And 30 compounds met the Lipinski’s rule of five. Among them, 10 compounds with better binding affinity than the known LAR inhibitor (BDBM50296375) were discovered by docking studies. Finally, molecular dynamics simulations and post-analysis experiments (RMSD, RMSF, PCA, DCCM and RIN) were conducted to explore the effect of ligands (ZINC97018474 and Compound 1) on LAR and preliminary understand why ZINC97018474 had better inhibitory activity than Compound 1 (BDBM50296375).

Communicated by Ramaswamy H. Sarma     

Computational Structure-Based De Novo Design of Hypothetical Inhibitors against the Anti- Inflammatory Target COX-2

Cyclooxygenase-2 (COX-2) produces prostaglandins in inflamed tissues and hence has been considered as an important target for the development of anti-inflammatory drugs since long. Administration of traditional non-steroidal anti-inflammatory drugs (NSAIDs) and other COX-2 selective inhibitors (COXIBS) for the treat of inflammation has been found to be associated with side effects, which mainly includes gastro-intestinal (GI) toxicity. The present study involves developing a virtual library of novel molecules with high druglikeliness using structure-based de novo drug designing and 2D fingerprinting approach. A library of 2657 drug like molecules was generated. 2D fingerprinting based screening of the designed library gave a unique set of compounds. Molecular docking approach was then used to identify two compounds highly specific for COX-2 isoform. Molecular dynamics simulations of protein-ligand complexes revealed that the candidate ligands were dynamically stable within the cyclooxygenase binding site of COX-2. The ligands were further analyzed for their druglikeliness, ADMET properties and synthetic accessibility using knowledge based set of rules. The results revealed that the molecules are predicted to selectively bind to COX-2 enzyme thereby potentially overcoming the limitations posed by the drugs in clinical use.     

Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

Computational Chemistry in Lead Identification,Library Design and Lead Optimisation

Abstract

We describe a variety of the computational techniques which we use in the drug discovery and design process. Some of these computational methods are designed to support the new experimental technologies of high-throughput screening and combinatorial chemistry. We also consider some new approaches to problems of long-standing interest such as protein-ligand docking and the prediction of free energies of binding.     

Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of PfDHFR inhibitors

Abstract

Plasmodium falciparum dihydrofolate reductase enzyme (PfDHFR) is counted as one of the attractive and validated antimalarial drug targets. However, the point mutations in the active site of wild-type PfDHFR have developed resistance against the well-known antifolates. Therefore, there is a dire need for the development of inhibitors that can inhibit both wild-type and mutant-type DHFR enzyme. In the present contribution, we have constructed the common feature pharmacophore models from the available PfDHFR. A representative hypothesis was prioritized and then employed for the screening of natural product library to search for the molecules with complementary features responsible for the inhibition. The screened candidates were processed via drug-likeness filters and molecular docking studies. The docking was carried out on the wild-type PfDHFR (3QGT); double-mutant PfDHFR (3UM5 and 1J3J) and quadruple-mutant PfDHFR (1J3K) enzymes. A total of eight common hits were obtained from the docking calculations that could be the potential inhibitors for both wild and mutant type DHFR enzymes. Eventually, the stability of these candidates with the selected proteins was evaluated via molecular dynamics simulations. Except for SPECS14, all the prioritized candidates were found to be stable throughout the simulation run. Overall, the strategy employed in the present work resulted in the retrieval of seven candidates that may show inhibitory activity against PfDHFR and could be further exploited as a scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

Ligand‐based pharmacophore modelling and screening of DNA minor groove binders targeting Staphylococcus aureus

The recognition of DNA by small molecules is of special importance in the design of new drugs. Many natural and synthetic compounds have the ability to interact with the minor groove of DNA. In the present study, identification of minor groove binding compounds was attained by the combined approach of pharmacophore modelling, virtual screening and molecular dynamics approach. Experimentally reported 32 minor groove binding compounds were used to develop the pharmacophore model. Based on the fitness score, best three pharmacophore hypotheses were selected and used as template for screening the compounds from drug bank database. This pharmacophore‐based screening provides many compounds with the same pharmacological properties. All these compounds were subjected to four phases of docking protocols with combined Glide‐quantum‐polarized ligand docking approach. Molecular dynamics results indicated that selected compounds are more active and showed good interaction in the binding site of DNA. Based on the scoring parameters and energy values, the best compounds were selected, and antibacterial activity of these compounds was identified using in vitro antimicrobial techniques. Copyright © 2014 John Wiley & Sons, Ltd.     

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening,molecular dynamics simulation,and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol^?1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.     

Fourteenth research symposium University of Durham 1974

Abstract

Background: Few studies analysing lichen diversity have simultaneously considered interactions among drivers that operate at different spatial and temporal scales.

Aims: The aims of this study were to evaluate the relative importance of host tree, and local, landscape and historical factors in explaining lichen diversity in managed temperate forests, and to test the potential interactions among factors acting at different spatial scales.

Methods: Thirty-five stands were selected in the ?rség region of western Hungary. Linear models and multi-model inference within an information-theory framework were used to evaluate the role of different variables on lichen species richness.

Results: Drivers at multiple spatial scales contributed to shaping lichen species richness both at the tree and plot levels. Tree-level species richness was related to both tree- and plot-level factors. With increasing relative diffuse light lichen species richness increased; this effect was stronger on the higher than on the lower part of the trunks. At the plot scale, species richness was affected by local drivers. Landscape and historical factors had no, or only a marginal, effect.

Conclusions: Lichen conservation in temperate managed forests could be improved if the complex interactions among host tree quality and availability, micro-climatic conditions, and management were taken into consideration.     

Homology modeling,docking and structure-based virtual screening for new inhibitor identification of Klebsiella pneumoniae heptosyltransferase-III

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative opportunistic pathogen commonly associated with hospital-acquired infections that are often resistant even to antibiotics. Heptosyltransferase (HEP) belongs to the family of glycosyltransferase-B (GT-B) and plays an important in the synthesis of lipopolysaccharides (LPS) essential for the formation of bacterial cell membrane. HEP-III participates in the transfer of heptose sugar to the outer surface of bacteria to synthesize LPS. LPS truncation increases the bacterial sensitivity to hydrophobic antibiotics and detergents, making the HEP as a novel drug target. In the present study, we report the 3D homology model of K. pneumoniae HEP-III and its structure validation. Active site was identified based on similarities with known structures using Dali server, and structure-based pharmacophore model was developed for the active site substrate ADP. The generated pharmacophore model was used as a 3D search query for virtual screening of the ASINEX database. The hit compounds were further filtered based on fit value, molecular docking, docking scores, molecular dynamics (MD) simulations of HEP-III complexed with hit molecules, followed by binding free energy calculations using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA). The insights obtained in this work provide the rationale for design of novel inhibitors targeting K. pneumoniae HEP-III and the mechanistic aspects of their binding.

Communicated by Ramaswamy H. Sarma     

Identification of novel G-protein-coupled receptor 40 (GPR40) agonists by hybrid in silico-screening techniques and molecular dynamics simulations thereof

Abstract

Diabetes is a major health problem worldwide predisposing to increased mortality and morbidity. The current antidiabetic therapies have serious side effects and thus have emphasis on further need to develop effective medication therapy. Free fatty acid1 receptor (FFA1R) or G-protein-coupled receptor 40 (GPR40) represents an interesting target for developing novel antidiabetic drug. In the current study, the FFA1R agonistic activity of drug-like molecules was screened by employing pharmacophore modeling, docking, and molecular dynamics (MD) simulation. Hierarchical screening of virtual library of drug-like compounds was performed. This combined computational approach of pharmacophore mapping and structure-based approach was used to identify common hits, and the absorption, distribution, metabolism and excretion (ADME) prediction supported the analysis of their pharmacokinetic potential. MD simulation studies of the GPR40 complex with the most promising hit found in this study further validated are approached. The key residues Arg183, Arg258, Tyr91, and Tyr240 of the binding pocket were acknowledged as essential and were found to be associated in the key interactions with the most potential hit. These studies will hopefully provide scope for efficiently designing and screening new compounds as active drug candidates with more selectivity for hGPR40. To the best of our knowledge, this is the first example of the successful application of both ligand and structurebased virtual-screening techniques to discover novel GPR40 agonists.

Communicated by Ramaswamy H. Sarma     

Discovery of novel insomnia leads from screening traditional Chinese medicine database

Insomnia is a prominent modern disease that affects an increasing population. Undesirable side effects of commercial drugs highlight the need to develop novel insomnia drugs. Virtual screening of traditional chinese medicine Database@Taiwan (TCM Database@Taiwan) identified 2-O-Caffeoyl tartaric acid (1), 2-O-Feruloyl tartaric acid (2), and Mumefural (3) as potential agonists for both gamma-amino butyric acid (GABA) or benzodiazepine (BZ) binding sites. The TCM candidates exhibited higher affinity than GABA and Zolpidem, a phenomenon that could be attributed to higher quantity of stabilizing H-bonds. Efficacy profiles using support vector machines and pharmacophore contour also suggest drug potential of the TCM candidates. Fragments added to the de novo derivatives 3a, 3b, 3c for GABA binding site, and 1a, 2a, and 3d for BZ binding site contributed to new binding sites and structural stability, further optimizing binding to GABA or BZ binding sites. Increased opening of the ion channel by candidate ligands provide strong support for their potential biological functions. The dual binding properties of the TCM candidates present a unique opportunity to develop twin-targeting drugs with less side effects. Derivative structures can be used as starting points for developing high affinity GABA_A receptor agonists with specificity towards GABA binding site and BZ binding site.     

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 novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling,virtual screening,flexible docking,molecular dynamics simulation,and post-molecular dynamics analysis

Abstract

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski’s rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.

Communicated by Ramaswamy H. Sarma