Application of an integrated cheminformatics-molecular docking approach for discovery for physicochemically similar analogs of fluoroquinolones as putative HCV inhibitors

BackgroundHepatitis C Virus (HCV) infection is a major public health concern across the globe. At present, direct-acting antivirals are the treatment of choice. However, the long-term effect of this therapy has yet to be ascertained. Previously, fluoroquinolones have been reported to inhibit HCV replication by targeting NS3 protein. Therefore, it is logical to hypothesize that the natural analogs of fluoroquinolones will exhibit NS3 inhibitory activity with substantially lesser side effects.MethodIn this study, we tested the application of a recently devised integrated in-silico Cheminformatics-Molecular Docking approach to identify physicochemically similar natural analogs of fluoroquinolones from the available databases (Ambinter, Analyticon, Indofines, Specs, and TimTec). Molecular docking and ROC curve analyses were performed, using PatchDock and Graphpad software, respectively, to compare and analyze drug-protein interactions between active natural analogs, Fluoroquinolones, and HCV NS3 protein.ResultIn our analysis, we were able to shortlist 18 active natural analogs, out of 10,399, that shared physicochemical properties with the template drugs (fluoroquinolones). These analogs showed comparable binding efficacy with fluoroquinolones in targeting 32 amino acids in the HCV NS3 active site that are crucial for NS3 activity. Our approach had around 80 % sensitivity and 70 % specificity in identifying physicochemically similar analogs of fluoroquinolones.ConclusionOur current data suggest that our approach can be efficiently applied to identify putative HCV drug inhibitors that can be taken for in vitro testing. This approach can be applied to discover physicochemically similar analogs of virtually any drug, thus providing a speedy and inexpensive approach to complement drug discovery and design, which can tremendously economize on time and money spent on the screening of putative drugs.     

3D QSAR and molecular docking studies of benzimidazole derivatives as hepatitis C virus NS5B polymerase inhibitors

The urgent need for novel HCV antiviral agents has provided an impetus for understanding the structural requisites of NS5B polymerase inhibitors at the molecular level. Toward this objective, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of 67 HCV NS5B polymerase inhibitors were performed using two methods. First, ligand-based 3D QSAR studies were performed based on the lowest energy conformations employing the atom fit alignment method. Second, receptor-based 3D QSAR models were derived from the predicted binding conformations obtained by docking all NS5B inhibitors at the allosteric binding site of NS5B (PDB ID: 2dxs). Results generated from the ligand-based model were found superior (r2cv values of 0.630 for CoMFA and 0.668 for CoMSIA) to those obtained by the receptor-based model (r2cv values of 0.536 and 0.561 for CoMFA and CoMSIA, respectively). The predictive ability of the models was validated using a structurally diversified test set of 22 compounds that had not been included in a preliminary training set of 45 compounds. The predictive r2 values for the ligand-based CoMFA and CoMSIA models were 0.734 and 0.800, respectively, while the corresponding predictive r2 values for the receptor-based CoMFA and CoMSIA models were 0.538 and 0.639, respectively. The greater potency of the tryptophan derivatives over that of the tyrosine derivatives was interpreted based on CoMFA steric and electrostatic contour maps. The CoMSIA results revealed that for a NS5B inhibitor to have appreciable inhibitory activity it requires hydrogen bond donor and acceptor groups at the 5-position of the indole ring and an R substituent at the chiral carbon, respectively. Interpretation of the CoMFA and CoMSIA contour maps in context of the topology of the allosteric binding site of NS5B provided insight into NS5B-inhibitor interactions. Taken together, the present 3D QSAR models were found to accurately predict the HCV NS5B polymerase inhibitory activity of structurally diverse test set compounds and to yield reliable clues for further optimization of the benzimidazole derivatives in the data set.     

Binding of low molecular weight inhibitors promotes large conformational changes in the dengue virus NS2B-NS3 protease: fold analysis by pseudocontact shifts

The two-component dengue virus NS2B-NS3 protease (DEN NS2B-NS3pro) is an established drug target, but inhibitor design is hampered by the lack of a crystal structure of the protease in its fully active form. In solution and without inhibitors, the functionally important C-terminal segment of the NS2B cofactor is dissociated from DEN NS3pro ("open state"), necessitating a large structural change to produce the "closed state" thought to underpin activity. We analyzed the fold of DEN NS2B-NS3pro in solution with and without bound inhibitor by nuclear magnetic resonance (NMR) spectroscopy. Multiple paramagnetic lanthanide tags were attached to different sites to generate pseudocontact shifts (PCS). In the face of severe spectral overlap and broadening of many signals by conformational exchange, methods for assignment of (15)N-HSQC cross-peaks included selective mutation, combinatorial isotope labeling, and comparison of experimental PCSs and PCSs back-calculated for a structural model of the closed conformation built by using the structure of the related West Nile virus (WNV) protease as a template. The PCSs show that, in the presence of a positively charged low-molecular weight inhibitor, the enzyme assumes a closed state that is very similar to the closed state previously observed for the WNV protease. Therefore, a model of the protease built on the closed conformation of the WNV protease is a better template for rational drug design than available crystal structures, at least for positively charged inhibitors. To assess the open state, we created a binding site for a Gd(3+) complex and measured paramagnetic relaxation enhancements. The results show that the specific open conformation displayed in the crystal of DEN NS2B-NS3pro is barely populated in solution. The techniques used open an avenue to the fold analysis of proteins that yield poor NMR spectra, as PCSs from multiple sites in combination with model building generate powerful information even from incompletely assigned (15)N-HSQC spectra.     

Microscopic binding of butyrylcholinesterase with quinazolinimine derivatives and the structure–activity correlation

Butyrylcholinesterase (BChE) is not only an important protein for development of anti-cocaine medication but also an established drug target to develop new treatment for Alzheimer’s disease (AD). The molecular basis of interaction of a new series of quinazolinimine derivatives as BChE inhibitors has been studied by molecular docking and molecular dynamics (MD) simulations. The molecular docking and MD simulations revealed that all of these inhibitors bind with BChE in similar binding mode. Based on the similar binding mode, we have carried out three-dimensional quantitative structure–activity relationship (3D-QSAR) studies on these inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), to understand the structure–activity correlation of this series of inhibitors and to develop predictive models that could be used in the design of new inhibitors of BChE. The study has resulted in satisfactory 3D-QSAR models. We have also developed ligand-based 3D-QSAR models. The contour maps obtained from the 3D-QSAR models in combination with the simulated binding structures help to better interpret the structure–activity relationship and is consistent with available experimental activity data. The satisfactory 3D-QSAR models strongly suggest that the determined BChE-inhibitor binding modes are reasonable. The identified binding modes and developed 3D-QSAR models for these BChE inhibitors are expected to be valuable for rational design of new BChE inhibitors that may be valuable in the treatment of Alzheimer’s disease.     

Comparative molecular field analysis of non-steroidal aromatase inhibitors related to fadrozole

Summary A series of non-steroidal inhibitors of aromatase, structurally related to fadrozole (2), was investigated with the aim of developing a 3D QSAR model using the Comparative Molecular Field Analysis (CoMFA) technique. The alignment of the molecules was performed following two approaches (atom-by-atom and field fit), both starting from an initial hypothesis of superimposition of fadrozole to a steroidal inhibitor (3). From a number of CoMFA models built with different characteristics, one was recognized as the most statistically relevant; this one is discussed in detail. The features of the 3D QSAR model are consistent with those of other 3D and QSAR models of aromatase and its inhibitors.     

Structural evidence of differential forms of nanosponges of beta-cyclodextrin and its effect on solubilization of a model drug

Nanosponges (NS) are a recently developed class of hyper-branched polymers, nano-structured to form three dimensional meshwork; obtained by reacting cyclodextrins with a cross linker like diphenyl carbonate. Herein, we report an anomalous behavior of NS with regards to physical and morphological characteristics and drug encapsulation behavior by minor synthetic modification. Two distinct forms viz. crystalline and para-crystalline of NS were identified and extensively characterized by use of high resolution transmission electron microscopy (HR-TEM), X-ray powder diffraction (XRPD), scanning electron microscope, atomic force microscope, optical microscope and Fourier transform infra-red attenuated total reflectance spectroscopy (FTIR-ATR). Dimension of the crystal lattice was found to be equal to 0.61 nm. Higher magnifications clearly showed a zone axis with a hexagonal symmetry as that of beta-cyclodextrin. XRPD patterns were in concurrence with the HR-TEM results. Solubility studies with a model drug dexamethasone (DEX) showed more than three folds increase in the solubility of the drug in the crystalline NS as compared to the para-crystalline ones. Percent drug association and drug loading for DEX was found to be higher in the crystalline type of NS. An In vitro drug kinetic study evidenced a faster release of DEX from the crystalline type NS. The particle sizes of the formulations were as follows: crystalline NS: 688.6 ± 38.0 nm, para-crystalline NS: 702.2 ± 21.2 nm with polydispersity indices of 0.155 and 0.132; zeta-potential of ?26.55 ± 1.7 and ?23.42 ± 2.1 respectively. Differential scanning calorimetry and thermogravimetric analysis revealed that both forms encapsulated the drug satisfactorily. FTIR-ATR and Raman spectroscopy showed weak interactions. Crystallinity of NS was thus found to be an important factor in solubilization, in vitro kinetics and encapsulation behavior and can be tuned to give a tailored drug release profile or formulation characteristics.     

Design,synthesis and biological evaluation of some 2-(6-nitrobenzo[d]thiazol-2-ylthio)-N-benzyl-N-(6-nitrobenzo[d]thiazol-2-yl)acetamide derivatives as selective DprE1 inhibitors

Abstract

Tuberculosis (TB) is an infectious disease and caused by various strains of mycobacteria. In the present study, pharmacophore model was developed using single ligand by ligand-based drug discovery approach. The key features responsible for DprE1 inhibitory activity were taken into consideration for developing pharmacophore. After the virtual screening, top 1000 hits were further subjected to docking study using GLIDE module, Schrödinger. Docking studies have shown promising interaction with amino residues with better glide score. Ligand-based drug design approach yielded a series of 15, 2-(6-nitrobenzo[d]thiazol-2-ylthio)-N-benzyl-N-(6-nitrobenzo[d]thiazol-2-yl)acetamide derivatives. All synthesized derivatives were characterized using NMR, mass, CHN analysis. The synthesized compounds were screened for In vitro antitubercular activity against Mycobacterium tuberculosis (H₃₇Rv). Four compounds, 5g (MIC-1.01?μM); 5i (MIC-0.91?μM); 5k (MIC-0.82?μM); and 5o (MIC-1.04?μM) has shown promising activity compared to MIC of standard isoniazid (INH) and DprE1 enzyme inhibition was compared to BTZ043. Two halogen-substituted compounds have exhibited drastic enzyme inhibition.     

QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents

The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correctly classify 92.16% and 87.56% of 706 compounds in an external test set. A comparison of the statistical parameters of the QuBiLs-MAS LDA-based models with those for models reported in the literature reveals comparable to superior performance, although the latter were built over much smaller and less diverse datasets, representing fewer mechanisms of action. It may therefore be inferred that the QuBiLs-MAS method constitutes a valuable tool useful in the design and/or selection of new and broad spectrum agents against life-threatening fungal infections.     

Combined 3D-QSAR modeling and molecular docking study on indolinone derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1

3-Phosphoinositide-dependent protein kinase-1 (PDK1) is a promising target for developing novel anticancer drugs. In order to understand the structure-activity correlation of indolinone-based PDK1 inhibitors, we have carried out a combined molecular docking and three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling study. The study has resulted in two types of satisfactory 3D-QSAR models, including the CoMFA model (r(2)=0.907; q(2)=0.737) and CoMSIA model (r(2)=0.991; q(2)=0.824), for predicting the biological activity of new compounds. The detailed microscopic structures of PDK1 binding with inhibitors have been studied by molecular docking. We have also developed docking-based 3D-QSAR models (CoMFA with q(2)=0.729; CoMSIA with q(2)=0.79). The contour maps obtained from the 3D-QSAR models in combination with the docked binding structures help to better interpret the structure-activity relationship. All of the structural insights obtained from both the 3D-QSAR contour maps and molecular docking are consistent with the available experimental activity data. This is the first report on 3D-QSAR modeling of PDK1 inhibitors. The satisfactory results strongly suggest that the developed 3D-QSAR models and the obtained PDK1-inhibitor binding structures are reasonable for the prediction of the activity of new inhibitors and in future drug design.     

Accounting of ligand–receptor interactions to explore and design novel architecture for PTP 1B inhibition: a legitimate approach

Computer‐aided drug design was performed on a diverse set of 103 biphenyl derivatives that demonstrated antidiabetic activity by restraining the protein tyrosine phosphatase 1B (PTP 1B) receptor. A four‐point pharmacophore hypothesis using the PHASE module of Schrödinger suite with one hydrogen bond acceptor (A) and three aromatic rings (R) as pharmacophoric features was generated. The hypothesis, ARRR.2, considered the best hypothesis in the present study is characterized by survival score (3.553), cross‐validated r² (Q²) (0.722), regression coefficient (0.949), Pearson R (0.867), and F value (492.6). The developed pharmacophore model was externally validated by predicting the activity of test set molecules. Docking algorithm combined with the drug–receptor binding free energetic and pharmacokinetic drug profile envisaged a novel concept, which may provide structural insights for the development of potential PTP 1B inhibitors. The study also provided a valid rapport between pharmacophore drug mapping, atom‐based three‐dimensional quantitative structure–activity relationship, molecular docking, sitemap, molecular simulations, and pharmacokinetic prediction approaches demonstrating the trends in activity. The results of these ligand–receptor relationship studies may account to design a legitimate template for the development and optimization of highly selective and potent PTP 1B inhibitors. Copyright © 2012 John Wiley & Sons, Ltd.     

Structure-guided fragment-based<Emphasis Type="Italic"> in silico</Emphasis> drug design of dengue protease inhibitors

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC₅₀ = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC₅₀ = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.