Exploring the P2 and P3 ligand binding features for hepatitis C virus NS3 protease using some 3D QSAR techniques

Several three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and catalyst pharmacophore feature building programs for a series of 26 truncated ketoacid inhibitors designed particularly for exploring the P2 and P3 binding pockets of HCV NS3 protease. The structures of these inhibitors were built from a structure template extracted from the crystal structure of HCV NS3 protease. The structures were aligned through docking each inhibitor into the NS3 active site using program GOLD. The best CoMSIA model was identified from the stepwise analysis results and the corresponding pharmacophore features derived were used for constructing a pharmacophore hypothesis by the catalyst program. Pharmacophore features obtained by CoMFA and CoMSIA are found to be in accord with each other and are both mapped onto the molecular 5K surface of NS3 active site. These pharmacophore features were also compared with those obtained by the catalyst program and mapped onto the same NS3 molecular surface. The pharmacophore building process was also performed for 20 boronic acid based NS3 inhibitors characterized by a long hydrophobic side chain attached at position P2. This latter pharmacophore hypothesis built by the catalyst program was also mapped onto the molecular surface of NS3 active site to define a second hydrophobic feature at position P2. The possibility of using the pharmacophore features mapped P2 and P3 binding pocket to design more potent depeptidized NS3 inhibitors was discussed.     

Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints: simultaneous optimization and structure-based diversity

New applications of fingerprints of multiple potential 4-point three-dimensional (3D) pharmacophores in combinatorial library design and virtual screening are presented. Preliminary results demonstrating the feasibility of a simulated annealing process for combinatorial reagent selection that concurrently optimizes product diversity in BCUT chemistry space and in terms of unique 4-point pharmacophores are discussed, and the advantage of using a customized chemistry-space derived for the library design is demonstrated. In addition, an extension to the multiple pharmacophore method for structure-based design that uses the shape of the target site as an additional constraint is presented. This development enables the docking process to be quantified in terms of the number and identities of the pharmacophoric hypotheses that can be matched by a compound or a library of compounds. The design of an example combinatorial library based on the Ugi condensation reaction and a serine protease active site is described.     

Synergy between combinatorial chemistry and de novo design

Traditional de novo design algorithms are able to generate many thousands of ligand structures that meet the constraints of a protein structure, but these structures are often not synthetically tractable. In this article, we describe how concepts from structure-based de novo design can be used to explore the search space in library design. A key feature of the approach is the requirement that specific templates are included within the designed structures. Each template corresponds to the "central core" of a combinatorial library. The template is positioned within an acyclic chain whose length and bond orders are systematically varied, and the conformational space of each structure that results (core plus chain) is explored to determine whether it is able to link together two or more strongly interacting functional groups or pharmacophores located within a protein binding site. This fragment connection algorithm provides "generic" 3D molecules in the sense that the linking part (minus the template) is built from an all-carbon chain whose synthesis may not be easily achieved. Thus, in the second phase, 2D queries are derived from the molecular skeletons and used to identify possible reagents from a database. Each potential reagent is checked to ensure that it is compatible with the conformation of its parent 3D conformation and the constraints of the binding site. Combinations of these reagents according to the combinatorial library reaction scheme give product molecules that contain the desired core template and the key functional/pharmacophoric groups, and would be able to adopt a conformation compatible with the original molecular skeleton without any unfavorable intermolecular or intramolecular interactions. We discuss how this strategy compares with and relates to alternative approaches to both structure-based library design and de novo design.     

Modeling aided design of potent glycogen phosphorylase inhibitors

Molecular modeling has been used to assist in the development of a novel series of potent glycogen phosphorylase inhibitors based on a phenyl diacid lead, compound 1. In the absence of suitable competitive binding assays, compound 1 was predicted to bind at the AMP allosteric site based on superposition onto known inhibitors which bind at different sites in the enzyme and analyses of the surrounding protein environment associated with these distinct sites. Possible docking modes of compound 1 at the AMP allosteric site were further explored using the crystal structure of rabbit muscle glycogen phosphorylase complexed with a Bayer diacid compound W1807 (PDB entry 3AMV). Compound 1 was predicted to interact with positively charged arginines at the AMP allosteric site in the docking model. Characterization of the binding pocket by a grid-based surface calculation of the docking model revealed a large unfilled hydrophobic region near the central phenyl ring, suggesting that compounds with larger hydrophobic groups in this region would improve binding. A series of naphthyl diacid compounds were designed and synthesized to access this hydrophobic cleft, and showed significantly improved potency.     

Molecular scaffold-based design and comparison of combinatorial libraries focused on the ATP-binding site of protein kinases

Compound libraries were designed to target specifically the ATP cofactor-binding site in protein kinases by combining knowledge- and diversity-based design elements. A key aspect of the approach is the identification of molecular building blocks or scaffolds that are compatible with the binding site and therefore capture some aspects of target specificity. Scaffolds were selected on the basis of docking calculations and analysis of known inhibitors. We have generated 75 molecular scaffolds and applied different strategies to compute diverse compounds from scaffolds or, alternatively, to screen compound databases for molecules containing these scaffolds. The resulting libraries had a similar degree of molecular diversity, with at most 12% of the compounds being identical. However, their scaffold distributions differed significantly and a small number of scaffolds dominated the majority of compounds in each library.     

Allosteric pocket of the dengue virus (serotype 2) NS2B/NS3 protease: In silico ligand screening and molecular dynamics studies of inhibition

The allosteric pocket of the Dengue virus (DENV2) NS2B/NS3 protease, which is proximal to its catalytic triad, represents a promising drug target (Othman et al., 2008). We have explored this binding site through large-scale virtual screening and molecular dynamics simulations followed by calculations of binding free energy. We propose two mechanisms for enzyme inhibition. A ligand may either destabilize electronic density or create steric effects relating to the catalytic triad residues NS3-HIS51, NS3-ASP75, and NS3-SER135. A ligand may also disrupt movement of the C-terminal of NS2B required for inter-conversion between the “open” and “closed” conformations. We found that chalcone and adenosine derivatives had the top potential for drug discovery hits, acting through both inhibitory mechanisms. Studying the molecular mechanisms of these compounds might be helpful in further investigations of the allosteric pocket and its potential for drug discovery.     

Predicting function from structure: examples of the serine protease inhibitor canonical loop conformation found in extracellular proteins

The prediction of protein function from structure is becoming of growing importance in the age of structural genomics. We have focused on the problem of identifying sites of potential serine protease inhibitor interactions on the surface of proteins of known structure. Given that there is no sequence conservation within canonical loops from different inhibitor families we first compare representative loops to all fragments of equal length among proteins of known structure by calculating main-chain RMS deviation. Fragments with RMS deviation below a certain threshold (hits) are removed if residues have solvent accessibilities appreciably lower than those observed in the search structure. These remaining hits are further filtered to remove those occurring largely within secondary structure elements. Likely functional significance is restricted further by considering only extracellular protein domains. Also a test is performed to see if the loop can dock into the binding site of the serine protease trypsin without unacceptable steric clashes. By comparing different canonical loop structures to the protein structure database we show that the method was able to detect previously known inhibitors. In addition, we discuss potentially new canonical loop structures found in secreted hydrolases, toxins, viral proteins, cytokines and other proteins. We discuss the possible functional significance of several of the examples found.     

Predicting function from structure: examples of the serine protease inhibitor canonical loop conformation found in extracellular proteins.

The prediction of protein function from structure is becoming of growing importance in the age of structural genomics. We have focused on the problem of identifying sites of potential serine protease inhibitor interactions on the surface of proteins of known structure. Given that there is no sequence conservation within canonical loops from different inhibitor families we first compare representative loops to all fragments of equal length among proteins of known structure by calculating main-chain RMS deviation. Fragments with RMS deviation below a certain threshold (hits) are removed if residues have solvent accessibilities appreciably lower than those observed in the search structure. These remaining hits are further filtered to remove those occurring largely within secondary structure elements. Likely functional significance is restricted further by considering only extracellular protein domains. Also a test is performed to see if the loop can dock into the binding site of the serine protease trypsin without unacceptable steric clashes. By comparing different canonical loop structures to the protein structure database we show that the method was able to detect previously known inhibitors. In addition, we discuss potentially new canonical loop structures found in secreted hydrolases, toxins, viral proteins, cytokines and other proteins. We discuss the possible functional significance of several of the examples found.     

Molecular docking and analysis of interactions between vascular endothelial growth factor (VEGF) and SPARC protein

The extracellular module of SPARC/osteonectin binds to vascular endothelial growth factor (VEGF) and inhibits VEGF-stimulated proliferation of endothelial cells. In an attempt to identify the binding site for SPARC on VEGF, we hypothesized that this binding site could overlap at least partially the binding site of VEGF receptor 1 (VEGFR-1), as SPARC acts by preventing VEGF-induced phosphorylation of VEGFR-1. To this end, a docking simulation was carried out using a predictive docking tool to obtain modeled structures of the VEGF-SPARC complex. The predicted structure of VEGF-SPARC complex indicates that the extracellular domain of SPARC interacts with the VEGFR-1 binding site of VEGF, and is consistent with known biochemical data. Following molecular dynamics refinement, side-chain interactions at the protein interface were identified that were predicted to contribute substantially to the free energy of binding. These provide a detailed prediction of key amino acid side-chain interactions at the protein-protein interface. To validate the model further, the identified interactions will be used for designing mutagenesis studies to investigate their effect on binding activity. This model of the VEGF-SPARC complex should provide a basis for future studies aimed at identifying inhibitors of VEGF-induced angiogenesis.     

Identification of chikungunya virus nsP2 protease inhibitors using structure-base approaches

The nsP2 protease of chikungunya virus (CHIKV) is one of the essential components of viral replication and it plays a crucial role in the cleavage of polyprotein precursors for the viral replication process. Therefore, it is gaining attention as a potential drug design target against CHIKV. Based on the recently determined crystal structure of the nsP2 protease of CHIKV, this study identified potential inhibitors of the virus using structure-based approaches with a combination of molecular docking, virtual screening and molecular dynamics (MD) simulations. The top hit compounds from database searching, using the NCI Diversity Set II, with targeting at five potential binding sites of the nsP2 protease, were identified by blind dockings and focused dockings. These complexes were then subjected to MD simulations to investigate the stability and flexibility of the complexes and to gain a more detailed insight into the interactions between the compounds and the enzyme. The hydrogen bonds and hydrophobic contacts were characterized for the complexes. Through structural alignment, the catalytic residues Cys1013 and His1083 were identified in the N-terminal region of the nsP2 protease. The absolute binding free energies were estimated by the linear interaction energy approach and compared with the binding affinities predicted with docking. The results provide valuable information for the development of inhibitors for CHIKV.     

Molecular modeling study of CP-690550 derivatives as JAK3 kinase inhibitors through combined 3D-QSAR,molecular docking,and dynamics simulation techniques

To develop more potent JAK3 kinase inhibitors, a series of CP-690550 derivatives were investigated using combined molecular modeling techniques, such as 3D-QSAR, molecular docking and molecular dynamics (MD). The leave-one-out correlation (q²) and non-cross-validated correlation coefficient (r²) of the best CoMFA model are 0.715 and 0.992, respectively. The q² and r² values of the best CoMSIA model are 0.739 and 0.995, respectively. The steric, electrostatic, and hydrophobic fields played important roles in determining the inhibitory activity of CP-690550 derivatives. Some new JAK3 kinase inhibitors were designed. Some of them have better inhibitory activity than the most potent Tofacitinib (CP-690550). Molecular docking was used to identify some key amino acid residues at the active site of JAK3 protein. 10 ns MD simulations were successfully performed to confirm the detailed binding mode and validate the rationality of docking results. The calculation of the binding free energies by MMPBSA method gives a good correlation with the predicted biological activity. To our knowledge, this is the first report on MD simulations and free energy calculations for this series of compounds. The combination results of this study will be valuable for the development of potent and novel JAK3 kinase inhibitors.     

Molecular docking/dynamics studies of Aurora A kinase inhibitors

The binding modes of a known 1,4,5,6-tetrahydropyrrolo[3,4-c]pyrazole, quinazoline, pyrimidine and indolinone series of Aurora A kinase inhibitors have been studied using molecular docking and molecular dynamics (MD) simulations. Crystallographic bound compound 8 was precisely predicted by our docking procedure as evident from 0.43 Å root mean square (rms) deviations. In addition compound 25 (AZ_68) has been successfully cross-docked within the Aurora A kinase active site, which was pre-organized for inhibitor 8. We found four key sites (A: solvent-exposed front pocket, B: hinge region, C: selectivity pocket and D: solvent-exposed phosphate binding region) of the Aurora A kinase contributing towards the binding of these compounds. We suggest that the small hydrophobic substituents at C-6 position of pyrrolopyrazole nucleus (in compounds 1–8); C-6 and C-7 positions of the quinazoline moiety (in compounds 9–23); C-2 position of the quinazoline and C-4 position of the pyrimidine (in compound 25) could be more effective and selective through increased hydrophobic contacts and selectivity pocket interactions with these modifications of Aurora A kinase inhibitors. Five representative complexes were subjected to 1000 ps of MD simulation to determine the stability of the predicted binding conformations. The low value of the root mean square deviations (ranging from 0.725 to 1.820 Å) between the starting complex structure and the energy minimized final average complex structure suggests that the Glide Extra Precision (XP) derived docked complexes are in a state of near equilibrium. The structure-based drug design strategy described in this study will be highly useful for the development of new inhibitors with high potency and selectivity.     

P1 and P1′ para-fluoro phenyl groups show enhanced binding and favorable predicted pharmacological properties: Structure-based virtual screening of extended lopinavir analogs against multi-drug resistant HIV-1 protease

Crystal structure of multidrug-resistant (MDR) clinical isolate 769, human immunodeficiency virus type-1 (HIV-1) protease in complex with lopinavir (LPV) (PDB ID: 1RV7) showed altered binding orientation of LPV in the expanded active site cavity, causing loss of contacts and decrease in potency. In the current study, with a goal to restore the lost contacts, three libraries of LPV analogs containing extended P1 and/or P1′ phenyl groups were designed and docked into the expanded active site cavity of the MDR769 HIV-1 protease. The compounds were then ranked based on three criteria: binding affinity, overall binding profile and predicted pharmacological properties. Among the twelve proposed extensions in different combinations, compound 14 (consists of para-fluoro phenyl group as both P1 and P1′ moieties) was identified as a lead with improved binding profile, binding affinity against the MDR protease and favorable predicted pharmacological properties comparable to those of LPV. The binding affinity of 14 against wild type (NL4-3) HIV-1 protease was comparable to that of LPV and was better than LPV against an ensemble of MDR HIV-1 protease variants. Thus, 14 shows enhanced binding affinity by restoring lost contacts in the expanded active site cavity of MDR769 HIV-1 protease variants suggesting that it may have higher potency compared to that of LPV and hence should be further synthesized and evaluated against NL4-3 as well as MDR variants of HIV-1.     

一个组织型纤溶性溶解酶原激活剂(T-pa)非共价类抑制剂的药效模型

为了研究组织型纤溶性溶解酶原激活剂（T－pa)的非共价类抑制剂的三维定量构效关系，本文采用分子模拟软件Catalyst4.0(molecular simulation company)构建T-pa的非共价类抑制剂的三维药效模型。14个非共价类的抑制剂及其体外活性数据被用于构建此药效模型。此药效模型有3个疏水区特性，一个正离子化区特性和氢键供体区特性，且结构与活性相关系数为r=0.962。与T－pa的晶体结构比较，此药物模型在化学状态和疏水性上与其能很好的相匹配。且利用此是找到的抑制剂（bbzi14)的活性构象，与晶体结构中此抑制剂的结合构象基本一致。通过此药效集团模型反映的抑制剂与受体的相互作用模式，能为发现新型亲和配基和抑制剂提供有用的启示。     

一个组织型纤溶性溶解酶原激活剂(T-pa)非共价类抑制剂的药效模型

为了研究组织型纤溶性溶解酶原激活剂(T-pa)的非共价类抑制剂的三维定量构效关系,本文采用分子模拟软件Catalyst 4.0(molecular simulation company)构建T-pa的非共价类抑制剂的三维药效模型。14个非共价类的抑制剂及其体外活性数据被用于构建此药效模型。此药效模型有3个疏水区特性,一个正离子化区特性和氢键供体区特性,且结构与活性相关系数为r=0.962。与T-pa的晶体结构比较,此药物模型在化学状态和疏水性上与其能很好的相匹配。且利用此模型查找到的抑制剂(bbzi14)的活性构象,与晶体结构中此抑制剂的结合构象基本一致。通过此药效集团模型反映的抑制剂与受体的相互作用模式,能为发现新型亲和配基和抑制剂提供有用的启示。     

Structure-based design of inhibitors of the rice blast fungal enzyme trihydroxynaphthalene reductase

Rice Blast Disease, caused by the fungus Pyricularia oryzae, is one of the most important diseases of rice. Several enzymes in the melanin biosynthetic pathway have proven to be valuable targets for development of rice blast fungicides. In particular, inhibitors of trihydroxynaphthalene reductase (3HNR), which catalyzes the conversion of trihydroxynaphthalene to vermelone, have yielded commercially useful rice fungicides. The X-ray structure of 3HNR has been published recently, presenting an opportunity to use this information in the de novo design of novel 3HNR inhibitors that may exhibit useful rice blast activity. We used the LeapFrog program to develop a docking model for interaction of ligands with the active site of THNR. The final model gave a good correlation between calculated binding energy and log Ki and was used to design novel ligands and score compounds for synthesis. Using this as a tool, we synthesized inhibitors in the nanomolar range and also developed several inhibitors that did not conform to the properties of the THNR active site. Leapfrog was able to locate a previously unrecognized binding pocket that could accommodate these otherwise anomalous regions of structure.     

Identification of non-resistant ROS-1 inhibitors using structure based pharmacophore analysis

Proto-oncogene receptor tyrosine kinase ROS-1 plays a key role in regulating a variety of cancers mainly non-small cell lung cancer (NSCLC). The marketed ROS-1 inhibitors such as Crizotinib suffer from the tribulations of growing resistance due to mutations primarily Gly2032Arg in the ROS-1 protein. To curb the problem of resistance, researchers have developed inhibitors such as Lorlatinib against the mutant protein. The present study was designed to identify inhibitors against wild type (WT) as well as mutant ROS-1 protein that will offer a broader spectrum of activity. Exploring crystal structure of ROS-1 complexed with Lorlatinib, receptor-ligand pharmacophore model was developed using Discovery Studio (DS) software. The developed pharmacophore model consisted of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) and two hydrophobic features (HY), subsequently utilized for virtual screening of commercially available databases and the retrieved hits were further subjected to fitness score and Lipinski’s filter. Thereafter, the retrieved hits were docked in WT and mutated (Gly2032Arg) proteins of ROS-1. Total five molecules were retrieved with good docking scores and good binding interactions within the active site of WT and mutated ROS-1. The binding energies of the ligand-receptor complexes were predicted via calculation of MM-GBSA score. To predict the stability of the ligand receptor complexes with mutant and wild type proteins, molecular dynamic simulation was performed. Thus, these identified hits show good binding affinities with WT and mutant ROS-1 proteins that may be further evaluated for their in-vitro/in-vivo activity.     

A structural insight into the inhibitory mechanism of an orally active PI3K/mTOR dual inhibitor,PKI-179 using computational approaches

The PI3K/AKT/mTOR signaling pathway has been identified as an important target for cancer therapy. Attempts are increasingly made to design the inhibitors against the key proteins of this pathway for anti-cancer therapy. The PI3K/mTOR dual inhibitors have proved more effective than the inhibitors against only single protein targets. Recently discovered PKI-179, an orally effective compound, is one such dual inhibitor targeting both PI3K and mTOR. This anti-cancer compound is efficacious both in vitro and in vivo. However, the binding mechanisms and the molecular interactions of PKI-179 with PI3K and mTOR are not yet available. The current study investigated the exact binding mode and the molecular interactions of PKI-179 with PI3Kγ and mTOR using molecular docking and (un)binding simulation analyses. The study identified PKI-179 interacting residues of both the proteins and their importance in binding was ranked by the loss in accessible surface area, number of molecular interactions of the residue, and consistent appearance of the residue in (un)binding simulation analysis. The key residues involved in binding of PKI-179 were Ala-805 in PI3Kγ and Ile-2163 in mTOR as they have lost maximum accessible surface area due to binding. In addition, the residues which played a role in binding of the drug but were away from the catalytic site were also identified using (un)binding simulation analyses. Finally, comparison of the interacting residues in the respective catalytic sites was done for the difference in the binding of the drug to the two proteins. Thus, the pairs of the residues falling at the similar location with respect to the docked drug were identified. The striking similarity in the interacting residues of the catalytic site explains the concomitant inhibition of both proteins by a number of inhibitors. In conclusion, the docking and (un)binding simulation analyses of dual inhibitor PKI-179 with PI3K and mTOR will provide a suitable multi-target model for studying drug–protein interactions and thus help in designing the novel drugs with higher potency.     

Prediction of the binding mode of biarylpropylsulfonamide allosteric AMPA receptor modulators based on docking, GRID molecular interaction fields and 3D-QSAR analysis

A novel approach of combining flexible molecular docking, GRID molecular interaction fields, analysis of ligand-protein hydrogen bond interactions, conformational energy penalties and 3D-QSAR analysis was used to propose a binding mode in the dimer interface of the iGluR2 receptor for the biarylpropylsulfonamide class of positive allosteric AMPA modulators. Possible binding poses were generated by flexible molecular docking. GRID molecular interaction fields of the binding site, ligand-protein hydrogen bonding interactions and conformational energy penalties were used to select the most likely binding mode. The selected binding poses were subjected to a 3D-QSAR analysis using previously published activity data. The resulting model (2 LVs, R2=0.89, q2=0.61) predicted the activities of the compounds in the test set with a standard deviation on error of prediction of 0.17. The proposed binding mode was validated by interpretation of the PLS-coefficient regions from the 3D-QSAR analysis in terms of interactions between the receptor and the modulators.