Binding of novel fullerene inhibitors to HIV-1 protease: insight through molecular dynamics and molecular mechanics Poisson–Boltzmann surface area calculations

The objectives of this study include the design of a series of novel fullerene-based inhibitors for HIV-1 protease (HIV-1 PR), by employing two strategies that can also be applied to the design of inhibitors for any other target. Additionally, the interactions which contribute to the observed exceptionally high binding free energies were analyzed. In particular, we investigated: (1) hydrogen bonding (H-bond) interactions between specific fullerene derivatives and the protease, (2) the regions of HIV-1 PR that play a significant role in binding, (3) protease changes upon binding and (4) various contributions to the binding free energy, in order to identify the most significant of them. This study has been performed by employing a docking technique, two 3D-QSAR models, molecular dynamics (MD) simulations and the molecular mechanics Poisson–Boltzmann surface area (MM–PBSA) method. Our computed binding free energies are in satisfactory agreement with the experimental results. The suitability of specific fullerene derivatives as drug candidates was further enhanced, after ADMET (absorption, distribution, metabolism, excretion and toxicity) properties have been estimated to be promising. The outcomes of this study revealed important protein–ligand interaction patterns that may lead towards the development of novel, potent HIV-1 PR inhibitors.     

3D-QSAR studies of dihydropyrazole and dihydropyrrole derivatives as inhibitors of human mitotic kinesin Eg5 based on molecular docking

Human mitotic kinesin Eg5 plays an essential role in mitoses and is an interesting drug target against cancer. To find the correlation between Eg5 and its inhibitors, structure-based 3D-quantitative structure-activity relationship (QSAR) studies were performed on a series of dihydropyrazole and dihydropyrrole derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Based on the LigandFit docking results, predictive 3D-QSAR models were established, with cross-validated coefficient values (q2) up to 0.798 for CoMFA and 0.848 for CoMSIA, respectively. Furthermore, the CoMFA and CoMSIA models were mapped back to the binding sites of Eg5, which could provide a better understanding of vital interactions between the inhibitors and the kinase. Ligands binding in hydrophobic part of the inhibitor-binding pocket were found to be crucial for potent ligand binding and kinases selectivity. The analyses may be used to design more potent EG5 inhibitors and predict their activities prior to synthesis.     

Pharmacophore generation,atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors

DNA gyrase subunit B (GyrB) is an attractive drug target for the development of antibacterial agents with therapeutic potential. In the present study, computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives. A pharmacophore model using 49 molecules revealed structural and chemical features necessary for these molecules to inhibit GyrB. The best fitted model AADDR.13 was generated with a coefficient of determination (r²) of 0.918. This model was validated using test set molecules and had a good r² of 0.78. 3D contour maps generated by the 3D atom-based QSAR revealed the key structural features responsible for the GyrB inhibitory activity. Extra precision molecular docking showed hydrogen bond interactions with key amino acid residues of ATP-binding pocket, important for inhibitor binding. Further, binding free energy was calculated by the MM-GBSA rescoring approach to validate the binding affinity. A 10 ns MD simulation of inhibitor #47 showed the stability of the predicted binding conformations. We identified 10 virtual hits by in silico high-throughput screening. A few new molecules were also designed as potent GyrB inhibitors. The information obtained from these methodologies may be helpful to design novel inhibitors of GyrB.     

Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors

The paper describes the construction, validation and application of a structure-based 3D QSAR model of novel acetylcholinesterase (AChE) inhibitors. Initial use was made of four X-ray structures of AChE complexed with small, non-specific inhibitors to create a model of the binding of recently developed aminopyridazine derivatives. Combined automated and manual docking methods were applied to dock the co-crystallized inhibitors into the binding pocket. Validation of the modelling process was achieved by comparing the predicted enzyme-bound conformation with the known conformation in the X-ray structure. The successful prediction of the binding conformation of the known inhibitors gave confidence that we could use our model to evaluate the binding conformation of the aminopyridazine compounds. The alignment of 42 aminopyridazine compounds derived by the docking procedure was taken as the basis for a 3D QSAR analysis applying the GRID/GOLPE method. A model of high quality was obtained using the GRID water probe, as confirmed by the cross-validation method (q² _LOO=0.937, q² _{L50% O}=0.910). The validated model, together with the information obtained from the calculated AChE-inhibitor complexes, were considered for the design of novel compounds. Seven designed inhibitors which were synthesized and tested were shown to be highly active. After performing our modelling study the X-ray structure of AChE complexed with donepezil, an inhibitor structurally related to the developed aminopyirdazines, has been made available. The good agreement found between the predicted binding conformation of the aminopyridazines and the one observed for donepezil in the crystal structure further supports our developed model.     

Structure-based drug design: exploring the proper filling of apolar pockets at enzyme active sites

The proper filling of apolar pockets at enzyme active sites is central for increasing binding activity and selectivity of hits and leads in medicinal chemistry. In our structure-based design approach toward the generation of potent enzyme inhibitors, we encountered a variety of challenges in gaining suitable binding affinity from the occupation of such pockets. We summarize them here for the first time. A fluorine scan of tricyclic thrombin inhibitors led to the discovery of favorable orthogonal dipolar C-F...CO interactions. Efficient cation-pi interactions were established in the S4 pocket of factor Xa, another serine protease from the blood coagulation cascade. Changing from mono- to bisubstrate inhibitors of catechol O-methyltransferase, a target in the L-Dopa-based treatment of Parkinson's disease, enabled the full exploitation of a previously unexplored hydrophobic pocket. Conformational preorganization of a pocket at an enzyme active site is crucial for harvesting binding affinity. This is demonstrated for two enzymes from the nonmevalonate pathway of isoprenoid biosynthesis, IspE and IspF, which are pursued as antimalarial targets. Disrupting crystallographically defined water networks on the way into a pocket might cost all of the binding free enthalpy gained from its occupation, as revealed in studies with tRNA-guanine transglycosylase, a target against shigellosis. Investigations of the active site of plasmepsin II, another antimalarial target, showed that principles for proper apolar cavity filling, originally developed for synthetic host-guest systems, are also applicable to enzyme environments.     

QSAR and Docking Studies of Thiazolidine-4-carboxylic Acid Derivatives as Neuraminidase Inhibitors

In order to understand the chemical-biological interactions governing their activities toward neuraminidase(NA), QSAR models of 28 thiazolidine-4-carboxylic acid derivatives with inhibitory influenza A virus were developed. Here a quantitative structure activity relationship(QSAR) model was built by three-dimensional holographic atomic vector field(3 D-HoVAIF) and multiple linear regression(MLR). The estimation stability and prediction ability of the model were strictly analyzed by both internal and external validations. The correlation coefficient(R2) of established MLR model was 0.984, and the cross-validated correlation coefficient(Q2) of MLR model was 0.947. Furthermore, the cross-validated correlation coefficient for the test set(Qext2) was 0.967. The binding mode pattern of the compounds to the binding site of integrase enzyme was confirmed by docking studies. The results of present study indicated that this model can aid in designing more potent neuraminidase inhibitors.     

Insight into the structural requirements of narlaprevir-type inhibitors of NS3/NS4A protease based on HQSAR and molecular field analyses

In the life cycle of hepatitis C virus (HCV), NS3/NS4A protease has been proved to play a vital role in the replication of the HCV virus. Narlaprevir and its derivatives, the inhibitors of NS3/NS4A, would be potentially developed as important anti-HCV drugs in the future. In this study, quantitative structure-activity relationship (QSAR) analyses for 190 narlaprevir derivatives were conducted using comparative molecular field analysis (CoMFA), comparative molecular indices analysis (CoMSIA) and hologram quantitative structure-activity relationship (HQSAR) techniques. Both of the best CoMFA and HQSAR models showed statistical significance for the training set and good predictive accuracy for the test set, which strongly manifested the robustness of the CoMFA and HQSAR models. The CoMFA contour maps and the HQSAR contribution maps were both presented. Furthermore, based on the essential factors for ligand binding derived from the QSAR models, sixteen new derivatives were designed and some of them showed higher inhibitory activities confirmed by our models and molecular docking studies. General speaking, this study provides useful suggestions for the design of potential anti-HCV drugs.     

雌激素β受体喹啉类配体的分子对接及3D-QSAR研究

对33个喹啉衍生物的雌激素β受体活性进行了分子对接以及比较分子力场分析(CoMFA)和比较分子相似性指数分析(CoMSIA). 对接结果显示氢键和疏水作用是配体与受体结合的主要因素,同时结果亦显示对接结合能与观测值pIC50具有极显著的线性相关性. 根据对接后各优势构象将33个样本进行叠合并进行CoMFA与CoMSIA研究,均得到了较优的结果,其中以选用立体场、静电场和疏水场建立的CoMSIA模型结果最优,其主成分数,r2,q2（LOO）和r2pred分别为2, 0.894, 0.708和0.802. 构效关系模型分析显示基团的空间位阻、电性及疏水作用是影响活性的主要因素     

Anchor-based design of improved cholera toxin and E. coli heat-labile enterotoxin receptor binding antagonists that display multiple binding modes

The action of cholera toxin and E. coli heat-labile enterotoxin can be inhibited by blocking their binding to the cell-surface receptor GM1. We have used anchor-based design to create 15 receptor binding inhibitors that contain the previously characterized inhibitor MNPG as a substructure. In ELISA assays, all 15 compounds exhibited increased potency relative to MNPG. Binding affinities for two compounds, each containing a morpholine ring linked to MNPG via a hydrophobic tail, were characterized by pulsed ultrafiltration (PUF) and isothermal titration calorimetry (ITC). Crystal structures for these compounds bound to toxin B pentamer revealed a conserved binding mode for the MNPG moiety, with multiple binding modes adopted by the attached morpholine derivatives. The observed binding interactions can be exploited in the design of improved toxin binding inhibitors.     

Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies

The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA was implemented to search for new inhibitors of candida N-myristoyl transferase as potential antifungal agents and glycogen phosphorylase (GP) inhibitors as potential antidiabetic agents. The process culminated in five selective micromolar antifungal leads and nine GP inhibitory leads.     

Structure activity relationships of quinoxalin-2-one derivatives as platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors, derived from molecular modeling

We previously reported a quinoxalin-2-one compound (Compound 1) that had inhibitory activity equivalent to existing platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors. Lead optimization of Compound 1 to increase its activity and selectivity, using structural information regarding PDGFbeta R-ligand interactions, is urgently needed. Here we present models of the PDGFbeta R kinase domain complexed with quinoxalin-2-one derivatives. The models were constructed using comparative modeling, molecular dynamics (MD) and ligand docking. In particular, conformations derived from MD, and ligand binding site information presented by alpha-spheres in the pre-docking processing, allowed us to identify optimal protein structures for docking of target ligands. By carrying out molecular modeling and MD of PDGFbeta R in its inactive state, we obtained two structural models having good Compound 1 binding potentials. In order to distinguish the optimal candidate, we evaluated the structural activity relationships (SAR) between the ligand-binding free energies and inhibitory activity values (IC50 values) for available quinoxalin-2-one derivatives. Consequently, a final model with a high SAR was identified. This model included a molecular interaction between the hydrophobic pocket behind the ATP binding site and the substitution region of the quinoxalin-2-one derivatives. These findings should prove useful in lead optimization of quinoxalin-2-one derivatives as PDGFb R inhibitors.     

Insight into crucial inhibitor–enzyme interaction of arylamides as novel direct inhibitors of the enoyl ACP reductase (InhA) from Mycobacterium tuberculosis: computer-aided molecular design

Abstract  

The enoyl ACP reductase enzyme (InhA) involved in the type II fatty acid biosynthesis pathway of Mycobacterium tuberculosis is an attractive target enzyme for antitubercular drug development. Arylamide derivatives are a novel class of InhA inhibitors used to overcome the drug-resistance problem of isoniazid, the frontline drug for tuberculosis treatment. Their remarkable property of inhibiting the InhA enzyme directly without requiring any coenzyme, makes them especially appropriate for the design of new antibacterials. In order to find a sound binding conformation for the different arylamide analogs, molecular docking experiments were performed with subsequent QSAR investigations. The X-ray conformation of one arylamide within its cocrystallized complex with InhA was used as a starting conformation for the docking experiments. The results thus obtained are perfectly consistent (rmsd = 0.73 ?) with the results from X-ray analysis. A thorough investigation of the arylamide binding modes with InhA provided ample information about structural requirements for appropriate inhibitor–enzyme interactions. Three different QSAR models were established using two three-dimensional (CoMFA and CoMSIA) and one two-dimensional (HQSAR) techniques. With statistically ensured models, the QSAR results obtained had high correlation coefficients between molecular structure properties of 28 arylamide derivatives and their biological activity. Molecular fragment contributions to the biological activity of arylamides could be obtained from the HQSAR model. Finally, a graphic interpretation designed in different contour maps provided coincident information about the ligand–receptor interaction thus offering guidelines for syntheses of novel analogs with enhanced biological activity.     

Assessment and acceleration of binding energy calculations for protein–ligand complexes by the fragment molecular orbital method

In the field of drug discovery, it is important to accurately predict the binding affinities between target proteins and drug applicant molecules. Many of the computational methods available for evaluating binding affinities have adopted molecular mechanics‐based force fields, although they cannot fully describe protein–ligand interactions. A noteworthy computational method in development involves large‐scale electronic structure calculations. Fragment molecular orbital (FMO) method, which is one of such large‐scale calculation techniques, is applied in this study for calculating the binding energies between proteins and ligands. By testing the effects of specific FMO calculation conditions (including fragmentation size, basis sets, electron correlation, exchange‐correlation functionals, and solvation effects) on the binding energies of the FK506‐binding protein and 10 ligand complex molecule, we have found that the standard FMO calculation condition, FMO2‐MP2/6‐31G(d), is suitable for evaluating the protein–ligand interactions. The correlation coefficient between the binding energies calculated with this FMO calculation condition and experimental values is determined to be R = 0.77. Based on these results, we also propose a practical scheme for predicting binding affinities by combining the FMO method with the quantitative structure–activity relationship (QSAR) model. The results of this combined method can be directly compared with experimental binding affinities. The FMO and QSAR combined scheme shows a higher correlation with experimental data (R = 0.91). Furthermore, we propose an acceleration scheme for the binding energy calculations using a multilayer FMO method focusing on the protein–ligand interaction distance. Our acceleration scheme, which uses FMO2‐HF/STO‐3G:MP2/6‐31G(d) at R_int = 7.0 Å, reduces computational costs, while maintaining accuracy in the evaluation of binding energy. © 2015 Wiley Periodicals, Inc.