Investigation of binding features: Effects on the interaction between CYP2A6 and inhibitors

A computational investigation has been carried out on CYP2A6 and its naphthalene inhibitors to explore the crucial molecular features contributing to binding specificity. The molecular bioactive orientations were obtained by docking (FlexX) these compounds into the active site of the enzyme. And the density functional theory method was further used to optimize the molecular structures with the subsequent analysis of molecular lipophilic potential (MLP) and molecular electrostatic potential (MEP). The minimal MLPs, minimal MEPs, and the band gap energies (the energy difference between the highest occupied molecular orbital and lowest unoccupied molecular orbital) showed high correlations with the inhibition activities (pIC₅₀s), illustrating their significant roles in driving the inhibitor to adopt an appropriate bioactive conformation oriented in the active site of CYP2A6 enzyme. The differences in MLPs, MEPs, and the orbital energies have been identified as key features in determining the binding specificity of this series of compounds to CYP2A6 and the consequent inhibitory effects. In addition, the combinational use of the docking, MLP and MEP analysis is also demonstrated as a good attempt to gain an insight into the interaction between CYP2A6 and its inhibitors. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

血管紧张素转换酶与抑制肽结合模式的分子动力学研究

应用分子模拟方法研究了血管紧张素转换酶(Angiotensin-converting enzyme,ACE)C端结构域(C-domain)与两种抑制肽(RIGLF/AHEPVK)的结合机制,预测了两个体系的结合模式,提出在C-domain-RIGLF中His353,Asp377,Asp453,Phe457,His513,Tyr523和Phe527为RIGLF主要结合残基,而在C-domainAHEPVK中Gln281,His353,Ser355,Glu384,Lys511,His513和Tyr523等残基起关键作用.应用结合自由能计算比较了两个体系的结合能力,结果表明,RIGLF和AHEPVK均与C-domain活性位点残基存在较强作用,且AHEPVK对C-domain的结合能力较强,与实验结果一致.     

Development of energetic pharmacophore for the designing of 1,2,3,4-tetrahydropyrimidine derivatives as selective cyclooxygenase-2 inhibitors

We present here the Energetic pharmacophore model representing complementary features of the 1,2,3,4-tetrahydropyrimidine for selective cyclooxygenase-2 (COX-2) inhibition. For the development of pharmacophore hypothesis, a total of 43 previously reported compounds were docked on active site of COX-2 enzyme. The generated pharmacophore features were ranked using energetic terms of Glide XP docking for 1,2,3,4-tetrahydropyrimidine scaffold to optimize its structure requirement for COX-2 inhibition. The thirty new 4,5,6-triphenyl-1,2,3,4-tetrahydropyrimidine derivatives were synthesized and assessed for selective COX-2 inhibitory activity. Two compounds 4B1 and 4B11 were found to be potent and selective COX-2 inhibitors. The molecular docking studies revealed that the newly synthesized compounds can be docked into COX-2 binding site and also provide the molecular basis for their activity.     

Molecular dynamics simulation, free energy calculation and structure-based 3D-QSAR studies of B-RAF kinase inhibitors

(V600E)B-RAF kinase is the most frequent onco-genic protein kinase mutation in melanoma and is a promising target to treat malignant melanoma. In this work, a molecular modeling study combining QM-polarized ligand docking, molecular dynamics, free energy calculation, and three-dimensional quantitative structure-activity relationships (3D-QSAR) was performed on a series of pyridoimidazolone compounds as the inhibitors of (V600E)B-RAF kinase to understand the binding mode between the inhibitors and (V600E)B-RAF kinase and the structural requirement for the inhibiting activity. 3D-QSAR models, including CoMFA and CoMSIA, were developed from the conformations obtained by QM-polarized ligand docking strategy. The obtained models have a good predictive ability in both internal and external validation. Furthermore, molecular dynamics simulation and free energy calculations were employed to determine the detailed binding process and to compare the binding mode of the inhibitors with different activities. The binding free energies calculated by MM/PBSA gave a good correlation with the experimental biological activity. The decomposition of free energies by MM/GBSA indicates the van der Waals interaction is the major driving force for the interaction between the inhibitors and (V600E)B-RAF kinase. The hydrogen bond interactions between the inhibitors with Glu501 and Asp594 of the (V600E)B-RAF kinase help to stabilize the DFG-out conformation. The results from this study can provide some insights into the development of novel potent (V600E)B-RAF kinase inhibitors.     

Amino acids of ricin and its polypeptides

Ricin and its corresponding polypeptides (A & B chain) were purified from castor seed. The molecular weight of ricin subunits were 29,000 and 28,000 daltons. The amino acids in ricin determined were Asp45 The22 Ser40 Glu53 Cys4 Gly96 His5 Ile21 Leu33 Lys20 Met4 Phe13 Pro37 Tyr11 Ala45 Val23 Arg20 indicating that ricin contains approximately 516 amino acid residues. The amino acids of the two subunits of ricin A and B chains were Asp23 The12 Ser21 Glu29 Cys2 Gly48 His3 Ile12, Leu17 Lys10 Met2 Phe6 Pro17 Tyr7 Ala35 Val13 Arg13 while in B chain the amino acids were Asp22 The10 Ser19 Glu25 Cys2 Gly47 His1 Ile10, Leu15 Lys11 Met1 Phe7 Pro6 Tyr5 Ala32Val11 Arg10. The total helical content of ricin came around 53.6% which is a new observation.     

Structure-based virtual screening of dipeptidyl peptidase 4 inhibitors and their in vitro analysis

Type 2 diabetes mellitus (T2DM) is one of the most widely prevalent metabolic disorders with no cure to date thus remains the most challenging task in the current drug discovery. Therefore, the only strategy to control diabetes prevalence is to develop novel efficacious therapeutics. Dipeptidyl Peptidase 4 (DPP-4) inhibitors are currently used as anti-diabetic drugs for the inhibition of incretins. This study aims to construct the chemical feature based on pharmacophore models for dipeptidyl peptidase IV. The structure-based pharmacophore modeling has been employed to evaluate new inhibitors of DPP-4. A four-featured pharmacophore model was developed from crystal structure of DPP-4 enzyme with 4-(2-aminoethyl) benzenesulfonyl fluoride in its active site via pharmacophore constructing tool of Molecular Operating Environment (MOE) consisting F1 Hyd (hydrophobic region), F2 Hyd|Cat|Don (hydrophobic cationic and donor region), F3 Acc (acceptor region) and F4 Hyd (hydrophobic region). The generated pharmacophore model was used for virtual screening of in-house compound library (the available compounds which were used for initial screening to get the few compounds for the current studies). The resultant selected compounds, after virtual screening were further validated using in vitro assay. Furthermore, structure-activity relationship was carried out for the compounds possessing significant inhibition potential after docking studies. The binding free energy of analogs was evaluated via molecular mechanics generalized Born surface area (MM-GBSA) and Poisson-Boltzmann surface area (MM-PBSA) methods using AMBER 16 as a molecular dynamics (MD) simulation package. Based on potential findings, we report that selected candidates are more likely to be used as DPP-4 inhibitors or as starting leads for the development of novel and potent DPP-4 inhibitors.     

Pharmacoinformatics exploration of polyphenol oxidases leading to novel inhibitors by virtual screening and molecular dynamic simulation study

Polyphenol oxidases (PPOs)/tyrosinases are metal-dependent enzymes and known as important targets for melanogenesis. Although considerable attempts have been conducted to control the melanin-associated diseases by using various inhibitors. However, the exploration of the best anti-melanin inhibitor without side effect still remains a challenge in drug discovery. In present study, protein structure prediction, ligand-based pharmacophore modeling, virtual screening, molecular docking and dynamic simulation study were used to screen the strong novel inhibitor to cure melanogenesis. The 3D structures of PPO1 and PPO2 were built through homology modeling, while the 3D crystal structures of PPO3 and PPO4 were retrieved from PDB. Pharmacophore modeling was performed using LigandScout 3.1 software and top five models were selected to screen the libraries (2601 of Aurora and 727, 842 of ZINC). Top 10 hit compounds (C1-10) were short-listed having strong binding affinities for PPO1-4. Drug and synthetic accessibility (SA) scores along with absorption, distribution, metabolism, excretion and toxicity (ADMET) assessment were employed to scrutinize the best lead hit. C4 (name) hit showed the best predicted SA score (5.75), ADMET properties and drug-likeness behavior among the short-listed compounds. Furthermore, docking simulations were performed to check the binding affinity of C1-C10 compounds against target proteins (PPOs). The binding affinity values of complex between C4 and PPOs were higher than those of other complexes (−11.70, −12.1, −9.90 and −11.20 kcal/mol with PPO1, PPO2, PPO3, or PPO4, respectively). From comparative docking energy and binding analyses, PPO2 may be considered as better target for melanogenesis than others. The potential binding modes of C4, C8 and C10 against PPO2 were explored using molecular dynamics simulations. The root mean square deviation and fluctuation (RMSD/RMSF) graphs results depict the significance of C4 over the other compounds. Overall, bioactivity and ligand efficiency profiles suggested that the proposed hit may be more effective inhibitors for melanogenesis.     

Translational diffusion constants of the amino acids: measurement by NMR and their use in modeling the transport of peptides

In this work, the translational self-diffusion constants, DT's, of 12 amino acids (Ala, Arg, Asn, Asp, Cys, Glu, His, Ile, Lys, Met, Phe, and Ser) are measured by field gradient NMR and extrapolated to infinite dilution. The experiments were carried out in D2O at 298 K at pD approximately =3.5 in 50 mM sodium phosphate buffer. Of these 12 amino acids, 6 are being reported for the first time (Asp, Cys, Glu, His, Lys, and Met) and the remaining 6 (Ala, Arg, Asn, Ile, Phe, and Ser) are compared with DT's from the literature. When corrected for differences in solvent viscosity and temperature, the discrepancy between DT's measured in the present work and those reported previously is always <8%, which is reasonable given the range of values reported previously by different groups. With the present work, DT's for all of the amino acids are now available. These diffusion constants are then used in modeling studies of the diffusion and free solution electrophoretic mobility, mu, of several model peptides. For this set of peptides, it is shown that modeling using revised input parameters results in improved agreement between model and experimental mobilities.     

Design,synthesis and in silico study of pyridine based 1,3,4-oxadiazole embedded hydrazinecarbothioamide derivatives as potent anti-tubercular agent

Development of novel, safe and effective drug candidates combating the emerging drug resistance has remained a major focus in the mainstream of anti-tuberculosis research. Here, we inspired to design and synthesize series of new pyridin-4-yl-1,3,4-oxadiazol-2-yl-thio-ethylidene-hydrazinecarbothioamide derivatives as potential anti-tubercular agents. The anti-tubercular bioactive assay demonstrated that the synthesized compounds exhibit potent anti-tubercular activity (MIC = 3.9–7.81 μg/mL) in comparison with reference drugs Rifampicin and Isoniazid.We employed pharmacophore probing approach for the identification of CYP51 as a possible drug target for the synthesized compounds. To understand the preferable binding mode, the synthesized molecules were docked onto the active site of Sterol 14 α-demethylases (CYP51) target. From the binding free energy of the docking results it was revealed that the compounds were effective CYP51 inhibitors and acts as antitubercular agent.     

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.     

Pharmacophore model-aided virtual screening combined with comparative molecular docking and molecular dynamics for identification of marine natural products as SARS-CoV-2 papain-like protease inhibitors

Targeting SARS-CoV-2 papain-like protease using inhibitors is a suitable approach for inhibition of virus replication and dysregulation of host anti-viral immunity. Engaging all five binding sites far from the catalytic site of PLpro is essential for developing a potent inhibitor. We developed and validated a structure-based pharmacophore model with 9 features of a potent PLpro inhibitor. The pharmacophore model-aided virtual screening of the comprehensive marine natural product database predicted 66 initial hits. This hit library was downsized by filtration through a molecular weight filter of ≤ 500 g/mol. The 50 resultant hits were screened by comparative molecular docking using AutoDock and AutoDock Vina. Comparative molecular docking enables benchmarking docking and relieves the disparities in the search and scoring functions of docking engines. Both docking engines retrieved 3 same compounds at different positions in the top 1 % rank, hence consensus scoring was applied, through which CMNPD28766, aspergillipeptide F emerged as the best PLpro inhibitor. Aspergillipeptide F topped the 50-hit library with a pharmacophore-fit score of 75.916. Favorable binding interactions were predicted between aspergillipeptide F and PLpro similar to the native ligand XR8-24. Aspergillipeptide F was able to engage all the 5 binding sites including the newly discovered BL2 groove, site V. Molecular dynamics for quantification of Cα-atom movements of PLpro after ligand binding indicated that it exhibits highly correlated domain movements contributing to the low free energy of binding and a stable conformation. Thus, aspergillipeptide F is a promising candidate for pharmaceutical and clinical development as a potent SARS-CoV-2 PLpro inhibitor.     

Extra precision docking,free energy calculation and molecular dynamics studies on glutamic acid derivatives as MurD inhibitors

The binding modes of well known MurD inhibitors have been studied using molecular docking and molecular dynamics (MD) simulations. The docking results of inhibitors 1-30 revealed similar mode of interaction with Escherichia coli-MurD. Further, residues Thr36, Arg37, His183, Lys319, Lys348, Thr321, Ser415 and Phe422 are found to be important for inhibitors and E. coli-MurD interactions. Our docking procedure precisely predicted crystallographic bound inhibitor 7 as evident from root mean square deviation (0.96 Å). In addition inhibitors 2 and 3 have been successfully cross-docked within the MurD active site, which was pre-organized for the inhibitor 7. Induced fit best docked poses of 2, 3, 7 and 15/2Y1O complexes were subjected to 10 ns MD simulations to determine the stability of the predicted binding conformations. Induce fit derived docked complexes were found to be in a state of near equilibrium as evident by the low root mean square deviations between the starting complex structure and the energy minimized final average MD complex structures. The results of molecular docking and MD simulations described in this study will be useful for the development of new MurD inhibitors with high potency.     

Homology modeling and molecular dynamic simulation of UDP-N-acetylmuramoyl-l-alanine-d-glutamate ligase (MurD) from Mycobacterium tuberculosis H37Rv using in silico approach

The present study aimed to identify the prospective inhibitors of MurD, a cytoplasmic enzyme that catalyzes the addition of d-glutamate to the UDP-N-acetylmuramoyl-l-alanine nucleotide precursor in Mycobacterium tuberculosis (MTB), using virtual screening, docking studies, pharmacokinetic analysis, Molecular Dynamic (MD) simulation, and Molecular Mechanics Generalized Born and Surface Area (MM-GBSA) analyses. The three dimensional (3D) structure was determined based on the homology technique using a template from Streptococcus agalactiae. The modeled structure had three binding sites, namely; substrate binding site (Val18, Thr19, Asp39, Asp40, Gly75, Asn147, Gln171 and His192), the ATP binding site (Gly123, Lys124, Thr125, Thr126, Glu166, Asp283, and Arg314) and the glutamic acid binding site (Arg382, Ser463, and Tyr470). These residues mentioned above play a critical role in the catalytic activity of the enzyme, and their inhibition could serve as a stumbling block to the normal function of the enzyme. A total of 10,344 obtained from virtual screened of Zinc and PubChem databases. These compounds further screened for Lipinski rule of five, docking studies and pharmacokinetic analysis. Four compounds with good binding energies (ZINC11881196 = −10.33 kcal/mol, ZINC12247644 = −8.90 kcal/mol, ZINC14995379 =−8.42 kcal/mol, and PubChem6185 = −8.20 kcal/mol), better than the binding energies of the ATP (−2.31 kcal/mol) and the ligand with known IC₅₀, Aminothiazole (−7.11 kcal/mol) were selected for the MD simulation and MM-GBSA analyses. The result of the analyses showed that all the four ligands formed a stable complex and had the binding free energies better than the binding energy of ATP. Therefore, these ligands considered as suitable prospective inhibitors of the MurD after experimental validation.     

Synergistic use of compound properties and docking scores in neural network modeling of CYP2D6 binding: predicting affinity and conformational sampling

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known active site. Docking scores for the active site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85+/-6% is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound's formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12% improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23% above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding.     

Structure based pharmacophore study to identify possible natural selective PARP-1 trapper as anti-cancer agent

Inhibition of poly(ADP-ribose) polymerase-1 (PARP-1) has turned out an innovative approach for cancer therapy due to its involvement in DNA repair pathways. Although several potent PARP-1 inhibitors have been identified, they exhibit high toxicity, resistivity and diverse pharmacological profile in clinical trials, which necessitate for extensive investigation and development of selective inhibitors. Therefore, the study aimed to identify selective natural PARP-1 inhibitors to reduce toxicity and resistivity with high potency. Accordingly, the combined approach of structure-based pharmacophore and molecular docking study was performed. Hence, the two hits (SN00167272 and STOCK1N-92279) were identified to have all the pharmacophoric features that showed interaction with key residues (Gly863, Ser904, Tyr896, and Tyr907) and least conserved residues (Tyr889 and Asp766). Additionally, these inhibitors represented interactions with unique selective residues (Asp756, Val762, Glu763 and Val886) and exhibited strong interaction with PARP-1 through binding free energy and molecular dynamics study. Hence, the identified hits could further considered for experimental investigations as they may reduce off-target and resistivity of currently available inhibitors and developed as potential anti-cancer agents in the future. Also, the study provides a specific structural insight which could further help to design selective and potent PARP-1 inhibitors.     

In silico modeling of p450 substrates, inhibitors, activators, and inducers

Cytochrome P450 enzymes are the predominant mediators of phase I metabolism of exogenous small molecules. As a result of their extensive role in metabolism of xenobiotics, drug compounds, and endogenous compounds, as well as their wide tissue distribution, significant drug discovery resources are spent to avoid interacting with this class of enzymes. Here we review historical and recent in silico modeling of 7 cytochrome P450 enzymes of particular interest, specifically CYP1A2, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP3A4. For each we provide a brief biological background including known inhibitors, substrates, and inducers, as well as details of computational modeling efforts and advances in structural biology. We also provide similar details for 3 nuclear receptors known to regulate gene expression of these enzyme families.     

Molecular modeling studies on the urease active site and the enzyme-catalyzed urea hydrolysis

Summary These studies are an attempt to gain better insight into the pharmacophore requirements of urease. On the basis of published information on this enzyme (EXAFS, amino acid sequence, essential groups at the active site) a hypothetical nickel-tripeptide complex, as preliminary substitute for the urease active site was modeled using computer-aided molecular modeling techniques. The results suggest two alternative docking modes of urea and reaction intermediates, corresponding to two different reaction mechanisms. Both binding modes are compatible with the docking of known potent inhibitors such as selected hydroxamic acids and phosphorodiamides. The results can be used to help in the design of new potential inhibitors of urease.