Investigation on the binding mode of benzothiophene analogues as potent factor IXa (FIXa) inhibitors in thrombosis by CoMFA,docking and molecular dynamic studies

Recently, benzothiophenes attract much attention of interest due to its possible inhibitory activity targeting FIXa, a blood coagulation factor that is essential for the amplification or consolidation phase of blood coagulation. To explore this inhibitory mechanism, three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) studies on a series of 84 benzothiophene analogues, for the first time, were performed. As a result, a highly predictive CoMFA model was developed with the q²?=?0.52, r²?=?0.97 and r²_pred?=?0.81, respectively. The CoMFA contour maps, the docking analysis, as well as the MD simulation results are all in a good agreement, proving the reliability and robustness of the model. These models and the information, we hoped, would be helpful in screening and development of novel drugs against thrombosis prior to synthesis.     

Molecular mechanics PBSA ligand binding energy and interaction of Efavirenz derivatives with HIV-1 reverse transcriptase

In order to evaluate the properties of several HIV-1 reverse transcripase(RT) inhibitors, Efavirenz (SUSTIVA) and a set of its derivatives (benzoxazinones) have been placed into the nonnucleoside analogue binding site of the enzyme by molecular docking. The resulting geometries were used for a molecular dynamics simulation and binding energy calculations. The enzyme-inhibitor binding energies were estimated from experimental inhibitory activities (IC90). The correlation of the predicted and experimental binding energies were satisfactory acceptable as indicated by r2 = 0.865. Based on MD simulations, the obtained results indicate that the tight association of the ligand to the HIV-1 RT binding pocket was based on hydrogen bonding between Efavirenz's N1 and the oxygen of the backbone of Lys 101, with an estimated average distance of 1.88 A. Moreover, electrostatic interaction was mainly contributed by two amino acid residues in the binding site; Lys 101 and His 235. MD simulations open the possibility to study the reaction of the flexible enzyme to those substances as well as the overall affinity.     

Computational investigations of gram-negative bacteria phosphopantetheine adenylyltransferase inhibitors using 3D-QSAR,molecular docking and molecular dynamic simulations

Abstract

Phosphopantetheine adenylyltransferase (PPAT) has been recognized as a promising target to develop novel antimicrobial agents, which is a hexameric enzyme that catalyzes the penultimate step in coenzyme A biosynthesis. In this work, molecular modeling study was performed with a series of PPAT inhibitors using molecular docking, three-dimensional qualitative structure-activity relationship (3D-QSAR) and molecular dynamic (MD) simulations to reveal the structural determinants for their bioactivities. Molecular docking study was applied to understand the binding mode of PPAT with its inhibitors. Subsequently, 3D-QSAR model was constructed to find the features required for different substituents on the scaffolds. For the best comparative molecular field analysis (CoMFA) model, the Q² and R² values of which were calculated as 0.702 and 0.989, while they were calculated as 0.767 and 0.983 for the best comparative molecular similarity index analysis model. The statistical data verified the significance and accuracy of our 3D-QSAR models. Furthermore, MD simulations were carried out to evaluate the stability of the receptor–ligand contacts in physiological conditions, and the results were consistent with molecular docking studies and 3D-QSAR contour map analysis. Binding free energy was calculated with molecular mechanics generalized born surface area approach, the result of which coincided well with bioactivities and demonstrated that van der Waals accounted for the largest portion. Overall, our study provided a valuable insight for further research work on the recognition of potent PPAT inhibitors.

Communicated by Ramaswamy H. Sarma     

Moracin M from Morus alba L. is a natural phosphodiesterase-4 inhibitor

Phosphodiesterase-4 (PDE4) has been identified to be a promising target for treatment of asthma. Moracin M extracted from Chinese herbal drug 'Sang-Bai-Pi' (Morus alba L.) was studied for the inhibitory affinity towards PDE4. It inhibited PDE4D2, PDE4B2, PDE5A1, and PDE9A2 with the IC(50) values of 2.9, 4.5, >40, and >100 μM, respectively. Our molecular docking and 8ns molecular dynamics (MD) simulations demonstrated that moracin M forms three hydrogen bonds with Gln369, Asn321, and Asp318 in the active site and stacks against Phe372. In addition, comparative kinetics analysis of its analog moracin C was carried out to qualitatively validate their inhibitory potency as predicted by the binding free energy calculations after MD simulations.     

Docking-based CoMFA and CoMSIA analyses of tetrahydro-β-carboline derivatives as type-5 phosphodiesterase inhibitors

Tetrahydro-β-carboline derivatives (THBCs) have been identified as a class of potent Type-5 Phosphodiesterase (PDE5) inhibitors, showing benefits for the treatment of erectile dysfunction and also bearing anticancer properties. A computational strategy based on molecular docking studies, followed by docking-based Comparative Molecular Fields Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA), has been used to elucidate the atomic details of the PDE5/THBC interactions and to identify the most important features impacting the THBC PDE5 inhibitory activity. The final CoMSIA model resulted to be the more predictive, showing r(ncv)(2) = 0.96, r(cv)(2) = 0.688, SEE = 0.248, F = 104.800, and r(2)(pred) = 0.78. The results allowed us to obtain useful information for the design of new THBC analogues, potentially acting as PDE5 inhibitors, and to predict their potency prior to synthesis.     

3D-QSAR,molecular docking and molecular dynamics studies of a series of RORγt inhibitors

The discovery of clinically relevant inhibitors of retinoic acid receptor-related orphan receptor-gamma-t (RORγt) for autoimmune diseases therapy has proven to be a challenging task. In the present work, to find out the structural features required for the inhibitory activity, we show for the first time a three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations for a series of novel thiazole/thiophene ketone amides with inhibitory activity at the RORγt receptor. The optimum CoMFA and CoMSIA models, derived from ligand-based superimposition I, exhibit leave-one-out cross-validated correlation coefficient (R²_cv) of .859 and .805, respectively. Furthermore, the external predictive abilities of the models were evaluated by a test set, producing the predicted correlation coefficient (R²_pred) of .7317 and .7097, respectively. In addition, molecular docking analysis was applied to explore the binding modes between the inhibitors and the receptor. MD simulation and MM/PBSA method were also employed to study the stability and rationality of the derived conformations, and the binding free energies in detail. The QSAR models and the results of molecular docking, MD simulation, binding free energies corroborate well with each other and further provide insights regarding the development of novel RORγt inhibitors with better activity.     

Discovery of novel 5α-reductase type II inhibitors by pharmacophore modelling,virtual screening,molecular docking and molecular dynamics simulations

Benign prostatic hyperplasia (BPH) is caused by augmented levels of androgen dihydrotestosterone (DHT) which is involved in the growth of the prostate in humans. 5α-Reductase type II (5αR2) is an intracellular enzyme that catalyses the formation of DHT from testosterone; hence, the inhibition of 5αR2 has emerged as one of the most promising strategies for the treatment of BPH. In this study, a computational approach that integrates ligand-based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics (MD) simulations was adopted to discover novel 5αR2 inhibitors with less side effects. After validating by Fischer's randomisation and Güner–Henry test, the best quantitative pharmacophore model (Hypo1), consisting of two hydrogen-bond acceptors and three hydrophobic features, was subsequently used as a three-dimensional-query in virtual screening to identify potential hits from Maybridge and National Cancer Institute databases. These hits were further filtered by ADMET (absorption, distribution, metabolism, elimination and toxicology) and molecular docking experiments, and their binding stabilities were validated by 10-ns MD simulations. Finally, only one hit was identified as a potential lead based on higher predicted inhibitory activity to 5αR2 compared with the most active inhibitor (finasteride). Our results further suggest that this potential lead could easily be synthesised and has structural novelty, making it a promising candidate for treating BPH.     

3D-QSAR and molecular docking studies of benzaldehyde thiosemicarbazone, benzaldehyde, benzoic acid, and their derivatives as phenoloxidase inhibitors

Phenoloxidase (PO), also known as tyrosinase, is a key enzyme in insect development, responsible for catalyzing the hydroxylation of tyrosine into o-diphenols and the oxidation of o-diphenols into o-quinones. Inhibition of PO may provide a basis for novel environmentally friendly insecticides. In the present study, we determined the inhibitory activities and IC50 values of 57 compounds belonging to the benzaldehyde thiosemicarbazone, benzaldehyde, and benzoic acid families against phenoloxidase from Pieris rapae (Lepidoptera) larvae. In addition, the inhibitory kinetics of 4-butylbenzaldehyde thiosemicarbazone against PO was measured in air-saturated solutions for the oxidation of L-3,4-dihydroxyphenylalanine (L-DOPA). The results indicated that the compound is a reversible noncompetitive inhibitor. The bioactivity results were used to construct three-dimensional quantitative structure-activity relationship (3D-QSAR) models using two molecular field analysis techniques: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). After carrying out superimposition using common substructure-based alignment, robust and predictive 3D-QSAR models were obtained from CoMFA (q2=0.926, r2=0.986) and CoMSIA (q2=0.933, r2=0.984) with six optimum components. The 3D-QSAR model built here will provide hints for the design of novel PO inhibitors. The molecular interactions between the ligands and the target were studied using a flexible docking method (FlexX). The best scored candidates were docked flexibly, and the interaction between the representative compound 4-butylbenzaldehyde thiosemicarbazone and the active site was elucidated in detail.     

Characterization of adenosine receptor in its native environment: insights from molecular dynamics simulations of palmitoylated/glycosylated, membrane-integrated human A2B adenosine receptor

Selective A(2B) receptor antagonists and agonists may play a role in important pathologies such as gastrointestinal, neurological (i.e., Alzheimer disease and dementia) and hypersensitive disorders (i.e., asthma), diabetes, atherosclerosis, restenosis and cancer. Hence, it is regarded as a good target for the development of clinically useful agents. In this study, the effects of lipid bilayer, N-acetylglucosamine and S-palmitoyl on the dynamic behavior of A(2B)AR model is explored. Homology modeling, molecular docking and molecular dynamics simulations were performed to explore structural features of A(2B)AR in the presence of lipid bilayer. Twenty ns MD simulation was performed on the constructed model inserted in a hydrated lipid bilayer to examine stability of the best model. OSIP339391 as the most potent antagonist was docked in the active site of the model. Another MD simulation was performed on the ligand-protein complex to explore effects of the bilayer on this complex. A similar procedure was performed for the modified protein with N-acetylglucosamine and S-palmitoyl moieties in its structure. Phe173 and Glu174 located in EL2 were determined to be involved in ligand-receptor interactions through π-π stacking and hydrogen bonding. Asn254 was crucial to form hydrogen-bonding. The reliability of the model was assessed through docking using both commercial and synthetic antagonists and an r(2) of 0.70 was achieved. Our results show that molecular dynamics simulations of palmitoylated/glycosylated, membrane-integrated human A(2B)AR in its native environment is a possible approach and this model can be used for designing potent and selective A(2B)AR antagonists.     

Discovery of FIXa inhibitors by combination of pharmacophore modeling,molecular docking,and 3D-QSAR modeling

Human Coagulation Factor IXa (FIXa), specifically inhibited at the initiation stage of the blood coagulation cascade, is an excellent target for developing selective and safe anticoagulants. To explore this inhibitory mechanism, 86 FIXa inhibitors were selected to generate pharmacophore models and subsequently SAR models. Both best pharmacophore model and ROC curve were built through the Receptor–Ligand Pharmacophore Generation module. CoMFA model based on molecular docking and PLS factor analysis methods were developed. Model propagations values are q²?=?0.709, r²?=?0.949, and r²_pred?=?0.905. The satisfactory q² value of 0.609, r² value of 0.962, and r²_pred value of 0.819 for CoMSIA indicated that the CoMFA and CoMSIA models are both available to predict the inhibitory activity on FIXa. On the basis of pharmacophore modeling, molecular docking, and 3D-QSAR modeling screening, six molecules are screened as potential FIXa inhibitors.     

Docking studies on PARP-1 inhibitors: insights into the role of a binding pocket water molecule

The binding mode of a series of competitive PARP-1 inhibitors was investigated employing a molecular docking approach by using Autodock 3.0. A particular attention was given to the role played by a water molecule present in some but not all the so far available crystal structures of the catalytic domain of PARP-1. Good correlation between calculated binding energies and experimental inhibitory activities was obtained either by including (r2=0.87) or not (r2=0.84) the structural water molecule. Closer inspection of our results suggested that this water molecule should be considered part of the hydration shell of polar inhibitors and not as a structural water.     

Binding Mode Analyses and Pharmacophore Model Development for Stilbene Derivatives as a Novel and Competitive Class of α-Glucosidase Inhibitors

Stilbene urea derivatives as a novel and competitive class of non-glycosidic α-glucosidase inhibitors are effective for the treatment of type II diabetes and obesity. The main purposes of our molecular modeling study are to explore the most suitable binding poses of stilbene derivatives with analyzing the binding affinity differences and finally to develop a pharmacophore model which would represents critical features responsible for α-glucosidase inhibitory activity. Three-dimensional structure of S. cerevisiae α-glucosidase was built by homology modeling method and the structure was used for the molecular docking study to find out the initial binding mode of compound 12, which is the most highly active one. The initial structure was subjected to molecular dynamics (MD) simulations for protein structure adjustment at compound 12-bound state. Based on the adjusted conformation, the more reasonable binding modes of the stilbene urea derivatives were obtained from molecular docking and MD simulations. The binding mode of the derivatives was validated by correlation analysis between experimental K_i value and interaction energy. Our results revealed that the binding modes of the potent inhibitors were engaged with important hydrogen bond, hydrophobic, and π-interactions. With the validated compound 12-bound structure obtained from combining approach of docking and MD simulation, a proper four featured pharmacophore model was generated. It was also validated by comparison of fit values with the K_i values. Thus, these results will be helpful for understanding the relationship between binding mode and bioactivity and for designing better inhibitors from stilbene derivatives.     

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     

Design of novel quinoline-aminopiperidine derivatives as Mycobacterium tuberculosis (MTB) GyrB inhibitors: an in silico study

Tuberculosis (TB) is an infectious disease that causes a number of deaths, and the development of new, safer and more adequate TB inhibitors/drugs has become a necessity as well as a great challenge. Mycobacterial DNA gyrase B subunit has been identified to be one of the potentially underexploited drug targets in the field of anti-tubercular drug discovery. To design the novel and potent Mycobacterium tuberculosis (MTB) inhibitors, we performed molecular modeling studies that combined the 3D-QSAR, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Forty eight quinoline-aminopiperidine inhibitors which act on DNA gyrase B subunit were used for constructing 3D-QSAR models. The results showed that the best CoMFA model had the high performance with q²?=?0.643, r²?=?0.947, while the best CoMSIA model yielded q²?=?0.536, r²?=?0.948. The contour map was in good agreement with the docking and MD simulations which strongly demonstrated that the molecular modeling was reliable. Based on this information, several potential compounds were designed and their inhibitory activities were also verified by the accomplished models and ADME/T predictions. We hope that our research could bring new ideas to facilitate the development of novel inhibitors with higher inhibitory activity for TB.

Communicated by Ramaswamy H. Sarma     

Understanding microscopic binding of macrophage migration inhibitory factor with phenolic hydrazones by molecular docking, molecular dynamics simulations and free energy calculations

Macrophage migration inhibitory factor (MIF), an immunoregulatory protein, is a potential target for a number of inflammatory diseases. In the current work, the interactions between MIF and a series of phenolic hydrazones were studied by molecular docking, molecular dynamics (MD) simulations, binding free energy calculations, and binding energy decomposition analysis to determine the structural requirement for achieving favorable biological activity of phenolic hydrazones. First, molecular docking was used to predict the binding modes of inhibitors in the binding site of MIF. The good correlation between the predicted docking scores and the experimental activities shows that the binding conformations of the inhibitors in the active site of MIF are well predicted. Moreover, our results suggest that the flexibility of MIF is essential in ligand binding process. Then, MD simulations and MM/GBSA free energy calculations were employed to determine the dynamic binding process and compare the binding modes of the inhibitors with different activities. The predicted binding free energies given by MM/GBSA are not well correlated with the experimental activities for the two subsets of the inhibitors; however, for each subset, a good correlation between the predicted binding free energies and the experimental activities is achieved. The MM/GBSA free energy decomposition analysis highlights the importance of hydrophobic residues for the MIF binding of the studied inhibitors. Based on the essential factors for MIF-inhibitor interactions derived from the theoretical predictions, some derivatives were designed and the higher inhibitory activities of several candidates were confirmed by molecular docking studies. The structural insights obtained from our study are useful for designing potent inhibitors of MIF.     

Molecular docking and 3D QSAR studies on 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes based on the structural modeling of human CCR5 receptor

In the present study, we have used an approach combining protein structure modeling, molecular dynamics (MD) simulation, automated docking, and 3D QSAR analyses to investigate the detailed interactions of CCR5 with their antagonists. Homology modeling and MD simulation were used to build the 3D model of CCR5 receptor based on the high-resolution X-ray structure of bovine rhodopsin. A series of 64 CCR5 antagonists, 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes, were docked into the putative binding site of the 3D model of CCR5 using the docking method, and the probable interaction model between CCR5 and the antagonists were obtained. The predicted binding affinities of the antagonists to CCR5 correlate well with the antagonist activities, and the interaction model could be used to explain many mutagenesis results. All these indicate that the 3D model of antagonist-CCR5 interaction is reliable. Based on the binding conformations and their alignment inside the binding pocket of CCR5, three-dimensional structure-activity relationship (3D QSAR) analyses were performed on these antagonists using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. Both CoMFA and CoMSIA provide statistically valid models with good correlation and predictive power. The q(2)(r(cross)(2)) values are 0.568 and 0.587 for CoMFA and CoMSIA, respectively. The predictive ability of these models was validated by six compounds that were not included in the training set. Mapping these models back to the topology of the active site of CCR5 leads to a better understanding of antagonist-CCR5 interaction. These results suggest that the 3D model of CCR5 can be used in structure-based drug design and the 3D QSAR models provide clear guidelines and accurate activity predictions for novel antagonist design.     

Molecular docking and 3D-QSAR-based virtual screening of flavonoids as potential aromatase inhibitors against estrogen-dependent breast cancer

Aromatase, catalyzing final step of estrogen biosynthesis, is considered a key target for the development of drug against estrogen-dependent breast cancer (EDBC). Identification and development of naturally occurring compounds, such as flavonoids, as drugs against EDBC is in demand due to their lesser toxicity when compared to those of synthetic ones. Thus, a three-dimensional quantitative structure–activity relationship, using comparative molecular field analysis (CoMFA) was done on a series of 45 flavonoids against human aromatase. A significant cross-validated correlation coefficient (q²) of 0.827 was obtained. The best predictive CoMFA model explaining the biological activity of the training and test sets with correlation coefficient values (r²) of 0.916 and 0.710, respectively, when used for virtual screening of a flavanoids database following molecular docking revealed a flavanone namely, 7-hydroxyflavanone beta-D-glucopyranoside showing highest predicted activity of 1.09?μM. In comparison to a well-established inhibitor of aromatase, namely 7-hydroxyflavanone (IC₅₀: 3.8?μM), the derivative identified in the present study, namely 7-hydroxyflavanone beta-D-glucopyranoside exhibited about 3.5 folds higher inhibitory activity against aromatase. The result of virtual screening was further validated using molecular dynamics (MD) simulation analysis. Thus, a 25 ns MD simulation analysis revealed high stability and effective binding of 7-hydroxyflavanone beta-D-glucopyranoside within the active site of aromatase. To the best of our knowledge, this is the first report of CoMFA-based QSAR model for virtual screening of flavonoids as inhibitors of aromatase.     

Taxifolin prevents postprandial hyperglycemia by regulating the activity of α-amylase: Evidence from an in vivo and in silico studies

There has been a dramatic increase in the prevalence of diabetes mellitus (DM) and its associated complications globally. The postprandial stage of DM involves prompt elevation in the levels of blood glucose and α-amylase, a carbohydrate-metabolizing enzyme is mainly involved in the regulation of postprandial hyperglycemia. This study was designed to assess the ability of a well-known flavonoid, taxifolin (TFN), against postprandial hyperglycemia and its inhibitory effects on α-amylase activity through the assessment of therapeutic potentials of TFN in an alloxan-induced diabetic animal model. The binding potential TFN with an α-amylase receptor was also investigated through molecular dynamics (MD) simulation and docking of to compare the binding affinities and energies of TFN and standard drug acarbose (ACB) with target enzyme. TFN significantly improved the postprandial hyperglycemia, lipid profile, and serum levels of α-amylase, lipase, and C-reactive protein in a dose-dependent manner when compared with that of either DM-induced and ACB-treated alloxan-induced diabetic rats. Moreover, TFN also enhanced the anti-oxidant status and normal functioning of the liver in alloxan-induced diabetic rats more efficiently as compared to that of ACB-treated alloxan-induced diabetic rats. Therapeutic potentials of TFN were also verified by MD simulation and docking results, which exhibited that the binding energy and affinity of TFN to bind with receptor was significantly higher as compared to that of ACB. Hence, the results of this study signify that TFN might be a potent inhibitor of α-amylase that has the potential to regulate the postprandial hyperglycemia along with its anti-inflammatory and anti-oxidant properties during the treatment of DM.