Exploring dual inhibitory role of febrifugine analogues against Plasmodium utilizing structure-based virtual screening and molecular dynamic simulation

Malaria is an endemic disease caused by the protozoan parasite Plasomodium falciparum. Febrifugine analogues are natural compound obtained from the traditional Chinese herbs have shown significant antimalarial and anticancerous efficacy in experimental model. Development of resistance against the existing antimalarial drug has alarmed the scientific innovators to find a potential antimalarial molecule which can be further used by endemic countries for the elimination of this disease. In this study, structure-based virtual screening and molecular dynamics (MD) base approaches were used to generate potential antimalarial compound against plasmepsin II and prolyl-tRNA synthetase of Plasmodium. Here, we have docked series of febrifugine analogues (n = 11,395) against plasmepsin II in three different docking modes and then it was compared with previously reported target prolyl-tRNA synthetase. Extra precision docking resulted into 235 ligands having better docking score were subject for QikProp analysis. Better ligands (n = 39) obtained from QikProp analysis were subject for ADMET prediction and docking protocol validation through the estimation of receiver operator characteristics. In the later stage, 24 ligands obtained from ADMET study were subject for the estimation of binding energy through MM-GBSA and same were also docked against prolyl-tRNA synthetase to get compounds with dual inhibitor role. Finally, MD simulation and 2D fingerprint MACCS study of two best ligands have shown significant interaction with plasmepsin II and homology against known active ligand with noteworthy MACCS index, respectively. This study concludes that FA12 could be potential drug candidate to fight against Plasmodium falciparum parasites.     

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.     

Structure based virtual screening, 3D-QSAR,molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya

The transmission of mosquito-borne Chikungunya virus (CHIKV) has large epidemics worldwide. Till date, there are neither anti-viral drugs nor vaccines available for the treatment of Chikungunya. Accumulated evidences suggest that some natural compounds i.e., Epigallocatechin gallate, Harringtonine, Apigenin, Chrysin, Silybin, etc. have the capability to inhibit CHIKV replication in vitro. Natural compounds are known to possess less or no side effects. Therefore, natural compound in its purified or crude extracts form could be the preeminent and safe mode of therapies for Chikungunya. Wet lab screening and identification of natural compounds against Chikungunya targets is a time consuming and expensive exercise. In the present study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), Three Dimensional Quantitative Structure Activity Relation (3D-QSAR) and ADME properties to screen out potential compounds. Aim of the study is to identify potential lead/s from natural sources using in silico techniques that can be developed as a drug like molecule against Chikungunya infection and replication. Three softwares were used for molecular docking studies. Potential ligands selected by docking studies were subsequently subjected 3D-QSAR studies to predict biological activity. Based on docking scores and pIC₅₀ value, potential anti-Chikungunya compounds were identified. Best docked receptor-ligands were also subjected to MD for more accurate estimation. Lipinski’s rule and ADME studies of the identified compounds were also studied to assess their drug likeness properties. Results of in silico findings, led to identification of few best fit compounds of natural origin against targets of Chikungunya virus which may lead to discovery of new drugs for Chikungunya.

Communicated by Ramaswamy H. Sarma     

Febrifugine analogues as Leishmania donovani trypanothione reductase inhibitors: binding energy analysis assisted by molecular docking,ADMET and molecular dynamics simulation

Visceral leishmaniasis affects people from 70 countries worldwide, mostly from Indian, African and south American continent. The increasing resistance to antimonial, miltefosine and frequent toxicity of amphotericin B drives an urgent need to develop an antileishmanial drug with excellent efficacy and safety profile. In this study we have docked series of febrifugine analogues (n = 8813) against trypanothione reductase in three sequential docking modes. Extra precision docking resulted into 108 ligands showing better docking score as compared to two reference ligand. Furthermore, 108 febrifugine analogues and reference inhibitor clomipramine were subjected to ADMET, QikProp and molecular mechanics, the generalized born model and solvent accessibility study to ensure the toxicity caused by compounds and binding-free energy, respectively. Two best ligands (FFG7 and FFG2) qualifying above screening parameters were further subjected to molecular dynamics simulation. Conducting these studies, here we confirmed that 6-chloro-3-[3-(3-hydroxy-2-piperidyl)-2-oxo-propyl]-7-(4-pyridyl) quinazolin-4-one can be potential drug candidate to fight against Leishmania donovani parasites.     

Structure-based screening and molecular dynamics simulations offer novel natural compounds as potential inhibitors of Mycobacterium tuberculosis isocitrate lyase

Mycobacterium tuberculosis is the etiological agent of tuberculosis in humans and is responsible for more than two million deaths annually. M. tuberculosis isocitrate lyase (MtbICL) catalyzes the first step in the glyoxylate cycle, plays a pivotal role in the persistence of M. tuberculosis, which acts as a potential target for an anti-tubercular drug. To identify the potential anti-tuberculosis compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,748) against the MtbICL structure. The ligands were docked against MtbICL in three sequential docking modes that resulted in 340 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 27 compounds were found to fit well with re-docking studies. After refinement by molecular docking and drug-likeness analyses, three potential inhibitors (ZINC1306071, ZINC2111081, and ZINC2134917) were identified. These three ligands and the reference compounds were further subjected to molecular dynamics simulation and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the MtbICL and bound complexes. The binding free energy analyses were calculated to validate and capture the intermolecular interactions. The results suggested that the three compounds had a negative binding energy with ?96.462, ?143.549, and ?122.526 kJ mol^?1 for compounds with IDs ZINC1306071, ZINC2111081, and ZINC2134917, respectively. These lead compounds displayed substantial pharmacological and structural properties to be drug candidates. We concluded that ZINC2111081 has a great potential to inhibit MtbICL and would add to the drug discovery process against tuberculosis.     

In silico studies on p21-activated kinase 4 inhibitors: comprehensive application of 3D-QSAR analysis,molecular docking,molecular dynamics simulations,and MM-GBSA calculation

Abstract

P21-activated kinase 4 (PAK4) is a serine/threonine protein kinase, which is associated with many cancer diseases, and thus being considered as a potential drug target. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations were performed to explore the structure-activity relationship of a series of pyrropyrazole PAK4 inhibitors. The statistical parameters of comparative molecular field analysis (CoMFA, Q ² = 0.837, R ² = 0.990, and R ² _pred = 0.967) and comparative molecular similarity indices analysis (CoMSIA, Q ² = 0.720, R ² = 0.972, and R ² _pred = 0.946) were obtained from 3D-QSAR model, which exhibited good predictive ability and significant statistical reliability. The binding mode of PAK4 with its inhibitors was obtained through molecular docking study, which indicated that the residues of GLU396, LEU398, LYS350, and ASP458 were important for activity. Molecular mechanics generalized born surface area (MM-GBSA) method was performed to calculate the binding free energy, which indicated that the coulomb, lipophilic and van der Waals (vdW) interactions made major contributions to the binding affinity. Furthermore, through 100?ns MD simulations, we obtained the key amino acid residues and the types of interactions they participated in. Based on the constructed 3D-QSAR model, some novel pyrropyrazole derivatives targeting PAK4 were designed with improved predicted activities. Pharmacokinetic and toxicity predictions of the designed PAK4 inhibitors were obtained by the pkCSM, indicating these compounds had better absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Above research provided a valuable insight for developing novel and effective pyrropyrazole compounds targeting PAK4.     

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening,molecular dynamics simulation,and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol^?1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.     

Computational investigation of binding mechanism of substituted pyrazinones targeting corticotropin releasing factor-1 receptor deliberated for anti-depressant drug design

In spite of various research investigations towards anti-depressant drug discovery program, no one drug has not yet launched last 20 years. Corticotropin-releasing factor-1 (CRF-1) is one of the most validated targets for the development of antagonists against depression, anxiety and post-traumatic stress disorders. Various research studies suggest that pyrazinone based CRF-1 receptor antagonists were found to be highly potent and efficacious. In this research investigation, we identified the pharmacophore and binding pattern through 2D and 3D-QSAR and molecular docking respectively. Molecular dynamics studies were also performed to explore the binding pattern recognition. We establish the relationship between activity and pharmacophoric features to design new potent compounds. The best 2D-QSAR model was generated through multiple linear regression method with r² value of 0.97 and q² value of 0.89. Also 3D-QSAR model was obtained through k-nearest neighbor molecular field analysis method with q² value of 0.52 and q²_se value of 0.36. Molecular docking and binding energy were also evaluated to define binding patterns and pharmacophoric groups, including (i) hydrogen bond with residue Asp284, Glu305 and (ii) π–π stacking with residue Trp9. Compound 11i has the highest binding affinity compared to reference compounds, so this compound could be a potent drug for stress related disorders. Most of the compounds, including reference compounds were found within acceptable range of physicochemical parameters. These observations could be provided the leads for the design and optimization of novel CRF-1 receptor antagonists.

Communicated by Ramaswamy H. Sarma     

The systematic modeling studies and free energy calculations of the phenazine compounds as anti-tuberculosis agents

Abstract

Phenazine compounds have good activity against Mycobacterium tuberculosis (MTB). Based on the reported activities that were obtained in MTB H37Rv, a three-dimensional quantitative structure–activity relationship (3D-QSAR) model was built to design novel compounds against MTB. A fivefold cross-validation method and external validation were used to analyze the accuracy of forecasting. The model has a cross-validation coefficient q²=0.7 and a non-cross-validation coefficient r² = 0.903, indicating that the model has good predictive possibility. The design of anti-pneumococcus MTB compounds was guided by the obtained 3D-QSAR model, and several compounds with better activity were obtained. To test the activity of these compounds, molecular docking, molecular dynamics simulation, and post-simulation analysis of the already reported drug targets in MTB were carried out. Among the total 15 drug targets, only three targets (Rv2361c, Rv2965c, and Rv3048c) were selected based on the docking results. Initial results reported that these compounds possessed good inhibition activity for Rv2361c. The top nine complexes of Rv2361 ligands were only subjected to MD simulation which resulted in a stable dynamics of the structures and showed a residual fluctuation in inhibitors binding pocket. Free energy reported that overall, the derivatives hold strong energy against the protein target. Energetic contribution results showed that residues, Asp76, Arg80, Asn124, Arg127, Arg244, and Arg250, play a major role in total energy. Systems biology approach validates shortlisted drug effect on the entire system which might be useful to predict potential drug in wet lab as well.

Communicated by Ramaswamy H. Sarma     

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor

To study the pharmacophore properties of quinazolinone derivatives as 5HT₇ inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT₇ inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q² (cross validated correlation coefficient) of 0.642, 0.602 and r² (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT₇ antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r² obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.     

Prediction,docking study and molecular simulation of 3D DNA aptamers to their targets of endocrine disrupting chemicals

Abstract

Typical endocrine disrupting chemicals, including BPA (Bisphenol A), E₂ (17-β-Estradiol) and PCB 72 (polychlorinated biphenyl 72), are commonly and widely present in the environment with good chemical stability that are difficult to decompose in vitro and in vivo. Most of the high-qualified antibodies are required as the key biomaterials to fabricate the immunosensor for capturing and detecting. As an ideal alternative, the short-chain oligonucleotides (aptamer) are essentially and effectively employed with the advantages of small size, chemical stability and high effectiveness for monitoring these environmental contaminants. However, the molecular interaction, acting site and mode are still not well understood. In this work, we explored the binding features of the aptamers with their targeting ligands. The molecular dynamics simulations were performed on the aptamer–ligand complex systems. The stability of each simulation system was evaluated based on its root-mean-square deviation. The affinities of these proposed ligands and the predicted binding sites are analyzed. According to the binding energy analysis, the affinities between ligands and aptamers and the stability of the systems are BPA?>?PCB 72 >E₂. Trajectory analysis for these three complexes indicated that these three ligands were able to steadily bind with aptamers at docking site from 0 to 50?ns and contributed to alteration of conformation of aptamers.     

Structure-based virtual screening,molecular docking,ADMET and molecular simulations to develop benzoxaborole analogs as potential inhibitor against Leishmania donovani trypanothione reductase

Visceral leishmaniasis (VL) is the most fatal form of leishmaniasis and it affects 70 countries worldwide. Increasing drug resistant for antileishmanial drugs such as miltefosine, sodium stibogluconate and pentamidine has been reported in the VL endemic region. Amphotericin B has shown potential antileishmanial activity in different formulations but its cost of treatment and associated nephrotoxicity have limited its use by affected people living in the endemic zone. To control the VL infection in the affected countries, it is necessary to develop new antileishmanial compounds with high efficacy and negligible toxicity. Computer aided programs such as binding free energy estimation; ADMET prediction and molecular dynamics simulation can be used to investigate novel antileishmanial molecules in shorter duration. To develop antileishmanial lead molecule, we performed standard precision (SP) docking for 1160 benzoxaborole analogs along with reference inhibitors against trypanothione reductase of Leishmania parasite. Furthermore, extra precision (XP) docking, ADMET prediction, prime MM-GBSA was conducted over 115 ligands, showing better docking score than reference inhibitors to get potential antileishmanial compounds. Simultaneously, area under the curve (AUC) was estimated using ROC plot to validate the SP and XP docking protocol. Later on, two benzoxaborole analogs with best MM-GBSA ΔG-bind were subjected to molecular simulation and docking confirmation to ensure the ligand interaction with TR. The presented drug discovery based on computational study confirms that BOB27 can be used as a potential drug candidate and warrants further experimental investigation to fight against VL in endemic areas.     

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca²⁺-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the “open” and “closed” conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM’s inhibitors correlated well with available experimental data as the r² obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca²⁺-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca²⁺-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca²⁺-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.     

Structure-based approach for the study of thyroid hormone receptor binding affinity and subtype selectivity

Thyroid hormone (TH) possesses the ability to lower cholesterol and improve cardiac performance, which have prompted the efforts to design analogs that can utilize the cholesterol-lowering property without adversely affecting heart function. In order to gain insights into the interaction mechanism for agonists at the active site of thyroid hormone receptor β (TRβ), quantitative structure–activity relationship (QSAR) models have been developed on TRβ agonists, significant statistical coefficients were obtained (CoMFA, R²_cv, .732), (CoMSIA, R²_cv, .853), indicating the internal consistency of the models, the obtained models were further validated using the test set, the acquired R²_pred values .7054 and .7129 were in good agreement with the experimental results. The key amino acids affecting ligand binding were identified by molecular docking, and the detailed binding modes of the compounds with different activities were also determined. Furthermore, molecular dynamics (MD) simulations were conducted to assess the reliability of the derived models and the docking results. Moreover, TH exerts significant physiological effects through modulation of the two human thyroid hormone receptor subtypes. Because TRβ and TRα locate in different target cells, selective TR ligands would target specific tissues regulated by one receptor without affecting the other. Thus, the 3D information was analyzed to reveal the most relevant structural features involved in selectivity. The findings serve as the basis for further investigation into selective TRβ/TRα agonists.     

Ligand-based pharmacophore modeling and docking studies on vitamin D receptor inhibitors

In recent years, pharmacophore modeling and molecular docking approaches have been extensively used to characterize the structural requirements and explore the conformational space of a ligand in the binding pocket of the selected target protein. Herein, we report a pharmacophore modeling and molecular docking of 45 compounds comprising of the indole scaffold as vitamin D receptor (VDR) inhibitors. Based on the selected best hypothesis (DRRRR.61), an atom-based three-dimensional quantitative structure-activity relationships model was developed to rationalize the structural requirement of biological activity modulating components. The developed model predicted the binding affinity for the training set and test set with R²_(training) = 0.8869 and R²_(test) = 0.8139, respectively. Furthermore, molecular docking and dynamics simulation were performed to understand the underpinning of binding interaction and stability of selected VDR inhibitors in the binding pocket. In conclusion, the results presented here, in the form of functional and structural data, agreed well with the proposed pharmacophores and provide further insights into the development of novel VDR inhibitors with better activity.     

Identification of novel natural inhibitors of Opisthorchis felineus cytochrome P450 using structure-based screening and molecular dynamic simulation

Opisthorchis felineus is the etiological agent of opisthorchiasis in humans. O. felineus cytochrome P450 (OfCYP450) is an important enzyme in the parasite xenobiotic metabolism. To identify the potential anti-opisthorchid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,65,869) against the OfCYP450. The ligands were screened against OfCYP450 in four sequential docking modes that resulted in 361 ligands having better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 10 compounds were found to fit well with re-docking studies. After refinement by docking and drug-likeness analyses, four potential inhibitors (ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789) were identified. These ligands with reference compounds (itraconazole and fluconazole) were further subjected to molecular dynamics simulation (MDS) and binding energy analyses to compare the dynamic structure of protein after ligand binding and the stability of the OfCYP450 and bound complexes. The binding energy analyses were also calculated. The results suggested that the compounds had a negative binding energy with ?259.41, ?110.09, ?188.25, ?163.30, ?202.10, and ?158.79 kJ mol^?1 for itraconazole, fluconazole, and compounds with IDs ZINC2358298, ZINC8790946, ZINC70707116, and ZINC85878789, respectively. These lead compounds displayed significant pharmacological and structural properties to be drug candidates. On the basis of MDS results and binding energy analyses, we concluded that ZINC8790946, ZINC70707116, and ZINC85878789 have excellent potential to inhibit OfCYP450.     

Molecular modeling and dynamic simulations of agglutinin-like family members from Candida albicans: New insights into potential targets for the treatment of candidiasis

Infections by Candida albicans in immune compromised patients cause significant morbidity and mortality. In the search for potential molecular targets for drug development, the family of agglutinin-like proteins (Als) in C. albicans have been identified due to numerous attributes associated with high virulence, most prominently due to their role in adherence. Here, molecular models of individual members of the Als family illustrated common and unique structure features. Additionally, dynamic simulations were performed to display regions of high mobility. The results showed variations between Als members in the fluctuation of the A1B1 protein loop, which is located at the entrance to the peptide binding cavity, suggesting that this feature may be a factor contributing to observed differences in affinities to ligands and adhesion properties. Molecular docking results further suggested that ligand affinity could be influenced by movements in the A1B1 loop. In addition, a new site was identified in Als in an area adjacent to the peptide binding cavity that could serve as a new binding site for the design of future anti-adhesion ligands that provide increased specificity inhibiting Als proteins from C. albicans.