Autodock Vina Research Articles

Molecular Design and In-Silico Analysis of Trisubstituted Benzimidazole Derivatives as Ftsz Inhibitor

Tuberculosis (TB) is the fastest spreading infectious disease and one of the top ten diseases that kill millions of people annually. The rapid spread of a multidrug-resistant strain of Mycobacterium tuberculosis leads to multidrug-resistance tuberculosis (MDR-TB), which is very difficult to treat. Filament temperature-sensitive protein ring-Z (Ftsz) protein could be the best target to inhibit bacterial cytokinesis. This research is conducted to predict the antitubercular activity of trisubstituted benzimidazole derivatives targeting FtsZ protein by an in-silico approach (molecular docking, pharmacokinetic parameter, drug likeliness, toxicity prediction, and biological activity prediction). Amine and aldehyde substitutions are used as primary scaffolds to design 20 trisubstituted benzimidazole derivatives for molecular docking. AutoDock vina v.1.2.0 software was used to predict the binding interaction between ligand and receptor (FtsZ, PDB ID : 1RQ7). The drug-likeliness properties and toxicity of ligands were predicted from SwissADMET and ToxiM web servers, respectively. Compound A15 (2,3,5,6-tetrafluoro-N1-{6-fluoro-5-[4-(1H-imidazole-1-yl) phenoxy]-1H-1,3-benzodiazol-2-yl} benzene-1,4-diamine) showed the best binding energy (ΔG = −10.2 kcal/mol/) along with four hydrogen bond interactions (GLY107, PHE180, ASP 184). Similarly, compounds A19 and A20 have the best binding score of −9.8 kcal/mol, with excellent pharmacokinetic parameters. It is found that the binding energy of all ligands (ΔG = −8.0 to −10.2 kcal/mol) is better than the reference compound Moxifloxacin (ΔG = −7.7 kcal/mol). None of the ligands violate Lipinski’s rule, but all ligands’ toxicity is slightly high (>0.8 score). It is reported that the amine-substituted benzimidazole derivatives have better binding energy than the aldehyde substitution. Therefore, it is concluded that compounds A19 and A20 can be the best candidate as Ftsz protein inhibitors but an in-vitro animal study and toxicity study are necessary to validate these data.

In-vitro antigout potential of Alstonia scholaris flower, characterization and prospective ligand-receptor interaction of bioactive lead compound

Gout is an arthropathic and inflammatory disease. The prevalence and incidence of such disease has risen in last decades. It is associated with life style thus it could be recognize as life style diseases. In the present study, the flower extract of Alstonia scholaris Linn R.Br., Flower was initially subjected to extraction, isolation which leads to purification of pure eight compounds. All these compounds were identified using various spectroscopic techniques. In-vitro Xanthine oxidase inhibition activity was performed to determine the antigout potential of lead compounds. Compound 8 showed significant activity among all i.e. 14.7 ± 0.43 as compare to standard allopurinol 6.77 ± 0.26. Accordingly, in-silico studies using Autodock vina 4 showed the ligand-protein interaction of luteolin with 3AX7. The docking simulations showed significant binding pocket sites of respective proteins 3AX7 with the least binding energy −10.2 kcal/mol. Consequently, molecular docking simulations for 100ns indicated robust evidence with their conformational structural interaction which serve as active sites for Lead compound. Principal Component Analysis indicated first three PCs capture 23.8%, 39%, and 49% of structural variance in protein. Therefore compound 8 could be consider for potential drug design and development in gout therapy.

Molecular docking and ADMET studies of the interaction of 4-carboxyl-2,6-dinitrophenylazohydroxynaphthalenes with bovine serum albumin

Previous spectrophotometric investigations revealed strong binding affinities between four potential monoazo colourants (code-named AZ-01 to 04) and bovine serum albumin (BSA) which could dictate the tissue distribution and toxicity of the additives. The molecular docking interactions of the dyes with BSA were analyzed using AutoDock vina and PatchDock in order to elucidate the functional groups involved in complex stabilization. Docking conformations confirmed the ligands preferentially inserted into the hydrophobic cavities of BSA site I. Structure-BSA binding relationships revealed the binding of AZ-02 was driven by hydrogen bond donation from its free phydroxynaphthalene substituent to Ser-479 while the predominantly hydrazone form of its positional isomer, AZ-01, increased its lipophilicity and tendency for hydrophobic interactions. The relatively higher C/H ratio of AZ-03 and - 04, which contain additional C-7 substituents, was responsible for their stronger binding and the extensive involvement of their aromatic rings in ligand-site I complex stabilization via Pi-Pi T-shaped, Pi-alkyl and alkyl-alkyl interactions. Moreso, AZ-01, -03 and -04 exist predominantly as hydrazone tautomers with an overall positive charge which provided complementary modes for interaction with negatively charged aspartic and glutamic acids. The structure-BSA binding relationships of the molecules, which can be employed in synthesis of safer congeners, have been elucidated.

Structural analysis of human G-protein-coupled receptor 17 ligand binding sites.

The human G protein coupled membrane receptor (GPR17), the sensor of brain damage, is identified as a biomarker for many neurological diseases. In human brain tissue, GPR17 exist in two isoforms, long and short. While cryo-electron microscopy technology has provided the structure of the long isoform of GPR17 with Gi complex, the structure of the short isoform and its activation mechanism remains unclear. Recently, we theoretically modeled the structure of the short isoform of GPR17 with Gi signaling protein and identified novel ligands. In the present work, we demonstrated the presence of two distinct ligand binding sites in the short isoform of GPR17. The molecular docking of GPR17 with endogenous (UDP) and synthetic ligands (T0510.3657, MDL29950) found the presence of two distinct binding pockets. Our observations revealed that endogenous ligand UDP can bind stronger in two different binding pockets as evidenced by glide and autodock vina scores, whereas the other two ligand's binding with GPR17 has less docking score. The analysis of receptor-UDP interactions shows complexes' stability in the lipid environment by 100 ns atomic molecular dynamics simulations. The amino acid residues VAL83, ARG87, and PHE111 constitute ligand binding site 1, whereas site 2 constitutes ASN67, ARG129, and LYS232. Root mean square fluctuation analysis showed the residues 83, 87, and 232 with higher fluctuations during molecular dynamics simulation in both binding pockets. Our findings imply that the residues of GPR17's two binding sites are crucial, and their interaction with UDP reveals the protein's hidden signaling and communication properties. Furthermore, this finding may assist in the development of targeted therapies for the treatment of neurological diseases.

Comparative Study of Molecular Interaction of Quercetin and B4S With Kinensin-5 Protein In-Silico for the selective anticancer activity of Quercetin

Aim: To study the comparative molecular interactions of Quercetin and 3’-fluoro-4’-(trifluoromethyl)biphenyl-4-sulfonamide (B4S) with the active sites of Kinesin-5 protein using molecular docking analysis for the selective anticancer activity. Materials and Methods: The protein structures are collected from the protein data bank (PDB) website and the ligand structures were collected from the PUBCHEM website.The samples were regarded as (N=10) for Kinensin-5 protein with quercetin and (N=10) for Kinensin-5 protein with B4S according to the sample size calculations performed from clinicalc.com with pretest G power 80%. The total sample size was 20. The binding energy (kcal/mol) was calculated using Autodock vina software. The non-covalent protein ligand interactions were detected using protein–ligand interaction profiler (PLIP) webserver. Results: The mean binding affinity of Quercetin (-9.5 kcal/mol) was significantly (p=<0.001, p<0.05, 2-tailed t-test) higher than B4S (-7.21 kcal/mol) towards the active site aminoacid resiues of Kinensin-5 protein. Conclusion: The results indicate that Quercetine has better binding affinity compared the standard Kinensin-5 inhibitor B4S. Hence it may more selectively bind to the cancerous cells to inhibit their proliferation and can acts as a novel anti-cancer agent.

Molecular Docking and Site-Directed Mutagenesis of GH49 Family Dextranase for the Preparation of High-Degree Polymerization Isomaltooligosaccharide.

The high-degree polymerization of isomaltooligosaccharide (IMO) not only effectively promotes the growth and reproduction of Bifidobacterium in the human body but also renders it resistant to rapid degradation by gastric acid and can stimulate insulin secretion. In this study, we chose the engineered strain expressed dextranase (PsDex1711) as the research model and used the AutoDock vina molecular docking technique to dock IMO4, IMO5, and IMO6 with it to obtain mutation sites, and then studied the potential effect of key amino acids in this enzyme on its hydrolysate composition and enzymatic properties by site-directed mutagenesis method. It was found that the yield of IMO4 increased significantly to 62.32% by the mutant enzyme H373A. Saturation mutation depicted that the yield of IMO4 increased to 69.81% by the mutant enzyme H373R, and its neighboring site S374R IMO4 yield was augmented to 64.31%. Analysis of the enzymatic properties of the mutant enzyme revealed that the optimum temperature of H373R decreased from 30 °C to 20 °C, and more than 70% of the enzyme activity was maintained under alkaline conditions. The double-site saturation mutation results showed that the mutant enzyme H373R/N445Y IMO4 yield increased to 68.57%. The results suggest that the 373 sites with basic non-polar amino acids, such as arginine and histidine, affect the catalytic properties of the enzyme. The findings provide an important theoretical basis for the future marketable production of IMO4 and analysis of the structure of dextranase.

Treatment of Ischemic Stroke With Wenyang Huayu Formula: Network Pharmacology Analysis and Experimental Validation

Context: Wenyang Huayu formula (WYHYF) is a prescription useful for treating stroke. Objective: To evaluate the mechanism of WYHYF in the treatment of ischemic stroke. Materials and methods: Network pharmacology analysis was performed to identify the chemical components and potential targets of WYHYF related to cerebral ischemia-reperfusion. The Cytoscape software and STRING database were used to draw a “drug component target disease” and protein interaction network diagram, respectively. Metascape database was used for gene enrichment analysis, and Autodock vina software was used for molecular docking to determine the pathways and targets of WYHYF. Finally, the pathways and targets were verified in vivo in rats. Results: We identified 277 drug targets and 3777 disease targets of WYHYF. Enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes pathways yielded 222 entries. The results of molecular docking showed that the core components and core proteins had a good binding ability. Validation analysis in the animal model indicated that stigmasterol, C-homoerythrin, luteolin, and other components in WYHYF influence the effects of the Toll-like receptor 4(TLR4)/NF-κB signal pathway on IL-6, IL-1β, and tumor necrosis factor-alpha-α and exert neuroprotective effects, relieve reperfusion injury, and inhibit apoptosis and inflammation. Discussion and conclusions: WYHYF affects ischemic stroke through the interactions of multiple components, targets, and pathways. The mechanism may involve the TLR4/NF-κB signal pathway to inhibit apoptosis, reduce inflammation, and promote angiogenesis.

In Silico Study on the Interactions, Molecular Docking, Dynamics and Simulation of Potential Compounds from Withania somnifera (L.) Dunal Root against Cancer by Targeting KAT6A.

Cancer is characterized by the abnormal development of cells that divide in an uncontrolled manner and further take over the body and destroy the normal cells of the body. Although several therapies are practiced, the demand and need for new therapeutic agents are ever-increasing because of issues with the safety, efficacy and efficiency of old drugs. Several plant-based therapeutics are being used for treatment, either as conjugates with existing drugs or as standalone formulations. Withania somnifera (L.) Dunal is a highly studied medicinal plant which is known to possess immunomodulatory activity as well as anticancer properties. The pivotal role of KAT6A in major cellular pathways and its oncogenic nature make it an important target in cancer treatment. Based on the literature and curated datasets, twenty-six compounds from the root of W. somnifera and a standard inhibitor were docked with the target KAT6A using Autodock vina. The compounds and the inhibitor complexes were subjected to molecular dynamics simulation (50 ns) using Desmond to understand the stability and interactions. The top compounds (based on the docking score of less than -8.5 kcal/mol) were evaluated in comparison to the inhibitor. Based on interactions at ARG655, LEU686, GLN760, ARG660, LEU689 and LYS763 amino acids with the inhibitor WM-8014, the compounds from W. somnifera were evaluated. Withanolide D, Withasomniferol C, Withanolide E, 27-Hydroxywithanone, Withanolide G, Withasomniferol B and Sitoindoside IX showed high stability with the residues of interest. The cell viability of human breast cancer MCF-7 cells was evaluated by treating them with W. Somnifera root extract using an MTT assay, which showed inhibitory activity with an IC50 value of 45 µg/mL. The data from the study support the traditional practice of W. somnifera as an anticancer herb.

Molecular Epidemiology of SARS-CoV-2: The Dominant Role of Arginine in Mutations and Infectivity.

Background, Aims, Methods, Results, Conclusions: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global challenge due to its ability to mutate into variants that spread more rapidly than the wild-type virus. The molecular biology of this virus has been extensively studied and computational methods applied are an example paradigm for novel antiviral drug therapies. The rapid evolution of SARS-CoV-2 in the human population is driven, in part, by mutations in the receptor-binding domain (RBD) of the spike (S-) protein, some of which enable tighter binding to angiotensin-converting enzyme (ACE2). More stable RBD-ACE2 association is coupled with accelerated hydrolysis by proteases, such as furin, trypsin, and the Transmembrane Serine Protease 2 (TMPRSS2) that augment infection rates, while inhibition of the 3-chymotrypsin-like protease (3CLpro) can prevent the viral replication. Additionally, non-RBD and non-interfacial mutations may assist the S-protein in adopting thermodynamically favorable conformations for stronger binding. This study aimed to report variant distribution of SARS-CoV-2 across European Union (EU)/European Economic Area (EEA) countries and relate mutations with the driving forces that trigger infections. Variants' distribution data for SARS-CoV-2 across EU/EEA countries were mined from the European Centre for Disease Prevention and Control (ECDC) based on the sequence or genotyping data that are deposited in the Global Science Initiative for providing genomic data (GISAID) and The European Surveillance System (TESSy) databases. Docking studies performed with AutoDock VINA revealed stabilizing interactions of putative antiviral drugs, e.g., selected anionic imidazole biphenyl tetrazoles, with the ACE2 receptor in the RBD-ACE2 complex. The driving forces of key mutations for Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Lambda, and Omicron variants, which stabilize the RBD-ACE2 complex, were investigated by computational approaches. Arginine is the critical amino acid in the polybasic furin cleavage sites S1/S2 (681-PRRARS-686) S2' (814-KRS-816). Critical mutations into arginine residues that were found in the delta variant (L452R, P681R) and may be responsible for the increased transmissibility and morbidity are also present in two widely spreading omicron variants, named BA.4.6 and BQ.1, where mutation R346T in the S-protein potentially contributes to neutralization escape. Arginine binders, such as Angiotensin Receptor Blockers (ARBs), could be a class of novel drugs for treating COVID-19.

Biosynthesis of iron nanoparticles using brown algae Spatoglossum asperum and its antioxidant and anticancer activities through in vitro and in silico studies

Green synthesized metal nanoparticles play a significant role in biomedical applications. This investigation focused on eco-friendly synthesized iron nanoparticles using marine brown algae Spatoglossum asperum which was evaluated for its anticancer and free radical scavenging activity against glioblastoma. The formation of iron nanoparticles confirmed the surface plasmon resonance (SPR) peak at 400 nm by UV visible Spectrum. X-ray diffraction spectroscopy analysis confirmed the crystalline structure of iron nanoparticles. Fourier Transform Infrared spectroscopy analysis was used to identify the functional groups in the algae extract that are involved in the ferrous ion oxidation into iron nanoparticles (Fe3O4NPs). Scanning electron microscope images indicated that the produced nanoparticles were spherical and 16 nm in size, as had been predicted. The S. asperum-mediated Fe3O4NP has shown potential antioxidant activities against 2,2-diphenyl-1-picrylhydrayl and H2O2 activity and its scavenging inhibition was 80.13% and 62.21% determined at 50 µg/mL. The anticancer activity of the synthesized Fe3O4NP against human glioblastoma cells (LN-18) was analyzed and the Fe3O4NPs half inhibitory concentration was found to be 19.24 µg/mL. The findings of the investigation evaluated the binding affinities of different proteins expressed in glioblastoma with bioactive compounds in the S. asperum by performing molecular docking by autodock vina version 4.2. The results of the present investigation revealed that S. asperum-mediated iron oxide nanoparticles exhibited antioxidant potential and effectively suppressed the proliferation of glioblastoma cancer cells.

In Silico Identification of 1-DTP Inhibitors of Corynebacterium diphtheriae Using Phytochemicals from Andrographis paniculata.

A number of phytochemicals have been identified as promising drug molecules against a variety of diseases using an in-silico approach. The current research uses this approach to identify the phyto-derived drugs from Andrographis paniculata (Burm. f.) Wall. ex Nees (AP) for the treatment of diphtheria. In the present study, 18 bioactive molecules from Andrographis paniculata (obtained from the PubChem database) were docked against the diphtheria toxin using the AutoDock vina tool. Visualization of the top four molecules with the best dockscore, namely bisandrographolide (-10.4), andrographiside (-9.5), isoandrographolide (-9.4), and neoandrographolide (-9.1), helps gain a better understanding of the molecular interactions. Further screening using molecular dynamics simulation studies led to the identification of bisandrographolide and andrographiside as hit compounds. Investigation of pharmacokinetic properties, mainly ADMET, along with Lipinski's rule and binding affinity considerations, narrowed down the search for a potent drug to bisandrographolide, which was the only molecule to be negative for AMES toxicity. Thus, further modification of this compound followed by in vitro and in vivo studies can be used to examine itseffectiveness against diphtheria.

Structure-based pharmacophore modeling, virtual screening, and molecular dynamics simulation studies for identification of Plasmodium falciparum 5-aminolevulinate synthase inhibitors.

Plasmodium falciparum (Pf) 5-aminolevulinic acid synthase (5-ALAS) is an essential enzyme with high selectivity during liver stage development, signifying its potential as a prophylactic antimalarial drug target. The aim of this study was to identify important potential lead compounds which can serve as inhibitors of Pf 5-ALAS using pharmacophore modeling, virtual screening, qualitative structural assessment, in silico ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) evaluation and molecular dynamics simulation. The best model of the tertiary structure of Pf 5-ALAS was obtained using MolProbity, while the following databases were explored for the pharmacophore-based virtual screening: CHEMBL, ChemDiv, ChemSpace, MCULE, MCULE-ULTIMATE, MolPort, NCI Open Chemical Repository, LabNetwork and ZINC databases. 2,621 compounds were screened against the modeled Pf 5-ALAS using AutoDock vina. The post-screening analysis was carried out using Discovery Studio while molecular dynamics simulation was performed on the best hits using NAMD-VMD and Galaxy Europe platform. Compound CSMS00081585868 was observed as the best hit with a binding affinity of -9.9 kcal/mol and predicted Ki of 52.10 nM, engaging in seven hydrogen bonds with the target's active site amino acid residues. The in silico ADMET prediction showed that all ten best hits possessed relatively good pharmacokinetic properties. The qualitative structural assessment of the best hit, CSMS00081585868, revealed that the presence of two pyridine scaffolds bearing hydroxy and fluorine groups linked by a pyrrolidine scaffold contributed significantly to its ability to have a strong binding affinity with the receptor. The best hit also showed stability in the active site of Pf 5-ALAS as confirmed from the RMSD obtained during the MD simulation.

Cluster-based text mining for extracting drug candidates for the prevention of COVID-19 from the biomedical literature

ObjectiveThe coronavirus disease 2019 (COVID-19) health crisis that began at the end of 2019 made researchers around the world quickly race to find effective solutions. Related literature exploded and it was inevitable that an automated approach was needed to find useful information, namely text mining, to overcome COVID-19, especially in terms of drug candidate discovery. While text mining methods for finding drug candidates mostly try to extract bioentity associations from PubMed, very few of them mine with a clustering approach. The purpose of this study was to demonstrate the effectiveness of our approach to identify drugs for the prevention of COVID-19 through literature review, cluster analysis, drug docking calculations, and clinical trial data. MethodsThis research was conducted in four main stages. First, the text mining stage was carried out by involving Bidirectional Encoder Representations from Transformers for Biomedical to obtain vector representation of each word in the sentence from texts. The next stage generated the disease-drug associations, which were obtained from the correlation between disease and drug. Next, the clustering stage grouped the rules through the similarity of diseases by utilizing Term Frequency-Inverse Document Frequency as its feature. Finally, the drug candidate extraction stage was processed through leveraging PubChem and DrugBank databases. We further used the drug docking package AUTODOCK VINA in PyRx software to verify the results. ResultsComparative analyses showed that the percentage of findings using mining with clustering outperformed mining without clustering in all experimental settings. In addition, we suggest that the top three drugs/phytochemicals by drug docking analysis may be effective in preventing COVID-19. ConclusionsThe proposed method for text mining utilizing the clustering method is quite promising in the discovery of drug candidates for the prevention of COVID-19 through the biomedical literature.

In silico Structure Prediction, Molecular Docking, and Dynamic Simulation of Plasmodium falciparum AP2-I Transcription Factor.

Plasmodium falciparum Apicomplexan Apetala 2 Invasion (PfAP2-I) transcription factor (TF) is a protein that regulates the expression of a subset of gene families involved in P. falciparum red blood cell (RBC) invasion. Inhibiting PfAP2-I TF with small molecules represents a potential new antimalarial therapeutic target to combat drug resistance, which this study aims to achieve. The 3D model structure of PfAP2-I was predicted ab initio using ROBETTA prediction tool and was validated using Save server 6.0 and MolProbity. Computed Atlas of Surface Topography of proteins (CASTp) 3.0 was used to predict the active sites of the PfAP2-I modeled structure. Pharmacophore modeling of the control ligand and PfAP2-I modeled structure was carried out using the Pharmit server to obtain several compounds used for molecular docking analysis. Molecular docking and postdocking studies were conducted using AutoDock vina and Discovery studio. The designed ligands' toxicity predictions and in silico drug-likeness were performed using the SwissADME predictor and OSIRIS Property Explorer. The modeled protein structure from the ROBETTA showed a validation result of 96.827 for ERRAT, 90.2% of the amino acid residues in the most favored region for the Ramachandran plot, and MolProbity score of 1.30 in the 98th percentile. Five (5) best hit compounds from molecular docking analysis were selected based on their binding affinity (between -8.9 and -11.7 Kcal/mol) to the active site of PfAP2-I and were considered for postdocking studies. For the absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, compound MCULE-7146940834 had the highest drug score (0.63) and drug-likeness (6.76). MCULE-7146940834 maintained a stable conformation within the flexible protein's active site during simulation. The good, estimated binding energies, drug-likeness, drug score, and molecular dynamics simulation interaction observed for MCULE-7146940834 against PfAP2-I show that MCULE-7146940834 can be considered a lead candidate for PfAP2-I inhibition. Experimental validations should be carried out to ascertain the efficacy of these predicted best hit compounds.

In silico docking based screening of constituents from Persian shallot as modulators of human glucokinase.

Small molecule glucokinase (GK) modulators not only decrease fasting and basal plasma sugar contents but also progress glucose tolerance. The hydro-ethanolic extract of the Persian shallot (Allium hirtifolium Boiss.) decreased blood glucose, improved plasma insulin and amplified GK action. The present study was proposed to screen phytoconstituents from Persian shallot as human GK activators using in silico docking studies. A total of 91 phytoconstituents reported in Persian shallot (A. hirtifolium Boiss.) were assessed in silico for the prediction of drug-like properties and molecular docking investigations were carried out with human GK using AutoDock vina with the aim of exploring the binding interactions between the phytoconstituents and GK enzyme followed by in silico prediction of toxicity. Almost all the phytoconstituents tested showed good pharmacokinetic parameters for oral bioavailability and drug-likeness. In the docking analysis, cinnamic acid, methyl 3,4,5-trimethoxy benzoate, quercetin, kaempferol, kaempferol 3-O-β-D-glucopyranosyl-(1- > 4)-glucopyranoside, 5-hydroxy-methyl furfural, ethyl N-(O-anisyl) formimidate, 2-pyridinethione and ascorbic acid showed appreciable hydrogen bond and hydrophobic type interactions with the allosteric site residues of the GK enzyme. These screened phytoconstituents may serve as promising hit molecules for further development of clinically beneficial and safe allosteric activators of the human GK enzyme.

PTPRC, KDM5C, GABBR1 and HDAC1 are the Major Targets of Valproic Acid in Regulation of its Anticonvulsant Pharmacological Effects

Background: Valproic acid (VPA) is a small molecule which is the 3rd most prescribed drug among anticonvulsant therapeutics. Understanding of the pharmacology of VPA targets will help optimally rationalise the therapeutic effects and also minimise the undesired outcomes. Hence this study analysed the human specific targets of VPA and assessed the affinity of VPA to these targets to interpret potential safe therapeutic range for VPA. Materials and Methods: The targets of VPA were identified from the SwissTargetPrediction server and STITCH database and analysed for their affinity with VPA using Autodock vina 1.2.0. The volume of distribution (Vd, L) and the dose of VPA reported in the DrugBank database was used for estimation of the plasma and CSF concentration. The plasma and CSF Concentration Affinity (CA) ratio of VPA against each of the high affinity targets was assessed at variable Vd (0.1 to 0.4 L/kg) to identify the therapeutic safety window of VPA. Results: The plasma/CSF concentration of VPA range from 170 to 7000 μM and 17 to 700 μM respectively. The plasma concentration achieved was within the safety limits (170 to 700 μM) at higher Vd (>10 L), while at lower Vd (<10L), the plasma or CSF concentration achieved was of concern at VPA dose of >1000 mg/day. The plasma concentration at very low Vd (< 2L) was of concern even at dose of 500 mg/day. The affinity of VPA against all its human specific targets ranged from 2.9 to 52.1 mM. The CA ratio of VPA against its high affinity target was observed to be greater than 0.8, indicating potentially significant modulation of these targets. The following four targets showed CA ratio of over 1: PTPRC, KDM5C, GABBR1 and HDAC1, indicating their preferential targeting by VPA. CES1 and SLC22A12 are high affinity targets of VPA which can contribute to its undesired pharmacological effects (CNS oedema and hepatotoxicity). Conclusion: This study offers a novel insight into the anticonvulsant and undesired pharmacology of VPA by specifically identifying the targets involved and recommends an evidence-based approach to personalise dose titration of VPA to achieve optimal therapeutic benefits.

An Approach to Antifungal Efficacy through Well Diffusion Analysis and Molecular Interaction Profile of Polyherbal Formulation

In the current scenario, there is a thirst for research against emerging microorganisms, and it becomes challenging to introduce new drugs against organism virulence are pretty interesting. Herbal medicines are now gaining popularity as a treatment option for various diseases worldwide. The present study analyzes the antifungal effect of a polyherbal formulation through in vitro well diffusion method using fungal strains such as Candida albicans, Aspergillus niger, Aspergillus fumigatus, Cryptococcus neoformans, and Sporothrix schenckii. Molecular docking is done using the Auto dock vina tool to predict the mechanism of action of the phytomolecules present in the polyherbal formulation. The molecular interactions are visualized using molecular modelling (PyMOL) software. The antifungal effect was observed in a concentration-dependent manner with a significant zone of inhibition. Also, phytomolecules in polyherbal formulation showed potential inhibition on CYP450 Lanosterol 14 α-demethylase 1, 3 β-Glucan synthase, and Thymidylate synthase from docking analysis.

Elucidating type 2 diabetes mellitus risk factor by promoting lipid metabolism with gymnemagenin: An in vitro and in silico approach.

Introduction: Adipose tissue functions as a key endocrine organ which releases multiple bioactive substances and regulate obesity-linked complications. Dysregulation of adipocyte differentiation, triglyceride metabolism, adipokines production and lipid transport contributes to impaired lipid metabolism resulting in obesity, insulin resistance and type 2 diabetes. Gymnema sylvestre plant is frequently used in Ayurveda for treatment of diabetes and obesity. Gymnemagenin is a major bioactive compound of Gymnema sylvestre. The present study was undertaken to elucidate the role of gymnemagenin in lipid metabolism by in vitro and computational approaches. Methods: A panel of twelve genes viz., Fasn, Lipe, Lpl, Pparg, Plin2, Cidea, Scd1, Adipoq, Lep, Ccl2, Fabp4, and Slc2a4, essential in lipid metabolism were selected and gene expression pattern and triglyceride content were checked in adipocytes (3T3L1 cells) with/without treatment of gymnemagenin by Real time PCR and colorimetric estimation, respectively. Mode of action of gymnemagenin on Pparg and Fabp4 was accomplished by computational studies. Gene set enrichment and network pharmacology were performed by STRING and Cytoscape. Molecular docking was performed by AutoDock vina by POAP pipeline. Molecular dynamics, MM-PBSA were done by Gromacs tool. Results: In vitro study showed that gymnemagenin improved triglyceride metabolism by up regulating the expression of lipase genes viz., Lipe and Lpl which hydrolyse triglyceride. Gymnemagenin also up regulated the expression of anti-inflammatory gene Adipoq. Importantly, gymnemagenin treatment up regulated the expression of Pparg gene and the downstream target genes (Plin2, Cidea, and Scd1) which are associated with adipogenesis. However, gymnemagenin has no effect on expression of Fabp4, codes for a lipid transport protein. In silico study revealed that gymnemagenin targeted 12 genes were modulating 6 molecular pathways involved in diabetes and obesity. Molecular docking and dynamics revealed that gymnemagenin stably bind to active site residue of Pparg and failed to bind to Fabp4 active site compared to its standard molecules throughout 100ns MD production run. Gymnemagenin scored binding free energy of -177.94 and -25.406kJ/mol with Pparg and Fabp4, respectively. Conclusion: Gymnemagenin improved lipid metabolism by increasing triglyceride hydrolysis (lipolysis), up regulating the crucial gene of adipogenesis and increasing the expression of anti-inflammatory adipokine proving its therapeutic importance as anti-obesity and anti-diabetic phytocompound.

Mining Potential Drug Targets for Osteoporosis Based on CeRNA Network.

To identify key pathological hub genes, micro RNAs (miRNAs), and circular RNAs (circRNAs) of osteoporosis (OP) and construct their ceRNA network in an effort to explore the potential biomarkers and drug targets for OP therapy. GSE7158, GSE201543, and GSE161361 microarray datasets were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified by comparing OP patients with healthy controls and hub genes were screened by machine learning algorithms. Target miRNAs and circRNAs were predicted by FunRich and circbank, then ceRNA network were constructed by Cytoscape. Pathways affecting OP were identified by functional enrichment analysis. The hub genes were verified by receiver operating characteristic (ROC) curve and real time quantitative PCR (RT-qPCR). Potential drug molecules related to OP were predicted by DSigDB database and molecular docking was analyzed by autodock vina software. A total of 179 DEGs were identified. By combining three machine learning algorithms, BAG2, MME, SLC14A1, and TRIM44 were identified as hub genes. Three OP-associated target miRNAs and 362 target circRNAs were predicted to establish ceRNA network. The ROC curves showed that these four hub genes had good diagnostic performance and their differential expression was statistically significant in OP animal model. Benzo[a]pyrene was predicted which could successfully bind to protein receptors related to the hub genes and it was served as the potential drug molecules. An mRNA-miRNA-circRNA network is reported, which provides new ideas for exploring the pathogenesis of OP. Benzo[a]pyrene, as potential drug molecules for OP, may provide guidance for the clinical treatment.

Design, synthesis and molecular docking studies of 5-fluoro 1-aryl/alkyl sulfonyl benzimidazole derivatives for treatment of Parkinson’s disease

Novel sulfonyl derivatives of 5-fluoro-substituted benzimidazole were synthesized and characterized by 1H-NMR, 13C-NMR, 19F-NMR and mass spectrometry. Molecular docking study against monoamine oxidase B (MAO-B), responsible for Parkinson’s disease (PD), was performed. The binding energy and interactions with active amino acid residues in the binding site of newly synthesized derivatives, as well as conventional inhibitors (Selegiline and Rasagiline), were investigated and presented. According to the docking scores predicted by ADV (AutoDock vina) and AD (AutoDock), most of the synthesized derivatives have higher binding affinity toward MAO-B than the conventional inhibitors. This study shows that these fluoro-substituted benzimidazole derivatives can be developed into essential drugs for the treatment of PD. The antibacterial property of these compounds was investigated by disk diffusion test and minimum inhibitory concentration (MIC), against gram-negative and gram-positive bacteria. And the results were further verified by the bacteria kill test with respect to time. All the synthesized compounds demonstrated considerable antibacterial activity against both bacterial strains. Therefore, this work focuses on defining the efficiency of different types of sulfonyl derivatives of fluorinated benzimidazole in biomedical research for the treatment of PD highlighting their versatile biological properties.