Dataset Information

Arabinosyltransferase C enzyme of Mycobacterium tuberculosis, a potential drug target: An insight from molecular docking study.

ABSTRACT: Multi-drug resistant in Mycobacterium tuberculosis (M.tb) is considered as major bottleneck in the treatment and cure of tuberculosis (TB). Several anti-tubercular drugs fail in its efficacy due to drug-resistant M.tb developed mechanism for resistance. So, research across globe has been carried out to develop effective anti-TB drugs to improve the treatment of these strains. Traditional drug development methods have been proved unsuccessful as it fails to develop a broad-spectrum drug due to lack of structure based approach. Several studies have been conducted in this regard and identified several drug target sites that influence drug-resistant M.tb strains. In this study, the attempt was to study the interaction between the protein Arabinosyltransferase C with the two existing drugs (Ethambutol and Isoniazid) and five modified molecules derived from Ethambutol by calculating their binding affinity and mode of binding through molecular docking study using AutoDock 4. From the comparison study of the existing drug (EMB and INH) and the five proposed modified molecules (Emb1, Emb2, Emb3, Emb4 and Emb5), it is analysed that Emb1 and Emb3 with binding affinities -5.77 kcal/mol and -5.13 kcal/mol respectively can be considered as potential inhibitors of Arabinosyltransferase C in Mycobacterium tuberculosis which is responsible for cell wall synthesis. The facts provided may be further verified experimentally for future drug discovery process to make a stand against tuberculosis and contribute an advance research for worthy antimycobacterial strategies.

SUBMITTER: Das N

PROVIDER: S-EPMC7026281 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Arabinosyltransferase C enzyme of <i>Mycobacterium tuberculosis</i>, a potential drug target: An insight from molecular docking study.

Das Nisha N Jena Pradip Kumar PK Pradhan Sukanta Kumar SK

Heliyon 20200215 2

Multi-drug resistant in <i>Mycobacterium tuberculosis</i> (M.tb) is considered as major bottleneck in the treatment and cure of tuberculosis (TB). Several anti-tubercular drugs fail in its efficacy due to drug-resistant M.tb developed mechanism for resistance. So, research across globe has been carried out to develop effective anti-TB drugs to improve the treatment of these strains. Traditional drug development methods have been proved unsuccessful as it fails to develop a broad-spectrum drug du ...[more]

PMID: 32090179

Similar Datasets

Project description:BACKGROUND: Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors' real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano(isoniazid)ferrate(II) (PIF). RESULTS: The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. CONCLUSIONS: Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor's binding site. Utilization of the intrinsic flexibility of Mtb's InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamical-structure-based drug design of novel inhibitors for Mtb's InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs.br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm.

Project description:Malaria caused by genus Plasmodium, is a parasite which is the main health issue for humans and about half of the population were suffered. An every year, approximately 1.2-2.7 million people died due to malaria globally. Therefore to prevent the spreading of malaria from the glob novel active drugs with specific activities are necessary. The present study aimed to identify novel drug molecule together with the bioinformatic tools for the development of active malarial drugs. As the search for latest anti malarial compound was developed, this work determined six active blends from various drug databases which possess drug-like characteristics and presents a significant anti malarial actions in in-silico level. Compound ID 300238, 889, 76569, 87324, 45678, and Z185397112are a few of the ligands were got from the Toss lab, Maybridge, Cambridge, Life chem, Bitter, and Examine drug databases and docked against hexokinase 1 protein (PDB: 1CZA) with high throughput practical screening (HTVS) using Glide v6.6. Amid the 6 compounds, compound no: 300238 from Toss lab has the greatest docking score of -9.889 kcal/mol targeting 1CZA protein. The active sites of Hexokinase I of protein were determine by using superimposition of the destination and template structure showed similar structural folds and active sites which were decidedly conserved. The quality of hexokinase I protein was considered to be sterically stable where the protein was prepared by utilizing the software protein preparation execute in the Schrodinger suite. Prepared proteins were evaluated using SAVES and the studies of molecular dynamics of the hexokinase, and the GROMACS were performed for protein-ligand complex. The low HOMO-LUMO energy gaps of the compound verified the greater stability of the molecule. Here, the tested drug candidates have good absorption, distribution, metabolism, and excretion (ADME) properties which were established by using QikProp, version 3.4 of Schrodinger.

Project description:Computational prediction and protein structure modeling have come to the aid of various biological problems in determining the structure of proteins. These technologies have revolutionized the biological world of research, allowing scientists and researchers to gain insights into their biological questions and design experimental research much more efficiently. Pathogenic Mycobacterium spp. is known to stay alive within the macrophages of its host. Mycobacterium tuberculosis is an acid-fast bacterium that is the most common cause of tuberculosis and is considered to be the main cause of resistance of tuberculosis as a leading health issue. The genome of Mycobacterium tuberculosis contains more than 4,000 genes, of which the majority are of unknown function. An attempt has been made to computationally model and dock one of its proteins, Rv1250 (MTV006.22), which is considered as an apparent drug-transporter, integral membrane protein, and member of major facilitator superfamily (MFS). The most widely used techniques, i.e., homology modeling, molecular docking, and molecular dynamics (MD) simulation in the field of structural bioinformatics, have been used in the present work to study the behavior of Rv1250 protein from M. tuberculosis. The structure of unknown TB protein, i.e., Rv1250 was retrived using homology modeling with the help of I-TASSER server. Further, one of the sites responsible for infection was identified and docking was done by using the specific Isoniazid ligand which is an inhibitor of this protein. Finally, the stability of protein model and analysis of stable and static interaction between protein and ligand molecular dynamic simulation was performed at 100 ns The designing of novel Rv1250 enzyme inhibitors is likely achievable with the use of proposed predicted model, which could be helpful in preventing the pathogenesis caused by M. tuberculosis. Finally, the MD simulation was done to evaluate the stability of the ligand for the specific protein.

Dataset Information

Arabinosyltransferase C enzyme of Mycobacterium tuberculosis, a potential drug target: An insight from molecular docking study.

Publications

Arabinosyltransferase C enzyme of <i>Mycobacterium tuberculosis</i>, a potential drug target: An insight from molecular docking study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets