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Insights from the analysis of predicted Rv0679c protein peptide from Mycobacterium tuberculosis with Toll like Receptors in host.

ABSTRACT: Peptides of Rv0679c a membrane protein of the cell envelope (16.6 KDa) of Mycobacterium tuberculosis (M. tb), inhibited entry of live bacilli into epithelial (A549) and macrophage (U937) cell lines in vitro, suggesting a possible role in invasion. Receptors associated with Rv0679c antigen entry into cell lines were not characterized. We are reporting that Rv0679c peptides could bind to Toll like receptors (TLRs), the principal class of pathogen recognition receptors on host cells (PRR) by docking studies. Peptide structures were predicted using PEP FOLD and docking of truncated peptides with TLR's was performed using Cluspro 2.0. Docked complexes were analyzed using Swiss-PDB Viewer. Nine peptides of Rv0679c protein assessed were able to bind to TLR2-1 and TLR 4-MD2; however the binding energy was better with TLR 4-MD2. Peptide 30985 (-866.4 kcal/mol) has better binding energy with TLR2-1, in contrast peptide 30982 showed a better binding energy to TLR 4-MD2 dimer with a score of -1291.7 kcal/mol. Interactive residue analysis revealed that GLU 173 and SER 454 of TLR 1; ARG 447 and ARG 486 of TLR2; ARG 264 of TLR 4 and SER 120, LYS 122 and GLU 92 of MD2 region are predominant residues interacting with peptides of Rv0679c protein. Our study suggests that predominant residues and receptors of TLR2 and TLR4 are important for Rv0679c protein binding, which could further lead to invasion of M. tb into the host cell.

SUBMITTER: Lavarti R

PROVIDER: S-EPMC5295044 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Insights from the analysis of predicted Rv0679c protein peptide from Mycobacterium tuberculosis with Toll like Receptors in host.

Lavarti Rupa R Ganugapati Jayasree J Ratcha Shirisa S Rao Lakshmana Ss LS SivaSai Krovvidi Sr KS

Bioinformation 20160815 5

Peptides of Rv0679c a membrane protein of the cell envelope (16.6 KDa) of Mycobacterium tuberculosis (M. tb), inhibited entry of live bacilli into epithelial (A549) and macrophage (U937) cell lines in vitro, suggesting a possible role in invasion. Receptors associated with Rv0679c antigen entry into cell lines were not characterized. We are reporting that Rv0679c peptides could bind to Toll like receptors (TLRs), the principal class of pathogen recognition receptors on host cells (PRR) by dockin ...[more]

PMID: 28246463

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Project description:Combating the spread of drug resistant tuberculosis is a global health priority. Whole genome association studies are being applied to identify genetic determinants of resistance to anti-tuberculosis drugs. Protein structure and interaction modelling are used to understand the functional effects of putative mutations and provide insight into the molecular mechanisms leading to resistance.To investigate the potential utility of these approaches, we analysed the genomes of 144 Mycobacterium tuberculosis clinical isolates from The Special Programme for Research and Training in Tropical Diseases (TDR) collection sourced from 20 countries in four continents. A genome-wide approach was applied to 127 isolates to identify polymorphisms associated with minimum inhibitory concentrations for first-line anti-tuberculosis drugs. In addition, the effect of identified candidate mutations on protein stability and interactions was assessed quantitatively with well-established computational methods.The analysis revealed that mutations in the genes rpoB (rifampicin), katG (isoniazid), inhA-promoter (isoniazid), rpsL (streptomycin) and embB (ethambutol) were responsible for the majority of resistance observed. A subset of the mutations identified in rpoB and katG were predicted to affect protein stability. Further, a strong direct correlation was observed between the minimum inhibitory concentration values and the distance of the mutated residues in the three-dimensional structures of rpoB and katG to their respective drugs binding sites.Using the TDR resource, we demonstrate the usefulness of whole genome association and convergent evolution approaches to detect known and potentially novel mutations associated with drug resistance. Further, protein structural modelling could provide a means of predicting the impact of polymorphisms on drug efficacy in the absence of phenotypic data. These approaches could ultimately lead to novel resistance mutations to improve the design of tuberculosis control measures, such as diagnostics, and inform patient management.

Dataset Information

Insights from the analysis of predicted Rv0679c protein peptide from Mycobacterium tuberculosis with Toll like Receptors in host.

Publications

Insights from the analysis of predicted Rv0679c protein peptide from Mycobacterium tuberculosis with Toll like Receptors in host.

Similar Datasets

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