Identification and characterization of potential membrane-bound molecular drug targets of methicillin-resistant Staphylococcus aureus using in silico approaches

Aim. To identify novel putative drug targets of methicillin-resistant S. aureus (MRSA) through subtractive proteome analysis. Methods. Identification of non-homologous proteins in the human proteome, search of MRSA essential genes and evaluation of drug target novelty were performed using a protein BLAST server. Unique metabolic pathways identification was carried out using data and tools from KEGG (Kyoto Encyclopedia of Genes and Genomes). Prediction of sub-cellular proteins localization was performed using combination of PSORT v. 3.0.2, CELLO v. 2.5, iLoc-Gpos, and Pred-Lipo tools. Homology modeling was performed using SWISS-MODEL, Phyre2, I-TASSER web-servers and the MODELLER software. Results. Proteomes of six annotated methicillin-resistant strains : MRSA ATCC BAA-1680, H-EMRSA-15, LA MRSA ST398, MRSA 252, MRSA ST772, UTSW MRSA 55 were initially analyzed. The proteome analysis of the MRSA strains in several consequent steps allowed to identify two molecular targets: diadenylate cyclase and D-alanyl-lipoteichoic acid biosynthesis (DltB) protein which meet the requirements of being essential, membrane-bound, non-homologous to human proteome, involved in unique metabolic pathways and new in terms of not having approved drugs. Using the homology modeling approach, we have built three-dimensional structures of these proteins and predicted their ligand-binding sites. Conclusions. We used classical bioinformatics approaches to identify two molecular targets of MRSA :diadenylate cyclase and DltB which can be used for further rational drug design in order to find novel therapeutic agents for treatment of multidrug resistant staphylococcal infection.

• Publication year

  2019

• Venue

  Biopolymers and Cell

• Publication date

  2019-12-31

• Fields of study

  Biology, Medicine, Chemistry

• Identifiers
  DOI 10.7124/bc.000a18
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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