title: Identification and characterization of potential therapeutic candidates in emerging human pathogen Mycobacterium abscessus: a novel hierarchical in silico approach.
abstract: Mycobacterium abscessus, a non-tuberculous rapidly growing mycobacterium, is recognized as an emerging human pathogen causing a variety of infections ranging from skin and soft tissue infections to severe pulmonary infections. Lack of an optimal treatment regimen and emergence of multi-drug resistance in clinical isolates necessitate the development of better/new drugs against this pathogen. The present study aims at identification and qualitative characterization of promising drug targets in M. abscessus using a novel hierarchical in silico approach, encompassing three phases of analyses. In phase I, five sets of proteins were mined through chokepoint, plasmid, pathway, virulence factors, and resistance genes and protein network analysis. These were filtered in phase II, in order to find out promising drug target candidates through subtractive channel of analysis. The analysis resulted in 40 therapeutic candidates which are likely to be essential for the survival of the pathogen and non-homologous to host, human anti-targets, and gut flora. Many of the identified targets were found to be involved in different metabolisms (viz., amino acid, energy, carbohydrate, fatty acid, and nucleotide), xenobiotics degradation, and bacterial pathogenicity. Finally, in phase III, the candidate targets were qualitatively characterized through cellular localization, broad spectrum, interactome, functionality, and druggability analysis. The study explained their subcellular location identifying drug/vaccine targets, possibility of being broad spectrum target candidate, functional association with metabolically interacting proteins, cellular function (if hypothetical), and finally, druggable property. Outcome of the present study could facilitate the identification of novel antibacterial agents for better treatment of M. abscesses infections.
authors.affiliation: Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Pondicherry, India.
authors.forename: Buvaneswari
authors.initials: B
authors.lastname: Shanmugham
authors.forename: Archana
authors.initials: A
authors.lastname: Pan
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology; D021821:Communicable Diseases, Emerging / Q000188:drug therapy; D003198:Computer Simulation; D057225:Data Mining; D030541:Databases, Genetic; D055808:Drug Discovery; D006801:Humans; D009165:Mycobacterium Infections, Nontuberculous / Q000188:drug therapy; D009170:Nontuberculous Mycobacteria / Q000187:drug effects / Q000502:physiology
chemical_list: D000900:Anti-Bacterial Agents