Web of Science: 8 cites, Scopus: 8 cites, Google Scholar: cites,
antibacTR : dynamic antibacterial-drug-target ranking integrating comparative genomics, structural analysis and experimental annotation
Panjkovich, Alejandro (Universitat Autònoma de Barcelona. Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Gibert, Isidre (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)
Daura i Ribera, Xavier (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)

Data: 2014
Resum: Background : development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field. The last decades have seen a substantial decrease in the discovery of novel antibiotics, which combined with the recent thrive of multi-drug-resistant pathogens have generated a scenario of general concern. The procedures involved in the discovery and development of novel antibiotics are economically challenging, time consuming and lack any warranty of success. Furthermore, the return-on-investment for an antibacterial drug is usually marginal when compared to other therapeutics, which in part explains the decrease of private investment. - Results : in this work we present antibacTR, a computational pipeline designed to aid researchers in the selection of potential drug targets, one of the initial steps in antibacterial-drug discovery. The approach was designed and implemented as part of two publicly funded initiatives aimed at discovering novel antibacterial targets, mechanisms and drugs for a priority list of Gram-negative pathogens: Acinetobacter baumannii, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. However, at present this list has been extended to cover a total of 74 fully sequenced Gram-negative pathogens. antibacTR is based on sequence comparisons and queries to multiple databases (e. g. gene essentiality, virulence factors) to rank proteins according to their potential as antibacterial targets. The dynamic ranking of potential drug targets can easily be executed, customized and accessed by the user through a web interface which also integrates computational analyses performed in-house and visualizable on-site. These include three-dimensional modeling of protein structures and prediction of active sites among other functionally relevant ligand-binding sites. - Conclusions : given its versatility and ease-of-use at integrating both experimental annotation and computational analyses, antibacTR may effectively assist microbiologists, medicinal-chemists and other researchers working in the field of antibacterial drug-discovery. The public web-interface for antibacTR is available at 'http://bioinf. uab. cat/antibactr'.
Ajuts: European Commission 223101
Ministerio de Ciencia e Innovación BFU2010-17199
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Antibacterial-drug target ; Gram-negative bacteria ; Target druggability
Publicat a: PloS one, Vol. 15, No. 36 (2014) , ISSN 1932-6203

DOI: 10.1186/1471-2164-15-36
PMID: 24438389


10 p, 929.1 KB

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Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències de la salut i biociències > Institut de Biotecnologia i de Biomedicina (IBB)
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 Registre creat el 2016-05-23, darrera modificació el 2022-03-26



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