Abstract
BackgroundDevelopment 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.ResultsIn 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.ConclusionsGiven 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’.
Highlights
Development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field
Following the lines defined by previous studies [19], we developed an algorithm to score and rank potential drug targets in pathogenic organisms by evaluating a modular set of criteria that are commonplace in antimicrobialdevelopment efforts [7]: 1) the presence of the protein in different pathogens, 2) evolutionary conservation, 3) essentiality, 4) presence of isoforms and paralogs in the proteome, 5) similarity to human proteins
We have developed a database and web-based tool for the ranking of proteins from a set of user-selected bacterial proteomes according to a series of antibacterial-drugtarget-like properties
Summary
Development of novel antibacterial drugs is both an urgent healthcare necessity and a partially neglected field. 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. Since their initial discovery and application during the early 20th century, antibiotics have been playing a key role in public health worldwide. These ‘miracle drugs’ have contributed significantly to the increase in life expectancy since the end of World War II. Cases of resistance for these new Gram-positive antibiotics have been reported recently as well [9]
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