UniDrug-Target: A Computational Tool to Identify Unique Drug Targets in Pathogenic Bacteria

Abstract

BackgroundTargeting conserved proteins of bacteria through antibacterial medications has resulted in both the development of resistant strains and changes to human health by destroying beneficial microbes which eventually become breeding grounds for the evolution of resistances. Despite the availability of more than 800 genomes sequences, 430 pathways, 4743 enzymes, 9257 metabolic reactions and protein (three-dimensional) 3D structures in bacteria, no pathogen-specific computational drug target identification tool has been developed.MethodsA web server, UniDrug-Target, which combines bacterial biological information and computational methods to stringently identify pathogen-specific proteins as drug targets, has been designed. Besides predicting pathogen-specific proteins essentiality, chokepoint property, etc., three new algorithms were developed and implemented by using protein sequences, domains, structures, and metabolic reactions for construction of partial metabolic networks (PMNs), determination of conservation in critical residues, and variation analysis of residues forming similar cavities in proteins sequences. First, PMNs are constructed to determine the extent of disturbances in metabolite production by targeting a protein as drug target. Conservation of pathogen-specific protein's critical residues involved in cavity formation and biological function determined at domain-level with low-matching sequences. Last, variation analysis of residues forming similar cavities in proteins sequences from pathogenic versus non-pathogenic bacteria and humans is performed.ResultsThe server is capable of predicting drug targets for any sequenced pathogenic bacteria having fasta sequences and annotated information. The utility of UniDrug-Target server was demonstrated for Mycobacterium tuberculosis (H37Rv). The UniDrug-Target identified 265 mycobacteria pathogen-specific proteins, including 17 essential proteins which can be potential drug targets.Conclusions/SignificanceUniDrug-Target is expected to accelerate pathogen-specific drug targets identification which will increase their success and durability as drugs developed against them have less chance to develop resistances and adverse impact on environment. The server is freely available at http://117.211.115.67/UDT/main.html. The standalone application (source codes) is available at http://www.bioinformatics.org/ftp/pub/bioinfojuit/UDT.rar.

Whole-genome sequencing and identification of Morganella morganii KT pathogenicity-related genes

“…The pathogenicity genes allows usage of computation approaches to identify potential drug targets such as the conserved proteins found in common pathogens[90]. T3SSs is highly conserved in many disease-causing gram-negative pathogens and hence has been used as an alternative strategy for drug target design [90,91]. The efflux pumps which help to get rid of toxic substances also promote biofilms, thus making them attractive targets for antibiofilm measure [92,93].…”

Drug Resistance in Bacteria, Fungi, Malaria, and Cancer

“…A ranking system for the potential drug targets is developed based on the order of their functional importance for cell survival (Chanumolu et al 2012). The server finds unique proteins of pathogenic bacteria by comparing the proteomes of pathogenic and nonpathogenic bacteria and the mammalian proteomes.…”

“…Popular examples of this method include INVDOCK (Chanumolu et al 2012) and TarFisDock . Popular examples of this method include INVDOCK (Chanumolu et al 2012) and TarFisDock .…”

Computational Methods to Identify New Antibacterial Targets

“…INVDOCK-automated detection of protein and nucleic acid targets by inverse docking INVDOCK (24) has been developed by the Bioinformatics and Drug Design group (BIDD) at the National University of Singapore for the computer-automated identification of potential protein and nucleic acid targets of drugs, newly designed drug candidate, natural product, or other chemical compound. In addition to suggesting likely therapeutic targets of a query molecule, INVDOCK can also predict potential toxicity due to off-target effects (25).…”

“…The web server UniDrug-Target (24) has been specifically designed to combine bacterial biological information and computational methods to stringently identify bacterial pathogen-specific proteins as drug targets. The server compares the proteome sequences of pathogenic and non-pathogenic bacteria, and mammalian proteomes, to identify unique proteins present in pathogenic bacteria.…”