title: UniDrug-target: a computational tool to identify unique drug targets in pathogenic bacteria.
abstract: BACKGROUND
  Targeting 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.
  
  
  METHODS
  A 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.
  
  
  RESULTS
  The 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
  UniDrug-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.
authors.affiliation: Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India.
authors.forename: Sree Krishna
authors.initials: SK
authors.lastname: Chanumolu
authors.forename: Chittaranjan
authors.initials: C
authors.lastname: Rout
authors.forename: Rajinder S
authors.initials: RS
authors.lastname: Chauhan
mesh_terms: D000596:Amino Acids / Q000378:metabolism; D001419:Bacteria / Q000378:metabolism*; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors* / Q000737:chemistry; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D016503:Drug Delivery Systems / Q000379:methods*; D006801:Humans; D020407:Internet; D053858:Metabolic Networks and Pathways; D008958:Models, Molecular; D009169:Mycobacterium tuberculosis / Q000378:metabolism; D017434:Protein Structure, Tertiary
chemical_list: D000596:Amino Acids; D001426:Bacterial Proteins