title: Identification of proteins associated with Mycobacterium tuberculosis virulence pathway by their polar profile.
abstract: With almost one third of the world population infected, tuberculosis is one of the most devastating diseases worldwide and it is a major threat to any healthcare system. With the mathematical-computational method named "Polarity Index Method", already published by this group, we identified, with high accuracy (70%), proteins related to Mycobacterium tuberculosis bacteria virulence pathway from the Tuberculist Database. The test considered the totality of proteins cataloged in the main domains: fungi, bacteria, and viruses from three databases: Antimicrobial Peptide Database (APD2), Tuberculist Database, Uniprot Database, and four antigens of Mycobacterium tuberculosis: PstS-1, 38-kDa, 19-kDa, and H37Rv ORF. The method described was calibrated with each database to achieve the same performance, showing a high percentage of coincidence in the identification of proteins associated with Mycobacterium tuberculosis bacteria virulence pathway located in the Tuberculist Database, and identifying a polar pattern regardless of the group studied. This method has already been used in the identification of diverse groups of proteins and peptides, showing that it is an effective discriminant. Its metric considers only one physico-chemical property, i.e. polarity.
authors.affiliation: Departamento de Matemáticas, Facultad de Ciencias, Universidad Nacional Autónoma de México, C.P. 04510 D.F., México.
authors.forename: Carlos
authors.initials: C
authors.lastname: Polanco
authors.affiliation: Unidad de Cuidados intensivos y Unidad de Investigación Biomédica. Hospital Juárez de México, C.P. 07760 D.F., México.
authors.forename: Jorge Alberto
authors.initials: JA
authors.lastname: Castañón-González
authors.affiliation: Departamento de Inmunologia, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, C.P. 04510 D.F., México.
authors.forename: Raul
authors.initials: R
authors.lastname: Mancilla
authors.affiliation: Centro de Investigaciones Químicas, Universidad Autónoma del Estado de Morelos, C.P. 62209 Chamilpa, Cuernavaca, Morelos, México.
authors.forename: Thomas
authors.initials: T
authors.lastname: Buhse
authors.affiliation: Departamento de Matemáticas, Facultad de Ciencias, Universidad Nacional Autónoma de México, C.P. 04510 D.F., México; and Facultad de Ciencias de la Salud, Universidad Anahuac. C.P. 52786 Huixquilucan Estado de Mexico, México.
authors.forename: José Lino
authors.initials: JL
authors.lastname: Samaniego
authors.affiliation: Facultad de Ciencias de la Salud, Universidad Anahuac. C.P. 52786 Huixquilucan Estado de Mexico, México.
authors.forename: Arturo
authors.initials: A
authors.lastname: Gimbel
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000942:Antigens, Bacterial / Q000032:analysis / Q000378:metabolism; D001426:Bacterial Proteins / Q000032:analysis* / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D008969:Molecular Sequence Data; D009169:Mycobacterium tuberculosis / Q000378:metabolism / Q000472:pathogenicity*; D040901:Proteomics / Q000379:methods*
chemical_list: D000942:Antigens, Bacterial; D001426:Bacterial Proteins