title: In silico discovery and virtual screening of multi-target inhibitors for proteins in Mycobacterium tuberculosis.
abstract: Mycobacterium tuberculosis (MTB) is the principal pathogen which causes tuberculosis (TB), a disease that remains as one of the most alarming health problems worldwide. An active area for the search of new anti-TB therapies is concerned with the use of computational approaches based on Chemoinformatics and/or Bioinformatics toward the discovery of new and potent anti-TB agents. These approaches consider only small series of structurally related compounds and the studies are generally realized for only one target like a protein. This fact constitutes an important limitation. The present work is an effort to overcome this problem. We introduce here the first chemo-bioinformatic approach by developing a multi-target (mt) QSAR discriminant model, for the in silico design and virtual screening of anti-TB agents against six proteins in MTB. The mt-QSAR model was developed by employing a large and heterogeneous database of compounds and substructural descriptors. The model correctly classified more than 90% of active and inactive compounds in both, training and prediction series. Some fragments were extracted from the molecules and their contributions to anti-TB activity through inhibition of the six proteins, were calculated. Several fragments were identified as responsible for anti-TB activity and new molecular entities were designed from those fragments with positive contributions, being suggested as possible anti-TB agents.
authors.affiliation: REQUIMTE/Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal. alejspivanovich@gmail.com
authors.forename: Alejandro
authors.initials: A
authors.lastname: Speck-Planche
authors.forename: Valeria V
authors.initials: VV
authors.lastname: Kleandrova
authors.forename: Feng
authors.initials: F
authors.lastname: Luan
authors.forename: M Natália D S
authors.initials: MN
authors.lastname: Cordeiro
mesh_terms: D000995:Antitubercular Agents / Q000737:chemistry* / Q000494:pharmacology*; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors* / Q000378:metabolism; D019295:Computational Biology; D016002:Discriminant Analysis; D015195:Drug Design; D006801:Humans; D009169:Mycobacterium tuberculosis / Q000187:drug effects* / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D014376:Tuberculosis / Q000188:drug therapy / Q000382:microbiology
chemical_list: D000995:Antitubercular Agents; D001426:Bacterial Proteins