title: A Structure-Activity Relationship Study of Naphthoquinone Derivatives as Antitubercular Agents Using Molecular Modeling Techniques.
abstract: Tuberculosis (TB) is one of the major causes of death worldwide. Mycobacterium tuberculosis, the leading causative agent of TB, is responsible for the morbidity and mortality of a large population worldwide. In view of above and as a part of our effort to develop new and potent anti-TB agents, a series of substituted naphthoquinone derivatives were subjected to molecular modeling using various feature selection methods. The statistically significant best 2D-QSAR model having correlation coefficient [Formula: see text] and cross-validated squared correlation coefficient [Formula: see text] with external predictive ability of [Formula: see text] was developed by SA-PLS, and group-based QSAR model having [Formula: see text] and [Formula: see text] with [Formula: see text] was developed by SA-PLS. Further analysis using three-dimensional QSAR technique identifies a suitable model obtained by SA-partial least square method leading to antitubercular activity prediction. k-nearest neighbor molecular field analysis was used to construct the best 3D-QSAR model using SA-PLS method, showing good correlative and predictive capabilities in terms of [Formula: see text] and [Formula: see text]. The pharmacophore analysis results obtained from this study show that the distance between the aromatic/hydrophobic and the naphthoquinone moiety sites to the aliphatic and acceptor groups should be connected with almost the same distance for significant antitubercular activity. The information rendered by QSAR models may lead to a better understanding of structural requirements of antitubercular activity and also can help in the design of novel potent antitubercular activity.
authors.affiliation: Drug Research Laboratory, School of Pharmacy, Devi Ahilya University, Takshila Campus, Khandwa Road, Indore, 452 001, India. mukeshcsharma@yahoo.com.
authors.forename: Mukesh C
authors.initials: MC
authors.lastname: Sharma
mesh_terms: D000465:Algorithms; D000995:Antitubercular Agents / Q000737:chemistry* / Q000494:pharmacology*; D015195:Drug Design; D008958:Models, Molecular; D009169:Mycobacterium tuberculosis / Q000187:drug effects; D009285:Naphthoquinones / Q000737:chemistry* / Q000494:pharmacology*; D021281:Quantitative Structure-Activity Relationship
chemical_list: D000995:Antitubercular Agents; D009285:Naphthoquinones
keywords: Antitubercular agents; Mycobacterium tuberculosis; Naphthoquinone; PLS; QSAR; k-nearest neighbor