Non-Stochastic and Stochastic Linear Indices on the Molecular Pseudograph's Atom Adjacency Matrix: A Novel Approach for Computational in silico Screening and "Rational" Selection of New Lead Antibacterial Agents

Y. MARRERO PONCE; R. MEDINA MARRERO; Y. MARTÍNEZ; F. MARTÍNEZ; V. ROMERO ZALDÍVAR; E.A. CASTRO

J.Mol.Model

Año: 2006 vol. 12 p. 255 - 271

            A novel approach (TOMOCOMD-CARDD)to computer-aided “rational” design is illustrated. This approach is based on the calculation of the non-stochastic and stochastic linear indices of the molecular pseudograph’s atom adjacency matrix representing molecular structures. These TOMOCOMD-CARDD descriptors are introduced for the computational (virtual) screening and “rational” selection of new lead antibacterial agents using linear discrimination analysis. Both structure-based antibacterial activity classification models, including non-stochastic indices, classify correctly 91.61% and 90.75%, respectively, of 1525 chemicals in training sets. These models show high Matthews correlation coefficients (MCC = 0.84 and MCC = 0.82). External validation process was carried out to assess the robustness and predictive power of the obtained model. These QSAR  models permit the correct classification of 91.49% and 89.31% of 505 compounds in an external test set, yielding a MCC of 0.84 and 0.79, correspondingly. The TOMOCOMD-CARDD approach satisfactorily compares with respect to nine of the most useful models for antimicrobial selection reported to date. Finally, an in silico screening of 87 new chemicals reported in the anti-infective field with antibacterial activities is developed showing the ability of the TOMOCOMD-CARDD models to identify new lead antibacterial compounds.