Non-stochastic and stochastic linear indices of the molecular pseudograph's atom-adjacency matrix: a novel approach for computational in silico screening and "rational" selection of new lead antibacterial agents.
A novel approach (TOMOCOMD-CARDD) to computer-aided "rational" drug 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. The two structure-based antibacterial-activity classification models, including non-stochastic and 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 0.82). An external validation process was carried out to assess the robustness and predictive power of the model obtained. These QSAR models permit the correct classification of 91.49% and 89.31% of 505 compounds in an external test set, yielding MCCs of 0.84 and 0.79, respectively. The TOMOCOMD-CARDD approach compares satisfactorily 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.
Marrero-Ponce
Yovani
Y
Department of Pharmacy, Faculty of Chemical-Pharmacy, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba. yovanimp@qf.uclv.edu.cu
Marrero
Ricardo Medina
RM
Torrens
Francisco
F
Martinez
Yamile
Y
Bernal
Milagros García
MG
Zaldivar
Vicente Romero
VR
Castro
Eduardo A
EA
Abalo
Ricardo Grau
RG
D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000737:chemistry* / Q000145:classification / Q000494:pharmacology*; D019295:Computational Biology; D003198:Computer Simulation; D015195:Drug Design; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D015394:Molecular Structure; D013269:Stochastic Processes
D000900:Anti-Bacterial Agents