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

Abstract

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.

Bond-based global and local (bond, group and bond-type) quadratic indices and their applications to computer-aided molecular design. 1. QSPR studies of diverse sets of organic chemicals

“…An m · m matrix with nonnegative entries having this property is called a ''stochastic matrix'' [31]. Recently, some authors have introduced stochastic approach to atomic relationships for derived new MDs [15,16,[32][33][34][35][36].…”

Atom-based stochastic and non-stochastic 3D-chiral bilinear indices and their applications to central chirality codification

“…The atom-based molecular vector (x) used to represent smallto-medium size organic chemicals has been explained elsewhere in some detail [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42]44]. The components (x) ofx are numerical values, which represent a certain standard atomic property (atom label).…”

“…This method codifies the molecular structure by means of mathematical quadratic, linear and bilinear transformations. In order to calculate these algebraic maps for a molecule, the atom-based molecular vector,x (vector representation) and kth ''non-stochastic and stochastic graph-theoretical electronic-density matrices'', M k and S k correspondingly (matrix representations), are constructed [26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42]44]. Such atom-adjacency relationships and chemicalinformation codification will be applied in the present report to generate a series of atom-based MDs, atom, group and atomtype as well as total bilinear indices, to be used in drug design and chemoinformatic studies.…”

“…These MDs are based on the calculation of quadratic and linear maps similar to those defined in linear algebra [30]. Our research team has focused its efforts mainly on their application in drug design, so that many new drug(lead)-like compounds within different pharmacological skills have been found out [31][32][33][34][35][36][37]. This approach has been successfully applied to the prediction of several physicochemical and pharmacokinetical properties of organic compounds [27,[38][39][40][41][42].…”

Multi-target spectral moments for QSAR and Complex Networks study of antibacterial drugs

“…See for instance the works of Roy et al [4][5][6][7][8][9] using QSAR like predictive tools in this sense. Especially, QSAR models have been successfully applied to predict antibacterial drugs [10][11][12][13]. Unfortunately almost all QSAR models predict the biological activity of drugs against only one bacteria species; which means that they are one-target QSAR models (ot-QSAR).…”