Atom, Atom-Type, and Total Linear Indices of the “Molecular Pseudograph’s Atom Adjacency Matrix”: Application to QSPR/QSAR Studies of Organic Compounds

Abstract

Abstract:In this paper we describe the application in QSPR/QSAR studies of a new group of molecular descriptors: atom, atom-type and total linear indices of the molecular pseudograph's atom adjacency matrix. These novel molecular descriptors were used for the prediction of boiling point and partition coefficient (log P), specific rate constant (log k), and antibacterial activity of 28 alkyl-alcohols and 34 derivatives of 2-furylethylenes, respectively. For this purpose two quantitative models were obtained to describe the alkyl-alcohols' boiling points. The first one includes only two total linear indices and showed a good behavior from a statistical point of view (R 2 = 0.984, s = 3.78, F = 748.57, linear discriminant model for classifying antibacterial activity of these compounds was also achieved with the use of the atom and atom-type linear indices. The global percent of good classification in training and external test set obtained was of 94.12% and 100.0%, respectively. The comparison with other approaches (connectivity indices, total and local spectral moments, quantum chemical descriptors, topographic indices and Estate/biomolecular encounter parameters) reveals a good behavior of our method. The approach described in this paper appears to be a very promising structural invariant, useful for QSPR/QSAR studies and computer-aided "rational" drug design.

Prediction of the permeability of drugs through study on quantitative structure–permeability relationship

“…Through this experience, we have come to have interest in applying the model to a broader exploration of structure-permeability relationships [2]. Quantitative structure-permeability relationships (QSPRs) of the intestinal permeability across Caco-2 cells monolayer have been studied by many researchers [1,3]. The theoretical approach appears to be good to predict the human absorption of new drug candidates obtained by combinatorial chemistry methodologies, avoiding significant failure in late stage of the drug-discovery process.…”

“…The estimation of human oral absorption of new drug candidates in the early stage of the drug discovery process is a useful tool in the lead-compound selection [1]. Several in vitro approaches, based on cell cultures, were used in this area over the last few years.…”

Theoretical Studies on Pyrazole Derivatives as Anti-Breast Cancer Agents: Dft, Qsar and Docking Methods

“…The calculated R 2 is 0.962; which reveal an equitable fitness as well as the efficacy of the model as shown in equation 3. Also, the calculated CV.R 2 was 0.999 {(> 0.5) (standard)} (Ponce et al 2004) and this showed the reliability and acceptability of the model as well as the adjusted R 2 with 0.823 which is greater than 0.6 (standard). Thus, the QSAR model would be predictive.…”

Studies of 2-[5-(Aryloxymethyl)-1, 3, 4-Oxadiazol-2-Ylsulfanyl] Acetic Acid Derivatives for Anti-Bacterial Activities via Dft, Qsar and Docking Approaches

“…The obtained value for fitting factor (R 2 ) (0.998) showed that it fitted well. Also, the cross validation value (CV.R 2 ) (0.998) showed the steadfastness of the developed QSAR model, because the value obtained was higher than 0.5 (Standard) (Ponce et al 2004). More so, the calculated value for adjusted R 2 (0.988) exposed that the QSAR model is prognostic since the calculated value is greater than 0.6 (Standard) ( Table 2).…”