Comparison of Quantitative and Qualitative (Q)SAR Models Created for the Prediction of K_i and IC₅₀ Values of Antitarget Inhibitors.

ABSTRACT: Estimation of interaction of drug-like compounds with antitargets is important for the assessment of possible toxic effects during drug development. Publicly available online databases provide data on the experimental results of chemical interactions with antitargets, which can be used for the creation of (Q)SAR models. The structures and experimental K_i and IC₅₀ values for compounds tested on the inhibition of 30 antitargets from the ChEMBL 20 database were used. Data sets with K_i and IC₅₀ values including more than 100 compounds were created for each antitarget. The (Q)SAR models were created by GUSAR software using quantitative neighborhoods of atoms (QNA), multilevel neighborhoods of atoms (MNA) descriptors, and self-consistent regression. Th

SUBMITTER: Lagunin AA 

PROVIDER: S-EPMC6192375 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature