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Virtual generation of agents against Mycobacterium tuberculosis. A QSAR study
Emili Besalú1, Robert Ponec, Jesus Vicente de Julián-Ortiz
1Institute of Computational Chemistry, Universitat de Girona, Facultat de Ciències, Avda. Montilivi s/n, Girona, Spain. emili@iqc.udg.es
Abstract:
A QSAR approach based on the use of various topological indices as new theoretical molecular descriptors was applied to the study of a set of 64 anti-tuberculosis agents involving the substituted benzoxazines and phenylquinazolines. In order to evaluate the reliability of the proposed linear QSAR model, several statistical tests were proposed. The resulting model was subsequently applied to a wider virtual molecular library, which, together with the original set of 64 molecules with known activities contained another 512 molecules for which the predictions were made. Based on this prediction some new structures were proposed as especially promising candidates for active anti-tuberculotic drugs.