Improved QSAR modeling of anti-HIV-1 acivities by means of the optimized correlation weights of local graph invariants

Damián José Gabriel Marino, Eduardo Alberto Castro, Andrey Toropov

Research output: Contribution to journalArticle

Abstract

We report the results derived from the use of molecular descriptors calculated with the correlation weights (CWs) of local graph invariants for modeling of anti-HIV-1 potencies of two groups of reverse transcriptase inhibitors. The presence of different chemical elements in the molecular structure of the inhibitors and the Morgan extended connectivity values of zeroth-, first-, and second order have been examined as local graph invariants in the labeled hydrogen-filled graphs. We have computed via Monte Carlo optimization procedure the values of CWs which produce the largest possible correlation coefficient between the numerical data on the anti-HIV-1 potencies and those values of the descriptors on the training set. The model of the anti-HIV-1 activity obtained with compounds of training set by means of optimization of correlation weights of chemical elements present together with Morgan extended connectivity of first order makes up a sensible model for a satisfactory prediction of the endpoints of the compounds belonging to the test set.

Original languageEnglish
Pages (from-to)135-148
Number of pages14
JournalCentral European Journal of Chemistry
Volume4
Issue number1
DOIs
Publication statusPublished - Mar 2006

Keywords

  • Anti-HIV-1 activity
  • Correlation weight of local graph invariants
  • Flexible topological descriptors
  • QSAR Modeling

ASJC Scopus subject areas

  • Chemistry(all)

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