In silico prediction of the β-cyclodextrin complexation based on Monte Carlo method

Aleksandar M. Veselinović, Jovana B. Veselinović, Andrey A. Toropov, Alla P. Toropova, Goran M. Nikolić

Research output: Contribution to journalArticle

Abstract

In this study QSPR models were developed to predict the complexation of structurally diverse compounds with β-cyclodextrin based on SMILES notation optimal descriptors using Monte Carlo method. The predictive potential of the applied approach was tested with three random splits into the sub-training, calibration, test and validation sets and with different statistical methods. Obtained results demonstrate that Monte Carlo method based modeling is a very promising computational method in the QSPR studies for predicting the complexation of structurally diverse compounds with β-cyclodextrin. The SMILES attributes (structural features both local and global), defined as molecular fragments, which are promoters of the increase/decrease of molecular binding constants were identified. These structural features were correlated to the complexation process and their identification helped to improve the understanding for the complexation mechanisms of the host molecules.

Original languageEnglish
Pages (from-to)404-409
Number of pages6
JournalInternational Journal of Pharmaceutics
Volume495
Issue number1
DOIs
Publication statusPublished - Nov 10 2015

Keywords

  • CORAL software
  • Monte Carlo method
  • QSAR/QSPR
  • SMILES
  • β-Cyclodextrin

ASJC Scopus subject areas

  • Pharmaceutical Science

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    Veselinović, A. M., Veselinović, J. B., Toropov, A. A., Toropova, A. P., & Nikolić, G. M. (2015). In silico prediction of the β-cyclodextrin complexation based on Monte Carlo method. International Journal of Pharmaceutics, 495(1), 404-409. https://doi.org/10.1016/j.ijpharm.2015.08.078