Prediction of Thrombin and Factor Xa Inhibitory Activity with Associative Neural Networks

Title:Prediction of Thrombin and Factor Xa Inhibitory Activity with Associative Neural Networks

Volume: 10 Issue: 3

Author(s): Vasyl Kovalishyn, Vsevolod Tanchuk, Iryna Kopernyk, Volodymyr Prokopenko and Larysa Metelytsia

Affiliation:

Keywords: Drug design, factor Xa, QSAR, Neural Networks, thrombin.

Abstract: Quantitative structure-activity relationship studies on a series of selective inhibitors of thrombin and factor Xa were performed by using Associative Neural Network. To overcome the problem of overfitting due to descriptor selection, 5-fold cross-validation with variable selection in each step of the analysis was performed. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q²=0.74 - 0.87 for regression models. Predictions for the external evaluation sets obtained accuracies in the range of 0.71 - 0.82 for regressions. The proposed models can be potential tools for finding new drug candidates.

Cite this article as:

Kovalishyn Vasyl, Tanchuk Vsevolod, Kopernyk Iryna, Prokopenko Volodymyr and Metelytsia Larysa, Prediction of Thrombin and Factor Xa Inhibitory Activity with Associative Neural Networks, Current Computer-Aided Drug Design 2014; 10 (3) . https://dx.doi.org/10.2174/157340991003150302231419