The Multilevel Adaptive Description of Molecular Graphs in “Structure Property Problem”
Proposed and developed a method for solving the “structure property” problem, which is based on an adaptive choice of the description of molecules and the automatic selection of feature space in accordance with the characteristics of the training sample. Solved the problem of combinatorial explosion using Group Method of Data Handling. Used the clustering of objects in the training set to improve the predictive ability of the model.
A new approach for analyzing the “molecule–descriptor” matrix for the QSAR problem (Quantitative Structure–Activity Relationship) based on a fuzzy cluster structure of the learning sample is presented. The ways for generating fast rules for refusing prediction and searching the spikes in the learning sample are described. For this purpose, a special space of descriptors, simple for calculation, is introduced. The ways for optimizing the discriminant function according to fuzzy clustering parameters are examined. Highly predictive models based on the presented approach have been generated. The models are compared, and the efficiency of the described methods is revealed.
3D-QSAR and molecular docking were applied to predict inhibitory activity of 196 compounds towards poly-(ADP-riboso)-polymerase-1 (PARP). Proportion of experimentally active ligands was higher among compounds with good rankings from both methods (57%) compared to compounds scored as inactive by at least one method (40% for docking-active, QSAR-inactive compounds).
The solution of the "structure-property" based on the molecular graphs descriptorsselection with k-NN classifier is proposed. The results of comparing the construction ofpredictive models using the search and without it are given. The high stability of the classifier function construction quality is tested using the real sample of the molecular structures.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.