Abstract
Motivation: To find a correlation between the activities and structures of molecules is one of the most important subjects for molecular evaluation study. Traditional quantitative structure-activity relationship (QSAR) methodologies represent those attempts using physicochemical descriptors. Creating a new molecular description factor based on the results of a computational docking study will add new dimensions to molecular evaluation. Results: We propose a new molecular description factor analysis system called the Comparative Molecular Interaction Profile Analysis (CoMIPA) system in which the AutoDock program is used for docking evaluation of small molecule compound-protein complexes. Interaction energies are calculated, and the data sets obtained are called interaction profiles (IPFs). Using the IPF as a scoring indicator, the system could be a powerful tool to cluster the interacting properties between small molecules and bio macromolecules such as ligand-receptor bindings. Further development of the system will enable us to predict the adverse effects of a drug candidate.
Original language | English |
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Pages (from-to) | 1514-1523 |
Number of pages | 10 |
Journal | Bioinformatics |
Volume | 19 |
Issue number | 12 |
DOIs | |
Publication status | Published - 2003 Aug 12 |
Externally published | Yes |
ASJC Scopus subject areas
- Clinical Biochemistry
- Computer Science Applications
- Computational Theory and Mathematics