Molecular evaluation using in silico protein interaction profiles.
BACKGROUND
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.
Hayashi
Yoshiharu
Y
Division of Bioinformatics, KLIMERS (K-laboratories for Intelligent Medical Remote Services, Enkaku Iryou-laboratories) Co., Ltd., 2266-22 Anagahora, Shimoshidami, Moriyama-ku, Nagoya 463-0003, Japan. yhayashi@enkaku.co.jp
Sakaguchi
Katsuyoshi
K
Kobayashi
Mime
M
Kobayashi
Masaki
M
Kikuchi
Yo
Y
Ichiishi
Eiichiro
E
D000465:Algorithms; D001665:Binding Sites; D003198:Computer Simulation; D004735:Energy Transfer; D046911:Macromolecular Substances; D008956:Models, Chemical; D008958:Models, Molecular; D040081:Protein Array Analysis / Q000379:methods; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000145:classification*; D021281:Quantitative Structure-Activity Relationship
D046911:Macromolecular Substances; D011506:Proteins