Molecular evaluation using in silico protein interaction profiles

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 mole...

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Veröffentlicht in:Bioinformatics 2003-08, Vol.19 (12), p.1514-1523
Hauptverfasser: HAYASHI, Yosninaru, SAKAGUCHI, Katsuyoshi, KOBAYASHI, Mime, KOBAYASHI, Masaki, KIKUCHI, Yo, ICHIISHI, Eiichiro
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container_end_page 1523
container_issue 12
container_start_page 1514
container_title Bioinformatics
container_volume 19
creator HAYASHI, Yosninaru
SAKAGUCHI, Katsuyoshi
KOBAYASHI, Mime
KOBAYASHI, Masaki
KIKUCHI, Yo
ICHIISHI, Eiichiro
description 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. 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.
doi_str_mv 10.1093/bioinformatics/btg189
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source MEDLINE; Access via Oxford University Press (Open Access Collection); Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection
subjects Algorithms
Binding Sites
Biological and medical sciences
Computer Simulation
Energy Transfer
Fundamental and applied biological sciences. Psychology
General aspects
Macromolecular Substances
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Chemical
Models, Molecular
Protein Array Analysis - methods
Protein Binding
Protein Interaction Mapping - methods
Proteins - chemistry
Proteins - classification
Quantitative Structure-Activity Relationship
title Molecular evaluation using in silico protein interaction profiles
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