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Mime Kobayashi

dblp:69/2242 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › molecular informatics › cheminformatics
quantitative structure-activity relationship
0.012003
Molecular evaluation using in silico protein interaction profiles · Bioinform. 2003

Methods — techniques the papers use, named apart from their topics

molecular docking · 0.0clustering · 0.0
YearPublicationVenuePosition
2003 Molecular evaluation using in silico protein interaction profiles
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.
Yoshiharu Hayashi, Katsuyoshi Sakaguchi, Mime Kobayashi, Masaki Kobayashi, Yo Kikuchi, Eiichiro Ichiishi
Bioinform.3