Open Access<p>Developing a Kinase-Specific Target Selection Method Using a Structure-Based Machine Learning Approach</p>
Author(s) -
Arina Afanasyeva,
Chioko Nagao,
Kenji Mizuguchi
Publication year - 2020
Publication title -
advances and applications in bioinformatics and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.223
H-Index - 15
ISSN - 1178-6949
DOI - 10.2147/aabc.s278900
Subject(s) - kinome , pubchem , computer science , artificial intelligence , machine learning , docking (animal) , computational biology , protein data bank (rcsb pdb) , drug discovery , chembl , kinase , data mining , bioinformatics , chemistry , biology , biochemistry , medicine , nursing
Despite recent advances in the drug discovery field, developing selective kinase inhibitors remains a complicated issue for a number of reasons, one of which is that there are striking structural similarities in the ATP-binding pockets of kinases.