The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform

Characterizing the kinome selectivity profiles of kinase inhibitors is essential in the early stages of novel small-molecule drug discovery. This characterization is critical for interpreting potential adverse events caused by off-target polypharmacology effects and provides unique pharmacological i...

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Bibliographic Details
Main Author:	Wei Ma (299083) (author)
Other Authors:	Jiaqi Hu (1425412) (author), Zhuangzhi Chen (19739768) (author), Yaoqin Ai (19739771) (author), Yihang Zhang (6568571) (author), Keke Dong (3705337) (author), Xiangfei Meng (160218) (author), Liu Liu (512237) (author)
Published:	2024
Subjects:	Biochemistry Genetics Pharmacology Biotechnology Cancer Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified wide polypharmacology effects target polypharmacology effects subsequent machine learning molecule drug discovery internal compound collections also performs well whole kinome selectivity kinome selectivity profiles training data sets practical application scenarios model allows users drug repurposing development data sets 191 well systematically cleaning successfully identified still time small molecules similar models significantly improving quickly fine priori testing novel structures novel strategy novel small experimental profiling early stages com ).
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The Development and Application of KinomePro-DL: A Deep Learning Based Online Small Molecule Kinome Selectivity Profiling Prediction Platform

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