AiKPro: deep learning model for kinome-wide bioactivity profiling using structure-based sequence alignments and molecular 3D conformer ensemble descriptors

AiKPro: deep learning model for kinome-wide bioactivity profiling using structure-based sequence alignments and molecular 3D conformer ensemble descriptors

Abstract The discovery of selective and potent kinase inhibitors is crucial for the treatment of various diseases, but the process is challenging due to the high structural similarity among kinases. Efficient kinome-wide bioactivity profiling is essential for understanding kinase function and identi...

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Bibliographic Details
Main Authors: Hyejin Park, Sujeong Hong, Myeonghun Lee, Sungil Kang, Rahul Brahma, Kwang-Hwi Cho, Jae-Min Shin
Format: Article
Language:English
Published: Nature Portfolio 2023-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-37456-8

Internet

https://doi.org/10.1038/s41598-023-37456-8

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