Profiling Prediction of Kinase Inhibitors: Toward the Virtual Assay.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of medicinal chemistry"
DOI: 10.1021/acs.jmedchem.6b01611
Abstract: Kinome-wide screening would have the advantage of providing structure-activity relationships against hundreds of targets simultaneously. Here, we report the generation of ligand-based activity prediction models for over 280 kinases by employing Machine Learning methods on… read more here.
Keywords: kinase inhibitors; kinase; inhibitors toward; profiling prediction ... See more keywords
Profiling prediction of nuclear receptor modulators with multi-task deep learning methods: toward the virtual screening
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac351
Abstract: Nuclear receptors (NRs) are ligand-activated transcription factors, which constitute one of the most important targets for drug discovery. Current computational strategies mainly focus on a single target, and the transfer of learned knowledge among NRs… read more here.
Keywords: virtual screening; profiling prediction; task; multi task ... See more keywords