Bridging the gap between target-based and cell-based drug discovery with a graph generative multi-task model. (arXiv:2208.04944v1 [q-bio.QM])

Drug discovery is vitally important for protecting human against disease.
Target-based screening is one of the most popular methods to develop new drugs
in the past several decades. This method efficiently screens candidate drugs
inhibiting target protein in vitro, but it often fails due to inadequate
activity of the selected drugs in vivo. Accurate computational methods are
needed to bridge this gap. Here, we propose a novel graph multi task deep
learning model to identify compounds carrying both target inhibitory …

arxiv bio discovery drug discovery gap graph