A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
PaccMann^RL on SARS-CoV-2: Designing antiviral candidates with conditional generative models
[article]
2020
arXiv
pre-print
With the fast development of COVID-19 into a global pandemic, scientists around the globe are desperately searching for effective antiviral therapeutic agents. Bridging systems biology and drug discovery, we propose a deep learning framework for conditional de novo design of antiviral candidate drugs tailored against given protein targets. First, we train a multimodal ligand--protein binding affinity model on predicting affinities of antiviral compounds to target proteins and couple this model
arXiv:2005.13285v3
fatcat:w7i7zarvdbfalgrymwisa3gspe