Computational chemists typically assay drug candidates by virtually screening compounds against crystal structures of a protein despite the fact that some targets, like the μ Opioid Receptor and other members of the GPCR family, traverse many non-crystallographic states. We discover new conformational states of μOR with molecular dynamics simulation and then machine learn ligand-structure relationships to predict opioid ligand function. These artificial intelligence models identified a novel μ opioid chemotype.
@article{arxiv.1803.04479,
title = {Machine Learning Harnesses Molecular Dynamics to Discover New $\mu$ Opioid Chemotypes},
author = {Evan N. Feinberg and Amir Barati Farimani and Rajendra Uprety and Amanda Hunkele and Gavril W. Pasternak and Susruta Majumdar and Vijay S. Pande},
journal= {arXiv preprint arXiv:1803.04479},
year = {2018}
}