@article{770aa4dc0e824e1dbdb33bcb40763ba6,
title = "PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation",
keywords = "AGONY, ASSAY INTERFERENCE COMPOUNDS, ECSTASY, PAINS, aggregators, frequent hitters, in silico prediction, in vitro screening, machine learning, molecular similarity, promiscuous compounds, rule-based approaches, statistical methods",
author = "Conrad Stork and Johannes Kirchmair",
note = "Funding Information: This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - project number KI 2085/1– 1. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.",
year = "2018",
month = jul,
day = "29",
doi = "10.4155/fmc-2018-0116",
language = "English",
volume = "10",
pages = "1533--1535",
journal = "Future Medicinal Chemistry",
issn = "1756-8919",
number = "13",
}