Open AccessStructured data sets of compounds with multi-target and corresponding single-target activity from biological assays
Author(s) -
Christian Feldmann,
Dimitar Yonchev,
Jürgen Bajorath
Publication year - 2021
Publication title -
future science oa
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.825
H-Index - 23
ISSN - 2056-5623
DOI - 10.2144/fsoa-2020-0209
Subject(s) - chemical space , computational biology , drug target , promiscuity , set (abstract data type) , drug discovery , data set , chemistry , computer science , combinatorial chemistry , data mining , biology , biochemistry , artificial intelligence , ecology , programming language
Aim: Providing compound data sets for promiscuity analysis with single-target (ST) and multi-target (MT) activity, taking confirmed inactivity against targets into account. Methodology: Compounds and target annotations are extracted from screening assays. For a given combination of targets, MT and ST compounds are identified, ensuring test data completeness. Exemplary results & data: A total of 1242 MT compounds active against five or more targets and 6629 corresponding ST compounds are characterized, organized and made freely available. Limitations & next steps: Screening campaigns typically cover a smaller target space than compounds from the medicinal chemistry literature and their activity annotations might be of lesser quality. Reported compound groups will be subjected to target set-based promiscuity analysis and predictions.