Ten activity classes are provided that were extracted from ChEMBL version 24 for machine learning studies. Compounds are given in SMILES representations. The following selection criteria were applied. Compounds were required to be tested in a direct binding assay against a single human protein with a ChEMBL assay confidence score of 9. In addition, Ki measurements had to be available. If multiple Ki values were available for a compound and did not fall within the same order of magnitude, the compound was not selected. Furthermore only compounds with (mean) pKi of at least 5 were considered. Moreover, activity classes had to contain at least 200 compounds belonging to at least 50 computationally determined analog series. The 10 deposited cla...
This work provides an analysis of across-target bioactivity results in the screening data deposited ...
Natural compounds constitute a rich resource of potential small molecule therapeutics. While experim...
A total of 702 crystallographic ligands with activity against multiple targets from different protei...
Ten activity classes are provided that were extracted from ChEMBL version 24 for machine learning st...
<p>A total of 102 activity classes (ACs) were assembled from ChEMBL version 20 and were classified a...
Compound activity data sets for the 15 biological targets are deposited, along with structure-activi...
Scoring the activity of compounds in phenotypic high-throughput assays presents a unique challenge b...
Background: The World Anti-Doping Agency (WADA) publishes the Prohibited List, a manually compiled i...
<p>The analog database consisting of 1,297,204 virtual compounds is provided. Virtual compounds are ...
High-quality dataset gathered from ChEMBL version 22 based on UniProt accession P34972. Regarding to...
<p>A set of 52,815 unique bioactive compounds (human targets, high-confidence activity data) with no...
Additional file 2. Table with DU-145 ChEMBL assays used to retrieve compounds activitie
Additional file 1. Table with PC-3 ChEMBL assays used to retrieve compounds activitie
Active machine learning puts artificial intelligence in charge of a sequential, feedback-driven disc...
The prediction of compound properties from chemical structure is a main task for machine learning (M...
This work provides an analysis of across-target bioactivity results in the screening data deposited ...
Natural compounds constitute a rich resource of potential small molecule therapeutics. While experim...
A total of 702 crystallographic ligands with activity against multiple targets from different protei...
Ten activity classes are provided that were extracted from ChEMBL version 24 for machine learning st...
<p>A total of 102 activity classes (ACs) were assembled from ChEMBL version 20 and were classified a...
Compound activity data sets for the 15 biological targets are deposited, along with structure-activi...
Scoring the activity of compounds in phenotypic high-throughput assays presents a unique challenge b...
Background: The World Anti-Doping Agency (WADA) publishes the Prohibited List, a manually compiled i...
<p>The analog database consisting of 1,297,204 virtual compounds is provided. Virtual compounds are ...
High-quality dataset gathered from ChEMBL version 22 based on UniProt accession P34972. Regarding to...
<p>A set of 52,815 unique bioactive compounds (human targets, high-confidence activity data) with no...
Additional file 2. Table with DU-145 ChEMBL assays used to retrieve compounds activitie
Additional file 1. Table with PC-3 ChEMBL assays used to retrieve compounds activitie
Active machine learning puts artificial intelligence in charge of a sequential, feedback-driven disc...
The prediction of compound properties from chemical structure is a main task for machine learning (M...
This work provides an analysis of across-target bioactivity results in the screening data deposited ...
Natural compounds constitute a rich resource of potential small molecule therapeutics. While experim...
A total of 702 crystallographic ligands with activity against multiple targets from different protei...