Paper Info
Title
PrePeP: A Tool for the Identification and Characterization of Pan Assay Interference Compounds.
Abstract
Pan Assays Interference Compounds (PAINS) are a significant problem in modern drug discovery: compounds showing non-target specific activity in high-throughput screening can mislead medicinal chemists during hit identification, wasting time and resources. Recent work has shown that existing structural alerts are not up to the task of identifying PAINS. To address this short-coming, we are in the process of developing a tool, PrePeP, that predicts PAINS, and allows experts to visually explore the reasons for the prediction. In the paper, we discuss the different aspects that are involved in developing a functional tool: systematically deriving structural descriptors, addressing the extreme imbalance of the data, offering visual information that pharmacological chemists are familiar with. We evaluate the quality of the approach using benchmark data sets from the literature and show that we correct several short-comings of existing PAINS alerts that have recently been pointed out.
Year
DOI
Venue
2018
10.1145/3219819.3219849
KDD
Keywords
Field
DocType
Discriminative graph mining,chemoinformatics,structure activity relationships
Drug discovery,Computer science,Artificial intelligence,Pan-assay interference compounds,Cheminformatics,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4503-5552-0
0
0.34
References 
Authors
14
5
Name
Order
Citations
PageRank
Maksim Koptelov100.34
Albrecht Zimmermann219219.47
Pascal Bonnet372.62
R Bureau43012.13
Bruno Crémilleux537334.98