Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement

International Journal of Molecular Sciences

Viet-Khoa Tran-Nguyen¹  Didier Rognan¹ 

[1] Laboratoire d’Innovation Thérapeutique, UMR7200 CNRS-Université de Strasbourg, 67400 Illkirch, France;

关键词: PubChem BioAssay;    benchmarking;    data set;    assay selection;    false positives;    chemical bias;   

DOI  :  10.3390/ijms21124380

来源: DOAJ

【 摘 要 】

Developing realistic data sets for evaluating virtual screening methods is a task that has been tackled by the cheminformatics community for many years. Numerous artificially constructed data collections were developed, such as DUD, DUD-E, or DEKOIS. However, they all suffer from multiple drawbacks, one of which is the absence of experimental results confirming the impotence of presumably inactive molecules, leading to possible false negatives in the ligand sets. In light of this problem, the PubChem BioAssay database, an open-access repository providing the bioactivity information of compounds that were already tested on a biological target, is now a recommended source for data set construction. Nevertheless, there exist several issues with the use of such data that need to be properly addressed. In this article, an overview of benchmarking data collections built upon experimental PubChem BioAssay input is provided, along with a thorough discussion of noteworthy issues that one must consider during the design of new ligand sets from this database. The points raised in this review are expected to guide future developments in this regard, in hopes of offering better evaluation tools for novel in silico screening procedures.

【 授权许可】

Unknown