Ranking the selectivity of PubChem screening hits by activity-based protein profiling: MMP13 as a case study

• Published in: Bioorganic & medicinal chemistry Vol. 17; no. 3; pp. 1101 - 1108
• Main Authors: Nakai, Ryuichiro, Salisbury, Cleo M., Rosen, Hugh, Cravatt, Benjamin F.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.02.2009
• Subjects: Activity-based profiling; Combinatorial Chemistry Techniques; Databases, Factual; Drug Design; Drug Evaluation, Preclinical; Enzymes; High-throughput screening; Inhibitors; Matrix Metalloproteinase Inhibitors; Matrix Metalloproteinases, Secreted - antagonists & inhibitors; Metalloproteinase; Pilot Projects; Protease Inhibitors - chemistry; Structure-Activity Relationship; High-throughput screening; Enzymes; Metalloproteinase; Inhibitors; Activity-based profiling
• ISSN: 0968-0896; 1464-3391
• DOI: 10.1016/j.bmc.2008.03.018

High-throughput screening (HTS) has become an integral part of academic and industrial efforts aimed at developing new chemical probes and drugs. These screens typically generate several ‘hits’, or lead active compounds, that must be prioritized for follow-up medicinal chemistry studies. Among primary considerations for ranking lead compounds is selectivity for the intended target, especially among mechanistically related proteins. Here, we show how the chemical proteomic technology activity-based protein profiling (ABPP) can serve as a universal assay to rank HTS hits based on their selectivity across many members of an enzyme superfamily. As a case study, four metalloproteinase-13 (MMP13) inhibitors of similar potency originating from a publically supported HTS and reported in PubChem were tested by ABPP for selectivity against a panel of 27 diverse metalloproteases. The inhibitors could be readily separated into two groups: (1) those that were active against several metalloproteases and (2) those that showed high selectivity for MMP13. The latter set of inhibitors was thereby designated as more suitable for future medicinal chemistry optimization. We anticipate that ABPP will find general utility as a platform to rank the selectivity of lead compounds emerging from HTS assays for a wide variety of enzymes.