Computer-aided lead optimization: improved small-molecule inhibitor of the zinc endopeptidase of botulinum neurotoxin serotype A
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Updated: Jul 12, 2026

A High-throughput-compatible FRET-based Platform for Identification and Characterization of Botulinum Neurotoxin Light Chain Modulators
Published on: December 27, 2013
Jing Tang1, Jewn Giew Park, Charles B Millard
1Computer-Aided Molecular Design Laboratory, Mayo Clinic, Rochester, Minnesota, United States of America.
Abstract:
Optimization of a serotype-selective, small-molecule inhibitor of botulinum neurotoxin serotype A (BoNTA) endopeptidase is a formidable challenge because the enzyme-substrate interface is unusually large and the endopeptidase itself is a large, zinc-binding protein with a complex fold that is difficult to simulate computationally. We conducted multiple molecular dynamics simulations of the endopeptidase in complex with a previously described inhibitor (K(i) (app) of 7+/-2.4 microM) using the cationic dummy atom approach. Based on our computational results, we hypothesized that introducing a hydroxyl group to the inhibitor could improve its potency. Synthesis and testing of the hydroxyl-containing analog as a BoNTA endopeptidase inhibitor showed a twofold improvement in inhibitory potency (K(i) (app) of 3.8+/-0.8 microM) with a relatively small increase in molecular weight (16 Da). The results offer an improved template for further optimization of BoNTA endopeptidase inhibitors and demonstrate the effectiveness of the cationic dummy atom approach in the design and optimization of zinc protease inhibitors.
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