Chemical neighborhood exploration for substrate discovery in biocatalysis

Y Yaroslav V. Solovev (Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences) N Nikita N. Kostin (Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences) Y Yuri A. Prokopenko (Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences) P Patrick Masson I Ivan V. Smirnov (Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences) H Hongkai Zhang (Frontiers Science Center for New Organic Matter, State Key Laboratory of Medicinal Chemical Biology, College of Life Sciences and Academy for Advanced Interdisciplinary Studies) W Wei Zheng I Igor A. Yaroshevich (Department of Biophysics, Faculty of Biology, Lomonosov Moscow State University) A Alexey V. Stepanov (Department of Integrative Structural and Computational Biology, The Scripps Research Institute) P Petr A. Popov (School of Science, Constructor University Bremen) A Alexander G. Gabibov (Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences)

Abstract

Predicting the substrate reactivity strength for a given biocatalyst remains a central challenge in computational biocatalysis. Here, we present Subdate, a modular workflow that combines descriptor-guided organization of substrate analogs with ab initio metadynamics simulations to prioritize reactive candidates. The workflow integrates i) substrate library construction, ii) conformer generation and descriptors set definition, iii) library clustering, iv) representative-substrate selection, and v) reaction-barrier quantitative prediction. Applied to selected biocatalysts (human butyrylcholinesterase and the catalytic antibody A17) sharing an SN2 reaction mechanism, Subdate quantitatively identifies reactivity trends that match experimental kinetic measurements. The developed workflow provides a mechanism-aware strategy for reactive substrate prioritization for efficient sampling through the chemical library in biocatalysis.

Article Details

Volume / Issue Vol. 123, Issue 24
Published June 16, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (11)

Y

Yaroslav V. Solovev

Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

N

Nikita N. Kostin

Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

Y

Yuri A. Prokopenko

Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

P

Patrick Masson

I

Ivan V. Smirnov

Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences

H

Hongkai Zhang

Frontiers Science Center for New Organic Matter, State Key Laboratory of Medicinal Chemical Biology, College of Life Sciences and Academy for Advanced Interdisciplinary Studies

W

Wei Zheng

I

Igor A. Yaroshevich

Department of Biophysics, Faculty of Biology, Lomonosov Moscow State University

A

Alexey V. Stepanov

Department of Integrative Structural and Computational Biology, The Scripps Research Institute

P

Petr A. Popov

School of Science, Constructor University Bremen

A

Alexander G. Gabibov

Department of Peptide and Protein Technologies, M.M. Shemyakin and Yu.A. Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences