EventsThe 2nd International Electronic Conference on Medicinal Chemistry and Pharmaceutics
Published
This submission belongs to the session S6. New Modalities in Drug Discovery of the event The 2nd International Electronic Conference on Medicinal Chemistry and Pharmaceutics
Published date
28 Oct, 2026
Academic Editor
author-avatarMary J. Meegan
Contribution&Funding
Conceptualization,
[Andrii Zaremba]
Methodology,
[Andrii Zaremba]
Software,
[Andrii Zaremba]
Validation,
[Andrii Zaremba]
Investigation,
[Andrii Zaremba] ; [Polina Zaremba]
Resources,
[Andrii Zaremba]
Writing - original draft,
[Andrii Zaremba]
Writing - review,
[editing] ; [Polina Zaremba]
Visualization,
[Polina Zaremba]
Project administration,
[Andrii Zaremba] ; [Polina Zaremba]
Funding acquisition,
[Andrii Zaremba]
Funding: This research was supported by the National Academy of Sciences of Ukraine under grant No. 0125U002921.
Citation
Andrii Zaremba, Polina Zaremba, FDA-approved drugs as probes for mixMD: a pipeline modeled on the identification of cryptic pockets of SARS-CоV-2 3CLpro, in Proceedings of The 2nd International Electronic Conference on Medicinal Chemistry and Pharmaceutics, 1 November–30 November 2026, MDPI: Basel, Switzerland
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FDA-approved drugs as probes for mixMD: a pipeline modeled on the identification of cryptic pockets of SARS-CоV-2 3CLpro

1. Department of Virus Reproduction, D.K. Zabolotny Institute of Microbiology and Virology of the National Academy of Sciences of Ukraine, Kyiv, Ukraine
Abstract

Modern drug discovery relies on identifying biologically relevant, druggable pockets on target surfaces. Сurrent evidence indicates that the majority of these pockets are inherently inducible and remain cryptic prior to ligand binding. Mixed-solvent molecular dynamics (mixMD) is one of the few methods that enables identification of such pockets. Conventionally, mixMD involves deploying one or several small-molecule probes distributed within a polar solvent. However, we identified a limitation in this standard protocol stemming from the topological uniformity of such mixMD setups. So, we utilized the FDA-approved drug database as a source of clinically proven, topologically diverse structural scaffolds. We developed a comprehensive semi-automated pipeline that integrates ligand filtering, protonation, parameterization, and automated molecular system assembly. The preparatory stage was implemented by an automated combination of Open Babel for protonation and RDKit for mass filtering, 3D generation and energy minimization (MMFF94). Ligand parameterization was carried out by a separate script that used ACPYPE (AM1-BCC, GAFF2) for each ligand sequentially. Using GROMACS utilities, a custom script automated box sizing and stochastic probe placement based on user-specified ligand-to-water volume fractions and probe copy numbers. A dedicated auxiliary script processed all ligand topology files to prevent atom-type conflicts during system compilation. The prepared ligand topologies were added to the final system topology file. Subsequent system solvation and equilibration followed conventional protocols for Amber14SB-related systems. This pipeline was used to study 3CLpro of SARS-CоV-2, which is one of the key targets for the development of anti-covid drugs. Importantly, even within a relatively short molecular dynamics simulation, our approach enabled the identification of a previously unreported cryptic pocket located outside the active site of 3CLpro. It demonstrated the ability to bind bazedoxifene, a component of the mixMD solvent, which is a selective estrogen receptor modulator.

Keywords
mixMD probes
cryptic pockets
molecular dynamics
3CLpro
SARS-CоV-2
bazedoxifene
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