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Structure-based virtual screening for TRPM8 modulators

delete2026-01-28
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OA
AI
N
Nivya James
P
Pedro J. Ballester *
DOI:10.3389/fddsv.2026.1770904delete
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Abstract

Abstract

En 中文
Transient receptor potential melastatin 8 (TRPM8) is an emerging therapeutic target, yet the performance of available structural models for docking and optimal docking protocols for virtual screening (VS) remains unclear. Here, we benchmarked two available TRPM8 structural conformations (agonist-bound TRPM87WRE and antagonist-bound TRPM89B6G) using docking tools, Smina and rDock, using known TRPM8 inhibitors and property-matched decoys. rDock achieved the highest hit rates and outperformed Smina in ranking true actives at first-ranks than their corresponding decoys, whereas Smina showed a target-structure dependence on docking performance but delivered superior overall ranking quality across both target structures. Both docking tools displayed considerable overlap between active and decoy score distributions, indicating only moderate discriminatory power of docking scores alone. When prioritizing a small subset of top-ranked compounds, integrated screening approaches, particularly the consensus protocol, improved the recovery of true actives, while the hierarchical protocol achieved comparable performance at a substantially lower computational cost. Collectively, this work establishes a reproducible VS benchmark for TRPM8 and supports the use of different screening protocols to improve early hit identification.
Keywords:
benchmarking
ion channels
molecular docking
TRPM8
virtual screening

Journal

F
Frontiers in Drug Discovery
IF:
0
Papers:
25
Citations:
0

Organization

I
imperial college london
Scholars:
9.9K
Papers: 4.4K
Citations: 0
Cited Papers

Cited Papers

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A practical guide to machine-learning scoring for structure-based virtual screening
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errTran-Nguyen, Viet-Khoa; Junaid, Muhammad; Simeon, Saw; Ballester, Pedro J.
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Structures of a mammalian TRPM8 in closed state
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errZhao, Cheng; Xie, Yuan; Xu, Lizhen; Ye, Fan; Xu, Ximing; Yang, Wei; Yang, Fan; Guo, Jiangtao
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rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids
err2014-04-10
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errOAAI
errRuiz-Carmona, Sergio; Alvarez-Garcia, Daniel; Foloppe, Nicolas; Beatriz Garmendia-Doval, A.; Juhos, Szilveszter; Schmidtke, Peter; Barril, Xavier; Hubbard, Roderick E.; Morley, S. David
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Activation mechanism of the mouse cold-sensing TRPM8 channel by cooling agonist and PIP 2
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errOAAI
errYing Yin; Feng Zhang; Shasha Feng; Kevin John Butay; Mario J. Borgnia; Wonpil Im; Seok-Yong Lee
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Generating property-matched decoy molecules using deep learning
err2021-02-03
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errOAAI
errFergus Imrie; Anthony R Bradley; Charlotte M Deane
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