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Updated: Oct 19, 2025

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical
Gert-Jan Bekker1, Mitsugu Araki2, Kanji Oshima3
1Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan.
Abstract:
We have performed dynamic docking between a prototypic G-protein-coupled receptor (GPCR) system, the β2-adrenergic receptor, and its antagonist, alprenolol, using one of the enhanced conformation sampling methods, multicanonical molecular dynamics (McMD), which does not rely on any prior knowledge for the definition of the reaction coordinate. Although we have previously applied our McMD-based dynamic docking protocol to various globular protein systems, its application to GPCR systems would be difficult because of their complicated design, which include a lipid bilayer, and because of the difficulty in sampling the configurational space of a binding site that exists deep inside the GPCR. Our simulations sampled a wide array of ligand-bound and ligand-unbound structures, and we measured 427 binding events during our 48 μs production run. Analysis of the ensemble revealed several stable and meta-stable structures, where the most stable structure at the global free energy minimum matches the experimental one. Additional canonical MD simulations were used for refinement and validation of the structures, revealing that most of the intermediates are sufficiently stable to trap the ligand in these intermediary states and furthermore validated our prediction results. Given the difficulty in reaching the orthosteric binding site, chemical optimization of the compound for the second ranking configuration, which binds near the pocket's entrance, might lead to a high-affinity allosteric inhibitor. Accordingly, we show that the application of our methodology can be used to provide crucial insights for the rational design of drugs that target GPCRs.
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