Allostery is increasingly recognized as a transition-aware process in which local perturbations reshape conformational ensembles monitored by the reorganization of residue-residue contacts, leading to biased functions. This review highlights ensemble-comparison approaches to dissecting allosteric mechanisms, including those based on simulations, integration of simulation and experiment, and emerging machine learning-based predictions. These approaches provide mechanistic views of allostery that link ensemble redistribution to functional regulation. We argue that useful allosteric models should explain not only which residues connect distal sites but also which residue-residue contacts are reorganized, which regions respond cooperatively, and how these changes alter function. Understanding detailed allosteric mechanisms may help identify new allosteric pockets and guide the design of novel modulators to fine-tune biological processes for therapeutic benefit.
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Yao et al. (2026) studied this question.
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