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March 2, 2026Trends in Pharmacological Sciences5 citationsOpen Access

Leveraging conformational ensembles in allosteric drug discovery

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RNRuth NussinovCRClil RegevHJHyunbum Jang

Key Points

  • The aim is to explore how dynamic conformational ensembles can improve allosteric drug discovery.
  • Review of traditional drug discovery methods, particularly the induced fit model.
  • Analysis of advanced molecular dynamics simulations and experimental data.
  • Identification of dynamic ensembles in signaling protein systems.
  • Traditional models limit drug development by assuming rigid protein structures.
  • Dynamic ensembles reveal novel targetable regions such as cryptic pockets.
  • Ensemble-based approaches are proposed to enhance the effectiveness of therapeutics.

Abstract

Proteins involved in signaling networks, such as Ras, mammalian target of rapamycin (mTOR), and epidermal growth factor receptor (EGFR), exist as dynamic conformational ensembles in biomolecular condensates. These ensembles play a crucial role in allosteric drug discovery and action. Traditional approaches in drug discovery often trace back to the induced fit model, which viewed proteins as rigid entities with active and inactive states. However, this model's limitations hindered successful drug development. Advanced molecular dynamics simulations of oncogenic mutants and experiments reveal heterogeneous dynamic ensembles, which can uncover targetable spots like cryptic pockets and cooperative exosites that only exist transiently. In this review, we clarify traditional dogmas and show how recent knowledge improves allosteric drug design by leveraging conformational ensembles, with examples. We further discuss how ensemble-based approaches can advance promising therapeutics, unlocking their potential for more effective future strategies, including in biomolecular condensates.

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Cite This Study

Nussinov et al. (2026) studied this question.

synapsesocial.com/papers/69a528b3f1e85e5c73bf042ahttps://doi.org/10.1016/j.tips.2026.01.006
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