{"title":"Harnessing Allostery to Modulate Protein–Protein Interactions: From Function to Therapeutic Innovations","authors":"Sutanu Mukhopadhyay, Krishnendu Sinha, Suman Chakrabarty","doi":"10.1016/j.jmb.2025.169382","DOIUrl":null,"url":null,"abstract":"<div><div>Protein-protein interactions (PPIs) are ubiquitous mediators of cellular functions, and their dysregulation is central to numerous pathological conditions. Traditional drug discovery strategies targeting PPIs directly have faced considerable obstacles due to their extensive, flat, and dynamic interfaces, deemed conventionally “undruggable”. Allosteric regulation offers an alternative route, allowing modulation of these critical interactions through spatially distinct regulatory sites that can dynamically alter protein function without direct interference at the interface. Recent advances in computational methodologies, particularly enhanced molecular dynamics simulations and machine learning approaches, have significantly expanded our ability to identify and characterize cryptic allosteric sites and pathways. This perspective provides a comprehensive analysis of the evolving understanding of allosteric mechanisms in PPIs, highlights recent successes in computational identification and targeting of allosteric modulators, and outlines the challenges and opportunities in translating these insights into therapeutic strategies. Ultimately, this approach heralds a transformative potential in therapeutic interventions targeting complex biological networks.</div></div>","PeriodicalId":369,"journal":{"name":"Journal of Molecular Biology","volume":"437 20","pages":"Article 169382"},"PeriodicalIF":4.5000,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022283625004486","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Protein-protein interactions (PPIs) are ubiquitous mediators of cellular functions, and their dysregulation is central to numerous pathological conditions. Traditional drug discovery strategies targeting PPIs directly have faced considerable obstacles due to their extensive, flat, and dynamic interfaces, deemed conventionally “undruggable”. Allosteric regulation offers an alternative route, allowing modulation of these critical interactions through spatially distinct regulatory sites that can dynamically alter protein function without direct interference at the interface. Recent advances in computational methodologies, particularly enhanced molecular dynamics simulations and machine learning approaches, have significantly expanded our ability to identify and characterize cryptic allosteric sites and pathways. This perspective provides a comprehensive analysis of the evolving understanding of allosteric mechanisms in PPIs, highlights recent successes in computational identification and targeting of allosteric modulators, and outlines the challenges and opportunities in translating these insights into therapeutic strategies. Ultimately, this approach heralds a transformative potential in therapeutic interventions targeting complex biological networks.
期刊介绍:
Journal of Molecular Biology (JMB) provides high quality, comprehensive and broad coverage in all areas of molecular biology. The journal publishes original scientific research papers that provide mechanistic and functional insights and report a significant advance to the field. The journal encourages the submission of multidisciplinary studies that use complementary experimental and computational approaches to address challenging biological questions.
Research areas include but are not limited to: Biomolecular interactions, signaling networks, systems biology; Cell cycle, cell growth, cell differentiation; Cell death, autophagy; Cell signaling and regulation; Chemical biology; Computational biology, in combination with experimental studies; DNA replication, repair, and recombination; Development, regenerative biology, mechanistic and functional studies of stem cells; Epigenetics, chromatin structure and function; Gene expression; Membrane processes, cell surface proteins and cell-cell interactions; Methodological advances, both experimental and theoretical, including databases; Microbiology, virology, and interactions with the host or environment; Microbiota mechanistic and functional studies; Nuclear organization; Post-translational modifications, proteomics; Processing and function of biologically important macromolecules and complexes; Molecular basis of disease; RNA processing, structure and functions of non-coding RNAs, transcription; Sorting, spatiotemporal organization, trafficking; Structural biology; Synthetic biology; Translation, protein folding, chaperones, protein degradation and quality control.