Activation pathway of Src kinase reveals intermediate states as targets for drug design
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Unregulated activation of Src kinases leads to aberrant signalling, uncontrolled growth and differentiation of cancerous cells. Reaching a complete mechanistic understanding of large-scale conformational transformations underlying the activation of kinases could greatly help in the development of therapeutic drugs for the treatment of these pathologies. In principle, the nature of conformational transition could be modelled in silico via atomistic molecular dynamics simulations, although this is very challenging because of the long activation timescales. Here we employ a computational paradigm that couples transition pathway techniques and Markov state model-based massively distributed simulations for mapping the conformational landscape of c-src tyrosine kinase. The computations provide the thermodynamics and kinetics of kinase activation for the first time, and help identify key structural intermediates. Furthermore, the presence of a novel allosteric site in an intermediate state of c-src that could be potentially used for drug design is predicted.
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Recent MSM studies of the activation pathways of kinases or GPCRs reveal the potential for identifying putative allosteric binding sites or distinguishing between agonists and antagonists using structural information along putative functional pathways.
“Recent MSM studies of the activation pathways of kinases [62] or GPCRs [63] has similarly revealed the potential for identifying putative allosteric binding sites or distinguishing between agonists and antagonists using structural information along putative functional pathways.”
From Markov state models of biomolecular conformational dynamics (2014) · cites this paper as [62]
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- Authors
- Shukla, D., Meng, Y., Roux, B., & Pande, V. S.
- Affiliations
- Stanford University (US)
- University of Chicago (US)
- Corresponding author
- Pande, Vijay S.
- Venue
- Nature Communications
- Published
- 2014-03-03
- Volume
- 5
- Issue
- 1
- Pages
- 3397-3397
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC4465921
- OpenAlex
- W1978607920
- Cited by
- 333
- References
- 70
- Citations by year
- 2026: 12 · 2025: 11 · 2024: 23 · 2023: 17 · 2022: 25 · 2021: 27 · 2020: 24 · 2019: 33 · 2018: 36 · 2017: 45 · 2016: 36 · 2015: 27 · 2014: 17
- FWCI
- 17.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Communications (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA093577, CA093577)
- National Institute of General Medical Sciences (U54-GM07297)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- Src kinase, c-Src kinase, conformational change, structural intermediates, allosteric site, Markov state models, cancer drug targets, metastasis
- MeSH terms
- Allosteric Site, Humans, Thermodynamics, Drug Design, src-Family Kinases, Computational Biology, Molecular Dynamics Simulation
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