A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N
Hyperactivation caused by mutations in the Epidermal Growth Factor Receptor (EGFR) kinase domain is implicated in various diseases, including cancer. However, the structural mechanisms underlying overactivation in many EGFR mutations remain poorly understood, and exploring these mechanisms through c...
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Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025003095 |
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| author | Julian Behn R.N.V. Krishna Deepak Jiancheng Hu Hao Fan |
| author_facet | Julian Behn R.N.V. Krishna Deepak Jiancheng Hu Hao Fan |
| author_sort | Julian Behn |
| collection | DOAJ |
| description | Hyperactivation caused by mutations in the Epidermal Growth Factor Receptor (EGFR) kinase domain is implicated in various diseases, including cancer. However, the structural mechanisms underlying overactivation in many EGFR mutations remain poorly understood, and exploring these mechanisms through conventional experiments or in silico simulations is often labor- and cost-intensive. Here, we establish a Molecular Dynamics (MD) protocol capable of rapidly revealing EGFR mutant modes of action using multiple short simulations. We first simulated wild-type EGFR and the well-studied oncogenic mutations L858R and T790M/L858R under different simulation conditions, to derive a protocol which could recapitulate their experimentally established behavior. We then applied this protocol to three rare EGFR mutations: S768I, S768N, and D761N. Experimental studies have suggested that S768I and D761N are oncogenic, whereas S768N is likely a neutral mutation that does not significantly alter EGFR activity. Our simulation results were consistent with these functional indications and provided the corresponding molecular bases – S768I and S768N affect the orientation and stability of the catalytically important αC-helix, while D761N introduces a new hydrogen bonding network between the αC-helix and activation loop. Collectively, the protocol presented here provides a robust and rapid framework for characterizing EGFR mutation mechanisms and is readily adaptable to novel or uncharacterized variants. |
| format | Article |
| id | doaj-art-3d1b4ff44ffb4d24bfeac1a244702e38 |
| institution | Kabale University |
| issn | 2001-0370 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj-art-3d1b4ff44ffb4d24bfeac1a244702e382025-08-20T03:58:00ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-01273370337810.1016/j.csbj.2025.07.046A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761NJulian Behn0R.N.V. Krishna Deepak1Jiancheng Hu2Hao Fan3Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeBioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore; School of Arts and Sciences, Azim Premji University Bangalore, Bangalore, IndiaCancer and Stem Cell Program, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore; Division of Cellular and Molecular Research, National Cancer Centre Singapore, 11 Hospital Crescent, Singapore 169610, SingaporeBioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore; Cancer and Stem Cell Program, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore; Synthetic Biology Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117596, Singapore; Corresponding author at: Bioinformatics Institute (BII), Agency for Science, Technology and Research (A⁎STAR), Singapore 138671, Singapore.Hyperactivation caused by mutations in the Epidermal Growth Factor Receptor (EGFR) kinase domain is implicated in various diseases, including cancer. However, the structural mechanisms underlying overactivation in many EGFR mutations remain poorly understood, and exploring these mechanisms through conventional experiments or in silico simulations is often labor- and cost-intensive. Here, we establish a Molecular Dynamics (MD) protocol capable of rapidly revealing EGFR mutant modes of action using multiple short simulations. We first simulated wild-type EGFR and the well-studied oncogenic mutations L858R and T790M/L858R under different simulation conditions, to derive a protocol which could recapitulate their experimentally established behavior. We then applied this protocol to three rare EGFR mutations: S768I, S768N, and D761N. Experimental studies have suggested that S768I and D761N are oncogenic, whereas S768N is likely a neutral mutation that does not significantly alter EGFR activity. Our simulation results were consistent with these functional indications and provided the corresponding molecular bases – S768I and S768N affect the orientation and stability of the catalytically important αC-helix, while D761N introduces a new hydrogen bonding network between the αC-helix and activation loop. Collectively, the protocol presented here provides a robust and rapid framework for characterizing EGFR mutation mechanisms and is readily adaptable to novel or uncharacterized variants.http://www.sciencedirect.com/science/article/pii/S2001037025003095KinaseEpidermal growth factor receptorAsymmetric dimerSymmetric dimerCancer mutationsMolecular dynamics simulation |
| spellingShingle | Julian Behn R.N.V. Krishna Deepak Jiancheng Hu Hao Fan A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N Computational and Structural Biotechnology Journal Kinase Epidermal growth factor receptor Asymmetric dimer Symmetric dimer Cancer mutations Molecular dynamics simulation |
| title | A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N |
| title_full | A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N |
| title_fullStr | A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N |
| title_full_unstemmed | A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N |
| title_short | A molecular dynamics protocol for rapid prediction of EGFR overactivation and its application to the rare mutations S768I, S768N, D761N |
| title_sort | molecular dynamics protocol for rapid prediction of egfr overactivation and its application to the rare mutations s768i s768n d761n |
| topic | Kinase Epidermal growth factor receptor Asymmetric dimer Symmetric dimer Cancer mutations Molecular dynamics simulation |
| url | http://www.sciencedirect.com/science/article/pii/S2001037025003095 |
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