Mapping Structural Drivers of Insulin and its Analogs at the IGF-1 Receptor Using Molecular Dynamics and Free Energy Calculations
Abstract Insulin and insulin-like growth factor-1 receptors (IR, IGF-1R) belong to the family of receptor tyrosine kinases (RTKs), and share close structural resemblance. However, these receptors exhibit distinct activity profiles and functions in vivo. Binding of insulin to IGF-1R results in additional growth-factor-like behavior and cell proliferation, but its ∼100-fold reduced affinity to IGF-1R limits off-target activity. However, insulin analogs with increased potency at IGF-1R have oncogenicity as a key safety concern. Hence, the ability to accurately predict potency of novel analogs at IGF-1R could represent a key breakthrough towards rational insulin design. To date, a comprehensive molecular level understanding of insulin interactions at IGF-1R has remained elusive. This study capitalized on recent advancements in structural biology that provided high resolution structures of IGF-1R bound to IGF-1 and insulin. Initially, molecular dynamics (MD) simulations were employed to unravel the intricate interactions that characterize the receptor-ligand pairs. Next, free energy perturbation (FEP) calculations were performed to understand the increased affinity observed in insulin analogs, X10 and glargine. Subsequently, multiple mutations at the B10 position of insulin spanning different activities at IGF-1R and different metabolites of insulin glargine, encompassing various mitogenic potencies were studied using FEP. The calculations successfully captured directional shifts in potency for all studied mutants, with approximately 50% of the predicted values falling within 1 kcal/mol of experiment. Beyond its impressive accuracy, FEP’s ability to provide a detailed understanding of protein- and solvent-mediated contributions to the observed functional profiles underscores its utility in designing safe IGF-1R selective novel insulin analogs..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 11. Dez. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sena, Mohan Maruthi [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2023.12.02.569705 |
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| PPN (Katalog-ID): |
XBI041768418 |
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| 520 | |a Abstract Insulin and insulin-like growth factor-1 receptors (IR, IGF-1R) belong to the family of receptor tyrosine kinases (RTKs), and share close structural resemblance. However, these receptors exhibit distinct activity profiles and functions in vivo. Binding of insulin to IGF-1R results in additional growth-factor-like behavior and cell proliferation, but its ∼100-fold reduced affinity to IGF-1R limits off-target activity. However, insulin analogs with increased potency at IGF-1R have oncogenicity as a key safety concern. Hence, the ability to accurately predict potency of novel analogs at IGF-1R could represent a key breakthrough towards rational insulin design. To date, a comprehensive molecular level understanding of insulin interactions at IGF-1R has remained elusive. This study capitalized on recent advancements in structural biology that provided high resolution structures of IGF-1R bound to IGF-1 and insulin. Initially, molecular dynamics (MD) simulations were employed to unravel the intricate interactions that characterize the receptor-ligand pairs. Next, free energy perturbation (FEP) calculations were performed to understand the increased affinity observed in insulin analogs, X10 and glargine. Subsequently, multiple mutations at the B10 position of insulin spanning different activities at IGF-1R and different metabolites of insulin glargine, encompassing various mitogenic potencies were studied using FEP. The calculations successfully captured directional shifts in potency for all studied mutants, with approximately 50% of the predicted values falling within 1 kcal/mol of experiment. Beyond its impressive accuracy, FEP’s ability to provide a detailed understanding of protein- and solvent-mediated contributions to the observed functional profiles underscores its utility in designing safe IGF-1R selective novel insulin analogs. | ||
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| 700 | 1 | |a Chatterji, Monalisa |4 aut | |
| 700 | 1 | |a Khedkar, Anand |4 aut | |
| 700 | 1 | |a Ranganathan, Anirudh |4 aut | |
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