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Surfactant protein D (SP-D) is an essential component of the human pulmonary surfactant system, which is crucial in the innate immune response against glycan-containing pathogens, including Influenza A viruses (IAV) and SARS-CoV-2. Previous studies have shown that wild-type (WT) SP-D can bind IAV but exhibits poor antiviral activities. However, a double mutant (DM) SP-D consisting of two point mutations (Asp325Ala and Arg343Val) inhibits IAV more potently. Presently, the structural mechanisms behind the point mutations' effects on SP-D's binding affinity with viral surface glycans are not fully understood. Here we use microsecond-scale, full-atomistic molecular dynamics (MD) simulations to understand the molecular mechanism of mutation-induced SP-D's higher antiviral activity. We find that the Asp325Ala mutation promotes a trimannose conformational change to a more stable state. Arg343Val increases the binding with trimannose by increasing the hydrogen bonding interaction with Glu333. Free energy perturbation (FEP) binding free energy calculations indicate that the Arg343Val mutation contributes more to the increase of SP-D's binding affinity with trimannose than Asp325Ala. This study provides a molecular-level exploration of how the two mutations increase SP-D binding affinity with trimannose, which is vital for further developing preventative strategies for related diseases.
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Comparative Assessment of Water Models in Protein–Glycan Interaction: Insights from Alchemical Free Energy Calculations and Molecular Dynamics Simulations
Accurate computational simulations of protein–glycan dynamics are crucial for a comprehensive understanding of critical biological mechanisms, including host–pathogen interactions, immune system defenses, and intercellular communication. The accuracy of these simulations, including molecular dynamics (MD) simulation and alchemical free energy calculations, critically relies on the appropriate parameters, including the water model, because of the extensive hydrogen bonding with glycan hydroxyl groups. However, a systematic evaluation of water models’ accuracy in simulating protein–glycan interaction at the molecular level is still lacking. In this study, we used full atomistic MD simulations and alchemical absolute binding free energy (ABFE) calculations to investigate the performance of five distinct water models in six protein–glycan complex systems. We evaluated water models’ impact on structural dynamics and binding affinity through over 5.8 μs of simulation time per system. Our results reveal that most protein–glycan complexes are stable in the overall structural dynamics regardless of the water model used, while some show obvious fluctuations with specific water models. More importantly, we discover that the stability of the binding motif’s conformation is dependent on the water model chosen when its residues form weak hydrogen bonds with the glycan. The water model also influences the conformational stability of the glycan in its bound state according to density functional theory (DFT) calculations. Using alchemical ABFE calculations, we find that the OPC water model exhibits exceptional consistency with experimental binding affinity data, whereas commonly used models such as TIP3P are less accurate. The findings demonstrate how different water models affect protein–glycan interactions and the accuracy of binding affinity calculations, which is crucial in developing therapeutic strategies targeting these interactions.
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- Award ID(s):
- 2338401
- PAR ID:
- 10567461
- Publisher / Repository:
- ACS
- Date Published:
- Journal Name:
- Journal of Chemical Information and Modeling
- Volume:
- 64
- Issue:
- 24
- ISSN:
- 1549-9596
- Page Range / eLocation ID:
- 9459 to 9473
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1021/acs.jcim.4c01361
