2026-10-12T23:30:33Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34028758 2026-09-30T03:06:13Z category_1 category_4 category_873 portal_63 item_type_6 month_year_09_2026

Binding Free Energy Landscape of Different SARS-CoV‑2 Nsp1 Variants Interacting with NXF1-RRM: Insights from Molecular Dynamics Simulations and Markov State Models Hung Van Nguyen (21820160) Tri Minh Pham (25139971) Mai Suan Li (425259) Biophysics Biochemistry Chemical Sciences not elsewhere classified wt ), indicating strongest destabilizing effect molecular dynamics simulations intermolecular hydrogen bonds influences virus replication free energy landscape dynamical properties closer 2 nsp1 protein markov state models markov state model host immune surveillance host gene expression greater structural deviation yielding results consistent rrm domain plays e41k mutant exerts binding free energy nsp1 – nxf1 previous experimental work msm approach provides type nsp1 reference state host nxf1 experimental data msm analysis msm ). useful framework structural stability significant loss rrm complex reduced compactness realistic compared limited impact key factors k125e  induced changes important role great interest good agreement energetic analysis computational framework characterizing mutation binding energetics binding affinity also used affinity changes The interaction of the SARS-CoV-2 Nsp1 protein with the host NXF1-RRM domain plays an important role in host gene expression, which influences virus replication and host immune surveillance. Thus, understanding the key factors that determine their binding affinity, such as mutations, is of great interest. In this work, we investigated the effects of three Nsp1 mutantsD33K/E36K/E37K/E41K, L27D/V28D, and R124E/K125Eon its binding to the NXF1-RRM domain using structural and energetic analysis. To quantify the affinity changes, we developed a computational framework for calculating the free energy landscape of protein–protein binding based on the Markov state model (MSM). Our approach is based on fluctuations of the radius of gyration and the root mean square deviation (RMSD) from a reference state. We found that the D33K/E36K/E37K/E41K mutant exerts the strongest destabilizing effect, resulting in greater structural deviation, reduced compactness, and a significant loss of intermolecular hydrogen bonds. In contrast, the L27D/V28D and R124E/K125E mutants retain structural and dynamical properties closer to those of wild-type Nsp1 (WT), indicating that these mutations have a more limited impact on the stability of the Nsp1–NXF1-RRM complex. These results are in good agreement with the previous experimental work. We also used the molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) method to estimate the binding free energy of these complexes, yielding results consistent with the MSM analysis and experimental data. However, the binding free energy values obtained from the MSM method are more realistic compared to the MM-PBSA method, which tends to overestimate binding free energy values or produce unphysically negative results. Therefore, the MSM approach provides a useful framework for characterizing mutation-induced changes in the structural stability and binding energetics of Nsp1–NXF1-RRM complexes. 2026-09-29T00:00:00Z Text Journal contribution 10.1021/acs.jcim.6c02358.s001 https://figshare.com/articles/journal_contribution/Binding_Free_Energy_Landscape_of_Different_SARS-CoV_2_Nsp1_Variants_Interacting_with_NXF1-RRM_Insights_from_Molecular_Dynamics_Simulations_and_Markov_State_Models/34028758 CC BY-NC 4.0