Insights into the role of dynamical features in protein complex formation: The case of SARS-CoV-2 spike binding with ACE2
The functionality of protein-protein complexes is closely tied to the strength of their interactions, making the evaluation of binding affinity a central focus in structural biology. However, the molecular determinants underlying binding affinity are still not fully understood. In particular, the entropic contributions, especially those arising from conformational dynamics, remain poorly characterized. In this study, we investigate the relationship between protein motion and binding stability, as well as its role in protein function. To gain deeper insight into how protein complexes modulate their stability, we investigated a model system with a well-characterized and fast evolutionary history: a set of SARS-CoV-2 spike protein variants bound to the human ACE2 receptor, for which experimental binding affinity data are available. Through Molecular Dynamics simulations, we analyzed both structural and dynamical differences between the unbound (apo) and bound (holo) forms of the spike protein across several variants of concern. Our findings indicate that a more stable binding is associated with proteins that exhibit higher rigidity in their unbound state and display dynamical patterns similar to those observed after binding to ACE2. The increase in binding stability is not the sole driving force of SARS-CoV-2 evolution. More recent variants are characterized by a more dynamic behavior that determines a less efficient viral entry but could optimize other traits. These results suggest that to fully understand the strength of the binding between two proteins, the stability of each isolated partner should be investigated.
Authors
- Francesca Alessandrini (ORCID: https://orcid.org/0000-0002-9854-8968)
- Edoardo Milanetti (ORCID: https://orcid.org/0000-0002-3046-5170)
- Giancarlo Ruocco (ORCID: https://orcid.org/0000-0002-2762-9533)
- Leonardo Bo’
- Greta Grassmann (ORCID: https://orcid.org/0000-0002-6945-5834)
- Mattia Miotto (ORCID: https://orcid.org/0000-0002-0043-8921)
- Andrea Giansanti (ORCID: https://orcid.org/0000-0002-8113-8188)
Institutions
- Istituto Nazionale di Fisica Nucleare (IT)
- Center for Nano Science and Technology (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- Computational and Structural Biotechnology Journal
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.csbj.2025.10.033
- Primary Topic
- SARS-CoV-2 and COVID-19 Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00