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Teruel, N. F. B.

Publications and source records attributed to Teruel, N. F. B..

2 recordsLinked to original sources

Comprehensive Analysis of SARS-CoV-2 Spike Evolution: Epitope Classification and Immune Escape Prediction

The evolution of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has produced unprece-dented numbers of structures of the Spike protein. This study presents a comprehensive analysis of 1,560 published Spike protein structures, capturing most variants that emerged throughout the pandemic and covering diverse heteromerization and interacting complexes. We employ an interaction-energy informed geometric clustering to identify 14 epitopes characterized by their conformational specificity, shared interface with ACE2 binding, and glycosylation patterns. Our per-residue interaction evaluations accurately predict each residues role in antibody recognition and as well as experimental measurements of immune escape, showing strong correlations with DMS data, thus making it possible to predict the behaviour of future variants. We integrate the structural analysis with a longitudinal analysis of nearly 3 million viral sequences. This broad-ranging structural and longitudinal analysis provides insight into the effect of specific mutations on the energetics of interactions and dynamics of the SARS-CoV-2 Spike protein during the course of the pandemic. Specifically, with the emergence of widespread immunity, we observe an enthalpic trade-off in which mutations in the receptor binding motif (RBM) that promote immune escape also weaken the interaction with ACE2. Additionally, we also observe a second mechanism, that we call entropic trade-off, in which mutations outside of the RBM contribute to decrease the occupancy of the open state of SARS-CoV-2 Spike, thus also contributing to immune escape at the expense of ACE2 binding but without changes on the ACE2 binding interface. This work not only highlights the role of mutations across SARS-CoV-2 Spike variants but also reveals the complex interplay of evolutionary forces shaping the evolution of the SARS-CoV-2 Spike protein over the course of the pandemic.

biophysics↗

Surfaces: A software to quantify and visualize interactions within and between proteins and ligands

Computational methods for the quantification and visualization of the relative contribution of molecular interactions to the stability of biomolecular structures and complexes are fundamental to understand, modulate and engineer biological processes. Here we present Surfaces, an easy to use, fast and customizable software for quantification and visualization of molecular interactions based on the calculation of surface areas in contact. Surfaces calculations shows equivalent levels of correlations with experimental data as computationally expensive methods based on molecular dynamics. All scripts are available at https://github.com/nataliateruel/Surfaces Documentation is available at https://surfaces-tutorial.readthedocs.io/en/latest/index.html

bioinformatics↗