JMIR Publications

ABSTRACT

Background:

The COVID-19 pandemic requires a deep understanding of SARS-CoV-2, particularly how mutations in the Spike Receptor Binding Domain (RBD) Chain E affect its structure and function. Current methods lack comprehensive analysis of these mutations at different structural levels.

Objective:

To analyze the impact of specific COVID-19 associated point mutations (N501Y, L452R, N440K, K417N, E484A) on the SARS-CoV-2 Spike RBD structure and function using predictive modeling, including a graph-theoretic model, protein modeling techniques, and molecular dynamics simulations.

Methods:

The study employed a multi-tiered graph-theoretic framework to represent protein structure across three interconnected levels. This model incorporated 19 top-level vertices, connected to intermediate graphs based on 6-angstrom proximity within the protein's 3D structure. Graph-theoretic molecular metrics were applied to weigh vertices and edges at all levels. The study also used Iterative Threading Assembly Refinement (I-TASSER) to model mutated sequences and molecular dynamic simulation (MD) tools to evaluate changes in protein folding and stability compared to the wildtype.

Results:

Three distinct predictive modeling and analytical approaches successfully identified structural and functional changes in the SARS-CoV-2 Spike RBD (Chain E) resulting from mutations. The novel graph-theoretic model detected notable structural changes, with N501Y and L452R showing the most pronounced effects on conformation and stability. K147N and E484A mutations demonstrated less significant impacts. Ab initio modeling and MD simulation findings corroborated the graph-theoretic analysis. The multi-level analytical approach provided a comprehensive visualization of mutation effects, deepening our understanding of their functional consequences.

Conclusions:

This study advanced our understanding of SARS-CoV-2 Spike RBD mutations and their implications. The multi-faceted approach characterized the effects of various mutations, identifying N501Y and L452R as having the most substantial impact on RBD conformation and stability. The findings have important implications for vaccine development, therapeutic design, and variant monitoring. This research underscores the power of combining multiple predictive analytical approaches in virology, contributing valuable knowledge to ongoing efforts against the COVID-19 pandemic and providing a framework for future studies on viral mutations and their impacts on protein structure and function.