Publications by authors named "Yan Jeronimo Gomes Lobo"
Article Synopsis
- Molecular dynamics (MD) simulations generate complex data that are challenging to analyze with traditional methods; however, combining this with deep learning allows for better understanding of structural changes in proteins, such as those caused by mutations.
- The study specifically focuses on the SARS-CoV-2 spike protein's receptor-binding domain (RBD), using distance maps and deep convolutional neural networks to predict how point mutations affect the virus's infectivity and ability to evade immune responses.
- Results showed promising predictive success regarding mutant types that enhance receptor affinity and reduce immunogenicity, with significant correlations found between simulation data and binding free energy changes, potentially aiding in identifying more infectious and immune-evasive strains of the virus.
E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces.
Vitor Pimentel Dos Santos André Rodrigues Gabriel Dutra Luana Bastos Diego Mariano Yan Jerônimo Gomes Lobo
PeerJ
January 2023
Background: The SARS-CoV-2 pandemic reverberated, posing health and social hygiene obstacles throughout the globe. Mutant lineages of the virus have concerned scientists because of convergent amino acid alterations, mainly on the viral spike protein. Studies have shown that mutants have diminished activity of neutralizing antibodies and enhanced affinity with its human cell receptor, the ACE2 protein.
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