SARS-CoV-2 Mutation Detail Information

Virus Mutation SARS-CoV-2 Mutation G446S


Basic Characteristics of Mutations
Mutation Site G446S
Mutation Site Sentence The model's ability of predicting the impact of the G446S mutation on fitness, despite the complexity of correlating complete immune escape from REGN10987 to fitness, highlights the potential of our model to predict effects of unseen mutations.
Mutation Level Amino acid level
Mutation Type Nonsynonymous substitution
Gene/Protein/Region RBD
Standardized Encoding Gene S  
Genotype/Subtype Wuhan-Hu-1;Omicron(BA.1)
Viral Reference MN908947
Functional Impact and Mechanisms
Disease -
Immune -
Target Gene -
Clinical and Epidemiological Correlations
Clinical Information -
Treatment -
Location -
Literature Information
PMID 38820002
Title Biophysical principles predict fitness of SARS-CoV-2 variants
Author Wang D,Huot M,Mohanty V,Shakhnovich EI
Journal Proceedings of the National Academy of Sciences of the United States of America
Journal Info 2024 Jun 4;121(23):e2314518121
Abstract SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the identification of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by dissociation constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto an epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low-frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.
Sequence Data -
Mutation Information
Note
Basic Characteristics of Mutations
  • Mutation Site: The specific location in a gene or protein sequence where a change occurs.
  • Mutation Level: The level at which a mutation occurs, including the nucleotide or amino acid level.
  • Mutation Type: The nature of the mutation, such as missense mutation, nonsense mutation, synonymous mutation, etc.
  • Gene/Protein/Region: Refers to the specific region of the virus where the mutation occurs. Including viral genes, viral proteins, or a specific viral genome region. If the article does not specifically indicate the relationship between the mutation and its correspondence, the main
  • Gene/Protein/Region studied in the article is marked.
  • Genotype/Subtype: Refers to the viral genotype or subtype where the mutation occurs. If the article does not specifically indicate the relationship between the mutation and its correspondence, the main Genotype/Subtype studied in the article is marked.
  • Viral Reference: Refers to the standard virus strain used to compare and analyze viral sequences.
Functional Impact and Mechanisms
  • Disease: An abnormal physiological state with specific symptoms and signs caused by viral infection.
  • Immune: The article focuses on the study of mutations and immune.
  • Target Gene: Host genes that viral mutations may affect.
Clinical and Epidemiological Correlations
  • Clinical Information: The study is a clinical or epidemiological study and provides basic information about the population.
  • Treatment: The study mentioned a certain treatment method, such as drug resistance caused by mutations. If the study does not specifically indicate the relationship between mutations and their correspondence treatment, the main treatment studied in the article is marked.
  • Location: The source of the research data.
Literature Information
  • Sequence Data: The study provides the data accession number.