Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations

This dataset encompasses and describes the following features:

• Mutations in viruses like SARS-CoV-2 can make them escape vaccines and treatments.
• Accurately predicting these mutations is crucial for developing effective countermeasures.
• The study uses a type of AI called a Generative Adversarial Network (GAN) to analyze the virus's spike protein, which plays a key role in infection.
• The GAN generates protein sequences similar to natural ones, but which are also likely to evade immune responses.
• By analyzing these generated sequences, the researchers improve their AI model's ability to predict real-world escape mutations.
• This improved prediction could help design better vaccines and treatments, and prepare for future viral threats.