SYSTEM AND METHOD FOR PROVIDING NEOANTIGEN IMMUNOTHERAPY INFORMATION BY USING ARTIFICIAL-INTELLIGENCE-MODEL-BASED MOLECULAR DYNAMICS BIG DATA

摘要

The present invention relates to a system and method for predicting, based on molecular dynamics, a neoantigen and immune response induction, in which, by producing a neoantigen candidate group through genomic mutations, and then predicting MHC-antigen binding affinity for neoantigen candidates through molecular dynamics, the induction of immunity against a neoantigen with high binding potential can be verified. The present invention provides a method for providing neoantigen immunotherapy information for discovering a neoantigen by using AI-based molecular dynamics big data, the method comprising the steps of: (A) producing a neoantigen candidate group through genomic mutations; (B) filtering specificity of the neoantigen candidate group by tissues and diseases; (C) predicting in silico binding between a neoantigen and MHC; and (D) calculating and ranking TCR activities. According to such a present invention, precision medical technology combined with AI deep learning using big data of the present invention can contribute to medical industrialization of a specific neoantigen prediction technique customized for patients.