SYSTEMS AND METHODS FOR DYNAMIC-BACKBONE PROTEIN-LIGAND STRUCTURE PREDICTION WITH MULTISCALE GENERATIVE DIFFUSION MODELS
개요
출원인
Iambic Therapeutics, Inc.; CALIFORNIA INSTITUTE OF TECHNOLOGY; NVIDIA CORPORATION
발명자
Weili NIE; Arash VAHDAT; Zhuoran QIAO; Thomas F. MILLER; Animashree ANANDKUMAR; Matthew G. WELBORN
IPC 분류
CPC 분류
In some aspects, the present disclosure provides a method for generating a geometrical structure of a binding complex formed between a protein and a ligand. In some embodiments, the method comprises sampling an initial geometrical structure of the binding complex from a geometry prior. In some embodiments, the method comprises denoising, using a machine-learned stochastic differential equation (SDE), the initial geometrical structure to generate the geometrical structure of the binding complex.
원문 (중국어)
In some aspects, the present disclosure provides a method for generating a geometrical structure of a binding complex formed between a protein and a ligand. In some embodiments, the method comprises sampling an initial geometrical structure of the binding complex from a geometry prior. In some embodiments, the method comprises denoising, using a machine-learned stochastic differential equation (SDE), the initial geometrical structure to generate the geometrical structure of the binding complex.