Яндекс Метрика
Биология и ИИ

ProteinReDiff

FPT Software AI Center,University of Chicago,Indiana State University
Protein design

Передовой ИИ-фреймворк, созданный для проектирования белков и ускорения разработки новых лекарств. Модель использует диффузионные алгоритмы для точного редизайна структур, способных связываться с терапевтическими мишенями.

Proteins, serving as the fundamental architects of biological processes, interact with ligands to perform a myriad of functions essential for life. Designing functional ligand-binding proteins is pivotal for advancing drug development and enhancing therapeutic efficacy. In this study, we introduce ProteinReDiff, an efficient computational framework targeting the redesign of ligand-binding proteins. Using equivariant diffusion-based generative models, ProteinReDiff enables the creation of high-affinity ligand-binding proteins without the need for detailed structural information, leveraging instead the potential of initial protein sequences and ligand SMILES strings. Our evaluations across sequence diversity, structural preservation, and ligand binding affinity underscore ProteinReDiff’s potential to advance computational drug discovery and protein engineering. Our source code is publicly available at https: //github.com/HySonLab/Protein_Redesign.

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