Alphafold3 | Awesome Repository

AlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep learning system to predict the three-dimensional shapes of proteins, DNA, RNA, and ligands.

The system functions as a diffusion-based protein folding model that predicts the spatial coordinates of biomolecular atoms and interactions. It utilizes a GPU-accelerated inference pipeline to process genetic sequences and structural templates for molecular modeling.

The project covers structural bioinformatics analysis and protein interaction modeling to determine the physical arrangement of atoms within complex biomolecular assemblies. It incorporates a computational biology workflow that manages data pipelines and model inference.

Features

Structure Prediction Models - Predicts the 3D shapes of biomolecular interactions using a deep learning inference pipeline.
Diffusion-Based 3D Generators - Uses a denoising diffusion process to generate 3D atomic coordinates and structured molecular shapes.
GPU-Accelerated Inference - Utilizes GPU acceleration to compute structural predictions from complex biomolecular input data.
Diffusion Models - Generative model using a diffusion architecture to predict spatial coordinates of biomolecular atoms.

Features

Structure Prediction Models - Predicts the 3D shapes of biomolecular interactions using a deep learning inference pipeline.
Diffusion-Based 3D Generators - Uses a denoising diffusion process to generate 3D atomic coordinates and structured molecular shapes.
GPU-Accelerated Inference - Utilizes GPU acceleration to compute structural predictions from complex biomolecular input data.
Diffusion Models - Generative model using a diffusion architecture to predict spatial coordinates of biomolecular atoms.