[ protein design in the age of artificial intelligence].

Proteins with specific functions and characteristics play a crucial role in biomedicine and nanotechnology. protein design enables the customization of sequences to produce proteins with desired structures that do not exist in the nature. In recent years, with the rapid development of artificial intelligence (AI), deep learning-based generative models have increasingly become powerful tools, enabling the design of functional proteins with atomic-level precision.

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable clues for in-depth exploration of molecular-level biological processes. Protein-protein docking technology is widely used to simulate the spatial structure of proteins. However, there are still challenges in selecting candidate decoys that closely resemble the native structure from protein-protein docking simulations.

Empirical validation of ProteinMPNN's efficiency in enhancing protein fitness.

Protein engineering, which aims to improve the properties and functions of proteins, holds great research significance and application value. However, current models that predict the effects of amino acid substitutions often perform poorly when evaluated for precision. Recent research has shown that ProteinMPNN, a large-scale pre-training sequence design model based on protein structure, performs exceptionally well.

Tpgen: a language model for stable protein design with a specific topology structure.

Background: Natural proteins occupy a small portion of the protein sequence space, whereas artificial proteins can explore a wider range of possibilities within the sequence space. However, specific requirements may not be met when generating sequences blindly. Research indicates that small proteins have notable advantages, including high stability, accurate resolution prediction, and facile specificity modification.