A new age in protein design empowered by deep learning
The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of proteins. Along with novel architectures for generative modeling and sequence analysis, they have revolutionized the protein design field in the past few years remarkably by improving the accuracy and ability to identify novel protein sequences and structures. Deep neural networks can now learn and extract the fundamental features of protein structures, predict how they interact with other biomolecules, and have the potential to create new effective drugs for treating disease. As their applicability in protein design is rapidly growing, we review the recent developments and technology in deep learning methods and provide examples of their performance to generate novel functional proteins.
WOS:001113744900001
2023-11-15
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Funder | Grant Number |
French Agence Nationale de la Recherche (ANR) | ANR-22-CPJ2-0075-01 |
European Union | 945363 |
Microsoft Research AI4Science | |
Swiss National Science Foundation | |
NCCR in Chemical Biology | |
NCCR in Molecular Systems Engineering | |
ERC | 716058 |