Directed evolution: methodologies and applications
Directed evolution aims to expedite the natural evolution process of biological molecules
and systems in a test tube through iterative rounds of gene diversifications and library …
and systems in a test tube through iterative rounds of gene diversifications and library …
Deep generative molecular design reshapes drug discovery
Recent advances and accomplishments of artificial intelligence (AI) and deep generative
models have established their usefulness in medicinal applications, especially in drug …
models have established their usefulness in medicinal applications, especially in drug …
Illuminating protein space with a programmable generative model
Three billion years of evolution has produced a tremendous diversity of protein molecules,
but the full potential of proteins is likely to be much greater. Accessing this potential has …
but the full potential of proteins is likely to be much greater. Accessing this potential has …
Disease variant prediction with deep generative models of evolutionary data
Quantifying the pathogenicity of protein variants in human disease-related genes would
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …
Efficient evolution of human antibodies from general protein language models
Natural evolution must explore a vast landscape of possible sequences for desirable yet
rare mutations, suggesting that learning from natural evolutionary strategies could guide …
rare mutations, suggesting that learning from natural evolutionary strategies could guide …
Progen2: exploring the boundaries of protein language models
Attention-based models trained on protein sequences have demonstrated incredible
success at classification and generation tasks relevant for artificial-intelligence-driven …
success at classification and generation tasks relevant for artificial-intelligence-driven …
Language models enable zero-shot prediction of the effects of mutations on protein function
Modeling the effect of sequence variation on function is a fundamental problem for
understanding and designing proteins. Since evolution encodes information about function …
understanding and designing proteins. Since evolution encodes information about function …
Mega-scale experimental analysis of protein folding stability in biology and design
Advances in DNA sequencing and machine learning are providing insights into protein
sequences and structures on an enormous scale. However, the energetics driving folding …
sequences and structures on an enormous scale. However, the energetics driving folding …
Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure
Most known pathogenic mutations occur in protein-coding regions of DNA and change the
way proteins are made. Taking protein structure into account has therefore provided great …
way proteins are made. Taking protein structure into account has therefore provided great …
Protein remote homology detection and structural alignment using deep learning
Exploiting sequence–structure–function relationships in biotechnology requires improved
methods for aligning proteins that have low sequence similarity to previously annotated …
methods for aligning proteins that have low sequence similarity to previously annotated …