Machine learning-guided protein engineering
Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …
machine learning methods. These methods leverage existing experimental and simulation …
Machine learning for functional protein design
Recent breakthroughs in AI coupled with the rapid accumulation of protein sequence and
structure data have radically transformed computational protein design. New methods …
structure data have radically transformed computational protein design. New methods …
Graph denoising diffusion for inverse protein folding
Inverse protein folding is challenging due to its inherent one-to-many mapping
characteristic, where numerous possible amino acid sequences can fold into a single …
characteristic, where numerous possible amino acid sequences can fold into a single …
Scientific large language models: A survey on biological & chemical domains
Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …
natural language comprehension, representing a significant stride toward artificial general …
AlphaFold2 and deep learning for elucidating enzyme conformational flexibility and its application for design
The recent success of AlphaFold2 (AF2) and other deep learning (DL) tools in accurately
predicting the folded three-dimensional (3D) structure of proteins and enzymes has …
predicting the folded three-dimensional (3D) structure of proteins and enzymes has …
Dinoiser: Diffused conditional sequence learning by manipulating noises
While diffusion models have achieved great success in generating continuous signals such
as images and audio, it remains elusive for diffusion models in learning discrete sequence …
as images and audio, it remains elusive for diffusion models in learning discrete sequence …
AI models for protein design are driving antibody engineering
MF Chungyoun, JJ Gray - Current Opinion in Biomedical Engineering, 2023 - Elsevier
Therapeutic antibody engineering seeks to identify antibody sequences with specific binding
to a target and optimized drug-like properties. When guided by deep learning, antibody …
to a target and optimized drug-like properties. When guided by deep learning, antibody …
De novo protein design using geometric vector field networks
Innovations like protein diffusion have enabled significant progress in de novo protein
design, which is a vital topic in life science. These methods typically depend on protein …
design, which is a vital topic in life science. These methods typically depend on protein …
Diffusion language models can perform many tasks with scaling and instruction-finetuning
The recent surge of generative AI has been fueled by the generative power of diffusion
probabilistic models and the scalable capabilities of large language models. Despite their …
probabilistic models and the scalable capabilities of large language models. Despite their …
Structure-informed protein language models are robust predictors for variant effects
Emerging variant effect predictors, protein language models (pLMs) learn evolutionary
distribution of functional sequences to capture fitness landscape. Considering that variant …
distribution of functional sequences to capture fitness landscape. Considering that variant …