AlphaFold2 and its applications in the fields of biology and medicine
Z Yang, X Zeng, Y Zhao, R Chen - Signal Transduction and Targeted …, 2023 - nature.com
Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …
Synthetic biology: bottom-up assembly of molecular systems
The bottom-up assembly of biological and chemical components opens exciting
opportunities to engineer artificial vesicular systems for applications with previously unmet …
opportunities to engineer artificial vesicular systems for applications with previously unmet …
Therapeutics data commons: Machine learning datasets and tasks for drug discovery and development
Therapeutics machine learning is an emerging field with incredible opportunities for
innovatiaon and impact. However, advancement in this field requires formulation of …
innovatiaon and impact. However, advancement in this field requires formulation of …
Deep learning-based prediction of the T cell receptor–antigen binding specificity
Neoantigens play a key role in the recognition of tumour cells by T cells; however, only a
small proportion of neoantigens truly elicit T-cell responses, and few clues exist as to which …
small proportion of neoantigens truly elicit T-cell responses, and few clues exist as to which …
AlphaFold, artificial intelligence (AI), and allostery
R Nussinov, M Zhang, Y Liu, H Jang - The Journal of Physical …, 2022 - ACS Publications
AlphaFold has burst into our lives. A powerful algorithm that underscores the strength of
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …
biological sequence data and artificial intelligence (AI). AlphaFold has appended projects …
Antibody structure prediction using interpretable deep learning
Therapeutic antibodies make up a rapidly growing segment of the biologics market.
However, rational design of antibodies is hindered by reliance on experimental methods for …
However, rational design of antibodies is hindered by reliance on experimental methods for …
Fast end-to-end learning on protein surfaces
Proteins' biological functions are defined by the geometric and chemical structure of their 3D
molecular surfaces. Recent works have shown that geometric deep learning can be used on …
molecular surfaces. Recent works have shown that geometric deep learning can be used on …
Structure-based protein design with deep learning
S Ovchinnikov, PS Huang - Current opinion in chemical biology, 2021 - Elsevier
Since the first revelation of proteins functioning as macromolecular machines through their
three dimensional structures, researchers have been intrigued by the marvelous ways the …
three dimensional structures, researchers have been intrigued by the marvelous ways the …
[HTML][HTML] Deep generative modeling for protein design
A Strokach, PM Kim - Current opinion in structural biology, 2022 - Elsevier
Deep learning approaches have produced substantial breakthroughs in fields such as
image classification and natural language processing and are making rapid inroads in the …
image classification and natural language processing and are making rapid inroads in the …
In silico proof of principle of machine learning-based antibody design at unconstrained scale
Generative machine learning (ML) has been postulated to become a major driver in the
computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to …
computational design of antigen-specific monoclonal antibodies (mAb). However, efforts to …