Can we predict T cell specificity with digital biology and machine learning?
Recent advances in machine learning and experimental biology have offered breakthrough
solutions to problems such as protein structure prediction that were long thought to be …
solutions to problems such as protein structure prediction that were long thought to be …
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 …
Accurate structure prediction of biomolecular interactions with AlphaFold 3
The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of
proteins and their interactions, enabling a huge range of applications in protein modelling …
proteins and their interactions, enabling a huge range of applications in protein modelling …
Evolutionary-scale prediction of atomic-level protein structure with a language model
Recent advances in machine learning have leveraged evolutionary information in multiple
sequence alignments to predict protein structure. We demonstrate direct inference of full …
sequence alignments to predict protein structure. We demonstrate direct inference of full …
[HTML][HTML] Programmable protein delivery with a bacterial contractile injection system
Endosymbiotic bacteria have evolved intricate delivery systems that enable these organisms
to interface with host biology. One example, the extracellular contractile injection systems …
to interface with host biology. One example, the extracellular contractile injection systems …
Learning inverse folding from millions of predicted structures
We consider the problem of predicting a protein sequence from its backbone atom
coordinates. Machine learning approaches to this problem to date have been limited by the …
coordinates. Machine learning approaches to this problem to date have been limited by the …
OpenFold: Retraining AlphaFold2 yields new insights into its learning mechanisms and capacity for generalization
AlphaFold2 revolutionized structural biology with the ability to predict protein structures with
exceptionally high accuracy. Its implementation, however, lacks the code and data required …
exceptionally high accuracy. Its implementation, however, lacks the code and data required …
Equibind: Geometric deep learning for drug binding structure prediction
Predicting how a drug-like molecule binds to a specific protein target is a core problem in
drug discovery. An extremely fast computational binding method would enable key …
drug discovery. An extremely fast computational binding method would enable key …
High-resolution de novo structure prediction from primary sequence
Recent breakthroughs have used deep learning to exploit evolutionary information in
multiple sequence alignments (MSAs) to accurately predict protein structures. However …
multiple sequence alignments (MSAs) to accurately predict protein structures. However …
ColabFold: making protein folding accessible to all
ColabFold offers accelerated prediction of protein structures and complexes by combining
the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold's 40− 60 …
the fast homology search of MMseqs2 with AlphaFold2 or RoseTTAFold. ColabFold's 40− 60 …