I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction
Most proteins in cells are composed of multiple folding units (or domains) to perform
complex functions in a cooperative manner. Relative to the rapid progress in single-domain …
complex functions in a cooperative manner. Relative to the rapid progress in single-domain …
Modeling conformational states of proteins with AlphaFold
Many proteins exert their function by switching among different structures. Knowing the
conformational ensembles affiliated with these states is critical to elucidate key mechanistic …
conformational ensembles affiliated with these states is critical to elucidate key mechanistic …
Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations
Structure prediction for proteins lacking homologous templates in the Protein Data Bank
(PDB) remains a significant unsolved problem. We developed a protocol, CI-TASSER, to …
(PDB) remains a significant unsolved problem. We developed a protocol, CI-TASSER, to …
[HTML][HTML] Machine learning in protein structure prediction
M AlQuraishi - Current opinion in chemical biology, 2021 - Elsevier
Prediction of protein structure from sequence has been intensely studied for many decades,
owing to the problem's importance and its uniquely well-defined physical and computational …
owing to the problem's importance and its uniquely well-defined physical and computational …
Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data
Leveraging iterative alignment search through genomic and metagenome sequence
databases, we report the DeepMSA2 pipeline for uniform protein single-and multichain …
databases, we report the DeepMSA2 pipeline for uniform protein single-and multichain …
Transformer protein language models are unsupervised structure learners
Unsupervised contact prediction is central to uncovering physical, structural, and functional
constraints for protein structure determination and design. For decades, the predominant …
constraints for protein structure determination and design. For decades, the predominant …
Self-play reinforcement learning guides protein engineering
Y Wang, H Tang, L Huang, L Pan, L Yang… - Nature Machine …, 2023 - nature.com
Designing protein sequences towards desired properties is a fundamental goal of protein
engineering, with applications in drug discovery and enzymatic engineering. Machine …
engineering, with applications in drug discovery and enzymatic engineering. Machine …
Toward the solution of the protein structure prediction problem
Since Anfinsen demonstrated that the information encoded in a protein's amino acid
sequence determines its structure in 1973, solving the protein structure prediction problem …
sequence determines its structure in 1973, solving the protein structure prediction problem …
Deep learning techniques have significantly impacted protein structure prediction and protein design
HighlightsThe recent use of deep learning has dramatically improved the accuracy of non-
homologous protein structure modeling.Protein structure prediction problem was largely …
homologous protein structure modeling.Protein structure prediction problem was largely …