ArticleProteins2021
Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14.
Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Computational development of multi-epitope vaccine to induce adaptive immunity against multi-drug resistant Prevotella intermedia.BMC infectious diseases · 2025Article
- ProT-VAE: Protein Transformer Variational AutoEncoder for functional protein design.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A new age in structural S-layer biology: Experimental and in silico milestones.The Journal of biological chemistry · 2025Review
- Virtual screening assisted identification of a phytocompound as potent inhibitor against Candida lusitaniae; an in-silico study.BMC infectious diseases · 2025Article
- Targeting vascular dementia: Molecular docking and dynamics of natural ligands against neuroprotective proteins.PloS one · 2025Article
- Exploring Conformational Landscapes Along Anharmonic Low-Frequency Vibrations.The journal of physical chemistry. B · 2024Article
- Predicting therapeutic and side effects from drug binding affinities to human proteome structures.iScience · 2024Article
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- Sequence, structure prediction, and epitope analysis of the polymorphic membrane protein family in Chlamydia trachomatis.PloS one · 2024Article
- Insights into virulence: structure classification of themSystems · 2023Article
- Insights into the recognition mechanism in the UBR box of UBR4 for its specific substrates.Communications biology · 2023Article
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- Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Enabling technology and core theory of synthetic biology.Science China. Life sciences · 2023Review
- Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers.Nucleic acids research · 2023Article
- Genetic manipulation of candidate phyla radiation bacteria provides functional insights into microbial dark matter.bioRxiv : the preprint server for biology · 2023Article
- Structural basis for sequence-independent substrate selection by eukaryotic wobble base tRNA deaminase ADAT2/3.Nature communications · 2022Article
- Protein Function Analysis through Machine Learning.Biomolecules · 2022Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The trRosetta structure prediction method employs deep learning to generate predicted residue-residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to sequence information) both language model embeddings and template information weighted by sequence similarity to the target. We also developed a refinement pipeline that recombines models generated by template-free and template utilizing versions of trRosetta guided by the DeepAccNet accuracy predictor. Both benchmark tests and CASP results show that the new pipeline is a considerable improvement over the original trRosetta, and it is faster and requires less computing resources, completing the entire modeling process in a median < 3 h in CASP14. Our human group improved results with this pipeline primarily by identifying additional homologous sequences for input into the network. We also used the DeepAccNet accuracy predictor to guide Rosetta high-resolution refinement for submissions in the regular and refinement categories; although performance was quite good on a CASP relative scale, the overall improvements were rather modest in part due to missing inter-domain or inter-chain contacts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.