ArticleNature communications2015
Evolutionary-guided de novo structure prediction of self-associated transmembrane helical proteins with near-atomic accuracy.
Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 39 citations in OpenAlex.
- Transmembrane Homodimers Interface Identification: Predicting Interface Residues in Alpha-Helical Transmembrane Protein Homodimers Using Sequential and Structural Features.International journal of molecular sciences · 2025Article
- TMKit: a Python interface for computational analysis of transmembrane proteins.Briefings in bioinformatics · 2023Article
- Deep transfer learning for inter-chain contact predictions of transmembrane protein complexes.Nature communications · 2023Article
- Computationally designed GPCR quaternary structures bias signaling pathway activation.Nature communications · 2022Article
- Molecular mechanism of interaction between fatty acid delta 6 desaturase and acyl-CoA by computational prediction.AMB Express · 2022Article
- Deep learning approaches for conformational flexibility and switching properties in protein design.Frontiers in molecular biosciences · 2022Review
- Coarse Grained Molecular Dynamic Simulations for the Study of TNF Receptor Family Members' Transmembrane Organization.Frontiers in cell and developmental biology · 2020Article
- Experimental determination and data-driven prediction of homotypic transmembrane domain interfaces.Computational and structural biotechnology journal · 2020Article
- Refinement of evolutionary medicine predictions based on clinical evidence for the manifestations of Mendelian diseases.Scientific reports · 2019Article
- Computational Nanoscopy of Tight Junctions at the Blood-Brain Barrier Interface.International journal of molecular sciences · 2019Review
- A lipophilicity-based energy function for membrane-protein modelling and design.PLoS computational biology · 2019Article
- Structural Model of the ETR1 Ethylene Receptor Transmembrane Sensor Domain.Scientific reports · 2019Article
- Interfaces Between Alpha-helical Integral Membrane Proteins: Characterization, Prediction, and Docking.Computational and structural biotechnology journal · 2019Article
- De novo designed transmembrane peptides activating the α5β1 integrin.Protein engineering, design & selection : PEDS · 2018Article
- NMR relaxation parameters of methyl groups as a tool to map the interfaces of helix-helix interactions in membrane proteins.Journal of biomolecular NMR · 2017Article
- Forecasting residue-residue contact prediction accuracy.Bioinformatics (Oxford, England) · 2017Article
- Enhanced unbiased sampling of protein dynamics using evolutionary coupling information.Scientific reports · 2017Article
- Rosetta Broker for membrane protein structure prediction: concentrative nucleoside transporter 3 and corticotropin-releasing factor receptor 1 test cases.BMC structural biology · 2017Article
- The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design.Journal of chemical theory and computation · 2017Article
- Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
How specific protein associations regulate the function of membrane receptors remains poorly understood. Conformational flexibility currently hinders the structure determination of several classes of membrane receptors and associated oligomers. Here we develop EFDOCK-TM, a general method to predict self-associated transmembrane protein helical (TMH) structures from sequence guided by co-evolutionary information. We show that accurate intermolecular contacts can be identified using a combination of protein sequence covariation and TMH binding surfaces predicted from sequence. When applied to diverse TMH oligomers, including receptors characterized in multiple conformational and functional states, the method reaches unprecedented near-atomic accuracy for most targets. Blind predictions of structurally uncharacterized receptor tyrosine kinase TMH oligomers provide a plausible hypothesis on the molecular mechanisms of disease-associated point mutations and binding surfaces for the rational design of selective inhibitors. The method sets the stage for uncovering novel determinants of molecular recognition and signalling in single-spanning eukaryotic membrane receptors.
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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.