ArticleBioinformatics (Oxford, England)2016
3DRobot: automated generation of diverse and well-packed protein structure decoys.
Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed.
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- Deep Learning Enables Automatic Correction of Experimental HDX-MS Data with Applications in Protein Modeling.Journal of the American Society for Mass Spectrometry · 2024Article
- Structural Shifts of the Parvovirus B19 Capsid Receptor-binding Domain: A Peptide Study.Protein and peptide letters · 2024Article
- Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction.Science advances · 2023Article
- AlphaFold2 Model Refinement Using Structure Decoys.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- De novo protein fold design through sequence-independent fragment assembly simulations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Construction of a Deep Neural Network Energy Function for Protein Physics.Journal of chemical theory and computation · 2022Article
- Equilibrium Between Dimeric and Monomeric Forms of Human Epidermal Growth Factor is Shifted Towards Dimers in a Solution.The protein journal · 2022Article
- A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models.Bioengineering (Basel, Switzerland) · 2022Article
- An integrated protein structure fitness scoring approach for identifying native-like model structures.Computational and structural biotechnology journal · 2022Article
- Molecular free energy optimization on a computational graph.RSC advances · 2021Article
- DE-STRESS: a user-friendly web application for the evaluation of protein designs.Protein engineering, design & selection : PEDS · 2021Article
- Representations of protein structure for exploring the conformational space: A speed-accuracy trade-off.Computational and structural biotechnology journal · 2021Article
- Differentiable molecular simulation can learn all the parameters in a coarse-grained force field for proteins.PloS one · 2021Article
- A method for validating the accuracy of NMR protein structures.Nature communications · 2020Article
- Using physical features of protein core packing to distinguish real proteins from decoys.Protein science : a publication of the Protein Society · 2020Article
- Machine Learning Approaches for Quality Assessment of Protein Structures.Biomolecules · 2020Review
- Neighborhood Preference of Amino Acids in Protein Structures and its Applications in Protein Structure Assessment.Scientific reports · 2020Article
- Accurate prediction of chemical shifts for aqueous protein structure on "Real World" data.Chemical science · 2020Article
- SPECS: Integration of side-chain orientation and global distance-based measures for improved evaluation of protein structural models.PloS one · 2020Article
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3 authors.
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Abstract
motivationComputationally generated non-native protein structure conformations (or decoys) are often used for designing protein folding simulation methods and force fields. However, almost all the decoy sets currently used in literature suffer from uneven root mean square deviation (RMSD) distribution with bias to non-protein like hydrogen-bonding and compactness patterns. Meanwhile, most protein decoy sets are pre-calculated and there is a lack of methods for automated generation of high-quality decoys for any target proteins.
resultsWe developed a new algorithm, 3DRobot, to create protein structure decoys by free fragment assembly with enhanced hydrogen-bonding and compactness interactions. The method was benchmarked with three widely used decoy sets from ab initio folding and comparative modeling simulations. The decoys generated by 3DRobot are shown to have significantly enhanced diversity and evenness with a continuous distribution in the RMSD space. The new energy terms introduced in 3DRobot improve the hydrogen-bonding network and compactness of decoys, which eliminates the possibility of native structure recognition by trivial potentials. Algorithms that can automatically create such diverse and well-packed non-native conformations from any protein structure should have a broad impact on the development of advanced protein force field and folding simulation methods. AVAILIABLITY AND IMPLEMENTATION: http://zhanglab.ccmb.med.umich.edu/3DRobot/ CONTACT: jiay@phy.ccnu.edu.cn; zhng@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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