ArticleProtein science : a publication of the Protein Society2018
OPUS-CSF: A C-atom-based scoring function for ranking protein structural models.
Article in Protein science : a publication of the Protein Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- OPUS-Mut: Studying the Effect of Protein Mutation through Side-Chain Modeling.Journal of chemical theory and computation · 2023Article
- OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.Briefings in bioinformatics · 2022Article
- Secondary structure specific simpler prediction models for protein backbone angles.BMC bioinformatics · 2022Article
- Enhancing protein backbone angle prediction by using simpler models of deep neural networks.Scientific reports · 2020Article
- Computational reconstruction of atomistic protein structures from coarse-grained models.Computational and structural biotechnology journal · 2020Review
- A simple neural network implementation of generalized solvation free energy for assessment of protein structural models.RSC advances · 2019Article
- OPUS-SSF: A side-chain-inclusive scoring function for ranking protein structural models.Protein science : a publication of the Protein Society · 2019Article
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5 authors.
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Abstract
We report a C-atom-based scoring function, named OPUS-CSF, for ranking protein structural models. Rather than using traditional Boltzmann formula, we built a scoring function (CSF score) based on the native distributions (derived from the entire PDB) of coordinate components of mainchain C (carbonyl) atoms on selected residues of peptide segments of 5, 7, 9, and 11 residues in length. In testing OPUS-CSF on decoy recognition, it maximally recognized 257 native structures out of 278 targets in 11 commonly used decoy sets, significantly outperforming other popular all-atom empirical potentials. The average correlation coefficient with TM-score was also comparable with those of other potentials. OPUS-CSF is a highly coarse-grained scoring function, which only requires input of partial mainchain information, and very fast. Thus, it is suitable for applications at early stage of structural building.
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