Publication | Open Access
OPUS‐Rota: A fast and accurate method for side‐chain modeling
64
Citations
45
References
2008
Year
EngineeringMachine LearningSequence AlignmentNatural Language ProcessingData ScienceBenchmark StudyComputational LinguisticsBenchmark ComparisonOverall ChiSequence ModellingBenchmark DatasetsComputer EngineeringSequence IdentityComputer ScienceBioinformaticsComputational ScienceComputational BiologySystems BiologySide‐chain ModelingTheoretical ModelingData Modeling
In this paper, we introduce a fast and accurate side-chain modeling method, named OPUS-Rota. In a benchmark comparison with the methods SCWRL, NCN, LGA, SPRUCE, Rosetta, and SCAP, OPUS-Rota is shown to be much faster than all the methods except SCWRL, which is comparably fast. In terms of overall chi (1) and chi (1+2) accuracies, however, OPUS-Rota is 5.4 and 8.8 percentage points better, respectively, than SCWRL. Compared with NCN, which has the best accuracy in the literature, OPUS-Rota is 1.6 percentage points better for overall chi (1+2) but 0.3 percentage points weaker for overall chi (1). Hence, our algorithm is much more accurate than SCWRL with similar execution speed, and it has accuracy comparable to or better than the most accurate methods in the literature, but with a runtime that is one or two orders of magnitude shorter. In addition, OPUS-Rota consistently outperforms SCWRL on the Wallner and Elofsson homology-modeling benchmark set when the sequence identity is greater than 40%. We hope that OPUS-Rota will contribute to high-accuracy structure refinement, and the computer program is freely available for academic users.
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