AI Article Synopsis
- The paper presents OPUS-Rota, a new method for side-chain modeling that is both fast and accurate, outpacing most existing methods.
- In a comparison with well-known methods like SCWRL and NCN, OPUS-Rota achieves better accuracy while maintaining a similar speed to SCWRL, and has significantly lower runtime than others.
- OPUS-Rota demonstrates superiority in homology-modeling benchmarks and is offered freely for academic use, contributing to more precise structure refinement in research.
Article Abstract
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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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2525522 | PMC |
| http://dx.doi.org/10.1110/ps.035022.108 | DOI Listing |
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