Protein structure optimization by side-chain positioning via beta-complex
Journal of Global Optimization
| Hi-index | 3.84 |
Motivation: Modeling of side chain conformations constitutes an indispensable effort in protein structure modeling, protein–protein docking and protein design. Thanks to an intensive attention to this field, many of the existing programs can achieve reasonably good and comparable prediction accuracy. Moreover, in our previous work on CIS-RR, we argued that the prediction with few atomic clashes can complement the current existing methods for subsequent analysis and refinement of protein structures. However, these recent efforts to enhance the quality of predicted side chains have been accompanied by a significant increase of computational cost. Results: In this study, by mainly focusing on improving the speed of side chain conformation prediction, we present a RApid Side-chain Predictor, called RASP. To achieve a much faster speed with a comparable accuracy to the best existing methods, we not only employ the clash elimination strategy of CIS-RR, but also carefully optimize energy terms and integrate different search algorithms. In comprehensive benchmark testings, RASP is over one order of magnitude faster (~ 40 times over CIS-RR) than the recently developed methods, while achieving comparable or even better accuracy. Availability: RASP is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/rasp/rasp Contact: taijiao@moon.ibp.ac.cn Supplementary Information: Supplementary information is available at Bioinformatics online.