National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Bioinformatics. 2011 Mar 15;27(6):785-90. doi: 10.1093/bioinformatics/btr009. Epub 2011 Jan 6.
Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.
We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling.
CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html.
侧链建模在计算结构生物学中得到了广泛的应用。大多数流行的侧链建模程序都使用离散的刚性旋转异构体来探索构象空间，以提高速度和效率。然而，在蛋白质内部的紧密堆积环境中，这些方法将不可避免地导致原子碰撞，并阻碍预测准确性。
我们提出了一种侧链建模方法（CIS-RR），它将一种新颖的基于冲突检测的迭代搜索（CIS）算法与连续的旋转异构体扭转空间优化（RR）相结合。基准测试表明，与现有的流行的侧链建模方法相比，CIS-RR 更有效地消除了原子碰撞，并实现了可比甚至更好的预测准确性，同时具有可比的计算成本。我们相信，CIS-RR 可以成为一种用于准确侧链建模的有用方法。
CIS-RR 可在我们的网站上供非商业用户使用：http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html。
