Protein structure prediction using the hybrid energy function, fragment assembly and double optimization
Protein structure prediction using the hybrid energy function, fragment assembly and double optimization
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DOI：
10.3938/jkps.52.143
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发表时间：
2008-01-01
影响因子：
0.6
通讯作者：
Kim, Taek-Kyun
中科院分区：
文献类型：
--
作者：
Cho, Kwang-Hwi;Lee, Julian;Kim, Taek-Kyun
我们通过结合混合能量函数、片段组装和双重优化来进行蛋白质结构预测。在混合能量函数中，所有的主链原子都被明确地描述，但为了减少计算成本，侧链被建模为几个相互作用中心。该方法利用序列特征的相似性从结构数据库中获取主干的局部结构，通过能量最小化来确定片段的全局三级填充，从而减小了搜索空间。采用双优化方法获得能量最小的结构，其中利用构象空间退火（CSA）方法获得能量最小的主链片段组合，利用模拟退火方法获得给定主链结构的最优侧链。我们通过对属于不同结构类的两个蛋白质1bdd和1e01进行测试预测来证明我们方法的可行性。
We perform protein structure prediction by combining a hybrid energy function, fragment assembly, and double optimization. In the hybrid energy function, all the backbone atoms are described explicitly, but the side-chain is modeled as a few interaction centers in order to reduce computational costs. We reduce the search space by using a fragment assembly method, where the local structure of the backbone is obtained from a structural database using similarity of sequence features, and only the global tertiary packing of fragments is determined by minimizing the energy. The structure with the minimum energy is obtained using double optimization, where a combination of backbone fragments with minimum energy is obtained using the conformational space annealing (CSA) method, and the optimal side-chains for a given backbone structure are obtained using simulated annealing. We show the feasibility of our method by performing test predictions on two proteins, 1bdd and 1e01, that belong to distinct structural classes.