Guo Yu-Zhen, Feng En-Min, Wang Yong
Department of Applied Mathematics, Dalian University of Technology, Dalian 116024, PRC.
J Chem Phys. 2006 Oct 21;125(15):154102. doi: 10.1063/1.2357950.
Determining the functional conformation of a protein from its amino acid sequence remains a central problem in computational biology. In this paper, we establish the mathematical optimal model of protein folding problem (PFP) on two-dimensional space based on the minimal energy principle. A novel hybrid of elastic net algorithm and local search method (ENLS) is applied successfully to simulations of protein folding on two-dimensional hydrophobic-polar (HP) lattice model. Eight HP benchmark instances with up to 64 amino acids are tested to verify the effectiveness of proposed approach and model. In several cases, the ENLS method finds new lower energy states. The numerical results show that it is drastically superior to other methods in finding the ground state of a protein.
从氨基酸序列确定蛋白质的功能构象仍然是计算生物学中的核心问题。在本文中,我们基于最小能量原理建立了二维空间中蛋白质折叠问题(PFP)的数学优化模型。一种新颖的弹性网络算法与局部搜索方法的混合算法(ENLS)成功应用于二维疏水-极性(HP)晶格模型上的蛋白质折叠模拟。测试了八个包含多达64个氨基酸的HP基准实例,以验证所提出方法和模型的有效性。在几种情况下,ENLS方法发现了新的低能量状态。数值结果表明,在寻找蛋白质基态方面,它比其他方法具有显著优势。