Huang Wenqi, Liu Jingfa
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Biopolymers. 2006 Jun 5;82(2):93-8. doi: 10.1002/bip.20400.
We studied a three-dimensional off-lattice AB model with two species of monomers, hydrophobic (A) and hydrophilic (B), and present two optimization algorithms: face-centered-cubic (FCC)-lattice pruned-enriched-Rosenbluth method (PERM) and subsequent conjugate gradient (PERM++) minimization and heuristic conjugate gradient (HCG) simulation based on "off-trap" strategy. In PERM++, we apply the PERM to the FCC-lattice to produce the initial conformation, and conjugate gradient minimization is then used to reach the minimum energy state. Both algorithms have been tested in the three-dimensional AB model for all sequences with lengths 13 < or = n < or = 55. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. In several cases, we renew the putative ground states energy values.
我们研究了一种具有两种单体(疏水单体A和亲水单体B)的三维非晶格AB模型,并提出了两种优化算法:面心立方(FCC)晶格修剪富集罗森布鲁斯方法(PERM)以及基于“脱阱”策略的后续共轭梯度(PERM++)最小化和启发式共轭梯度(HCG)模拟。在PERM++中,我们将PERM应用于FCC晶格以生成初始构象,然后使用共轭梯度最小化来达到最低能量状态。这两种算法均已在三维AB模型中针对所有长度为13≤n≤55的序列进行了测试。数值结果表明,所提出的方法在寻找蛋白质基态方面非常有前景。在几种情况下,我们更新了假定的基态能量值。