用全局Optimization模拟蛋白质构象
Simulating Protein Conformations through Global Optimization
摘要：
半个多世纪以来，人们对蛋白质折叠问题进行了大量的研究。蛋白质折叠确实是科学中未解决的主要问题之一。在这项工作中，我们讨论了蛋白质构象的模拟模型。这个简单的模型是基于这样的想法，即对代表蛋白质构象骨架的原子链施加很少的几何要求。该模型导致制定的全球最优化问题，其解决方案对应于满足所需要求的构象。全局最优化问题采用最近提出的猴子搜索算法求解。最优化问题的简单性和所使用的元启发式搜索的有效性允许模拟大量的高质量构象。我们表明，即使只有很少的几何要求，一些模拟构象的结果是类似的（在RMSD方面）真正的蛋白质的构象实际上在自然界中。
英文摘要：
Many researches have been working on the protein folding problem from more than half century. Protein folding is indeed one of the major unsolved problems in science. In this work, we discuss a model for the simulation of protein conformations. This simple model is based on the idea of imposing few geometric requirements on chains of atoms representing the backbone of a protein conformation. The model leads to the formulation of a global optimization problem, whose solutions correspond to conformations satisfying the desired requirements. The global optimization problem is solved by the recently proposed Monkey Search algorithm. The simplicity of the optimization problem and the effectiveness of the used meta-heuristic search allowed the simulation of a large set of high-quality conformations. We show that, even though only few geometric requirements are imposed, some of the simulated conformation results to be similar (in terms of RMSD) to conformations real proteins actually have in nature.
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