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Investigation of the three-dimensional lattice HP protein folding model using a genetic algorithm

机译:利用遗传算法研究三维点阵HP蛋白折叠模型

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An approach to the hydrophobic-polar (HP) protein folding model was developed using a genetic algorithm (GA) to find the optimal structures on a 3D cubic lattice. A modification was introduced to the scoring system of the original model to improve the model's capacity to generate more natural-like structures. The modification was based on the assumption that it may be preferable for a hydrophobic monomer to have a polar neighbor than to be in direct contact with the polar solvent. The compactness and the segregation criteria were used to compare structures created by the original HP model and by the modified one. An islands' algorithm, a new selection scheme and multiple-points crossover were used to improve the performance of the algorithm. Ten sequences, seven with length 27 and three with length 64 were analyzed. Our results suggest that the modified model has a greater tendency to form globular structures. This might be preferable, since the original HP model does not take into account the positioning of long polar segments. The algorithm was implemented in the form of a program with a graphical user interface that might have a didactical potential in the study of GA and on the understanding of hydrophobic core formation.
机译:使用遗传算法(GA)开发了疏水极性(HP)蛋白质折叠模型的方法,以在3D立方晶格上找到最佳结构。对原始模型的评分系统进行了修改,以提高模型生成更自然结构的能力。所述改性基于这样的假设,即疏水性单体具有极性邻域比与极性溶剂直接接触可能是优选的。紧凑性和隔离标准用于比较原始HP模型和修改后的模型创建的结构。为了提高算法性能,采用了孤岛算法,新的选择方案和多点交叉算法。分析了十个序列,七个长度为27,三个长度为64。我们的结果表明,修改后的模型具有形成球状结构的更大趋势。这可能是更可取的,因为原始的HP模型未考虑长极性段的位置。该算法以带有图形用户界面的程序的形式实现,在GA的研究以及对疏水核形成的理解上可能具有一定的教学潜力。

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