Maher Brian, Albrecht Andreas A, Loomes Martin, Yang Xin-She, Steinhöfel Kathleen
Department of Informatics, King's College London, Strand, London WC2R 2LS, UK.
School of Science and Technology, Middlesex University, The Burroughs, London, NW4 4BT, UK.
Biomolecules. 2014 Jan 7;4(1):56-75. doi: 10.3390/biom4010056.
We introduce a Firefly-inspired algorithmic approach for protein structure prediction over two different lattice models in three-dimensional space. In particular, we consider three-dimensional cubic and three-dimensional face-centred-cubic (FCC) lattices. The underlying energy models are the Hydrophobic-Polar (H-P) model, the Miyazawa-Jernigan (M-J) model and a related matrix model. The implementation of our approach is tested on ten H-P benchmark problems of a length of 48 and ten M-J benchmark problems of a length ranging from 48 until 61. The key complexity parameter we investigate is the total number of objective function evaluations required to achieve the optimum energy values for the H-P model or competitive results in comparison to published values for the M-J model. For H-P instances and cubic lattices, where data for comparison are available, we obtain an average speed-up over eight instances of 2.1, leaving out two extreme values (otherwise, 8.8). For six M-J instances, data for comparison are available for cubic lattices and runs with a population size of 100, where, a priori, the minimum free energy is a termination criterion. The average speed-up over four instances is 1.2 (leaving out two extreme values, otherwise 1.1), which is achieved for a population size of only eight instances. The present study is a test case with initial results for ad hoc parameter settings, with the aim of justifying future research on larger instances within lattice model settings, eventually leading to the ultimate goal of implementations for off-lattice models.
我们引入了一种受萤火虫启发的算法方法，用于在三维空间中的两种不同晶格模型上进行蛋白质结构预测。具体而言，我们考虑三维立方晶格和三维面心立方（FCC）晶格。潜在的能量模型是疏水 - 极性（H - P）模型、宫泽 - 杰尔尼根（M - J）模型以及一个相关的矩阵模型。我们的方法在十个长度为48的H - P基准问题和十个长度从48到61的M - J基准问题上进行了测试。我们研究的关键复杂度参数是为达到H - P模型的最优能量值或与已发表的M - J模型值相比具有竞争力的结果所需的目标函数评估总数。对于有比较数据的H - P实例和立方晶格，我们在八个实例上获得了平均2.1的加速比，不包括两个极端值（否则为8.8）。对于六个M - J实例，有立方晶格且种群大小为100的运行的比较数据，在此情况下，先验地，最小自由能是终止标准。在四个实例上的平均加速比为1.2（不包括两个极端值，否则为1.1），这是在仅八个实例的种群大小下实现的。本研究是一个针对临时参数设置的具有初步结果的测试案例，目的是为未来在晶格模型设置内对更大实例的研究提供依据，最终实现非晶格模型实现的最终目标。
