Prediction of Native Protein Conformation by a Hybrid Algorithm of Clonal Selection and Differential Evolution

2021 ◽  
pp. 314-330
Author(s):  
Iryna Fefelova ◽  
Andrey Fefelov ◽  
Volodymyr Lytvynenko ◽  
Oksana Ohnieva ◽  
Saule Smailova
Keyword(s):  
Differential Evolution ◽  
Protein Conformation ◽  
Hybrid Algorithm ◽  
Clonal Selection ◽  
Native Protein

scholarly journals Reconstruction of the S-System by the Hybrid Algorithm of the Clonal Selection and Differential Evolution

2018 ◽  
pp. 41-51
Author(s):  
Andrej O. Fefelov ◽  
◽  
Volodymyr I. Lytvynenko ◽  
Muchamed Ali Taif ◽  
Mariia O. Voronenko ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Hybrid Algorithm ◽  
Clonal Selection

scholarly journals Prediction of the tertiary structure of a protein on a two-dimensional triangular lattice by a hybrid evolutionary algorithm

2021 ◽  
Vol 3 (2) ◽  
pp. 27-32
Author(s):  
I. M. Fefelova ◽  
◽  
V. I. Lytvynenko ◽  
A. O. Fefelov ◽  
◽  
...  
Keyword(s):  
Protein Folding ◽  
Hybrid Method ◽  
Triangular Lattice ◽  
Hybrid Algorithm ◽  
Tertiary Structure ◽  
Clonal Selection ◽  
Selection Differential ◽  
Artificial Immune ◽  
Hp Model ◽  
Polar Model

This work discusses the problem of forecasting the tertiary structure of a protein, based on its primary sequence. The problem is that science, with all its computing power and a set of experimental data, has not learned to build models that describe the process of protein molecule coagulation and predict the tertiary structure of a protein, based on its primary structure. However, it is wrong to assume that nothing is happening in this field of science. The regularities of folding (convolution) of the protein are known, methods for its modelling have been developed. Analysis of the current state of research in the field of these problems indicates the presence of shortcomings associated with the accuracy of forecasting and the time necessary to obtain the optimal solution. Consequently, the development of new computational methods, deprived of these shortcomings, seems relevant. In this work, the authors focused on the lattice model, which is a special case of the known hydrophobic-polar dill. protein conformation according to the chosen model, hybrid algorithms of cloning selection, differential are proposed. Since the processes of protein coagulation have not been fully understood, the researchers proposed several simplified models based on the physical properties of molecules and which leads to problems of combinatorial optimization. A hydrophobic-polar simplified model on the planar triangular lattice is chosen as a protein model. From the point of view of the optimization problem, the problem of protein folding comes down to finding a conformation with minimal energy. In lattice models, the conformation is represented as a non-self-cutting pathway. A hybrid artificial immune system in the form of a combination of clonal selection and differential evolution algorithms is proposed to solve this problem. The paper proposes a hybrid method and algorithm to solve the protein folding problem using the HP model on a planar triangular lattice. In this paper, a hybrid method and algorithm for solving the protein folding problem using the HP model on a planar triangular lattice are proposed. The developed hybrid algorithm uses special methods for encoding and decoding individuals, as well as the affinity function, which allows reducing the number of incorrect conformations (self-cutting solutions). Experimental studies on test hp-sequences were conducted to verify the effectiveness of the algorithm. The results of these experiments showed some advantages of the developed algorithm over other known methods. Experiments have been taught to verify the effectiveness of the proposed approach. The results labelled "Best" show the minimum energy values achieved over 30 runs, while the results labelled "Medium" show the robustness of the algorithm to achieve minima. Regarding robustness, the hybrid algorithm also offers an advantage, showing higher results. A comparative analysis of the performance results of the proposed algorithm on test sequences with similar results of other published methods allows us to conclude the high efficiency of the developed method. In particular, the result is more stable, and, in some cases, conformations with lower energy are obtained. Keywords: protein folding; hydrophobic-polar model; clonal selection; differential evolution; artificial immune systems; hydrophobic-polar model.

A hybrid algorithm based on self-adaptive gravitational search algorithm and differential evolution

2018 ◽  
Vol 113 ◽  
pp. 515-530 ◽  
Author(s):  
Fuqing Zhao ◽  
Feilong Xue ◽  
Yi Zhang ◽  
Weimin Ma ◽  
Chuck Zhang ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Gravitational Search ◽  
Self Adaptive

scholarly journals An Adaptive Hybrid Algorithm Based on Particle Swarm Optimization and Differential Evolution for Global Optimization

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaobing Yu ◽  
Jie Cao ◽  
Haiyan Shan ◽  
Li Zhu ◽  
Jun Guo
Keyword(s):  
Particle Swarm Optimization ◽  
Differential Evolution ◽  
Hybrid Algorithm ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Population Based ◽  
Stochastic Search ◽  
Adaptive Mutation ◽  
Swarm Optimization ◽  
Local Optima

Particle swarm optimization (PSO) and differential evolution (DE) are both efficient and powerful population-based stochastic search techniques for solving optimization problems, which have been widely applied in many scientific and engineering fields. Unfortunately, both of them can easily fly into local optima and lack the ability of jumping out of local optima. A novel adaptive hybrid algorithm based on PSO and DE (HPSO-DE) is formulated by developing a balanced parameter between PSO and DE. Adaptive mutation is carried out on current population when the population clusters around local optima. The HPSO-DE enjoys the advantages of PSO and DE and maintains diversity of the population. Compared with PSO, DE, and their variants, the performance of HPSO-DE is competitive. The balanced parameter sensitivity is discussed in detail.

Sign in / Sign up

Export Citation Format

Share Document