AIMOES: Archive information assisted multi-objective evolutionary strategy for ab initio protein structure prediction

Song, Shuangbao; Gao, Shangce; Chen, Xingqian; Jia, Dongbao; Qian, Xiaoxiao; Todo, Yuki

doi:10.1016/j.knosys.2018.01.028

Cited by 50 publications

(18 citation statements)

References 67 publications

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“…The structure ɣL[g+g+] is the most stable found along the surface conformation of N-For-L-Cys-NH2 .According to our knowledge, a conformational and electronic study of energetically favored conformations of N-For-L-Cys-NH2diamide at HF/3-21G and B3LYP/6-31G(d,p) (Zamora et al, 2002), shows that the most stable structure (global minimum) of this system adopts the structure ɣL [g+g+].in this work we found the same result with our technical computing AM1/GA-MNC. Results revealed that this techniques is useful for the generation of molecular structures constituting the conformational space of protein and could possibly be extended for the determination of molecular structures of other related molecules (Bora et al, 2019;Custódio et al, 2014;Daeyaert et al, 2005;Fu et al, 2018;Kaur and Kadam, 2018;Lucasius and Kateman, 1994;Luke, 1996;Song et al, 2018;Tian et al, 2018;Vitela and Castaños, 2012).…”

Section: The L Backbone Conformationmentioning

confidence: 99%

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

Int¹

2019

Preprint

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The generation of molecular structures constituting the conformational space of trans-N-For-L-Cys-NH2 was accomplished using the genetic algorithm MNC coupled to the semi-empirical AM1 method, AM1/GA-MNC. The structural and energy analysis of the obtained conformational space E=E(,ψ) locates 7 regions or minima ɣL, ɣD, L, D, L, ɛD and ɛL. The combination of these folds to structuring modes adopted by the side chain CH2-SH has allowed us to identify 27 stable geometric structures. The regions corresponding to helical folds αD and αL are not favorable for the system that is the subject of current study.Capsule Summary: Molecular structure of trans-N-For-L-Cys-NH2 was studied using the genetic algorithm MNC coupled to the semi-empirical AM1 method, AM1/GA-MNC and combination of the folds to structuring modes adopted by the side chain CH2-SH revealed the possibility of 27 stable geometric structures of N-For-L-Cys-NH2. Cite This Article As:

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Section: The L Backbone Conformationmentioning

confidence: 99%

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

Int¹

2019

Preprint

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show abstract

“…The structure ɣL[g+g+] is the most stable found along the surface conformation of N-For-L-Cys-NH2 .According to our knowledge, a conformational and electronic study of energetically favored conformations of N-For-L-Cys-NH2diamide at HF/3-21G and B3LYP/6-31G(d,p) (Zamora et al, 2002), shows that the most stable structure (global minimum) of this system adopts the structure ɣL [g+g+].in this work we found the same result with our technical computing AM1/GA-MNC. Results Table 4: Energies deviations from the global minimum and angles characterizing the minimum ɛL of N-For-L-Cys-NH2, AM1/GA-MNC Backbone [sidechain] ΔΔHf (kcal/mol) φ(°) ψ(°) χ1(°) χ2(°) ɛL [g-g+] 3. revealed that this techniques is useful for the generation of molecular structures constituting the conformational space of protein and could possibly be extended for the determination of molecular structures of other related molecules (Bora et al, 2019;Custódio et al, 2014;Daeyaert et al, 2005;Fu et al, 2018;Kaur and Kadam, 2018;Lucasius and Kateman, 1994;Luke, 1996;Song et al, 2018;Tian et al, 2018;Vitela and Castaños, 2012).…”

Section: The L Backbone Conformationmentioning

confidence: 99%

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

Int¹,

Bourjila²

2019

Preprint

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“…It is a biological-inspired, populationbased global optimization algorithm. Due to its simple concept, easy implementation, fast convergence, and excellent robustness, it has been more extensively utilized than other mainstream evolutionary algorithms, such as the genetic algorithm (GA) [28,29], the evolutionary strategy (ES) [30,31], and particle swarm optimization (PSO) [32] in recent years. DE is similar to the GA and ES but differs from them because a unique differential evolution operator is referenced in DE.…”

Section: Introductionmentioning

confidence: 99%

A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm

Wang

Gao

Wang

et al. 2020

Computational Intelligence and Neuroscience

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A dendritic neuron model with adaptive synapses (DMASs) based on differential evolution (DE) algorithm training is proposed. According to the signal transmission order, a DNM can be divided into four parts: the synaptic layer, dendritic layer, membrane layer, and somatic cell layer. It can be converted to a logic circuit that is easily implemented on hardware by removing useless synapses and dendrites after training. This logic circuit can be designed to solve complex nonlinear problems using only four basic logical devices: comparators, AND (conjunction), OR (disjunction), and NOT (negation). To obtain a faster and better solution, we adopt the most popular DE for DMAS training. We have chosen five classification datasets from the UCI Machine Learning Repository for an experiment. We analyze and discuss the experimental results in terms of the correct rate, convergence rate, ROC curve, and the cross-validation and then compare the results with a dendritic neuron model trained by the backpropagation algorithm (BP-DNM) and a neural network trained by the backpropagation algorithm (BPNN). The analysis results show that the DE-DMAS shows better performance in all aspects.

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AIMOES: Archive information assisted multi-objective evolutionary strategy for ab initio protein structure prediction

Cited by 50 publications

References 67 publications

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

Theoretical study of the potential energy surface of N-formyl-L-cysteine-amide by using a genetic algorithm multi niche crowding

A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm

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