Genetic algorithm with a crossover elitist preservation mechanism for protein–ligand docking

Guan, Boxin; Ning, Jiaxu

doi:10.1186/s13568-017-0476-0

Cited by 21 publications

(13 citation statements)

References 33 publications

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“…Manually adjusted parameters were used for grid box dimension (60 × 60 × 60 A°) and grid spacing (0.375 A°) to keep the ligand flexible around the protein active site. Empirical free energy function along with the Lamarckian genetic algorithm (LGA) was used to perform docking (LGA) . The default parameters of the LGA protocol like population size, energy evaluations, mutation rate, crossover, and elitism were 150 individuals, 250 000, 0.02, 0.8, and 1.0, respectively.…”

Section: Methodsmentioning

confidence: 99%

Molecular docking, dynamics, and pharmacology studies on bexarotene as an agonist of ligand‐activated transcription factors, retinoid X receptors

Chitranshi

Dheer

Kumar

et al. 2019

J of Cellular Biochemistry

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Retinoid X receptors (RXRs) belong to the nuclear receptor superfamily, and upon ligand activation, these receptors control gene transcription via either homodimerization with themselves or heterodimerization with the partnernuclear receptor. The protective effects of RXRs and RXR agonists have been reported in several neurodegenerative diseases, including in the retina. This study was aimed to prioritize compounds from natural and synthetic origin retinoids as potential RXR agonists by molecular docking and molecular dynamic simulation strategies. The docking studies indicated bexarotene as a lead compound that can activate various RXR receptor isoforms (α, β, and γ) and has a strong binding affinity to the receptor protein than retinoic acid, which is known as a natural endogenous RXR agonist. Dynamic simulation studies confirmed that the hydrogen bonding and hydrophobic interactions were highly stable in all the three isoforms of the RXR-bexarotene complex. To further validate the significance of the RXR receptor in neurons, in vitro pharmacological treatment of neuronal SH-SY5Y cells with bexarotene was performed. In vitro data from SH-SY5Y cells confirmed that bexarotene activated RXR-simulated neurite outgrowth significantly. We conclude that bexarotene could be potentially used as an exogenous activator of RXRs and emerge as a good drug target for several neurodegenerative disorders.

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Section: Methodsmentioning

confidence: 99%

Molecular docking, dynamics, and pharmacology studies on bexarotene as an agonist of ligand‐activated transcription factors, retinoid X receptors

Chitranshi

Dheer

Kumar

et al. 2019

J of Cellular Biochemistry

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“…The proposed method has been compared to other existing tools and obtains the best average root-mean-square deviation (RMSD). Guan et al 21 proposed a novel GA based on a crossover elitist preservation mechanism (crossover elitist preservation genetic algorithm mechanism (CEPGA)) for solving protein-ligand docking problems. The algorithm employed crossover elitist preservation to keep the elite individuals of the last generation and make the crossover more efficient and robust.…”

Section: Related State-of-the-art Stochastic Optimization Methodsmentioning

confidence: 99%

Probing molecular docking problem by an improved quantum-behaved particle swarm optimization algorithm

Fu¹,

Martino²,

Zhao³

2019

Journal of Algorithms & Computational Technology

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The main objective of molecular docking is to find a model of interaction between a protein and ligand with a minimum binding energy. This process is driven by intricate algorithms and scoring functions. This paper mainly concentrates on the search algorithm used for solving the docking problem. Here, a new approach is proposed for the molecular docking problem that utilizes a hybrid algorithm that combines an improved quantum-behaved particle swarm optimization algorithm (QPSO) and the Solis and Wets algorithm. The improved QPSO algorithm that is based on individual particle evolutionary processes is known as individual particle evolutionary particle swarm optimization (IEQPSO). The IEQPSO algorithm was tested and compared with particle swarm optimization, QPSO, and its variants with a suite of benchmark functions. The results indicated the superiority of the proposed approach according to benchmark test functions. Then, the hybrid algorithm based on the IEQPSO algorithm was used for optimizing the energy function of the molecular docking problem and was compared with the classical Lamarckian genetic algorithm used by molecular docking software. Molecular docking and molecular dynamics simulation experiments revealed the effectiveness and feasibility of the proposed algorithm in solving the molecular docking problem.

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“…During evolution of genetic operators, the best individuals of the previous generation can possibly lose their superiority and generate inferior individuals [33]. It will reduce searching efficiency of the genetic algorithm and even fail to converge to the optimal solution.…”

Section: (6) Elitist Preservationmentioning

confidence: 99%

Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging

Teng

Yang

et al. 2022

JMSE

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Underwater acoustic imaging employs a special form of array which includes numerous transducer elements to achieve beamforming. Although a large-scale array can bring high imaging resolution, it will also cause difficulties in hardware complexity and real-time application. In this paper, in order to reduce the number of array elements, a sparse optimization for Mills cross is proposed, considering the elements’ distributions and weights design. The improved genetic algorithm is adopted to generate evolutions for sparse solution. In order to ensure effective convergence and successful evolution, relevant genetic operators are proposed, including appropriate population coding, correct fitness function, reasonable selection strategy and efficient two-point orthogonal crossover, among others. Essentially, a satisfied sparse solution is a result of mutual restraint between array elements’ survivals and their weights. The simulations reveal that our sparse cross array decreases the number of elements by 8.25% compared to the conventional Mills cross multiplicative array, while keeping the advantages of narrow main lobe width and low sidelobe level. Improved genetic algorithm is an effective method for the underwater acoustic imaging array to implement the sparse optimization.

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Genetic algorithm with a crossover elitist preservation mechanism for protein–ligand docking

Cited by 21 publications

References 33 publications

Molecular docking, dynamics, and pharmacology studies on bexarotene as an agonist of ligand‐activated transcription factors, retinoid X receptors

Molecular docking, dynamics, and pharmacology studies on bexarotene as an agonist of ligand‐activated transcription factors, retinoid X receptors

Probing molecular docking problem by an improved quantum-behaved particle swarm optimization algorithm

Genetic Algorithm for Sparse Optimization of Mills Cross Array Used in Underwater Acoustic Imaging

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