Protein Structure Optimization with a "Lamarckian"' Ant Colony Algorithm

Oakley, Mark T.; Richardson, Elizabeth Grace; Carr, Harriet; Johnston, Roy L.

doi:10.1109/tcbb.2013.125

Cited by 5 publications

(3 citation statements)

References 33 publications

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“…The representation of the memory is equivalent to pheromones trails in the Ant Colony Optimization (ACO) algorithms 9 . The concept of ACO has been exploited recently in the computational chemistry context 10,41 . In MERA, every ligand leaves the pheromone trail during simulation and that trail is used as information for the next ligands positions on the dissociation pathway.…”

Section: Memory Enhanced Random Acceleration Molecular Dynamicsmentioning

confidence: 99%

Memetic algorithms for ligand expulsion from protein cavities

Rydzewski

Nowak

2015

The Journal of Chemical Physics

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Ligand diffusion through a protein interior is a fundamental process governing biological signaling and enzymatic catalysis. A complex topology of channels in proteins leads often to difficulties in modeling ligand escape pathways by classical molecular dynamics simulations. In this paper two novel memetic methods for searching the exit paths and cavity space exploration are proposed: Memory Enhanced Random Acceleration (MERA) Molecular Dynamics and Immune Algorithm (IA). In MERA, a pheromone concept is introduced to optimize an expulsion force. In IA, hybrid learning protocols are exploited to predict ligand exit paths. They are tested on three protein channels with increasing complexity: M2 muscarinic GPCR receptor, enzyme nitrile hydratase and heme-protein cytochrome P450cam. In these cases, the memetic methods outperform Simulated Annealing and Random Acceleration Molecular Dynamics. The proposed algorithms are general and appropriate in all problems where an accelerated transport of an object through a network of channels is studied.

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Section: Memory Enhanced Random Acceleration Molecular Dynamicsmentioning

confidence: 99%

Memetic algorithms for ligand expulsion from protein cavities

Rydzewski

Nowak

2015

The Journal of Chemical Physics

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“…Compared to traditional gradientbased optimization algorithms, which suffer from both low efficiency and accuracy, Swarm Intelligence (SI) algorithms have proven effective and robust [20][21]. The Ant Colony Optimization (ACO) [22] algorithm draws inspiration from the foraging behavior of ants to find the optimal path. While robust, the algorithm suffers from slow convergence.…”

Section: Introductionmentioning

confidence: 99%

A Novel Harmonic Detection Method for Microgrids Based on Variational Mode Decomposition and Improved Harris Hawks Optimization Algorithm

Wang,

Ren

et al. 2024

IEEE Access

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In the pursuit of enhancing harmonic detection precision within microgrids, this paper introduces a pioneering algorithm, VMD-DCHHO-HD, which amalgamates Variational Mode Decomposition (VMD) with an advanced Harris Hawk Optimization algorithm characterized by dynamic opposition-based learning and Cauchy mutation (DCHHO). This study establishes a fitness function based on Shannon entropy, thereby minimizing the Local Minimum Entropy (LME) as the optimization objective for DCHHO. Building upon this, the VMD crucial parameters are efficiently identified using the enhanced HHO algorithm (DCHHO), enabling precise decomposition of complex voltage signals. The proposed method effectively addresses issues commonly encountered in traditional Empirical Mode Decomposition (EMD) during harmonic analysis, such as mode mixing, endpoint effects, and significant errors. Notably, it adeptly captures harmonic components spanning diverse frequencies, offering a nuanced solution to common pitfalls in traditional methodologies. In simulation experiments, VMD-DCHHO-HD showcases remarkable proficiency in extracting microgrid voltage signals, excelling at discerning high-order, low-amplitude harmonic components amid noise. The algorithm's superior precision and heightened reliability, as affirmed by comparative analyses against existing methods, position it as an advanced tool for precise and robust harmonic analysis in microgrid systems.

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“…Those algorithms have been successfully applied to a wide range of problems in many different areas 24 . Particularly, they have proved to be a powerful tool solving biological problems related to protein folding 25 , genetic interactions detection 26 , RNA sequence design 27 , protein-protein interaction inhibitors design 28 , protein structure optimization 29 and protein-ligand docking 30 . Moreover, they have outperformed genetic algorithms in a wide range of combinatorial optimization problems 31 – 35 .…”

Section: Introductionmentioning

confidence: 99%

Metabolic pathways synthesis based on ant colony optimization

Gérard

Stegmayer

Milone

2018

Sci Rep

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One of the current challenges in bioinformatics is to discover new ways to transform a set of compounds into specific products. The usual approach is finding the reactions to synthesize a particular product, from a given substrate, by means of classical searching algorithms. However, they have three main limitations: difficulty in handling large amounts of reactions and compounds; absence of a step that verifies the availability of substrates; and inability to find branched pathways. We present here a novel bio-inspired algorithm for synthesizing linear and branched metabolic pathways. It allows relating several compounds simultaneously, ensuring the availability of substrates for every reaction in the solution. Comparisons with classical searching algorithms and other recent metaheuristic approaches show clear advantages of this proposal, fully recovering well-known pathways. Furthermore, solutions found can be analyzed in a simple way through graphical representations on the web.

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Protein Structure Optimization with a "Lamarckian"' Ant Colony Algorithm

Cited by 5 publications

References 33 publications

Memetic algorithms for ligand expulsion from protein cavities

Memetic algorithms for ligand expulsion from protein cavities

A Novel Harmonic Detection Method for Microgrids Based on Variational Mode Decomposition and Improved Harris Hawks Optimization Algorithm

Metabolic pathways synthesis based on ant colony optimization

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