Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions

Weiel, Marie; Götz, Markus; Klein, André; Coquelin, Daniel; Floca, Ralf; Schug, Alexander

doi:10.1038/s42256-021-00366-3

Cited by 22 publications

(11 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the average number of ATP–ribose hydrogen bonds in the unwound RNA was larger, and so the overall number of ATP-RNA interactions increased. The high local concentration of ATP close to the backbone also affects the surrounding hydration shell and biomolecular stability, − as the phosphate groups of the backbone offer direct hydration sides and interactions sites for the counter ions and ATP. , Quantifying these hydration shell changes would be exciting future work by complementing, e.g., small-angle X-ray scattering of time-averaged counterion distributions with MD simulations …”

Section: Resultsmentioning

confidence: 99%

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute

et al. 2023

Self Cite

View full text Add to dashboard Cite

A hallmark of Huntington's disease (HD) is a prolonged polyglutamine sequence in the huntingtin protein and, correspondingly, an expanded cytosine, adenine, and guanine (CAG) triplet repeat region in the mRNA. A majority of studies investigating disease pathology were concerned with toxic huntingtin protein, but the mRNA moved into focus due to its recruitment to RNA foci and emerging novel therapeutic approaches targeting the mRNA. A hallmark of CAG-RNA is that it forms a stable hairpin in vitro which seems to be crucial for specific protein interactions. Using in-cell folding experiments, we show that the CAG-RNA is largely destabilized in cells compared to dilute buffer solutions but remains folded in the cytoplasm and nucleus. Surprisingly, we found the same folding stability in the nucleoplasm and in nuclear speckles under physiological conditions suggesting that CAG-RNA does not undergo a conformational transition upon recruitment to the nuclear speckles. We found that the metabolite adenosine triphosphate (ATP) plays a crucial role in promoting unfolding, enabling its recruitment to nuclear speckles and preserving its mobility. Using in vitro experiments and molecular dynamics simulations, we found that the ATP effects can be attributed to a direct interaction of ATP with the nucleobases of the CAG-RNA rather than ATP acting as "a fuel" for helicase activity. ATP-driven changes in CAG-RNA homeostasis could be disease-relevant since mitochondrial function is affected in HD disease progression leading to a decline in cellular ATP levels.

show abstract

Section: Resultsmentioning

confidence: 99%

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…An Evolutionary Algorithm (EA) is a computational method that solves problems by mimicking the behaviour of living organisms using nature-inspired mechanisms 21 . The use of EAs for feature selection has received significant attention in academia, with various algorithms being proposed, including Particle Swarm Optimization (PSO) [22][23][24] , Genetic Algorithm (GA) 25,26 , Artificial Bee Colony (ABC) 27 , Genetic Programming (GP) 28 , Gravitational Search Algorithm (GSA) 29 and Ant Colony Optimization (ACO) 30,31 . One advantage of EAs is their population-based search approach, which involves a team of entities exploring the fitness landscape to find the globally optimum solution.…”

Section: B Evolutionary Algorithmsmentioning

confidence: 99%

Bird's Eye View Feature Selection for High-Dimensional Data

Belhaouari

Shakeel

Erbad

et al. 2023

Preprint

View full text Add to dashboard Cite

In machine learning, an informative dataset is crucial for accurate predictions. However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. To tackle this challenge, the Bird's Eye View (BEV) feature selection technique is introduced. This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. The proposed strategy in this paper leads to improved classification performance and a reduced number of features compared to conventional methods, as demonstrated by outperforming state-of-the-art feature selection techniques across multiple benchmark datasets.

show abstract

“…e weight factor balances the important parameters of global exploration and local exploitation in the optimization algorithm [22]. In the early stage of the algorithm, the particles in the space are scattered and chaotic.…”

Section: Adaptive Weightmentioning

confidence: 99%

Marine Predators Algorithm Based on Adaptive Weight and Chaos Factor and Its Application

Liang

Pan

Zhang

et al. 2022

Scientific Programming

View full text Add to dashboard Cite

Aiming at the problems of uneven distribution of initialized populations and unbalanced exploration and exploitation leading to slow convergence, low convergence accuracy, and easy to fall into local optimality of marine predators algorithm (MPA), a marine predators algorithm based on adaptive weight and chaos factor is proposed (ACMPA), the algorithm is applied to the traveling salesman problem (TSP), and the shortest path planning and research are carried out for the traveling salesman problem. Firstly, the improved adaptive weight strategy is used to balance the exploration and exploitation stage of the algorithm and improve the convergence accuracy of the algorithm. Secondly, the chaos factor is used to replace the random factor, and the ergodicity of the chaos factor is used to make it easier for predators to jump out of local optimization and enhance the optimization ability of the algorithm. Finally, 10 benchmark test functions, the CEC2015 test set, and the CEC2017 test set are used to evaluate the effectiveness of the ACMPA. The results show that, compared with the other four intelligent optimization algorithms, the improved ACMPA achieves better results in both mean and standard deviation, and the algorithm has a better effect on the shortest path problem.

show abstract

Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions

Cited by 22 publications

References 59 publications

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute

CAG-Repeat RNA Hairpin Folding and Recruitment to Nuclear Speckles with a Pivotal Role of ATP as a Cosolute

Bird's Eye View Feature Selection for High-Dimensional Data

Marine Predators Algorithm Based on Adaptive Weight and Chaos Factor and Its Application

Contact Info

Product

Resources

About