scholarly journals Iterated Local Search with Partition Crossover for Computational Protein Design

2021 ◽  
Author(s):  
François Beuvin ◽  
Simon Givry ◽  
Thomas Schiex ◽  
Sébastien Verel ◽  
David Simoncini
Keyword(s):  
Local Search ◽  
Protein Design ◽  
Iterated Local Search ◽  
Computational Protein Design

scholarly journals Iterated Local Search with Partition Crossover for Computational Protein Design

2021 ◽  
Author(s):  
François Beuvin ◽  
Simon de Givry ◽  
Thomas Schiex ◽  
Sébastien Verel ◽  
David Simoncini
Keyword(s):  
Local Search ◽  
Protein Design ◽  
Optimization Methods ◽  
Iterated Local Search ◽  
Biochemical Properties ◽  
Basins Of Attraction ◽  
Computational Protein Design ◽  
Local Minima ◽  
Search Optimization ◽  
Residue Interaction

Structure-based computational protein design (CPD) refers to the problem of finding a sequence of amino acids which folds into a specific desired protein structure, and possibly fulfills some targeted biochemical properties. Recent studies point out the particularly rugged CPD energy landscape, suggesting that local search optimization methods should be designed and tuned to easily escape local minima attraction basins. In this paper, we analyze the performance and search dynamics of an iterated local search (ILS) algorithm enhanced with partition crossover. Our algorithm, PILS, quickly finds local minima and escapes their basins of attraction by solution perturbation. Additionally, the partition crossover operator exploits the structure of the residue interaction graph in order to efficiently mix solutions and find new unexplored basins. Our results on a benchmark of 30 proteins of various topology and size show that PILS consistently finds lower energy solutions compared to Rosetta fixbb and a classic ILS, and that the corresponding sequences are mostly closer to the native.

scholarly journals Combining Heuristics with Simulation and Fuzzy Logic to Solve a Flexible-Size Location Routing Problem under Uncertainty

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 45
Author(s):  
Rafael D. Tordecilla ◽  
Pedro J. Copado-Méndez ◽  
Javier Panadero ◽  
Carlos L. Quintero-Araujo ◽  
Jairo R. Montoya-Torres ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Local Search ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Iterated Local Search ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Fuzzy Pattern ◽  
Reasonable Computing

The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.

scholarly journals cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design

2016 ◽  
Vol 23 (9) ◽  
pp. 737-749 ◽  
Author(s):  
Yuchao Pan ◽  
Yuxi Dong ◽  
Jingtian Zhou ◽  
Mark Hallen ◽  
Bruce R. Donald ◽  
...  
Keyword(s):  
Protein Design ◽  
Distributed Algorithm ◽  
Large Scale ◽  
Computational Protein Design

scholarly journals Discovery of Substrates for a SET Domain Lysine Methyltransferase Predicted by Multistate Computational Protein Design

Structure ◽  
2015 ◽  
Vol 23 (1) ◽  
pp. 206-215 ◽  
Author(s):  
Sylvain Lanouette ◽  
James A. Davey ◽  
Fred Elisma ◽  
Zhibin Ning ◽  
Daniel Figeys ◽  
...  
Keyword(s):  
Protein Design ◽  
Computational Protein Design ◽  
Set Domain ◽  
Lysine Methyltransferase

Electrostatics in computational protein design

2005 ◽  
Vol 9 (6) ◽  
pp. 622-626 ◽  
Author(s):  
Christina L Vizcarra ◽  
Stephen L Mayo
Keyword(s):  
Protein Design ◽  
Computational Protein Design
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