Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs

This paper describes the application of our distributed computing framework for crystal structure prediction, Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC), to predict the crystal structure of the two known polymorphs of bicalutamide. The paper describes our success in findin...

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Detalles Bibliográficos
Autores principales: Ferraro, Marta Beatriz, Facelli, Julio César
Publicado: 2009
Materias:
Crystal structure prediction
Drug polymorphism
Parallel genetic algorithms
Bicalutamide
Cluster prediction
Crystal conformation
Distributed Computing
Energy potential
Low energies
Lower energies
Modified genetic algorithms
Second optimization
Selection process
Spurious effects
Unit-cell volume
Cell membranes
Clustering algorithms
Computer science
Genetic algorithms
Intelligent computing
Parallel algorithms
Polymorphism
Crystal structure
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v5754LNCS_n_p120_Ferraro
http://hdl.handle.net/20.500.12110/paper_03029743_v5754LNCS_n_p120_Ferraro
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paper:paper_03029743_v5754LNCS_n_p120_Ferraro
record_format dspace
spelling paper:paper_03029743_v5754LNCS_n_p120_Ferraro2023-06-08T15:28:33Z Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs Ferraro, Marta Beatriz Facelli, Julio César Crystal structure prediction Drug polymorphism Parallel genetic algorithms Bicalutamide Cluster prediction Crystal conformation Crystal structure prediction Distributed Computing Drug polymorphism Energy potential Low energies Lower energies Modified genetic algorithms Parallel genetic algorithms Second optimization Selection process Spurious effects Unit-cell volume Cell membranes Clustering algorithms Computer science Genetic algorithms Intelligent computing Parallel algorithms Polymorphism Crystal structure This paper describes the application of our distributed computing framework for crystal structure prediction, Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC), to predict the crystal structure of the two known polymorphs of bicalutamide. The paper describes our success in finding the lower energy polymorph and the difficulties encountered in finding the second one. The results show that genetic algorithms are very effective in finding low energy crystal conformations, but unfortunately many of them are not plausible due to spurious effects introduced by the energy potential function used in the selection process. We propose to solve this by using a multi objective optimization GA approach, adding the unit cell volume as a second optimization target. © 2009 Springer Berlin Heidelberg. Fil:Ferraro, M.B. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Facelli, J.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2009 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v5754LNCS_n_p120_Ferraro http://hdl.handle.net/20.500.12110/paper_03029743_v5754LNCS_n_p120_Ferraro
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Crystal structure prediction
Drug polymorphism
Parallel genetic algorithms
Bicalutamide
Cluster prediction
Crystal conformation
Crystal structure prediction
Distributed Computing
Drug polymorphism
Energy potential
Low energies
Lower energies
Modified genetic algorithms
Parallel genetic algorithms
Second optimization
Selection process
Spurious effects
Unit-cell volume
Cell membranes
Clustering algorithms
Computer science
Genetic algorithms
Intelligent computing
Parallel algorithms
Polymorphism
Crystal structure
spellingShingle Crystal structure prediction
Drug polymorphism
Parallel genetic algorithms
Bicalutamide
Cluster prediction
Crystal conformation
Crystal structure prediction
Distributed Computing
Drug polymorphism
Energy potential
Low energies
Lower energies
Modified genetic algorithms
Parallel genetic algorithms
Second optimization
Selection process
Spurious effects
Unit-cell volume
Cell membranes
Clustering algorithms
Computer science
Genetic algorithms
Intelligent computing
Parallel algorithms
Polymorphism
Crystal structure
Ferraro, Marta Beatriz
Facelli, Julio César
Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
topic_facet Crystal structure prediction
Drug polymorphism
Parallel genetic algorithms
Bicalutamide
Cluster prediction
Crystal conformation
Crystal structure prediction
Distributed Computing
Drug polymorphism
Energy potential
Low energies
Lower energies
Modified genetic algorithms
Parallel genetic algorithms
Second optimization
Selection process
Spurious effects
Unit-cell volume
Cell membranes
Clustering algorithms
Computer science
Genetic algorithms
Intelligent computing
Parallel algorithms
Polymorphism
Crystal structure
description This paper describes the application of our distributed computing framework for crystal structure prediction, Modified Genetic Algorithms for Crystal and Cluster Prediction (MGAC), to predict the crystal structure of the two known polymorphs of bicalutamide. The paper describes our success in finding the lower energy polymorph and the difficulties encountered in finding the second one. The results show that genetic algorithms are very effective in finding low energy crystal conformations, but unfortunately many of them are not plausible due to spurious effects introduced by the energy potential function used in the selection process. We propose to solve this by using a multi objective optimization GA approach, adding the unit cell volume as a second optimization target. © 2009 Springer Berlin Heidelberg.
author Ferraro, Marta Beatriz
Facelli, Julio César
author_facet Ferraro, Marta Beatriz
Facelli, Julio César
author_sort Ferraro, Marta Beatriz
title Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
title_short Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
title_full Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
title_fullStr Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
title_full_unstemmed Parallel genetic algorithms for crystal structure prediction: Successes and failures in predicting bicalutamide polymorphs
title_sort parallel genetic algorithms for crystal structure prediction: successes and failures in predicting bicalutamide polymorphs
publishDate 2009
url https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v5754LNCS_n_p120_Ferraro
http://hdl.handle.net/20.500.12110/paper_03029743_v5754LNCS_n_p120_Ferraro
work_keys_str_mv AT ferraromartabeatriz parallelgeneticalgorithmsforcrystalstructurepredictionsuccessesandfailuresinpredictingbicalutamidepolymorphs
AT facellijuliocesar parallelgeneticalgorithmsforcrystalstructurepredictionsuccessesandfailuresinpredictingbicalutamidepolymorphs
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