Implementation, Validation and Profiling of a Genetic Algorithm for Molecular Conformational Optimization
Gueorguiev, Victor and Michelle Kuttel (2016) Implementation, Validation and Profiling of a Genetic Algorithm for Molecular Conformational Optimization. In Blauw, Frans F., Marijke Coetzee, Duncan A. Coulter, Elize M. Ehlers, Wai Sze Leung, Carl Marnewick and Dustin T. van der Haar, Eds. Proceedings Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists (SAICSIT 2016), Johannesburg.
Prediction of the lowest energy conformation of a protein chain is a challenging optimization problem in computational chemistry and biology. Simple lattice-based protein models have been shown to be effective representations of the characteristics of proteins important in protein folding. An effective genetic algorithm for conformational optimization of proteins represented by the hydrophobic-hydrophillic lattice model was recently published. In this work, we create a publically available implementation of this genetic optimization algorithm. Tests of our implementation show equivalent performance to that reported for the original, in terms of both optimal conformation and number of function evaluations. In addition, we test our implementation across a range of data set sizes to characterize the performance of the algorithm as chain length increases: benchmarking that is necessary for future optimization and parallelization of the algorithm.
|EPrint Type:||Conference Paper|
|Keywords:||Genetic algorithm; HP Lattice; conformational search; energy optimization; hydrophobic-hydrophilic model|
|Subjects:||J Computer Applications: J.2 PHYSICAL SCIENCES AND ENGINEERING|
I Computing Methodologies: I.6 SIMULATION AND MODELING
|Deposited By:||Kuttel, Michelle|
|Deposited On:||24 October 2016|