title: Protein structure optimization with a "Lamarckian" ant colony algorithm.
abstract: We describe the LamarckiAnt algorithm: a search algorithm that combines the features of a "Lamarckian" genetic algorithm and ant colony optimization. We have implemented this algorithm for the optimization of BLN model proteins, which have frustrated energy landscapes and represent a challenge for global optimization algorithms. We demonstrate that LamarckiAnt performs competitively with other state-of-the-art optimization algorithms.
authors.affiliation: University of Birmingham, Birmingham.
authors.forename: Mark T
authors.initials: MT
authors.lastname: Oakley
authors.affiliation: University of Birmingham, Birmingham.
authors.forename: E Grace
authors.initials: EG
authors.lastname: Richardson
authors.affiliation: University of Birmingham, Birmingham.
authors.forename: Harriet
authors.initials: H
authors.lastname: Carr
authors.affiliation: University of Birmingham, Birmingham.
authors.forename: Roy L
authors.initials: RL
authors.lastname: Johnston
mesh_terms: D000465:Algorithms; D000818:Animals; D001000:Ants; D019295:Computational Biology / Q000379:methods*; D008962:Models, Theoretical; D008968:Molecular Conformation; D009010:Monte Carlo Method; D010455:Peptides / Q000737:chemistry; D011336:Probability; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D010455:Peptides; D011506:Proteins