Evolutionary computation and multimodal search: a good combination to tackle molecular diversity in the field of peptide design.
The awesome degree of structural diversity accessible in peptide design has created a demand for computational resources that can evaluate a multitude of candidate structures. In our specific case, we translate the peptide design problem to an optimization problem, and use evolutionary computation (EC) in tandem with docking to carry out a combinatorial search. However, the use of EC in huge search spaces with different optima may pose certain drawbacks. For example, EC is prone to focus a search in the first good region found. This is a problem not only because of the undesirable and automatic rejection of potentially good search space regions, but also because the found solution may be extremely difficult to synthesize chemically or may even be a false docking positive. In order to avoid rejecting potentially good solutions and to maximize the molecular diversity of the search, we have implemented evolutionary multimodal search techniques, as well as the molecular diversity metric needed by the multimodal algorithms to measure differences between various regions of the search space.
Belda
Ignasi
I
Institut de Recerca Biomèdica, Parc Científic de Barcelona, Universitat de Barcelona, Josep Samitier, Barcelona, Spain.
Madurga
Sergio
S
Tarragó
Teresa
T
Llorà
Xavier
X
Giralt
Ernest
E
D000465:Algorithms; D003198:Computer Simulation; D019020:Directed Molecular Evolution / Q000379:methods*; D015195:Drug Design; D010455:Peptides / Q000737:chemistry*; D000085822:Prolyl Oligopeptidases; D012697:Serine Endopeptidases / Q000737:chemistry
D010455:Peptides; D012697:Serine Endopeptidases; D000085822:Prolyl Oligopeptidases