An immune algorithm for protein structure prediction on lattice models

Vincenzo Cutello*, Giuseppe Nicosia, Mario Pavone, Jonathan Timmis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

190 Citations (SciVal)

Abstract

We present an immune algorithm (IA) inspired by the clonal selection principle, which has been designed for the protein structure prediction problem (PSP). The proposed IA employs two special mutation operators, hypermutation and hypermacromutation to allow effective searching, and an aging mechanism which is a new immune inspired operator that is devised to enforce diversity in the population during evolution. When cast as an optimization problem, the PSP can be seen as discovering a protein conformation with minimal energy. The proposed IA was tested on well-known PSP lattice models, the HP model in two-dimensional and three-dimensional square lattices', and the functional model protein, which is a more realistic biological model. Our experimental results demonstrate that the proposed IA is very competitive with the existing state-of-art algorithms for the PSP on lattice models.

Original languageEnglish
Pages (from-to)101-117
Number of pages17
JournalIEEE Transactions on Evolutionary Computation
Volume11
Issue number1
DOIs
Publication statusPublished - Feb 2007

Keywords

  • Aging operator
  • Clonal selection algorithms
  • Functional model proteins
  • Hypermacromutation operator
  • Hypermutation operator
  • Immune algorithms (IAs)
  • Protein structure prediction problem
  • Three-dimensional HP model
  • Two-dimensional HP model

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