An extremal optimization search method for the protein folding problem: the go-model example

The protein folding problem consists of predicting the functional (native) structure of the protein given its linear sequence of amino acids. Despite extensive progress made in understanding the process of protein folding, this problem still remains extremely challenging. In this paper we introduce, implement and evaluate the Extremal Optimization method – a biologically inspired approach which has been applied very successfully to other optimization problems – for the protein folding problem using a widely studied G¯o-model of folding. Standard methods based on the variants of the Monte Carlo method have difficulty exploring low-energy regions efficiently due to the ruggedness of the search landscapes. Most computational methods in the protein folding literature do not keep track of which interactions remain unsatisfied during the search. Instead, in this paper, we propose an adaptive meta-search method which ensures that unexplored promising parts of the search landscape are v...

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Alena Shmygelska
• Keywords: Extremal Optimization, GECCO 2007, Protein Folding, Protein Folding Problem