Title :
Evolutionary design of the energy function for protein structure prediction
Author :
Widera, Pawel ; Garibaldi, Jonathan M. ; Krasnogor, Natalio
Author_Institution :
Sch. of Comput. Sci., Univ. of Nottingham, Nottingham
Abstract :
Automatic protein structure predictors use the notion of energy to guide the search towards good candidate structures. The energy functions used by the state-of-the-art predictors are defined as a linear combination of several energy terms designed by human experts. We hypothesised that the energy based guidance could be more accurate if the terms were combined more freely. To test this hypothesis, we designed a genetic programming algorithm to evolve the protein energy function. Using several different fitness functions we examined the potential of the evolutionary approach on a set of candidate structures generated during the protein structure prediction process. Although our algorithms were able to improve over the random walk, the fitness of the best individuals was far from the optimum. We discuss the shortcomings of our initial algorithm design and the possible directions for further research.
Keywords :
biology computing; genetic algorithms; proteins; random processes; automatic protein structure prediction; candidate structure generation; evolutionary design; genetic programming algorithm; protein energy function; protein sequence; random walk; Algorithm design and analysis; Atomic measurements; Computational efficiency; Computational modeling; Humans; Prediction methods; Predictive models; Proteins; Testing; Thermodynamics;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983095