Modeling metal protein complexes from experimental extended X-ray absorption fine structure using evolutionary algorithms

Experimental extended x-ray absorption fine structure (EXAFS) spectra carry information about the chemical structure of metal protein complexes. However, predicting the structure of such complexes from EXAFS spectra is not a simple task. Currently methods such as Monte Carlo Optimization or simulated annealing are used in structure refinement of EXAFS. These methods have proved somewhat successful in structure refinement but have not been successful in finding the global minima. Based on the success of using evolutionary algorithms to overcome local minima issues in other domains, we propose multiple approaches to better predict the structure of metal protein complexes; genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE).