We have developed a genetic algorithm for building macromolecular complexes using only a 3D-electron microscopy density map and the atomic structures of the relevant components. For efficient sampling the method uses map feature points calculated by vector quantisation. The fitness function combines a mutual information score that quantifies the goodness-of-fit with a penalty score that helps to avoid clashes between components. Testing the method on ten assemblies (containing 3 to 8 protein components) and simulated density maps at 10, 15, and 20 Å resolution resulted in identification of the correct topology in 90%, 70% and 60% of the cases, respectively. We further tested it on four assemblies with experimental maps at 7.2-23.5 Å resolution, showing the ability of the method to identify the correct topology in all cases. We have also demonstrated the importance of the map feature-point quality on assembly fitting in the lack of additional experimental information.
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