Fitting Low-Resolution Protein Structures into Cryo-EM Density Maps by Multiobjective Optimization of Global and Local Correlations

The rigid-body fitting of predicted structural models into cryo-electron microscopy (cryo-EM) density maps is a necessary procedure for density map-guided protein structure determination and prediction. We proposed a novel multiobjective optimization protocol, MOFIT, which performs a rigid-body density-map fitting based on particle swarm optimization (PSO). MOFIT was tested on a large set of 292 nonhomologous single-domain proteins. Starting from structural models predicted by I-TASSER, MOFIT achieved an average coordinate root-meansquare deviation of 2.46 angstrom, which was 1.57, 2.79, and 3.95 angstrom lower than three leading single-objective function-based methods, where the differences were statistically significant with p-values of 1.65 x 10(-6), 6.36 X 10(-8), and 6.44 X 10(-11) calculated using two-tail Student's t tests. Detailed analyses showed that the major advantages of MOFIT lie in the multiobjective protocol and the extensive PSO search simulations guided by the composite objective functions, which integrates complementary correlation coefficients from the global structure, local fragments, and individual residues with the cryo-EM density maps.

Automated summary

The newly proposed MOFIT protocol utilizes particle swarm optimization to perform rigid-body fitting of cryo-EM density maps, showcasing superior results compared to single-objective function-based methods. The key advantages of MOFIT lie in its multiobjective approach and extensive PSO search simulations, integrating various correlation coefficients for a comprehensive fitting guided by composite objective functions.