Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data
Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.
KeywordsCryo-EM SAXS Normal mode analysis Molecular dynamics simulations Coarse-grained models Fitting Modeling
We thank Sandhya P. Tiwari and Ashutosh Srivastava for carefully reading the manuscript and providing comments. This work was supported by FOCUS for Establishing Supercomputing Center of Excellence, JSPS KAKENHI Grant Number 17K07305, 16K07286, 26119006, 15K21711 and RIKEN Dynamic Structural Biology Project.
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