Hybrid Methods for Modeling Protein Structures Using Molecular Dynamics Simulations and Small-Angle X-Ray Scattering Data
Small-angle X-ray scattering (SAXS) is an efficient experimental tool to measure the overall shape of macromolecular structures in solution. However, due to the low resolution of SAXS data, high-resolution data obtained from X-ray crystallography or NMR and computational methods such as molecular dynamics (MD) simulations are complementary to SAXS data for understanding protein functions based on their structures at atomic resolution. Because MD simulations provide a physicochemically proper structural ensemble for flexible proteins in solution and a precise description of solvent effects, the hybrid analysis of SAXS and MD simulations is a promising method to estimate reasonable solution structures and structural ensembles in solution. Here, we review typical and useful in silico methods for modeling three dimensional protein structures, calculating theoretical SAXS profiles, and analyzing ensemble structures consistent with experimental SAXS profiles. We also review two examples of the hybrid analysis, termed MD-SAXS method in which MD simulations are carried out without any knowledge of experimental SAXS data, and the experimental SAXS data are used only to assess the consistency of the solution model from MD simulations with those observed in experiments. One example is an investigation of the intrinsic dynamics of EcoO109I using the computational method to obtain a theoretical profile from the trajectory of an MD simulation. The other example is a structural investigation of the vitamin D receptor ligand-binding domain using snapshots generated by MD simulations and assessment of the snapshots by experimental SAXS data.
KeywordsSmall-angle X-ray scattering Molecular dynamics simulation Solution structure Coarse-grained model MD-SAXS Endonuclease Vitamin D receptor
This work was financially supported by Innovative Drug Discovery Infrastructure through Functional Control of Biomolecular Systems, Priority Issue 1 in Post-K Supercomputer Development from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) to M.I. (Project ID: hp150269, hp160223, hp170255, and hp180191); by Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS) (Project ID: JP17am0101109) from Japan Agency for Medical Research and Development (AMED) to M.I.; and by RIKEN Dynamic Structural Biology Project to M.I. We further thank collaborators, Dr. Tomotaka Oroguchi (Keio Univ.), Prof. Hiroshi Hashimoto (Univ. of Shizuoka), Prof. Toshiyuki Shimizu (Tokyo Univ.), Prof. Mamoru Sato (Yokohama City Univ.), Dr. Yasuaki Anami (Univ. of Texas), Dr. Nobutaka Shimizu (KEK), Dr. Daichi Egawa (Showa Pharmaceutical Univ.), Dr. Toshimasa Itoh (Showa Pharmaceutical Univ.), and Prof. Keiko Yamamoto (Showa Pharmaceutical Univ.).
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