TY - JOUR
T1 - Combination of coarse-grained molecular dynamics simulations and small-angle X-ray scattering experiments
AU - Ekimoto, Toru
AU - Kokabu, Yuichi
AU - Oroguchi, Tomotaka
AU - Ikeguchi, Mitsunori
N1 - Funding Information:
The authors are grateful to Prof. Mamoru Sato, Prof. Masaaki Sugiyama, Prof. Hitoshi Kurumizaka and Dr. Takashi Oda for generously providing the SAXS data for nucleosomes. This work was financially supported by the 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, hp180191 and hp190171); by the Basis for Supporting Innovative Drug Discovery and Life Science Research (BINDS) from the Japan Agency for Medical Research and Development (AMED) (19am0101109j0003) to M. I.; a Grant-in Aid for Scientific Research on Innovative Areas “Molecular Engine” (18H05426) to M. I.; and by a RIKEN Dynamic Structural Biology Project to M. I. This research used computational resources of the K computer provided by the RIKEN Center for Computational Science. Finally, we celebrate the 80th anniversary of Prof. Nobuhiro Gō. His excellent research on biomolecules has largely inspired us to computationally study biomolecular structures. We are honored to make a contribution to this anniversary issue.
Publisher Copyright:
© 2019 THE BIOPHYSICAL SOCIETY OF JAPAN.
PY - 2019
Y1 - 2019
N2 - The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representa-tions are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.
AB - The combination of molecular dynamics (MD) simulations and small-angle X-ray scattering (SAXS), called the MD-SAXS method, is efficient for investigating protein dynamics. To overcome the time-scale limitation of all-atom MD simulations, coarse-grained (CG) representa-tions are often utilized for biomolecular simulations. In this study, we propose a method to combine CG MD simulations with SAXS, termed the CG-MD-SAXS method. In the CG-MD-SAXS method, the scattering factors of CG particles for proteins and nucleic acids are evaluated using high-resolution structural data in the Protein Data Bank, and the excluded volume and the hydration shell are modeled using two adjustable parameters to incorporate solvent effects. To avoid overfitting, only the two parameters are adjusted for an entire structure ensemble. To verify the developed method, theoretical SAXS profiles for various proteins, DNA/RNA, and a protein-RNA complex are compared with both experimental profiles and theoretical profiles obtained by the all-atom representation. In the present study, we applied the CG-MD-SAXS method to the Swi5-Sfr1 complex and three types of nucleosomes to obtain reliable ensemble models consistent with the experimental SAXS data.
KW - MD simulation
KW - nucleosome
KW - protein solution structure
KW - SAXS
KW - structural ensemble
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U2 - 10.2142/biophysico.16.0_377
DO - 10.2142/biophysico.16.0_377
M3 - Article
AN - SCOPUS:85099256538
SN - 2189-4779
VL - 16
SP - 377
EP - 390
JO - Biophysics and physicobiology
JF - Biophysics and physicobiology
ER -