Hybrid Approachfor BiomolecularStructure Modeling
Osamu Miyashita
RIKEN Center for Computational Science,
Computational Structural Biology Research Team

2nd R-CCS international symposium, 2020/2/17-18

Structural Biology
CellHemoblogin

Adenovirus

Imatinib (Gleevec®)
Tyrosine Kinase inhibitor
Anticancer drug (Leukemia)

https://en.wikipedia.org/wiki/Imatinib

David S. Goodsell
and the RCSB PDB
Image from: Milne & Subramaniam, Nat.
Rev. Microbiol 2009

Structures of biomolecules areimportant to understand functions,and for drug development
Dynamics is essential for function

Integrative/Hybrid Modeling3D structure
2D images

X-ray crystallography
NMR structure

Cryo-Electron Microscopy(volume/images)

X-ray Free Electron Laser (XFEL)

Simulation & Modeling

Uchihashi(2018)

SAXS
Atomic ForceMicroscopy

Structure andDynamics

Interpretation of new X-raycrystallography data
• X-ray crystallography provides structural information at high-resolution• Cryo temperatures, crystal packing, artificially modified proteins• Crystal contact-free space (CCFS) to reconciling X-ray structures withdynamics in solutions• MD simulations to refine interpretations
Kohda’s group
Kyushu University

Matsuoka et al, 2016

Bala et al,
BBA Gen 2020

Dynamics of Flexible Loop: MD and Exp
Tim21 loop2 conformation:
Experimental data areinconsistentConf ensemble
from modeling &MD~40 µsec

Crystal packing can be
examined by MD toimprove crystal design

Distance to closest neighbor

MD trajectory vsExperimental Data
CCFS best agreement

Bala et al BBA General Subjects (2020), Srivastava et al BBA General Subjects (2020)

Fitting X-ray into Cryo-EM Data
Implementation of biased molecular dynamics simulation with EM volume
cryo-EM volume

Bias strength

E = E molecule + k(1− f EM )Molecular Mechanics• all atom models• coarse grained model

repl nrepl 3
repl 2
repl 1

release factor 2

Biasing Force• model ó mapagreement~ low energy

strong
Biasing force
mdexchg

mdexchg

mdexchg

md

Replica exchange: Different biasing force
constant ki is assigned to each replica

weakMiyashita et al (2017), Mori et al (2019)

Biomolecule Imaging by X-ray Free Electron Laser
SPring-8 SACLA(C) RIKEN

Single-particle coherent diffraction imaging (CDI)
Experimental setup for single particle CDI• Application to noncrystallizable samples• Challenging approach with potentiallyvery high impact- Single molecule in natural condition- Time-resolved study on Dynamics- Requires strong beamGaffney & Chapman, Science (2007)

3D Reconstruction from XFEL Single Particle Data
Particle streamStopper

X-ray beam
Diffraction pattern
recorded on a
pixelated detector
K. J. Gaffney and H. N. Chapman, Science (2007) 316 1444-1448• Angles are not known• Arrangement of all 2D diffraction
patterns need to be calculated.
• Computationally extensive for alarge dataset• Applications to experimental datawith Nishino group @ Hokkaido U

Real space 3Dstructure after
phase recovery
Nakano et al, JSR 2017, 2018
Nakono et al, Biophys. Physicobiol. 2019

Challenges for
Biomolecular Modeling from XFEL Data
BIG DATA:
millions of images
X-ray laser

data collection
setup

Further algorithm
developments and dataprocessing are required in
multiple aspects

3D structure
in realspace

reliable phase
recoverynoise robust angularassignment algorithms

reliable datafilteringalgorithms

Challenges: going fromStructure to Dynamics
EMUchihashi et al 2018

motionGeeves & Holmes 1999

• More experimental data arecollected.
• New time resolvedexperimental techniques• Modeling of conformational
dynamics through analysesof large data sets

Millions of images

Highspeed AFM

Multipleconformations
capturedNango et al 2016
XFEL

Time-resolved SFXby XFELSummary• Development of computational algorithms and tools for
integrative structural biology and applications• Obtain new structural and dynamical information combining
experimental data and simulation• More experimental data and more complex biological molecules
require further computational resources and algorithms:
Development of tools to utilize new data using Fugaku

EM

Multipleconformations
captured

XFELMillions of images

Acknowledgements• Florence Tama (R-CCS & Nagoya University) andMiki Nakano, Sandhya Tiwari, Bhaskar Dasgputa (RIKEN)
Arpita Srivastava, Atsushi Tokuhisa, Tetsuro Nagai (former m.)• Yuji Sugita team (RIKEN)• Daisuke Kohda and Siqin Bala (Kyushu U)• Slavica Jonic (CNRS, France)• Yasumasa Joti (JASRI)• Yoshinori Nishino, Akinori Suzuki and the lab (Hokkaido U)• Changyong Song (POSHTECH) and team members• Kenji Iwasaki lab (Tsukuba U)• Hideki Shigematsu (RIKEN)• Focus Establishing Supercomputing Center of Excellence• Japan Society for the Promotion of Science• RIKEN Pioneering Project