Strategic Programs for Innovative Research Field 1 Supercomputational Life Science11

2014.9 Vol.

CONTENTS

Open Up SPECIAL TALK

Discussion meeting

Large-scale analysis of life data toward disclosureof the diversity and complexity of life programs
Atsushi Niida The University of Tokyo ／ Satoshi Ito The University of Tokyo／ Masanori Kakuta Tokyo Institute of Technology

SCLS Eyes

2

S-cruise From the field of software development

Designing and evaluating new medicines on a computer
Aiming to construct the platform of IT-based drug discovery
Nozomu Kamiya ／ Takashi Mitsui Fujitsu Limited

ZOOM IN

6

Close-up on SCLS Research

Theme 1 Simulations of biomolecules under cellular environments

Structural analysis of protein in solution by molecular
dynamics simulation and small angle X-ray scattering
Yuichi Kokabu

Yokohama City University

8

Theme 1 Simulations of biomolecules under cellular environments

Coarse-grained simulation : Investigation of the molecularmechanism of signaling pathway using CafeMol
Ryo Kanada Kyoto University

9

Theme 3 Hierarchical integrated simulation for predictive medicine

Development of a central nervous system model for
elucidating the onset mechanism of Parkinson’s disease
Jun Igarashi

Okinawa Institute of Science and Technology Graduate University

SCLS Gotcha!

Osaka University education program on high performance computing
Past and future of acceptance of applications from the public
to use the SCLS computer system

10

11
11

Discussion
meeting

Theme 4 Large-scale analysis of life data

Large-scale analysis of life data towardand complexity of life programs
Aiming to analyze the biomolecular network by using the genome as thestandard, promote development of a system for processing and analyzing avast amount of DNA information, and contribute to medical application

Various advanced measurement technologies such as cutting-edge sequencers are accelerating refinement and size
increases of life system data. Theme 4 “Large-scale analysis of life data” (Leader: Prof. Satoru Miyano, The Institute of Medical
Science, The University of Tokyo) aims to construct an infrastructure for cutting-edge, large-scale data analysis optimized
for the K computer, understand the complexity, diversity and evolution of life programs, and promote analytical studies on
biomolecular networks by using the genome as the standard. We interviewed three researchers who are struggling at thefrontline of bioinformatics by utilizing state-of-the-art information processing technologies.

Encounter with bioinformatics●How did you happen to get involved
in bioinformatics studies?

One day, Prof. Miyano invited me to the

Aided Design: CAD), and I was also

Niida: In the undergraduate school,that I was going to use the fastest

supercomputers. However, technology

of cancer. Just when I f inished mymy studies with help from Dr. Ito andgenome project was completed. The

Ito: I graduated from the school

felt that I wanted to study fundamental

aroused my interest in bioinformatics.

computational fluid mechanics. My fields invitation, I came to this laboratory

Innovation” of the Strategic Programs

full understanding of biology, and amof industrial innovation, computers

other members. On the other hand,

K computer project. I never imagined

performing simulation studies using

I worked on the molecular biology

computer in Japan, but I’m continuing

undergraduate course, the humanother members.

encounter with genomic scienceof engineering and majored inscience. At that time, at Prof. Miyano’is closely related to Field 4, “Industrial

in April last year. I still do not have afor Innovative Research. In the fieldreceiving guidance from Dr. Niida andhave been used extensively (Computer

the members of the laboratory are not

I was not very good at computers, andso I studied it in my way. After I finished

my graduate school, I came to the labof Prof. Miyano and started to work on

the methodology of bioinformatics.

2 BioSupercomputing Newsletter Vol.11

development in the industrial field is so

subdivided or narrow, and studies are

conducted on almost every topic. Well, I

Masanori Kakuta
Postdoctoral researcher, Akiyama Lab., Department ofComputer Science, Graduate School of Information Scienceand Engineering, Tokyo Institute of Technology

There is still room for improvement in large-scale data
analysis using HPC. I want to develop information
processing systems for actualizing faster and more efficient
data analysis to make large-scale analysis possible.

Satoshi Ito
Project Researcher, Human Genome Center
The Institute of Medical Science
The University of Tokyo
Assistant Professor, Laboratory of DNA
Atsushi Niida Project
Information Analysis, Human Genome Center
Institute of Medical Science,

The University of Tokyo

I am presently engaged in exploratory
research of cancer evolution by simulation
on joint studies with medical practitioners.
I want to develop a cancer treatment
strategy by simulation in the future tocontribute to custom-made medicine.

It is important to establish a collaboration
bet ween large -scale sequence data,
bioinformatics for analyzing the data, andbiologists and medical doctors. I want todevelop software to help this collaboration.

disclosure of the diversity
yet accustomed to parallelization andof proteins. I continued

am supporting that part. We are thus

one year and a half after

optimization of the K computer, and I
cooperating together.

working at the lab for

Simulation of cancer evolution

I f i n i s h e d my d o c t o r a l

Kakuta: I was in the depar tment ofcourse. In the middle

course. Then I went to a graduate

Akiyama Lab and started

engineering and star ted to use

Theme 4 project. I’ve been

graduate school, I studied interactions

I also felt that working on

estimated three-dimensional structures

would broaden my studies.

science during my undergraduateof 2011, I moved to theschool of agriculture to study applied

to participate in thecomputer for the f irst time. In theinterested in HPC itself, but

among proteins, and analy zed andlarge-scale computation

Also working on simulation of cancer

Fig. : Top left: Tumor obtained by simulation calculation
Top right: Profile of genomic mutations
Bottom: Visualized time-historical evolution of a tumor● In Theme 4 project, what actual

which extracts expression modules,

Niida: The Miyano Lab is carrying out

the mRNA expression data based onpractitioners and experimental cancer

transcription program of cancer by

from them, which need to be analyzed

experimental data. Dr. Ito and otherto analyze the data from joint study

to the K computer. Another study is also

EEM (Extraction of Expression Module),

studies. While it is well known that the

researches are you conducting?

or genes that are co-expressed, fromvarious joint studies with medical

gene set information, and identify thelabs. We receive a huge amount of data

combining the analytical results withquickly. One of our ongoing studies ismembers are helping us to transfer EEM

laboratories by using a software called

simulation of cancer born out of joint

BioSupercomputing Newsletter Vol.11 3

Discussion
meeting

Large-scale analysis of life data toward disclosure of the diversity and complexity of life programs
DNA of cancer differs among individuals,
we found recently that the DNA isdiverse even within a single patient,and differs depending even on the partwithin a single tumor. It has been foundthat, in cancer development, the firstnormal cell accumulates mutation andproduces clones that have a mutation(s)dif ferent from the mother cell andeach other. When we observe a formed

tumor, there are many subclones thathave mutations in completely different
genes. Actually, when we conducted

multi-sampling of a colorectal cancer orsampled DNAs from different parts ofthe tumor in a joint study, we obtained

profiles of completely different genes.

To answer why such a phenomenon
occurs, we will investigate themechanism of evolution by performing
a simulation. Dr. Ito has converted oursimulation model so that it runs on the

K computer. We are running it whilechanging the parameters to searchfor key parameters involved in thedevelopment of non-uniformity in atumor. We are planning to simulate theentire life of a cancer also to determine
effective drugs, aiming to use the resultsin therapeutic strategy.

● Mr. Ito is also involved in the
study, engaged in porting thesoftware to the K computer.

one. For example, a pipeline software

mos t memb er s of the Miyano L ab

Most sof tware needs to resolve themassively parallel supercomputers suchare people in bioinformatics who use

support running of existing software

have done parallelization. Therefore,

assume that Dr. Niida wants to run a

K computer without experience of usingc o n s i s t s o f C l a n g u a g e m a i n l y, R

statistical language partially, and shell

Ito: Yes. Not only Dr. Niida, but also

script for connecting C and R parts.

are not familiar with MPI programs or

flow before porting. Although there

as the K computer. So my first task is tosupercomputers, there are few whoon the K computer. For example, let us

there may be a great barrier to using thecertain software on the K computer onother HPCI supercomputers.

a large scale. He tells me his intention,and I analy ze the contentsof the sof t ware, and judge
whether the program can beported to the K computer as
it is or not. If it is not possible,

I substitute another program

for the software, or re-write

the program directly to make it
run on the K computer. It is also
necessary to do parallelization,and I do the work so that Dr.
Niida can use the software.

Niida: The K computer is arather high hurdle for me insome respects. The K computeris designed for persons who

have long used HPC, such as
those engaged in astronomy

and physics. I feel the K
computer has parts that are
difficult for biologists to use.

Ito: Yes. There are dif f icult

parts. There are various

bioinformatics sof tware

programs. Each of them is acombination of two or more

p ro gr ams an d s o, in manycases, they are written in two

or more languages instead ofFig. : The concept of Genomon-Fusion for the K computer,a software for detecting cancer variants on a large-scaleand comprehensively at the transcriptomic levels. Various
improvements were made to port the program to the K
computer such as integration of MPI processes, because
multiple MPI processes would lose time due to the MPI
barrier mechanism.

Toward ultra-fast large scale analysis
Kakuta: I am mainly developing a

g r o u p o f m i c r o o r g a n i ms w i t h i n atheir amount by analyzing them as a

the K computer and also analyzing

sp e cies of micro organisms w ithin

how microorganisms interac t withmetagenomic analysis pipeline using

actual data using the pipeline.

Metagenomic analysis is a method foranalyzing the genome of the entire

4 BioSupercomputing Newsletter Vol.11

certain environment. There are various

an environment, but it is possible todetermine what species are present

in which part of the environment andmixture. It is also possible to investigate
the environment by measuring thepercentages of the species. However,metagenomic analysis processes a

mu ch l ar g e r am o u nt o f s e qu e n ce

data than genomic sequencing of one
microorganism. The project in which
I am involved aims to conduct large-

scale computation by the K computer

to analy ze this enor mous amount

Sample acquisitionof data. The metagenomic analysis

pipeline compares frac tions of the

DNA extraction

DNA sequencing

Estimation of microorganisms and their genes throughutilization of known nucleotide sequences

genome, which is obtained via a nextgeneration sequencer, and sequences inthe existing databases through a seriesof processes. The pipeline can identify
genes contained in the sample data
and analyze their relative abundance

based on their functions. A parallelized

homology search tool called GHOST-

Comparison of composition of existing
microorganisms and their genes

MP plays the central role in the analysis
pipeline. Graduate students are writing

programs to run on a processor, andI am conver ting them one by one

into a parallelized program that runson the K computer to enable large-

scale analysis. We are aiming at highly
precise analysis, but this requires along computation time. To shor ten
the time, we are developing efficientand highly parallelized methods, andReconstruction and comparison of
metabolic pathway

Fig. : Schematic illustration of metagenomic
analysis using systematic and functional
analysesalso increasing the sp e e d of each

subprogram. We are trying to develop
a n u l t r a - f as t , l a r g e - s c a l e a na l y sis

program by approaching it from bothsides.

We want to utilize bioinformatics in medicine● What do you want to accomplish
through this and future studies?

Ito: My first goals are to develop ais increasing in various kinds ofNiida: In the ongoing simulationa huge amount of data in publicalready indispensable for analyzing

parameters but also to f ind theacquire biological knowledge, andthat lead to diversity by comparing

pipeline. Next-generation sequencing

a new concept of cancer research. To

thus completely different approaches

improve simulation, but it is also crucial

cope with such a situation, I want topractitioners to acquire new knowledge,

the characteristics of supercomputers

to our own analysis. In the future, I

in a sophisticated way.

bioinformatics that is useful to medicine.

analysis, but the amount of data

p ip e lin e fo r b i o l o gis t s to anal y ze

study, my goals are not only to identify

and restricted databases in order toprinciples of evolution and mechanisms

to carr y out computation using thewith experimental data, and to findtechnologies are rapidly progressing,achieve the goals, it is important to

may be required in several years. To

to communicate with in-service medical

develop software programs by merging

and to feed back experimental data

and the requirements of bioinformatics

want to make a discover y by using

K akut a: Not only in metagenomic

experiments. Computers areexperimental data, but I think that
faster and larger-scale analysis byparallelization will be increasingly

demanded in the future. I wish I could
contribute as much as possible tomeeting such a demand.

After the interview, the interviewees
answered questions from and talked freely

After SPECIAL TALK

with young researchers and students. Visit
the URL below for more information.

●See the URL on the right for longer version of this discussion meeting. http://www.scls.riken.jp/eng/newsletter/vol.11/openup.html

BioSupercomputing Newsletter Vol.11 5

SCLS Eyes S-cruise From the field of software development

Designing and evaluating new
medicines on a computer
Aiming to construct the platformof IT-based drug discovery
Fujitsu working jointly with the University of Tokyo
toward an innovative drug discovery process

Manager,Bio-IT R&D Office, Research & Development Division, Nozomu Kamiya
Next-Generation Healthcare Innovation Center, Fujitsu Limited(left in the photo)
Bio-IT R&D Office, Research & Development Division,
Next-Generation Healthcare Innovation Center, Fujitsu Limited

Takashi Mitsui(right in the photo)

Theme 2 “Simulation Applicable to Drug Design” (representative: specially appointed professor Hideaki Fujitani, ResearchCenter for Advanced Science and Technology, the University of Tokyo) aims to optimize MP-CAFEE, which is a method of
calculating the binding free energy based on molecular dynamics, for the K computer, identify a low-molecular weightcompound(s) that strongly interacts with a target protein that causes a disease, and develop and establish an efficientand quick technology for developing new drugs. Fujitsu started a joint study with the Research Center for Advanced
Science and Technology, the University of Tokyo (hereinafter referred to as “RCAST”) in 2011, and is tackling to conduct
IT-based drug discovery. We interviewed the leading researchers in Fujitsu on the circumstances and objectives of theinnovative drug discovery technology.

The IT-based drug discovery by Fujitsu
─ Why is Fujitsu working on the
R&D of IT-based drug discovery ?

Kamiya Fujitsu started to import andsell computational chemistry software anddevelop original software programs jointlywith research institutes and companies
in Japan in 1983, which is more than 30
years ago. At the time, Japan was behind
the USA, etc., on software development.
For example, let’s say that a university
bought a supercomputer, but they could
not use it effectively. So we started inhouse software development full-scale.
In 2003, the sequencing of the humangenome was completed, providing an
impetus to the biotechnology industry.
Fujitsu established the BioIT Business
Development Unit (present NextGeneration Healthcare Innovation Center)in 2004 to accelerate the bio-related
business, and has also concentrated
its efforts on technologies called ITbased drug discovery, which use
computational science, through its own
research activities and collaboration withcompanies, universities and research
institutes in Japan and overseas.
─ What is the IT-based drug
discovery targeted by Fujitsu?
MitsuiConventional drug discovery

6 BioSupercomputing Newsletter Vol.11

involves the selection of possibly
promising candidates for drugs amonga vast number of low-molecular weightcompounds by using the experience andknowledge of researchers, and repeating
synthesis and experiments. According
to one’s estimate, out of a total numberof candidate compounds, only one outof thirty thousand is finally approved asa new drug. The process requires a longtime, may be a decade or longer, andcosts several tens of billions of yen. Our
drug development technology involves
using computer simulation to design
the structure of a compound, virtuallyon the computer, that has drug efficacy
based on the structure of the target
protein, and creating a new compoundin a short period of time at a low cost.
We also have developed technologies forpredicting and evaluating the activities ofdrug candidates by molecular dynamics
simulation that assumes a biologicalenvironment.

Kamiya The technology is characterized
by the capability of designing diverse
chemical structures, which may not
be found in existing compounds, andnarrowing them down to promisingones before synthesis and evaluation. For
this purpose, Fujitsu developed original

software for designing low-molecularweight compounds, which is called
OPMF (Optimum Packing of MolecularFragments). Based on the threedimensional X-ray structural analysis ofthe (target) protein, a new compoundthat can bind to the active site is designedby connecting fragments. The efficacy ofthe chemical structure so obtained is thenpredicated by using MAPLE CAFEE for anenvironment that reproduces biologicalconditions, including the water molecules
surrounding the protein.

─ Is MAPLE CAFEE different from
MP-CAFEE?
Kamiya When Prof. Fujitani was in
Fujitsu Laboratories, he constructed
a force field that uniformly processes
biopolymers such as proteins and organic
molecules, and developed a method
for calculating the molecular dynamics
from the state in which the protein andcompound are separate until they arebound, and determining the binding freeenergy. This calculation method is called
MP-CAFEE. MAPLE CAFEE is the nameof the system constructed by Fujitsu byusing this calculation method.

SCLS Eyes
ProteinProtein

Molecular simulation

Water
Example: A reaction at a partof the target protein causes a
disease.
Identification Designingof the target a compound

Synthesis
Evaluation

Preclinicaltest

Clinical tests

Approval / saleFig. 1: Fujitsu developed OPMF, a software for designing a lowmolecular weight compound which strongly binds to andinactivates the target protein which causes a disease, enablinghighly effective novel compounds to be created in a short period oftime at low cost.

CandidatecompoundCandidatecompoundDrug A

Drug B

Drug C

Selection of target, synthesis of a compound, bioassay

Water Drug molecule

Example: A highly effective
compound is bound to thereaction (active) site to inhibit
the reaction.

CandidatecompoundIT-based drug discovery platform
Research Center for Advanced Scienceand Technology, the University of Tokyo

Biomedicine, biophysics (large-scale simulation)

Fujitsu

Molecular design, molecular simulation

Fig. 2: Schematic view of joint studies on IT-based drug discovery between
Fujitsu and RCAST and pharmaceutical companies.

Construction of IT-based drug discovery platform jointly with RCAST─ You started joint studies with
RCAST in 2011.

Mitsui During the process of doing R&D
toward the creation of low-molecularweight drugs by using computer
simulation, RCAST appreciated thetechnologies of Fujitsu for designing andevaluating low-molecular weight drugs;
and we started joint studies. In concreteterms, Fujitsu designs low-molecularweight drug candidates by using OPMF,
narrows them down to likely promisingones, and provides the information to
Fujitani Laboratory in RCAST. At the
Fujitani Laboratory, they calculate theextent the compound acts on the protein
via simulation. They notify the results of
the analysis to Fujitsu, and Fujitsu feeds
back the data into the design. Throughthis joint study, we are also using thecomputational power of the K computer,although indirectly.
Kamiya For the Theme 2 in FY 2012,
Fujitsu designed about 300 compounds
for a target protein in cancer therapy, andthe binding free energy was calculatedusing the K computer. Last fiscal year,

the results were used to improve studies
and further elaborate the designs of thecompounds. We chose 25 compounds
from them, and calculated their binding
free energy. Eight compounds werepredicted to have strong binding freeenergy, and studies will start jointlywith the experimental group toward
development of drugs for a cancer
remedy.

─ What is the goal of Fujitsu in
the joint study with RCAST?
Mitsui We aim to construct a platform
for IT-based drug discovery, which
innovates the development process,by using the excellent study knowhow
and results of RCAST, the large-scale
simulation technology performed by Prof.
Fujitani et al., and the molecular designand simulation technologies of Fujitsu.
We will also conduct joint studies witha pharmaceutical company to produce
the fruits of new drugs by IT-based drug
discovery.
─ What are the current issues in
R&D?
Proposal ofcompoundEstimation of binding free energy
by K computer

Feedback

Compound designingby the fragment method

Mitsui The biggest problem is thecomputational power. We want to quickly
check how the efficacy changes by achange in the design of a compound,and reflect the results for improving thecompound. In other words, we want fastcycles. However, calculation of binding
free energy requires a vast amountof computation, and thus we want touse as high a computational power as
possible. It would be meaningless to use
IT-based drug discovery if it is faster toactually synthesize the compound thancalculating.
─ What do you think about the
future of IT-based drug discovery ?

Kamiya IT-based drug discovery isa highly promising new-generation
process for developing innovative andhighly effective compounds in a shortperiod of time at low cost. We believethat establishment and application ofthis innovative technology will help
to create new therapeutic drugs forvarious diseases. It would be wonderful
if computational science can contributeto improving medicine, such as making
it possible to cure diseases that are
difficult today. We mentioned that thesuccess rate of a new drug is one out of
30 thousand. This means that we need tosynthesize thirty thousand compounds
to develop one drug. If such experiments
can be replaced by computation, it would
sharply reduce the labor and difficulties
for developing a drug. Also to achieve thisgoal, we want to produce results as earlyas possible.

Fig. 3: Schematic view of the joint study between Fujitsu and RCAST on Theme 2. Fujitsu
designs candidate compounds, and the results of binding free energy calculation are fed
back and used to elaborate the design.

● See the URL on the right for detailed information on this report

http://www.scls.riken.jp/eng/newsletter/vol.11/sclseyes.html
BioSupercomputing Newsletter Vol.11 7

Close-up on SCLS Research

Theme 1 Simulations of biomolecules under cellular environments

Structural analysis of protein in solution by molecular
dynamics simulation and small angle X-ray scattering
Computational Life Science Laboratory, Graduate School of Medical Life Science,
Yokohama City University

Yuichi Kokabu
Biopolymers such as proteins exist
i n s o l u t i o n . A p r ote i n i n s o l u t i o ndoes not have a single determined
structure, but undergoes structuralfluctuations by thermal fluctuation.
Therefore, determining the structureof a protein in solution including its
struc tural f luc tuations is a key forunderstanding the in vivo functions of
the protein. In this article, two methods
for determining (or estimating) the
protein structures in solution, namely
molecular dynamics (MD) simulationand small angle X-ray scattering (SAXS),
are explained by taking our recent study
results for example.
MD simulation reproduces behaviors
of a protein in solution by solving
the equations of motion. With thismethod, the atomic-level behaviors
of a protein can be estimated. We
estimated the structure of Rad51 protein
filaments in solution, which catalyzes
strand exchange in homologous
recombination, by per forming MD
simulation of a dimer as a minimal unit

Fig. 1 : Structure of a dimer of Rad51 estimated by MD
simulationof the filament (Fig. 1).
On the other hand, SAXS irradiates
X-rays directly to the protein in solution
and determines the general form of themolecule from the scattering pattern.
Although the resolution is low, SAXS
can measure the protein struc ture
in solution including its struc turalfluctuations by thermal fluctuation. Thistime, we analyzed the structure of aprotein called Swi5-Sfr1 complex (S/S) in
solution, which is an activator of Rad51,
by using SA XS, and found that theprotein takes an extremely elongatedform in solution.
This elongated structure f its wellto the groove of the estimated Rad51
filament model (Fig. 2). Therefore, we
hy p othesize d that Rad51 f ilamentis activated by binding of S/S to thegroove, and are verifying it.
MD simulation can estimate astruc ture including f luc tuations at
an atomic-level resolution, and its
confidence factor can be increased byexperimental verification. Aiming toverify the results of MD simulationby comparing with the experimental
d a t a o f SA X S , w e d e v e l o p e d atheoretical method for calculating
the SAXS scattering pattern fromthe results of MD simulation. We canjudge that a result of MD simulation
is valid if the SAXS pattern calculated
from the MD simulation agrees withthe experimental SAXS pattern. Thismethod was applied to a mutant
protein Swi5-Sfr1dN177, in which the
177 residues from the N terminus of
Sfr1 are lost, to analyze the proteins tr uc ture in s o lu tio n in clu din gfluctuations at an atomic level.
Today, we are using the method
for a DNA-binding protein calleda nucleosome. A nucleosome is ahuge molecule, and it would require● See the URL on the right for detailed information on this reportand profile of the author.

8 BioSupercomputing Newsletter Vol.11

Fig. 2 : Model of Swi5-Sfr1 (magenta) binding to
the groove of Rad51 filament in solution

enormous computation, i.e., too muchtime, to estimate its structure by allatom MD simulation. Therefore, we areusing coarse-grained MD simulation,
w hich c al culates th e s tr uc ture by
substituting a particle for an amino acid,to analyze the fluctuations in the DNA
terminus of the nucleosome and its
SAXS scattering pattern.

http://www.scls.riken.jp/eng/newsletter/vol.11/zoomin01.html

Close-up on SCLS Research

Theme 1 Simulations of biomolecules under cellular environments

Coarse-grained simulation : Investigation of the molecularmechanism of signaling pathway using CafeMol
Laboratory of Theoretical Biophysics, Department of Biophysics,
Division of Biological Sciences, Graduate School of Science, Kyoto University

Ryo Kanada
For cells to adapt to the environment,
mechanisms are required for transmitting
signals from outside of the cell to the
nucleus, amplifying the signals, andexpressing a gene and/or changing theactivity of a protein. These mechanisms
are called a signaling pathway. In our
project, we are focusing on mitogena c t i v a t e d p r o t e i n k i n a s e (M A P K )cascades, which are a typical signaling
pathway model.
For example, in a mammalian MAPK
cascade (one of pathways) shown in
Fig. 1, a stimulus from outside activates
upstream Ras and Raf (MAPKKK), which
phosphorylates and activates anotherprotein MEK1 (MAPKK) downstream,
and then ERK2 (MAPK). Proteins arethus successively ac tivated (Ras →R a f (M A PK K K ) → M EK1 (M A PK K ) →ERK2 (MAPK)) until the signal reaches
the nucleus. The cascade not only
determines the fate of the cell (whether
to undergo proliferation, differentiation,
or apoptosis, etc.), but is also known to
be closely related to canceration (cancer
development). Therefore, elucidation of
the activation mechanism in signaling
pathways is strongly demanded also
from a medical point of view. However,
Stimulus

Nucleusthe precise molecular mechanism still
remains unclear
One of the reasons for the difficultyof understanding the mechanism isthat it is challenging to experimentally
determine how the upstream protein(for example, MEK1) approaches thedownstream protein (for example, ERK2),
and forms a complex in terms of atomiclevel structure. In our study, we aim toestimate the structure of the MEK1-ERK2
complex and its formation dynamics byusing a theoretical approach, and thestructures of MEK1 and EKR2 which are
already known.
For this purpose we are using
CafeMol*, which is a coarse-grained
molecular dynamics simulation programd e ve l o p e d by o u r r e s ea rc h tea m .
CafeMol assumes each amino acid that
constitutes a protein as a bead, andcalculates the dynamics. Therefore,
the computation cost is significantly
reduced compared to all-atom molecular
dynamics methods (even a physicalevent of a millisecond order in a hugesystem such as a chromatin fiber canbe reproduced by making full-scale useof the K computer, a supercomputer).
By using our original atomic interaction based coarse
grained (AICG)
Cell membranemodel to represent the interactions(force f ield) among beads, we canperform more practical calculations
than conventional coar se - graine dsimulation, as our method considers thedependency on the amino sequence andthe secondary structures of the proteins.
A complex structure estimated fromthe coarse-grained simulation using
CafeMol is shown in Fig. 2. This structure
w as co mp are d w i th th e s t r u c ture
estimated from existing docking servers(ClusPro, etc.), and they were found toagree well with each other. CafeMol canalso reproduce the time-dependent
progress of protein binding, whichcannot be performed with a docking
ser ver. We are planning to use thisadvantage to investigate the effectsof the presence of a scaffold protein(s)(KSR) and crowded environments within
the cell on the dynamics of complex
formation, and reveal the molecularmechanism of signal transmission.
Note :＊ H. Kenzaki et al., J. Chem. Theory Comput. , 7, pp 19791989 (2011) [http://www.cafemol.org/]

Cytoplasm

Change in gene expression
Fig. 1 : MAPK cascade signaling pathway● See the URL on the right for detailed information on this reportand profile of the author.

Fig. 2 : Coarse-grained simulation of MEK1 and ERK2 by CafeMol

http://www.scls.riken.jp/eng/newsletter/vol.11/zoomin02.html

BioSupercomputing Newsletter Vol.11 9

Close-up on SCLS Research

Theme 3 Hierarchical integrated simulation for predictive medicine

Development of a central nervous system model for
elucidating the onset mechanism of Parkinson’s disease
Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University

Jun Igarashi
We are conducting simulation studiesof the brain by using the K computer
to elucidate the mechanisms whereby
Parkinsonian symptoms develop,
and investigate an effective remedy.
Parkinson’s disease is a disorder of thecentral ner vous system and causes
various symptoms mainly related
to movement, such as slowness of
movement, shaking of the body, muscle
rigidity, and difficulty in maintaining
posture. Parkinson’s disease is the secondm o s t co m m o n n e u r o d e g e n e r at i ve
disease after Alzheimer’s disease, andaf fects several million people in theworld.
The cause of Parkinson’s disease isloss of dopamine-generating cells inthe substantia nigra compac ta, thecauses of which have been suggested
to be mitochondria abnormality, andthe ef fec ts of reac tive ox ygen. The
resultant dopamine depletion triggers
an abnormal and strong synchronousner vous ac tivit y of about 8-14Hz in
the basal ganglia. The basal ganglia
is interconnected with the thalamus
and cerebral cor tex forming a loop(basal ganglia → thalamus → cerebral

cortex → basal ganglia); and the entire
circuit is in charge of processing
information that controls voluntar y
movement, etc. The abnormal
synchronous ner vous activity in thebasal ganglia in Parkinson’s disease
is believed to af fect the entire loop,
inhibiting normal information processing
and causing various symptoms. However,
it is still poorly understood how thebasal ganglia, thalamus and cerebral
cortex affect each other and cause thevarious symptoms of Parkinson’s disease.
Factors obstructing elucidation of themechanism include the limited numberof nerve cells and the limited range ofthe brain that can be actually monitored,
and the dif f icult y of measuring theinteractions among nerve cells, which
are connected in a complex way.
In brain simulation, the ac tivitiesof all nerve cells and interactions arerecorded, and the nerve activities canbe investigated repeatedly for various
conditions. We aim to simulate theentire nerve circuit of the basal ganglia,
thalamus and cerebral cor te x , andinvestigate their mutual interactions byusing the enormous arithmetic capacity
Primary motor cortex

Thalamusof the K computer, and investigate andimprove deep brain stimulation andother remedies. At present, we aredeveloping models of the basal ganglia,
thalamus and cerebral cortex, separately.
The basal ganglia is being modeled so as
to reproduce the abnormal synchronous
nervous activity. The pathological neuraloscillation in Park insonian diseasehas been successfully reproduced byimitating the characteristics of nerve
cells and synapses in the subthalamic
nucleus and globus pallidus lateralsegment under dopamine depletion.
The thalamus and cerebral cortex arebeing modeled, focusing on elucidating
the mechanism of Parkinsonian tremor.
The tremor is known to synchronize
w i t h t h e n e u r a l o s c ill at i o n (a b o u t
10Hz) at the thalamus and cerebral
cortex, but at a half of the cycle. We aredeveloping a neural circuit modelof the thalamus that can reproduce
the oscillation, and a model ofthe cerebral cortex that expresses
the body movements involved intremor. We are also testing the entire
model that connects the models
o f th e b as al gan glia, thalamus
and cerebral cortex. At the final
stage, we are planning to evaluate
the development mechanism of
Parkinsonian symptoms by usinga model of the whole body, which
includes the spinal cord andmusculoskeletal models that feedback sensory signals to the brain.

Fig. : Left: Schematic illustration of the connections between the basal ganglia, thalamus and cerebral cortex
Right: Three-dimensional illustration of the planned neural circuit model between the cerebral cortex and the thalamus● See the URL on the right for detailed information on this reportand profile of the author.

10 BioSupercomputing Newsletter Vol.11

http://www.scls.riken.jp/eng/newsletter/vol.11/zoomin03.html

Osaka University education programon high performance computing

Osaka University
Graduate School of Engineering Sciencebe main player in super-computational
science/engineering. These subjects
are also provided as part of the“Osaka
U n i v e r s i t y G r a d u a te P ro g r a m fo r
Advanced Interdisciplinary Studies”
th ro u g h th e Ce nte r fo r Ad va n ce d
Medical Engineering and Informatics(MEI Center) educational program, andwill accept students from all graduate
schools by arranging the classes on
Saturdays.
These classes are, at the same time,o p e n to e ng i n e e rs/res ea rch e rs ofindustries and graduate students ofother universities as part of the MEI
Center Skill Course, an Osaka University
E x tensio n . I n this fra m ewo rk , th e
auditors will be given certificates issued
by the President of Osaka University.
A s an outreach activit y, a series
of wo rk sh o ps o n H P CI with th e Kcomputer as a primary resource fordrug discovery and medicine has been
held annually in Osaka and Tokyo.
This provides a forum to translate theoutputs of frontier research towards

in-silico drug design, in-silico medicine
and predictive medicine at academic
and research institutions into advanced
industrial technologies by inviting
lecturers from cutting-edge researchg ro u p s . Pl e n a r y/ key n ote l e c t u re s
as well as sessions are organized at
co n fe re n ce s h o s te d b y a c a d e m i csocieties/institutes in order to promotehigh per formance computing inbioengineering, bioinformatics and life
sciences, among others.
T his yea r, a n intro d u c to r y cl a s s
entitled“Introduction to Biosimulation”
is being launched for universit y
freshmen regardless of their academic
study area to provide an opportunity
to open their eyes to supercomputing
science/engineering. These activities
are aimed at encouraging the young
generation, especially current
students, to engage in computational
pharmaceutics, medicine andbioengineering. For details, please
visit the website at http://hpci.me.es.
osaka-u.ac.jp/

Osaka University Graduate Schoolof Engineering Science has been
conducting an“Education Program for
Predictive Medicine and Drug Discovery
on a High Performance Computing
Infrastruc ture (H PCI)” jointly with
the Graduate School of Information
Science and Technology since 2011,as part of the“SupercomputationalLife Science(SCLS)”. The core of thiseducation program is the pair of classes“Biosimulation”and“Bioinformatics”
provided for graduate students who will

5th workshop on HPCI with the K computer as
primary resource for drug discovery and medicine

Past and future of acceptance of applications from the public
RIKEN HPCI Program
to use the SCLS supercomputer system
for Computational Life Sciences
The objectives of SCLS are to driveb rea k t h ro u g h a cco m p l is h m e nt s
by taking advantage of HPCI (High
Performance Computing Infrastructure)with the K computer at the core, as
well as to form a wider community forcomputational life science users bysupporting research and developing
human resources. To achieve theseo bj e c t i v e s , w e h a v e p ro v i d e d a
SCLS supercomputer system highly
compatible with the K computer andpublicly invited research agendas thatutilize this SCLS supercomputer system,

Comments
from

users
We very much appreciatethat you applied a patch to thesoftware that could not run on the
SCLS supercomputer system. The
software became available in thesystem, and we were able to complete
our research agenda as planned.

a s p a r t of o u r su p p o r t
Next call The FY2015 first round callfor the active and broadplanned to start invitations from February 2015use of HPCI by life science
researchers and engineers.
those agendas. As of the end of the
Any researchers and engineers who
FY2014 first round call (the system was
are involved in life science can apply
available for use from April 2014; fivefor the use of the SCLS supercomputer
agendas were adopted), 23 agendas
system, and actually we have had aincluding new ones had been going on,
number of applicants from researchand 117 persons had been involved inand educational institutions to private
those agendas.
companies. An applicant who has a
Next, we plan the FY2015 first roundresearch agenda can use the SCLS
call which starts looking for applicantssupercomputer system free of charge,
from around February 2015. As we are
and also extend the use period byapproaching the end of the Strategic
submitting a continuation request.
Programs for Innovative Research, theAcceptance of applications from the
FY2015 first round call for the SCLS
public to use the SCLS supercomputersupercomputer system will be the lastsystem (the first call was in FY2012)
one that SCLS carries out. Although we
has been made four times up to the
do not have much time left for using
FY2014 first round call. A total of 34
the system, we look forward to yourresearch agendas were adopted, andapplication.
144 persons have been involved in

BioSupercomputing Newsletter Vol.11 11

"Rental Exhibition Panels" are now available to introduce research on computational
life science and SCLS

To disseminate the research results and enhance understanding of computational life science, Supercomputational Life Science (SCLS)
provides rental panels that can be used to introduce research to anyone, who are not researchers, at any time in a simple way. Thesepanels can be exhibited at an event held in a school or an educational facility or an event for promoting awareness of science andtechnology, as well as used in class. We will notify the details on the website of SCLS as soon as they are fixed.

SCLS website redesigned

The redesigned website for SCLS has been launched!
We provide a variety of information that allows many people to enjoy SCLS activities. http://www.scls.riken.jp/

For researchers andengineers

S-cruise software, a portal that discloses the results fromthe software developed using the K computer, e-SCLS thatprovides training sessions for enhanced sampling, gene
network analysis, etc., and public invitations relating to a SCLS
supercomputer system compatible with the K computer

For students andworking people

e-SCLS that offers academic seminars on our website
where people can learn the basics of computational life
science

For educators

SCLS on-site class in which people can enjoy SCLS courses,
and SCLS rental exhibition that provides information onrental panels that introduce research on SCLS

People who are new
to Computational Life
Science and SCLS

Beginners which explains SCLS in an easy-to-understandway using Q&A and animations, and Biosupercomputing
Newslet ter that provides more information thanpublications

The SCLS website filled with informationthat makes people familiar with theworld of computational life science.
Search with the keyword "Field 1".

October 2 (Thu) to 4 (Sat)2014 Annual Convention, JSBi 2014 - the 3rd Joint Conference on
Informatics in Biology, Medicine and Pharmacology⃝Location : Sendai International Center (Sendai-shi, Miyagi)
October 4 (Sat): Sponsored sessions and training sessions are held together with the HPCI
human resource development programs of AIST

Ocober 7 (Tue) 2014 to February 3 (Tue) 2015 ⃝Every Tuesday, 5:00 p.m. - 6:30 p.m.

Remote lecture with Kobe University Education Center on
Computational Science and Technology"Basics of Computational Life Science - from the intersection of Life science and Scienceand engineering to application to society" (total of 15 sessions)⃝Location : Kobe University, Faculty of Engineering building, 1F
We will notify the details on the website of SCLS as soon as they are fixed.

Strategic Programs for Innovative Research Field 1

Supercomputational Life Science

SPIRE (Strategic Programs for Innovative Research) is a MEXT program aiming to produce ground-breaking results in computer science technology
by maximizing the benefits of the HPCI (High Performance Computing Infrastructure) centered on the supercomputer K computer, andencouraging developments in five research fields that need to be strategically addressed.
“Supercomputational Life Science” has conducted research with the mission of understanding and predicting life phenomena based on large-scale
simulation and advanced data analysis, and to apply these results to design and implement medicine and medical care with its research.

BioSupercomputing Newsletter Vol.11 2014.9

www.scls.riken.jp/en/

RIKEN HPCI Program for Computational Life Sciences
7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe Hyogo 650-0047, Japan
Tel:+81-78-940-5692 Fax:+81-78-304-8785

Issued: September 2014

RIKEN 2014-055