Strategic Programs for Innovative Research Field 1 Supercomputational Life Science13

2015.9 Vol.
CONTENTS

Open Up SPECIAL TALK

Discussion meeting

Accurately predict the absolute binding freeenergy using K computer to support the drug
design of next-generation
Takefumi Yamashita ／ Keiko Shinoda

SCLS Eyes

The University of Tokyo

S-cruise From the field of software development

Realize molecular dynamics simulations of huge
biological systems with K computer
Yuji Sugita ／ Jaewoon Jung ／ Takaharu Mori

ZOOM IN

RIKEN

2

6

Close-up on SCLS Research

Theme 1 Simulations of biomolecules in cellular environments

Whole bacteria cytoplasm modeling andall-atom molecular dynamics simulations
Isseki Yu

RIKEN

8

Theme 3 Hierarchical integrated simulation for predictive medicine

Modeling human for understanding humanAkihiko Murai

National Institute of Advanced Industrial Science and Technology

9

Theme 3 Hierarchical integrated simulation for predictive medicine

Neural control of human quiet standing and biped walking
Movement fluctuation and its degeneration caused by neurological disease
Taishin Nomura ／ Chunjiang Fu

Osaka University

10

SCLS Gotcha!

“On Interdisciplinarity studies - the integration of biology,
physics, chemistry and mathematics”
Third Advisory Committee Meeting

11

11

NEXT STAGE・Challenging the priority issues on post-K computer
Innovative drug discovery infrastructure throughfunctional control of biomolecular systems
Yasushi Okuno

RIKEN

Integrated computational life science
to support personalized and preventive medicine
Satoru Miyano The University of Tokyo

www.scls.riken.jp/

1214Discussion
meeting

Theme 2 Simulation Applicable to Drug Design

Accurately predict the absolute binding free energy
the drug design of next-generation
Clarif y biomolecular behavior by the simulation science to suppor t
exploration of small molecular drug and antibody drug candidates

Theme 2 Simulation Applicable to Drug Design (Representative: The University of Tokyo, Professor Hideaki Fujitani) searches
for candidate compounds that strongly bind to target proteins of diseases using the absolute binding free energy computation
method based on the originally developed molecular dynamics (MD) method. Furthermore, they analyze interaction between
proteins aiming at renovation of the drug design process by the computational science. This time, we interviewed two
researchers who are involved with the studies on new chemical compounds which suppress functions of target proteins ofdiseases and design of antibody drugs utilizing the K computer.

Encounter with the biosimulation research● First, I'd like to hear about how
you two started working on thepresent research.

biological field such as the molecular

2011. Since then I have studied onproteins. That is my background. I was

dynamics calculation that targets

computational science since I was

simulation. I thought the simulation

Yamashita : I have worked on theattracted to describing physicalphenomena in mathematics in myhigh school days and worked on thecomputational science. I was interested
in quantum mechanics and studied

on proton. Having found a lot of

phenomena greatly affected by the
proton in the field, I was engaged in the

2 BioSupercomputing Newsletter Vol.13

biology in the US and studied oninterested in drug design using protein
would be applied more widely thanI expected, so I decided to challenge

this theme. The research directly

connected to medical service is related
to priority issues in the society, so thatis worth doing. I am really happy if I
can contribute to the society. I joined
the University of Tokyo in January,biosimulation and the molecular
proteins related to drugs.

Shinoda : I was very attracted to thephenomenon called “phase transition”
in physics in my college days. So, I

worked in an experiment laboratory first,
and was involved with studies mainlywith X-ray diffraction experiments ofalloy using synchrotron radiation. I hada chance to observe phenomena that
could rarely be seen in the experiments

Takefumi Yamashita

Structure of kinasecombined with inhibitor: The ribbon
and red balls indicate
kinase and inhibitor,
respectively

Associate Professor, Ph.D
Research Center for Advanced Science and Technology
Systems Biology and Medicine
The University of Tokyo

In the simulation research with the K computer weshould not be afraid of any failure. That is important.
Through those experiences like trial and errors we surely
obtain reliable results. Further, we need to find a visionthat leads to the next step from such experiences.

Keiko Shinoda

Conventional computer-assisted drug design method

Assistant Professor Dr. Sci.
Research Center for Advanced Science andTechnology Systems Biology and Medicine
The University of TokyoI think that it is important to continue
making researches with simulation methods
or systems to make use of the highperformance by the K computer in the lightof using the K computer. Performing thecomputation in large quantities enables us
to obtain statistical interpretation even in
the case of the computation, whose scale isnot big respectively.

X-ray crysChemicaltallographic compound
analysisdesignExperiment

Medicinal
drugs

Feedback

Antigen (orange) and an
antibody (blue).
The important residues
which interact in the antigen
and antibody boundary
surface are shown as atoms.

using K computer to support

New computational drug design with the supercomputer
Feedback
X-ray crysChemical Utlize supertallographic compound computer Experiment
MP-CAFEE
analysisdesigncomputation

Medicinal
drugs

in silico
Feedback

Figure : Possibility of new computational drug design method

and I was very excited with it. But,

had worked on various themes suchthe researches including examination ofmodel researches and theory to findchemical calculation as a post-doctoral

drug design have its clear purposesat the same time I hoped to dig into
how and why such phenomena occur.
I took a master course and a doctoral

course of different graduate schools. I
studied on phase transition of diluted

ferromagnet in the master's course andon quantum liquid based on an integral

equation theory in the doctoral course.
I was involved with a research with the
MD simulation for the first time when

I was a post-doctoral researcher of

National Institute of Advanced Industrial

Science and Technology. After that, I

as material development or quantum

researcher of enterprises. Meanwhile, I
had been in half-hearted attitude all thetime. I could take time to hypothesize

and carefully by myself. I could not
dig into my research, which mademe frustrated. I was employed by the

University of Tokyo in December, 2010,a month before Dr. Yamashita was. WithMD simulations of biomolecules using
the supercomputer and examinationof their structures and dynamics, I

their structures and dynamics to supportand direct relation to the output. Such

researches really interested me andwere worthwhile doing. The professorsof the wet team working with me are
eager to develop drugs with the resultsof computational science. The results ofsimulation research are directly applied

for drug design, which gave me a greatpressure on me; however, I will make aneffort to do it.

researched to develop drugs. Because

Promote research that contributes to new drug design● What researches are you two
working on for Theme 2?

Yamashita : What I first dealt with Theme
2 was a research on molecular target
drugs that inhibit kinase. Many drugs
have an effect by suppressing functionsof the proteins that cause the disease. In

order to discover a drug, it is necessary
to find out chemical compounds
which strongly interact with the target
protein in vivo. Therefore, we attempt
to evaluate absolute binding freeenergy of target proteins and chemicalcompounds by simulations with asupercomputer so as to find chemicalcompounds that can be used as drugs.
The absolute binding free energy is thephysical quantity that indicates how
much molecules can recognize target
proteins. We predict the activity of
new candidate compounds with high

BioSupercomputing Newsletter Vol.13 3

Discussion
meeting

Accurately predict the absolute binding free energy using K computer to support the drug design ofprecision by the method of the absolutebinding free energy computation, "MPCAFEE", developed by Prof. Fujitani andhis colleagues. We design and searchfor chemical compounds with highinhibitory activity. The MD program, theengine of "MP-CAFEE", is "GROMACS".
It has been developed as an open
source program. We tuned this up for
the K computer in cooperation with
developers of Stockholm University
and others. The computation improved
approximately twice as efficiently as
the primary version. This speedingup allows the absolute binding freeenergy computation to be performed
more efficiently. In this way, a technicalbase to find out promising candidate
compounds has been established. Largescale data began to be accumulated
since last year. It enables us to write
papers that examine possibility of new
drug design. Now our important mission
is to analyze the computation results
and provide outcomes as science.
I have been doing a basic research,and my greatest motivation is in there
while I am attracted to mysterious
aspects of basic phenomena andthings not clarified when doing theapplied research for drug design. Whileapplication progresses steadily towarda practical use, there actually are a lotof thing remaining insufficient in basic

parts. Not all are completed as perfectmethods. As long as we belong to
Academia, we need to continue theresearch further. In order to achieve
it, we perform actual computation
widely and obtain results, continuingresearches for such aspects.
Shinoda : I have studied molecular
dynamics for antibody drug
development against cancer. The useof antibodies that bind specifically toantigens has achieved considerable
success in cancer therapy in recent
years. Antibodies are applied to themethods such as pre-targeting method,which involve separating the targeting
antibody from the subsequent deliveryof therapeutic agent that binds to thetumor-localized antibody. Now wetry to improve the affinity of current
treated antibodies and investigate basic
mechanism: a specific way of binding
antigens - antibodies by simulations.
This is because the antibody treated by
us is very unique. There is a proline in theregion where antigens are recognized,
and its conformation changes fromcis to trans by binding to antigen (cistrans isomerization). This transition
requires great amount of energy and it
is said that it assumes a switching rolefor various biological processes. It takes
too much time to see the mechanismof this transition by the MD simulation

Figure : Binding structure of "Cupid" and"Psyche" used for the pre- targeting therapy.
The antibody connected to "Cupid" (indicatedas ribbon) binds to the target protein, and"Psyche" (indicated as van der Waals in the
middle) that carries drugs specifically binds to"Cupid".

directly; however, if we can obtain a clue
to understand the mechanism, it canbe applied to the design of the part forrecognizing antigens, we believe.
In order to clarify the binding
processes and structures, we performed
nearly 1,000 MD simulations using
the K computer, and obtained various
trajectories of antigen binding toantibody. In other words, we intend
to estimate the mechanism observing
various cases by performing theextensive simulations. It is biologicallyessential to clarify such an underlying
mechanism, which leads to drug designin the future.

Building up research vision for the next generation is also a mission● Going into the final year, how doyou wish to advance your researchbased on the results obtained so
far?

results can show is only imitation of

built up purely

In order to get close to the real

remarks "experi-a method for high speed computation

at various phases, so as to verify

Yamashita : As I have just mentioned,

being established so we are challenging
a large-scale computation of over 200

chemical compounds for one theme.
In the future, it will be important tobrush up the method to elucidate "Why"through more detailed analyses. I'm suredrugs such as the kinase inhibitor will

the reality and nothing but prediction.

phenomena, it is necessary to conduct
proper experiments and verifications
consistency between the simulationand the reality. I believe that repeatingsuch processes will lead to realizationof highly accurate simulations and also
be helpful for improving the speed andefficiency of drug design process.

About the relation between experi-

be designed and explored efficiently.

ments and simulations, I suggest thatfor applying simulation results to drugthat simulations are not performed toFurther, the experiment is importantdesign, I believe. No matter how goodthe simulation result is, what simulation

4 BioSupercomputing Newsletter Vol.13

young researchers should understandagree with experimental results. Models
themselves are based on physics andfrom the theory. My

ments are impor-tant" doesn't meanthat simulations

results are to be

adjusted to makethem consistent

with experimental results conveniently
but means that we find some parts of

the reality that the model can’t repro-

duce. Experiments are, so to speak,something like "checking the answers"

and are important to find out why thesimulation results do not agree withexperimental results, which is very

important and the researchers must benext-generation
done for in the simulation research.

attempt. For instance, the variation oflast conducting

to reflect the major theme that I havewidened by changing the approaches

simulations, weThinking of those things, I’m going

been in charge of in order to researchoutcome, adding the simulations
to respond to new questions while
brushing up methods and techniques.

The simulation results are given to theresearchers for the next experiments
but the beneficial of the results is in

my hands. So, if we can make use ofthem for the improvement of the future

analysis techniques, or acquire hints tounderstand interesting characteristics
of proteins from them, the research
will be even more meaningful andinteresting. Not only using the methods

that have already been established,
but also making them improving with
our knowledge is fantastic. In somecases, the absolute binding free energy
is not the only way and there may

be other techniques by which better

results are obtained in combination
with the absolute binding free energy.
Algorithms can also be improved basedon a new viewpoint. We have mainly
focused on speed-up but I believe there

must be other approaches that we caneffective candidate compounds can befor the activity prediction. They may be

worthless in the immediate future but I
believe it is also our important mission

to propose the ideas and theories thatcan be utilized in the next generation or
next challenge.

Shinoda : Last year, we performed

approximately 1,000 MD simulations in
an antigen- antibody system containing

water with different initial velocity,

and analyzed binding process andstructure, water dynamics, and so on.

We continue the analysis now, and ourjob for this year is to summarize theanalysis results, I suppose. Dr. Yamashita
has just mentioned that "GROMACS"
has come to run in the K computer. I

actually have received its benefit, which

made my job much easier. However,as the MD computation was toughwork, we paid great attention to it. In

particular, the K computer in the earlystage was not always capable of giving
100% of the expected data. It caused
some problems such as half-way systemfreezing and data crashed by errors. At

nearly 1,200
could acquire ap-

proximately 1,000
date out of them.
Further, data

being obtained
successfully, we

needed to check ifthey were complete being. Anyway, as it

was my very first time to perform such a

massive computation at the beginning,
we had no idea which part to check inthe data, so as to draw out data setsbringing outcome. Finally, we managed
to finish checking, and then at least

approximately 1,000 of them were allright. The analysis still going on, we've

found that the time of binding, durationand frequency of the binding vary ineach case and that some do not evenbind. Thus we have observed various

behaviors. I presume that such a massive

simulation had never been performed

for a binding process of antigens andantibodies so far. In this sense, we

carefully examine the dynamics of thebinding process from these results.

Wish to make use of the research results for medical service● Look forward five and ten years
later, what researches do you wish
to work on in the future?

researches. Of course, as long as weat the molecular structure, and said toactual medical service so I try to perform

feel something strange in this result".

research, it usually takes about five years

research to clarify the cause of a disease

Yamashita : Thinking of the cycle of aobtain answer of the research. So, ten
years are not a long period. As I saidat the beginning, being interested inphysical mechanisms, I am not going

to continue only biology researches.
However, because molecular behavior
in proteins and cells have been clarified

one after another and the biosimulation
is making great progress, I find thisfield very interesting. In this sense, inthe future we are going to focus not
only on one single protein but perform

simulations for a protein complex andfocus on proteins playing special roles. I
continue exploring interesting physicalphenomena based on the results of suchtreat biomolecules, we cannot ignore

a simulation research to support it. A
is a good example. After all, the clues
seem to be hidden in various diseases.

me "there's something wrong with it. I
Surprisingly I asked him why he knew

that, and he said "you'd see it putting
yourself in the molecule's position".

I wish I would say, "Make it little moved,

I think slight difference in proteins

and we'll get an antibody to bind better"in some cases. I am sure that it will bemolecular simulation. Further, throughcauses unexpected serious symptoms

more important in the future to reveal
what small errors in design or assembly
should cause at molecular or atomic
levels. I want to contribute to that.

Shinoda : At present I have only
treated only one kind of antibody. I
want to is a kind of be a workman,

or a specialist who knows all about
simulations of antibodies in five years.

Experts of the quantum chemistry
would find errors intuitively looking●See the URL on the right for detailed information on this report

only looking at visualized images of

the research of antibodies, I do my best

to clarify the mechanism of importantphenomena, which contributes tothe medical service. Of course I workon researches on the computational

science with the computer simulation
technique, however at the same time

I have a feeling to face the biology orother approaches such as statistical
dynamics, which is still a vague idea.

http://www.scls.riken.jp/eng/newsletter/vol.13/openup.html
BioSupercomputing Newsletter Vol.13 5

SCLS Eyes S-cruise From the field of software development

Realize molecular dynamics
simulations of huge biologicalsystems with K computer

Highly parallel molecular dynamics simulation software"GENESIS"RIKEN Theoretical Molecular Science Laboratory, Chief Scientist,
RIKEN Advanced Institute for Computational Science, Computational Biophysics Research Team, Team Leader

Yuji Sugita

RIKEN Advanced Institute for Computational Science, Computational Biophysics Research Team, Research Scientist

Jaewoon Jung

RIKEN Theoretical Molecular Science Laboratory, Research Scientist

Takaharu Mori

A joint research team consisting of Yuji Sugita, the team leader of the Computational Biophysics Research Team of RIKEN
Advanced Institute for Computational Science, and his colleagues, has released the molecular dynamics simulation
software, "GENESIS", for massively parallel supercomputers. It was released as an open-source software on May 8, 2015.
"GENESIS" has successfully realized high parallel efficiency by introducing their original computational algorithms suited tothe architecture of the K computer. It has also enabled us to perform a fast molecular dynamics simulation for a system incellular environments, consisting of 100 million atoms, which could hardly have been simulated so far. Moreover, it allows
simulations of biomolecules like proteins, cell membranes, glycans, and nucleic acids at the molecular level. Therefore, it
greatly attracted researchers' attention. It is expected to be utilized widely from basic studies to drug discovery in the future.
We interviewed the developers about the process of development of GENESIS and key features.

The molecular dynamics software which makes full use of the maximum performance of K
computer─When did you start the development of "GENESIS"?

Sugita We star ted it around 2010,
before the emergence of the K computer.
The computational method to simulatemotions of molecules according to thelaws of physics is called the "Molecular
Dynamics (MD) method". A number of MD
simulation software has been developed
all over the world so far. If you try to apply
conventional computational algorithms
to a large -scale molecular assembly
system with a large number of CPUs likethe K computer, the computation speed
is easily saturated due to the significant
communication between CPUs. Therefore,
we started to develop a new MD simulation
program that is capable of fully utilizing the
maximum performance of the K computer.
However, to be honest, it was obviously noteasy to develop such software, and barriers

to start the development were really high.
Moreover, in order to create software thatcan be used for research, various functions
should be introduced. I often felt it was ahopeless task during the development. I
was afraid that Dr. Mori and Dr. Jung, whoplayed a key role in the development,
had to continue their work without clear
prospects. We had no idea when we could
reach the goal.
Mori First, we made efforts to reproduce
the same energy and force values asexisting software. If we cannot obtainthe same results, it means "GENESIS" haserrors somewhere. After that, simulation
methods such as temperature and pressure
control algorithms were introduced.
The algorithm that I introduced first was
actually wrong. The temperature control
was okay, but there were a lot of troubles
in pressure control. Anyway, we solved

the problems one by one while keeping
studying. Because such basic algorithms
are prerequisites for research, we planned
to do basic work prior to developing new
methods.
Jung I had been involved in quantum
mechanical/molecular mechanical (QM/
MM) calculations before I joined thisproject. So I didn't know much about
MD simulation. I had to learn about thetheories of MD one by one, and wrote thesource codes from scratch. It was reallyattractive for me to use the K computer,one of the most advanced computersin the world. This was my motivation todevelop "GENESIS". I was sure that I would
have a chance to experience new things I
had never done. I expected to make newachievements, and thought that the newresearch topic was a good challenge forme.

ATDYN and SPDYN, and analysis tools. In
ATDYN, where the atomic decomposition
method is introduced, interactions to be
calculated are distributed over processors for parallelization. On the other hand,
SPDYN uses an algorithm that divides theentire space into small subdomains andcells by the space decomposition method.
In SPDYN, each subdomain is assigned to aprocessor, and interactions are computedin each subdomain. In other words, ATDYN
divides interactions simply by the number

ATDYN and SPDYN─ When did you overcome thebarriers, and when did the development work with great progress?

Sugita I think it was since the development of SPDYN got off the ground. "GENESIS" consists of two MD simulators named

6 BioSupercomputing Newsletter Vol.13

SCLS Eyes
Replica 4

Cell
Domainn step MDof CPUs, while SPDYN divides data according to the space. Since, data communication is performed mainly between neighboring domains in SPDYN, communication
costs are greatly reduced. Therefore, MD
simulation could be performed faster forlarger systems with SPDYN. We obtained
efficient data partitioning by excluding unnecessary data. To develop SPDYN, I guessthat there had been a lot of problems, but
Dr. Jung did a really great job.

─ Another important function of"GENESIS" is the Replica-Exchange
Molecular Dynamics method(REMD), isn't it?

Rejected

AdoptedReplica 1

In the domain decomposition method in SPDYN, the whole system (box)of the simulation is divided into subdomains (solid line frames) and cells(dotted line frame). In parallel computation by the MPI protocol, each
MPI process is assigned to each domain, and information on particle
like forces and coordinates and particles moving across the domains arecommunicated (Arrow).

n step MD

AdoptedAdoptedReplica 2

Fig. 1: Domain decomposition method in SPDYN

n step MD

Rejected

Replica 3

Exchange information suchas coordinates and particle
forces between domains

n step MD

Temperatureexchange

Temperatureexchange

Temperatureexchange

Fig. 2: Replica exchange molecular dynamics (REMD) method

In the REMD method, copies (replicas) of the target system are prepared, and different
temperatures are assigned to each replica. MD simulations are performed in parallel,
and temperature exchange is attempted at certain intervals. If exchange is accepted,
temperature is exchanged, and if rejected, the computation is continued without thetemperature being exchanged.

Sugita In the REMD method, simulationsof different conditions are mixed by
preparing a number of copies of thetarget system. For example, simulations at
different temperatures are performed inparallel, and temperatures are exchanged
between replicas at a certain frequency.
Exchanging temperatures enable us tosearch various structures of proteins in thesimulations. Of course, the conventional
MD may be able to do a similar structuresampling, but it requires much longer
computational time. Presumably, it isdifficult even with the K computer. In thisrespect, the REMD method enables us

to obtain a lot of structures in the same
computational time. In the conventionalMD, proteins often stay in states close to
the initial structure at low temperature,
while REMD helps us to search protein
conformations in different states by
mixing high temperature simulations. In
addition, "GENESIS" is capable of changing
various parameters such as pressure,surface tension and biasing forces as wellas temperature. Dr. Mori worked on thedevelopment of the REMD method withgreat efforts.

To establish a higher-performance MD method
─ "GENESIS" was released as
open-source software from May 8,
2015.
Sugita Because GENESIS has been updated frequently, we have to choose thebest timing of release carefully. GENESIS
has the top benchmark performancein the world, and we published a paper
about it. At that time, we thought it was
the best timing for the first release. Our future goal is to improve "GENESIS" up to theglobal standards of MD programs, in otherwords, the representative MD simulation
software. In our laboratory, we expect that
individual researchers add new functions
to "GENESIS", and utilize them in theirown research. Eventually, we will update"GENESIS" by incorporating those into the
future release version.
M o r i I am now doing application
research on membrane proteins using"GENESIS", and also developing "GENESIS"on the side. To do my application research,
I have to introduce new algorithms into
"GENESIS" that are not available currently.
I think "GENESIS" should be developed
gradually by doing this.
Jung As for me, I’m developing an evenfaster and user-friendly "GENESIS" that canbe used not only for the K computer but
also for usual PC clusters. For example, thedevelopment of "GENESIS GPGPU version",where graphic processing units (GPU) areused for MD simulation, is going to befinished soon. It makes the MD simulationmuch faster. Furthermore, a project forthe post-K computer has already started.
"GENESIS" has been selected as one of thetarget applications of the post-K. A vendor
and a software developer are jointly doinga co-design that allows evolution not
only of the software but also of machine

After SPECIAL TALK
● See the URL on the right for detailed information on this reportarchitecture at the same time so as to realize
a faster "GENESIS".
Sugita In the future, we are planning
to incorporate useful functions that thepresent “GENESIS” cannot do, and also
add original features to “GENESIS”, inother words, greater advantage over other
MD programs. Furthermore, we aim to
speed-up “GENESIS” even for machines
other than the K computer. Improvement
in computation speed of “GENESIS” forvarious hardware platforms will increase
the number of “GENESIS” users. We believe"GENESIS" will be widely utilized for not
only basic research but also industrial
applications such as drug discovery.

After the interview, the interviewees
answered questions from and talked
freely with young researchers andstudents. Visit the URL below for more
information.

http://www.scls.riken.jp/eng/newsletter/Vol.13/sclseyes.html
BioSupercomputing Newsletter Vol.13 7

Close-up on SCLS Research

Theme 1 Simulations of biomolecules in cellular environments

Whole bacteria cytoplasm modeling and all-atom
molecular dynamics simulations
RIKEN Theoretical Molecular Science Laboratory

Isseki Yu

When you hear that “Water occupies

consist of 10-100 million atoms. This ultra

approximately 70% of the whole space inlarg e s c a l e m o d e l w as d eve l o p e d bya cell”, you may imagine an environment

researchers of RIKEN (Takaharu Mori andwith sufficient space but actually, it is not.

Ryuhei Harada) and research collaborator

The space where 30% of the whole volume

in U.S. (Prof. Michael Feig, Michigan Stateis occupied by molecules except those of

University) [1]. Since all genes of mycoplasma

water is extremely crowded environment,

have already been understood, the types

and a number of proteins or smalland structure for most of the proteins canmolecules are packed in it like a crowded

be estimated. Further, since omics data fortrain. The question of how the proteins andother macromolecules and metabolites

small molecules move and interact eachare available, we can also estimate types,

other in such a crowded environment is

structure, and concentrations of them in cell.

important for the fields of biology and drug

In this way, we have successfully reproduced

design. However, it is difficult to measurebiomolecules (except cell membranes andthe dynamics of molecules in cell withDNAs), and their concentration in cell at theexperimental ways, and therefore its details"atomic level", almost perfectly using various

have not been clarified.

experimental data. We are simulating the

We aim to elucidate the dynamics of"whole cytoplasm model" developed inbiomolecules in cell at the atomic level

this way with the MD simulation programby large-scale molecular dynamics (MD)"GENESIS" (developed by researchers ofsimulation using the K computer (simulation

the Advanced Institute for Computational

to reproduce the dynamics of molecules

Sciencein detail by calculating forces that act onis the program into which various new

atoms, and repeatedly solving equations oftechnologies are incorporated so as tomotion for them) Specifically, we simulate

enable super large-scale parallel MD

cytoplasm of bacteria called Mycoplasma

simulation. Its efficiency does not decline

genitalium.

even when hundreds of thousands of CPU's

T he cons truc te d c y toplasm mo dels[2]

) on the K computer. GENESIS

run simultaneously[3]

study was made possible by combining thecomputation power of the K computer withthe high efficiency of GENESIS.
Presently, the simulation itself has almost
been completed, and now we are analyzing
how the biomolecules move in cells withina time period of around 100 nanoseconds.
We have confirmed that the speed at which
proteins diffuse corresponds well withexperimental values. In addition, we haveobtained new insights for the structureof enzymes and dynamics of metabolites
in cells, that can never be seen in a dilute
solution environment in vitro. We intend
its application to the field of drug designin the future, and are planning to perform
longer simulations so as to investigate theinteraction between proteins, and bindingof metabolites and enzymes in cells.

. In other words, our

400 nanometers

Cytoplasm[1] Complete Atomistic Model of a Bacterial Cytoplasm
for Integrating Physics, Biochemistry, and Systems
Biology Journal of Molecular Graphics and Modelling.
Michael Feig, Ryuhei Harada, Takaharu Mori, Isseki Yu,
Koichi Takahashi and Yuji Sugita.
J. Mol. Graph. Model., 58, 1–9 (2015).
[2] GENESIS website
http://www.riken.jp/TMS2012/cbp/en/research/software/genesis/index.html[3] GENESIS: a hybrid ‐ parallel and multi ‐ scale
molecular dynamics simulator with enhanced
sampling algorithms for biomolecular and cellular
simulations.
Jaewoon Jung, Takaharu Mori, Chigusa Kobayashi,
Yasuhiro Matsunaga, Takao Yoda, Michael Feig, Yuji
Sugita.
WIREs Comput. Mol. Sci., (DOI: 10.1002/wcms.1220)

100 nanometers

Fig. ： Right: Schema of Mycoplasma genitalium. Left: Atomic model of mycoplasmal cytoplasm. Eachmacromolecule is indicated by different colors. One side is approximately 100 nanometers in length, andconsists of 100 million atoms including water molecules.
● See the URL on the right for detailed information on this reportand profile of the author.

8 BioSupercomputing Newsletter Vol.13

http://www.scls.riken.jp/eng/newsletter/Vol.13/zoomin01.html

Close-up on SCLS Research

Theme 3 Hierarchical integrated simulation for predictive medicine

Modeling human for understanding human
Digital Human Reserach Group,
Human Informatics Research Institute,
National Institute of Advanced Industrial Science and Technology

Akihiko Murai

We create a human model on a computer,and attempt to understand human beings
by estimating their state based on measured

problems that minimize the quadratic sumof muscle tensions based on this model.

We develop an application known asdata such as motion data. Since it costs a"Magic mirror". This system realizes real-very detailed human model that consists

activity, and is capable of performing

great deal to perform computation for aof an enormous number of elements, high-level parallel computation by, for example, asuper computer is needed.

One type of information that represents

the state of human beings is somatosensory

information such as muscle activity. We
successfully estimate the muscle activity
by utilizing measurement with opticalmotion capture, a floor reaction force plate,an electromyograph and a human model.

Regarding a human being as a rigid bodylink system driven by wires enables us toapply a kinematics/dynamics computation,
which is developed in the field of robotics.

We create a human musculoskeletal
model by processing the data obtainedby CT-scanning an actual skeleton sample(published as AIST adult male skeleton
shape data), and positioning endpoints

and passing points of muscles, tendonsand ligaments based on the anatomical

time estimation and visualization of muscle
high-speed estimation at 60 frames per
second. A subject moves his/her bodyin front of a display, and an image of thesubject captured by a video camera anda musculoskeletal model that indicatesmuscle activity are superimposed on thedisplay. Since this makes the subject feelthat he/she is seeing his/her own muscles

through his/her clothes, this application iscalled "Magic mirror". This "Magic mirror"
has potential for various applications suchas quantitative diagnoses of movement

disorder, confirmation of rehabilitation

effects, support of sports training, and soon. Conventionally, advice in these fields

are given based on motion observationand empirical rules. Visualization of muscle

activity allows quantitative understandingof the state of the subject, and further, thereal-time visualization allows biofeedback.

We develop a neuromuscular skeleton

knowledge. Joint angle, floor reaction force,system with an anatomical neural circuit

the whole body, are estimated by solving

to clarify the human motion control

joint torque, and activity of each muscle inkinematics, dynamics and optimization

model built on a musculoskeletal model

is a primitive part of human motion, ismodeled, and muscle activity after a timedelay by nerve signal transfer is output
when proprioceptive sensation is input.
Information such as muscle length andtension, which are the input and outputof this system, is computed by the above
kinematics/dynamics computation, andthe network between input and output
is identified from experimental data. Thissystem realizes simulation not only of asomatic reflex such as the knee jerk seen inhumans, but also of reactions to tripping

seen in human. It is also expected that

understanding the relationship between
the sensation and the kinetics allows
enhancement of kinetic performance,
which leads to development of sportswear

and shoes that realize such enhanced
performance.

system. The somatosensory reflex, which
Fig.2：Neuromuscular skeleton
system (left). Simulation of gait andtripping(right).

Fig.1：Real-time muscle activity visualization
system "Magic mirror". The color changes fromgreen to red when muscle is activated.
● See the URL on the right for detailed information on this reportand profile of the author.

http://www.scls.riken.jp/eng/newsletter/Vol.13/zoomin02.html

BioSupercomputing Newsletter Vol.13 9

Close-up on SCLS Research

Theme 3 Hierarchical integrated simulation for predictive medicine

Neural control of human quiet standing
and biped walking

Movement fluctuation andits degeneration causedby neurological disease

Department of Mechanical Science and Bioengineering,
Graduate School of Engineering Science, Osaka University

Taishin Nomura
Chunjiang Fu

I n t h e c u rr e n t e ra when hum ano id

University Hospital and Toneyama National

development, many readers would not be

patients become unstable, and they tend to

robots have reached the pinnacle of theirmuch impressed by a mathematical modelthat simulates physical motion in humanbeings and is able to stand straight or walkon two feet. However, for us, who study

brain and neural control (motor control)of human biological motion, there seems

to be considerable difference between theappearance and kinetic properties of the
motion of humanoids and humans.

When we maintain upright posture andHospital. The postures of some of thesefall down easily. Comparison of the postural

sway (foot pressure center CoP variation)of such patients and that of healthy young
persons has revealed that the postural swayof healthy young persons is greater than theother, contrary to intuition (see figure). In

other words, the posture of a healthy young
person is flexible, and that of the above
patients is rigid.

We have built a mathematical model

stand still, the posture of the body movesof postural control (computer simulation

during quiet standing. The upright postureresults of the experimentally observed

infinitesimally. This is called postural sway
is something like an inverted pendulum thatis mechanically unstable, and the central

nervous system of human beings stabilizes

it by generating muscle forces so that thependulum does not fall down. Given thisperspective, one may think that “the larger
the postural sway amplitude, the lower
the stability is”. However, we have provedthat this intuition may not be necessarily
correct. We are studying the standing

posture and walking movement of patients
who suffer from Parkinson's disease, which

is a neurological disease accompanied

by movement disorder, in collaboration

with the Department of Neurology, Osakamodel), and attempted to explain the

behaviors by the logic of mechanicaldynamics and systems science. As a result,it was found that the human brain does
not always continuously perform control
to pull back displacement from the upright

posture and there are time zones in whichefficiency. The latest study revealed thatintermittently without controlling it, which

can be explained in the same way as that ofa human being yields its position to gravity

brain/neural control of biped ambulation

allowed us to elegantly explain the relatively

standing posture.

persons. In fact, assuming continuousfunctions is higher in human beings than in

postural sway seen in the above patients.

leads to kinetic fluctuation. We believe that

small variation in control parameters of theby clarifying mechanisms of generation

controller) may makea detailed and large-scale mathematicalunstable, whereas

and skeletal system of humans built in aintermittent control,

similar to that of a human being (motion

be stabilized in a robust

motion fluctuation observed in patientsthe control parameters

control function that are thought to affectintermittent control isusing the K computer continues.

large postural sway seen in healthy young

It is often said that "flexibility of vital

control allows us to explain the small

artificial devices such as robots". Flexibility

Further, in continuous control, even aa basis for health science will be obtainedb r a i n (a s a m o t i o n

and loss of this movement fluctuation. Can

the upright posturemodel of the central nervous system, muscle

we clarified that insupercomputer reproduce flexible motion

the upright posture canfluctuation)? Can the degeneration ofmanner even whenbe reproduced by the variations in thevary greatly, and that

Parkinson's disease patients? Our challenge

Fluctuation of center of pressure during quiet standing
Healthy young person VS Parkinson’s disease patient(postural reflex disorder)
For quantitative diagnosis based on measurement and motor symptoms
Parkinson's disease patient

Healthy young personmuch better in energy
Fig. ：Fluctuation of center of pressure during quiet standing.
Upper figure: Postural sway in a Parkinson's disease patientwith postural reflex disorder. Lower figure: Postural sway of ahealthy young person.
●See the URL on the right for detailed information on this reportand profile of the author.

10 BioSupercomputing Newsletter Vol.13

http://www.scls.riken.jp/eng/newsletter/Vol.13/zoomin03.html

Lecture at Faculty of Human Development, KOBE University“On interdisciplinary studies - the integrationof biology, physics, chemistry and mathematics”
Deputy PD, RIKEN HPCI Program for Computational Life Sciences

I gave a lecture titled “On interdisciplinary studies” to new undergraduate students in the Faculty of
Human Development, Kobe Universityo n 19 t h a n d 26t h i n J u n e , 2 015 ,as par t of “ Invitation to Human
D e v e l o p m e n t ” w h o s e ke y w o rd i s“interdisciplinary studies”. I have been
g ivi n g t h e o p p o r t u n it y to d el ive rsuch lectures over the past four years.
Through the main theme --- “Rapid
improvement of technologies such as

supercomputers and DNA sequencer
has promoted the integration of biology,
mathematics, physics and chemistry in
the 21st century”--- I had talked about
interdisciplinary studies until last year.
In the last lecture a student asked
me,“My major is liberal arts but it issaid that majoring in science is helpful
in the business society. What is youropinion?”Responding to this question,
I decided to emphasize the importanceof harmonious development of liberalarts and science, and the need ofinterdisciplinary studies in order tosolve real-life problems in this year,
the outline of the lecture being
almost the same.
The concept of“Designer baby”
by genome editing technology has
become a big worldwide issue now.
Most science researchers believe
their studies are done for the good,otherwise, they could not work
creatively and progressively. The
The building of Faculty of Human Development, KOBE idea itself is natural and correct.

Yukihiro Eguchi

But, whether further studies should now
be done and whether the results can be
accepted by society is another matter.
Sufficient consideration should be given
from the viewpoints of both liberal artsand science.
I suggest to students that“interdisciplinary studies”be thought of on a
two-dimensional plane, X-axis shows
academic fields including liberal artsand science, and Y-axis shows depthof exploration of a special field, giving
them examples of T-shaped persons andΠ-shaped persons. Computational life
science is a field engaged in by Π-shaped
persons with in-depth knowledge ofcomputational science and life science,and it requires also knowledge of aliberal arts field such as Bioethics. In
the lecture, I had unexpected feedback
from a student, saying "A cuneate person
would be good". I really hope thatyoung students will build new creativeinterdisciplinary research fields in the
future.

University

Third Advisory Committee Meeting

Planning and Coordination GroupRIKEN HPCI Program for Computational Life Sciences

T h e t h i rd a d v i s o r y c o m m i t t e emeeting was held at the RIKEN Tokyo
office on July 3rd, 2015.
This is a very important committeewith participation of experts fromscientific and industrial fields inside andoutside Japan giving advice on researchcontent and activities in order to assist
the Strategic Programs for Innovative
Research Field 1,“Super ComputationalLife Science”. In view of advice from thefirst committee (in January, 2012) andthe second (in September, 2013), allGroup photo

the research achievements until now
were presented, and then a wayof taking these final achievements
into the next project was mainly
discussed because the current
project has mostly completed its
term. First, general responses to thecommittee's recommendations weremade by the deputy PD of Researchand Development, and then there were
presentations delivered (final goal,
progress, achievement and further
future development) by each leader offour research groups. A presentation(research and development assistance,
widespread research influence, networkof personal contacts and manpower
training) was finally made by the deputy
PD in charge of Establishment of the
Research System for Computational
Science. After each presentation, there
were many questions and answers,
a n d p ro p o s a l s f ro m m e m b e rs of

Photo of the meetingthe committee, which brought thecommittee much benefit. An importanttask that we must challenge from now
until next March is accelerating further
research for the final achievement,
and successfully taking it into the next
project. At the committee meeting,precious advice was given for resolutionof the challenges. We would like totake this opportunity to thank all
members of the committee, Dr. Mitiko
Go, Prof. Peter Kohl and Dr. Masaharu
Kanaoka.

BioSupercomputing Newsletter Vol.13 11

NEXT STAGE

As a "Flagship 2020" project, the Ministry of Education, Culture, Sports, Science and Technology is promoting thedevelopment of the post-K computer, which is a machine that will succeed the K computer. As a national technologicalinfrastructure platform, nine priority issues have been set as social and scientific themes to be addressed.
In the category "Achievement of a society that provides health and longevity", organizations were selected to implement
two priority issues: (1) "Innovative drug discovery infrastructure through functional control of biomolecular systems",and (2) "Integrated computational life science to support personalized and preventive medicine", Both projects launchedin Feb. 2015. What epoch-making results will priority issues (1) and (2) bring to life sciences? We interviewed Dr. Yasushi
Okuno and Dr. Satoru Miyano, who are supervising these issues.

Innovative drug discovery
infrastructure through functional
control of biomolecularsystems

Priority issue 1 Supervisor

Senior Visiting Scientist

Yasushi Okuno

RIKEN Quantitative Biology Center

The Post-K computer will realize ultra-high speed molecular simulations toachieve not only functional inhibition but also functional control of many
biomolecules including factors that cause side-effects, in order to discover safeand highly effective drugs.
Aiming at full-scale use by 2020, devel-

development while holding down

Moreover,generation supercomputer, has started.

important issue for drug development

establish

opment of the post-K computer, a next-

2020 is the year of the Tokyo Olympics, andwe are going for the gold medal of scienceand technology with the post-K as ournumber one weapon.

The post-K development focuses onsocial as well as scientific issues, and weare developing a computational technique(application) that would bring innovation tonine priorities such as drug development,

medicine, weather, manufacturing, spaceand so on. I am in charge of supervising"Innovative drug discovery infrastructuredevelopment cost" has become a mostand the medical field. Our final goal is tocontribute to overcoming obstacles that the

drug companies encounter, by using theoverwhelming power of the post-K. In the
post-K, we achieve a computational speed(molecular dynamics calculation) to simulatebiomolecular behaviors that is dozens oftimes faster than that of the K computer.
It allows us to aim at reproducing in vivo

molecule behaviors over longer time periods(millisecond level), and promoting drug
development simulation for more molecules

through functional control of biomolecularin vivo . Based on such development work,

priorities. At this opportunity, let me

to which dynamic control of disease-causing

systems", which is one of these nine

introduce the study goal and an outline ofour drug development with the post-K.

Over the past dozen years or so, thenumber of approvals of new medicinesremains at the same level (around 20 items/ yr) in the drug industry while research anddevelopment expenses continue rising,which has become a serious bottleneck.
Therefore, "to accelerate new medicine

12 BioSupercomputing Newsletter Vol.13

we are exploring a new drug design method

proteins and multiple drug developmentrelated proteins are added. Specifically, weare developing new structural life sciences
and a next-generation drug development

computational technique (SubthemeB) through the development of a newmolecular simulation technique that allows

operation of the post-K at its maximum
computational power (Subtheme A).

we aim toa highly precise and ultra-highspeed innovative drug development
computational base while developing an

integrated system for which these corecomputation techniques are connectedalong the drug development computation
flow (Subtheme C). Use of the drug
development computational base with thepost-K as a key in actual pharmaceuticalscenarios leads to promotion of efficiency

in drug development processes. For
example, the experimental processes ofpast drug development are replaced bycomputer simulations, and this dramaticallyreduces the development cost of medical

supplies and thus medical cost. We arealso exploring an innovative approach for

new drug development, such as drugs

for dynamic functional control of target

proteins, epigenetic drug development thattargets the macromolecular assemblage ofprotein-nucleic acids, and systemic drugs

based on the simulation of a super largescale biological system. It allows creation

Challenging the priority issues on post-K computer

Organization for direct application of post-K to drug discovery
Biomolecular
structure dynamics（MD）

Human andpost-K co-design

Understandingof biologicalmolecule function

Identiﬁcation of
key regulating site

Construction of innovative drug
design computational base with
post-K MD as base

Exploration of new structural life sciences bytemporal and spatial functional analysis oftarget biological molecule system

Ultra-high speed molecularsimulation with post-K computer

Design of candidate
compoundLong timescale dynamics method

Dynamic molecular regulation

Generalized-ensemble algorithms

Interaction between proteins

Highly precise drug design

Interaction between
nucleic acid and protein

Drug design-related big data

Sugita, RIKEN

Advancement of MDwith post-K computer

Hayashi, Kyoto University

Okuno, Kyoto University

Tsuda, The University of Tokyo

Kono, JAEA

Coarse graining modeling

Target molecule network

Intracellular environmental target

Takada, Kyoto University(Shinoda, Nagoya University)

Kono, JAEA (Sugita, RIKEN)(Kitao, The University of Tokyo)

Viral target

Multi-scale modeling

Subtheme B (Ikeguchi, Yokohama City University):
Development of next-generation
drug design computational techniques

Subtheme C (Okuno, Kyoto University):
Development of drug design
big data integration system

Free energy calculation

Shinoda, Nagoya University(Ikeguchi, Yokohama City University)

Subtheme A (Sugita, RIKEN):
Advancement of MD and associatedalgorithms by post-K computer

Hirokawa, AIST

Fujitani, The University of Tokyo

QM/MM Free Energy method

Sugita, RIKEN (Ikeguchi, Yokohama City University)

Function control domain DB

Ikeguchi, Yokohama City University

Kitao, The University of Tokyo

Terada, The University of Tokyo

Reseach Implementation System for priority issue 1of new medicines that so far were difficult

gives a big dream to young people who

advancing research and developmentof pharmaceuticals. As a result, they are

is often said that supercomputers have thedevelopment computational base. We hope

to develop, and speeds-up development

are the scientists of tomorrow. Indeed, it

expected to contribute to the needs ofperformance of future general purpose

patients for new medicines.

of 2035.

nation put high priority, not only brings

opinions. Your continued support is greatly

Therefore, we have great

appreciated for successful development of

expectations of the post-K and a hugeindustrial benefits and lets us reach the top

the post K, which will support continuous

responsibility. We, who are involved in theof world supercomputer rankings, but also

development of industry and science infield of drug development, are vigorously

Japan.

Development
Developmentof
ofdrugdrugdesign
design big
big data
data integration
integration systemsystemwithwithpost-K
post-Kcomputer
computeras
as aa base
base

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post-Kcomputer
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Whatpost-K
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processdevelopment
process
SubstituteSubstituteforforwetexperimentwetexperiment

Revamp
Revampmedicine
medicineproduction
productionmethod
methodCreation
Creationofofnew
newdrug
drug
designdesigntarget
target100
million100
millionIntracellular
Intracellularenvironment
environment

・・
Highlypreciseprediction
Highlyprecisepredictionofoflarge-scalelarge-scaleintermolecularintermolecularinteraction
interaction
Macromolecular
Macromolecular(preciseestimation
ofof
complexpose,(preciseestimation
complexpose,
systemMDsystemMD
prediction
targetselectivity)
prediction
of oftargetselectivity)
million1010
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aggregationTime
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forforhighlyprecisecomputation
bindingfree
freeenergy
energycomputation
ofofbindingms
ms

us with your prospective and constructive

us the future computational environment

sciences. The supercomputer, on which theμsμs

2015 viewpoints, but continuously provide

which is to be completed in 2020, brings

greatly changed my view of computational

100ns
100ns

a machine available in 2035 evaluated byfrom now. This means that the post-K,

I received a very strong impression that

Post-K
Post-Kcomputer
computeryou will not simply look at the post-k ascomputers that will be available 15 years

Working with the present the K computer,

Simulation
size
Simulation
size(atoms)(atoms)so as to construct of a world-class drug

Time
Time

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

ChemicalChemicalcompoundcompoundgeneration
generationmethod
methodDe
Denovo,novo,FBDD
FBDDChemicalChemicalcompoundcompounddesigndesignChemicalChemicalcompoundcompoundlibrary
library(commercially(commerciallyavailable,
available,
public,public,virtual)
virtual)ProteinProteinDB
DB

Big
Bigdatadataanalysis
analysis
Activity
Activityprediction
prediction
Drug
Drugdevelopment
developmentlarge
largedatabasedatabase(assayinformation,
information,omics,
omics,(assaypathwayinformation,
information,
pathwayclinicaldata)data)clinical

Bigdatadataanalysis
analysisBig
ADMETprediction
prediction
ADMET

Virtualscreening
screening
VirtualDockingcomputation
computation
Docking

Estimation
Estimationofofkey
key regulating
regulating sites
sites

Protein target
target site
site
ProteinDB
DB

Side-eﬀect
Side-eﬀect
prediction
prediction
Leadoptimization
optimization
Lead

Complexmulti-conformation
multi-conformationanalysis
analysisComplex
Systemsconstruction
construction
Systems
Combinationoptimization
optimization
Combination
algorithm
algorithm

Homology
Homology modelingmodeling

APO
APOmulti-conformation
multi-conformation generation
generation
Estimation
Estimationof
ofnetwork
network between
between proteinsproteins

Lead
LeadsearchsearchChemicalstructure
structure
Chemicalevaluation
evaluation
Denovo,novo,FBDD
FBDD
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Drug
Drug design
design target,
target,side-eﬀect-relatedside-eﬀect-related
proteinprotein structure
structure DB
DB

Bindingfree
freeenergy
energycomputation
computation
Binding

Prediction ofof selectivity
selectivity
Prediction
Evaluation ofof bonding
bonding
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with multiple
multiple proteinsproteins
with
Evasionofof
Evasionsideeﬀects
eﬀectsside

Finalcandidate
candidatecompoundcompoundFinal

http://www.scls.riken.jp/eng/newsletter/Vol.13/nextstage01.html

BioSupercomputing Newsletter Vol.13 13

NEXT STAGE

Integrated computational life
science to support personalized
and preventive medicine
Priority issue 2

Supervisor

Professor Satoru Miyano
The Institute of Medical Science, The University of Tokyo

Creation of the new paradigm called integrated computational
life science supports personalized and preventive health care,and the super computer supports a healthy, long-life society.
Disease appears as a phenomenon of

On the other hand, the genome

to blood ejection. It should be emphasized

produce epigenomic data and RNA sequence

continuously employing almost all nodes

disorders in related organs. As a background

sequencing technologies, which can also

which is often called “the blueprint of life”,

data, have already produced genomeof disease, we need to consider our genome,

and various data of molecules such as
epigenome, RNA, protein, etc. These arecollectively-referred to as “omics” and drive

cells for creating biological functions. Further,each cell in our individual has a specific stateof cell called “cellular context” that changes

with the environmental factors and aging.

Cellular contexts vary from cells to cells,

and therefore, the functions of organs also
depend on their cellular contexts. Moreover,for the genome, which was previously
considered not to change through our life,

it has been recently reported that genomic

mutations accumulate along with aging
steadily in our hematopoietic stem cells.

Cancer develops in the long organismspatiotemporal process while being affectedby various environmental factors. It is no

exaggeration to say that this process begins
since a person is born. Not only the variations

sequence data in petabyte order. Moreover,high precision clinical data such as imaging
or physiological data have also made a large-

scale data mountain. In the Grand Challenge

Program and the following Strategic
Programs for Innovative Research Field 1,

the world’s top level simulation technologies
had been developed that include the heart

simulator UT-Heart that successfully used thefull power of the K computer. We had also
development of technologies for large-scale

analysis of life data that allowed us to analyze
all genes and non-coding RNAs of size morethan dozens of terabytes. These technologies

led us to important discoveries in cancer
biology and development of various
prediction methods (e.g. for drug resistance,cancer survival) that could not be achieved
without the K computer.

Of course, it was a very epoch-making

in population but also everybody has ascientific contribution that thebiological reality of the aging society that

achieved a full simulation ofvariety in its life. It may be said that this is the
genomic science has unraveled.

Fig. 1：Evolution of clone during 12 years
when hypoplastic anemia worsened tomyelo dysplasia syndrome

14 BioSupercomputing Newsletter Vol.13

multi-scale simulator UT-Heart

1.5 heartbeats from sarcomere

Fig. 2：Data assimilation
biological simulationthat this simulation took 17 hours byof the K computer just for 1.5 heartbeats. In

cancer research, international collaborations

are building a catalog of cancer mutations
with frequency more than 5% for major 50

cancer types/subtypes. The world-wide total

computing power spent for this catalogbuilding was similar to the power of the K
computer. However, in order to understand“personal cancer”, we need to carry out
the comprehensive analysis of mutations

with frequency less than 1% by wholegenome sequencing. This analysis requires,
theoretically, 5,000 days by the K computer,an unrealistic analysis. As described above,
while human diversity has been identified
from various viewpoints, a strong need is todevelop technologies to fill the gap between

the molecular mechanisms of individual
pathologies and the large-scale imaging
and physiological data, and further, healthand genome information. The above heartChallenging the priority issues on post-K computer

The Institute of Medical Science,
The University of Tokyo (PI Satoru Miyano)

Large-Scale Data Sharing ofCancer Genomes andClinical Information

Guidelines for
Human Genomes
by Ministries MEXT,MHLW and METI

Research Administrator

Nagoya U
Med School

Kyoto Pref
Med U

Biomedical
Researchers

Collecting cancer
samples
Kyoto UMed School
Nagoya U
Hospital

Tsukuba U
Med School

Providing research platforms
Providing clinical information
Collaboration with computational
science and simulation researchers

Publicity Oﬃcial

Reﬂection to
public policy

U Tokyo
Kyushu U
Med School Med School

Satoru Miyano (U Tokyo)

Shigeo Wada (Osaka U)

Toshiaki Hisada (UT-Heart Inc)

SubthemeA：Understanding
individuality and spatialtemporal heterogeneity ofcancer by large-scale sequencing

S u b t h e m e Ｂ： S u p p o r t i n g
personalized medicine by data
assimilation based biologicalsimulation

SubthemeＣ：Bridging basic
medicine and clinical medicine
by fusing heart simulation andmolecular simulation

Data Analysis

Academic Institutions(ELSI Sociologists)

National Cancer
CenterPost-K computer Development(AICS)

Data Providers
Hospitals
Collaboration
Institutions

Simulation

Co-Design

Experiments/
Validation

Kyoto Pref U
Hosptial

Biomedical
Institutions
Clinicians
Physicians
Biomedical
Scientists

Data Analysis

Academic Institutions(Oﬃce of Intellectual Properties)

Collaborators
RIKEN
U Tokyo Grad Sch Sci
U Arizona
TMDU
Development of
medical devices byintegration of
medicalmeasurement andsimulation

Predictive Preventive Personalized Participatory Medicine

Health/Medical
Care Applications

Clinical Sequence basedon Whole Genomes

Institute of Medical Science,
U Tokyo Kyoto U HospitalIndustries(IT/Medical
Devices)

Cooperative/Specilized
Hospitals Assigned to Cancer Therapy

Society that provides healthand longevity
by post-K computer

PMDA
Translational Research Center,
U TokyoIndustries(IT/Medical Devices)
Engineers
R&D

Pharmaceutical / Medical Device
Companies

Reseach Implementation System for Priority issue 2

simulation and cancer genome research arelish the integrated computational life

biological simulation" (Supervisor: Shigeo

biomedical issues that Japan and humans

personalized/preventive medicine. This

Science, Osaka University) (Fig. 2), wesome of the extremely important scientific/
must challenge. However, even for thesecases alone, we need a new computing

environment exceeding the K computer,and simultaneously we will face with a big

mission that we develop technologies tofully exploit it for overcoming the difficulties.
It has been gradually recognized that thecomplexity of integrative understanding of
diseases is far beyond human abilities. This is

one of the reasons why development of the
post-K computer is inevitable.

In priority issue 2, our goal is to estab-science that constitutes the basis forrequires a methodology for comprehensive
understanding of pathological states andexploration of their effective treatments

through a view from genome to the whole
body, both environment- and organismspatiotemporally. We consider that thismethodology can be realized by "information
technology", "application of physics
principles", and "utilization of big data"enhanced with the post-K scale computation.

To achieve the goal, we are tackling threesubthemes. In Subtheme A, "Understanding
individuality and spatial-

temporal heterogeneity

individual data for a high-level, organism
hierarchy integrative simulation. Parallel tothe approach based on the large-scale data,

in Subtheme C, "Bridging basic medicine andclinical medicine by fusing heart simulationand molecular simulation" (Supervisor:

Toshiaki Hisada (UT-Heart Inc) (Fig. 3), weare integrating studies on the molecular

cellular level and those on individual organ
levels to develop a simulation model for

quantitative capture by associating microwith macromechanics.

In the present era when we will witness theadvent of the super-aged society, we believe

Satoru Miyano) (Fig.1), weconstitute an essential basis to support thewill analyze large-scale dataof an unprecedented scalein the field of life sciences.

In Subtheme B, "Supporting
personalized medicine by●See the URL on the right for detailed information on this report.

are developing a technique to assimilate

of cancer by large-scalesequencing" (Supervisor:

Fig. 3：Fusion of heart simulation and molecular simulation

Wada (Graduate School of Engineering

data assimilation basedthat the solutions by the priority issue 2 will
healthy and longevity society. Further, forvarious diseases that occur along with aging,
we believe that contributions of the newparadigm, "Integrated Computational Life
Science", to the health of citizens should beof great social significance.

http://www.scls.riken.jp/eng/newsletter/Vol.13/nextstage02.html

BioSupercomputing Newsletter Vol.13 15

SP Symposium RP Reporting session EX Exhibition SM Seminar WS Workshop

RP

WS Science and Society pioneered by K computer

Supercomputational Life Science 2015

SM

⃝Date : October 20 (Tue) – 21 (Wed) in 2015

⃝Location : Takeda Hall, The University of Tokyo

The 2nd day 9:30 a.m. - 6:25 p.m. The reporting session
by Strategic Programs for Innovative Research Field 1“Supercomputational Life Science”

SP

Read this QR codefor more information
about programs,
application, etc.

The 53rd Annual Meeting of the BiophysicalSociety of Japan⃝Date：September 13 (Sun) – 15 (Tue)⃝Location：Kanazawa University Kakuma Campus (Kanazawa-shi, Ishikawa)
Symposium September 13 (Sun) a.m.
Biosupercomputing opened by next-generation supercomputer post-K
Organizer : Mitsunori Ikeguchi (Yokohama City University)

EX

Science (Kobe-shi, Hyogo)

RP

The Second Project Report Meeting of the
HPCI System Including K computer in thefiscal year 2015

⃝Date：October 26 (Mon)⃝Location：National Museum of Emerging Science andInnovation (Koto-ku, Tokyo)

SM

Integration between bioinformatics and physicalchemistry in life science
Wide view point on bioinformatics⃝Tutorial Session : October 30 (Fri) 3:45 p.m. - 5:15 p.m.

Course on Parallel sequence similarity search program “GHOST-MP”

EX⃝Sponsored Session : October 28 (Wed) 4:00 p.m. - 5:30 p.m.
Chairman : Yukihiro Eguchi (RIKEN HPCI Program for ComputationalLife Sciences)

Informatics in Biology,
Medicine and Pharamacology 2015
The 2015 Annual Conference of JapaneseSociety for Bioinformatics⃝Date：October 29 (Thu) – 31 (Sat)⃝Location：Uji Campus Kyoto University (Kyoto-shi, Kyoto)⃝Sponsored Session : October 30 (Fri) 1:30 p.m. - 3:30 p.m.

Science Agora 2015

⃝Date：November 14 (Sat) – 15 (Sun)‒ the period holding the exhibition⃝Location：National Museum of Emerging Science andInnovation (Koto-ku, Tokyo)

WS

BMB 2015 Biochemistry and Molecular Biology⃝Date：December 1 (Tue) – 4 (Fri)⃝Location：Kobe Portopia Hotel (kobe-shi, Hyogo)⃝Workshop: December 4 (Fri) 2:00 p.m. - 4:30 p.m.

New Paradigm Creation in Personalized andPreventive Medicine- the Gift from Big medical data and Supercomputer -Organizers : Satoru Miyano (Human Genome Center, The Institute ofMedical Science, The University of Tokyo)

Seiya Imoto (Health Intelligence Center, The Institute of

CBI Annual Meeting 2015

⃝Date：October 27 (Tue) – 29 (Thu)⃝Location：Tower Hall Funabori (Edogawa-ku, Tokyo)

SM

For more details, please visit our website
http:www.scls.riken.jp/e-scls/2015-2016.html

RIKEN Open House Day at RIKEN AICS (Kobe)⃝Date：October 24 (Sat)⃝Location：RIKEN advanced institute for Computational

Foundations of Computational Life
Sciences Ⅱ⃝Date : October 7 (Wed) in 2015 – February 3 (Wed) in 2016
Every Wednesday 5:00 p.m. - 6:30 p.m.
⃝Location : 1F the school building of Faculty of Engineering,
Kobe University C3-101 (Creative Design Studio on Technology ２)(Hongo, Bunkyo-ku, Tokyo)⃝Participation fee : free (Reception fee will be charged)
The 1st day 10:00 a.m. - 5:50 p.m. International Workshop
on Current Topics (6:00 p.m. –Reception)

Remote lecture with Kobe University Education Centeron Computational Science and Engineering

Medical Science, The University of Tokyo)

SP

The 9th K Computer Symposium (tentative title)⃝Date：January 29 (Fri) in 2016
⃝Location：Yomiuri Otemachi Hall (Chiyoda-ku, Tokyo)

SP

The 39th Annual Meeting of Japanese Societyof Biorheology⃝Date：June 18 (Sat) – 19 (Sun) in 2016
⃝Location：The Tokai University Club (Chiyoda-ku, Tokyo)⃝Theme : Biorheology based on medicine-engineeringcollaboration on thrombotic events, blood flow andarteriosclerosis⃝Annual President: Shinya Goto (Cardiovascular Medicine,

Department of Medicine (Cardiology), Tokai University School of Medicine)

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.13 2015.9
RIKEN HPCI Program for Computational Life Sciences
7-1-26 Minatojima-minamimachi, Chuo-ku, Kobe Hyogo 650-0047, Japan
Tel : +81-78-940-5835 Fax : +81-78-304-8785

Issued: August 2015

RIKEN 2015-057