Next-Generation Integrated Simulation of Living Matter

BioSupercomputing
Newsletter 3
Vol.

2010.12

Participants in the summer school 2010 for
the Integrated Simulation of Living Matter(See pages 10 and 11 of the text)

CONTENTS●SPECIAL INTERVIEW ◦The role of supercomputers is important for integrating various leading-edge research bases for proactive use.
Manager Clinical Development Planning and Management
Mochida Pharmaceutical Co., Ltd. Visiting Professor Tohoku University Kazumi Nishijima

2-3◦Sonic simulation research in the body which is essential for promotion of ultrasound therapy and development
4-5of therapeutic apparatus
Extraordinary researcher, Department of Mechanical Engineering, School of Engineering, University of Tokyo Akira Sasaki●Report on Research ◦Achievement of a Multiscale Molecule Simulation of QM/MD/CGM (Molecular Scale WG)
Institute for Protein Research, Osaka University

Yasushige Yonezawa ／ Shusuke Yamanaka ／ Hiromitsu Shimoyama ／ Hideki Yamazaki ／ Haruki Nakamura

6

RIKEN, Computational Science Research Program Ikuo Fukuda◦Towards development and experimental demonstration of liver model basedon large-scale metabolic simulation at individual cellular level (Cell Scale WG)
School of Medicine, Keio University Ayako Yachie-Kinoshita◦Exhaustive Protein-Protein Interaction Network Prediction by Using MEGADOCK (Data Analysis Fusion WG)

7

8
Graduate School of Information Science and Engineering, Tokyo Institute of Technology
Yutaka Akiyama ／ Yuri Matsuzaki ／ Nobuyuki Uchikoga ／ Masahito Ohue
◦Whole Brain Simulation of the Insect Olfactory System
9Research Center for Advanced Science and Technology, The University of Tokyo Tomoki Kazawa, Stephan Shuichi Haupt●Report◦The summer school 2010 for the Integrated Simulation of Living Matter was held.
RIKEN, Computational Science Research Program Yasuhiro Ishimine (Organ and Body Scale WG)
The Institute of Medical Science, The University of Tokyo Teppei Shimamura (Data Analysis WG)
10
RIKEN, Computational Science Research Program Yasuhiro Sunaga (Cell Scale WG)
Kyoto University Graduate School of Informatics Naoki Honda (Brain and Neural WG)
RIKEN, Computational Science Research Program Gen Masumoto (High-Performance Computing Team)RIKEN, Computational Science Research Program Kosuke Matsunaga (Molecular Scale WG)◦After participation in the summer school 2010 for the Integrated Simulation of Living Matter,
11
First year of doctor s course, The University of Tokyo Graduate School of Science Ken Saito
12●ISLiM Participating Institutions / Event Infomation / Topics

S

PECIAL INTERVIEW

Future of Life Science Pioneered by Biosupercomputing

The role of supercomputers isimportant for integrating various
leading-edge research bases forproactive use.

Manager
Clinical Development Planning and Management
Mochida Pharmaceutical Co., Ltd.
Visiting Professor Tohoku University

Kazumi Nishijima■The success rate for development of new
drugs is only one part per 25 thousand.
━ Fr o m t h e s t a n d p o i n t o f p r o m o t i n g r e s e a r c h a n ddevelopment in the pharmaceutical industry, Mr. Nishijima has
been involved in various leading-edge research bases.
● Nishijima（dispense with the Mr.） Firstly, I was involved in Spring-8.
In order to make shared use of exclusive beam line (BL) by the Japan
Pharmaceutical Manufacturers Association (JPMA), a consortium for the
analysis of protein structure by the JPMA was launched by 22 companies (19companies due to merger, etc., at present). All the Japanese pharmaceuticalcompanies are among the medium-sized businesses in the world. It is quitedifficult for one such company to construct an exclusive BL in a world's
top level public institution. Therefore, the industry attempted to launch
the consortium for use by all the companies in this industry. Thereafter,
moreover, many drug discovery companies also came to use the NMR(nuclear magnetic resonance) facility of RIKEN (Yokohama Laboratory),
J-PARC (Japan Proton Accelerator Research Complex) in Tokai Village andthe radiation light facility PF of the High Energy Accelerator Research
Organization (Tsukuba City), and 8 companies joining the consortium havealready sent samples to the experimental module “Kibo” of the International
Space Station. Finally, the ten quadrillion speed computer “Kei,”and the XFEL
(X-ray free energy laser) in Harima Science Park City (Hyogo Prefecture) were
promoted in the fourth Basic Program for Science and Technology, and wewill also promote an approach to use these facilities for drug discovery in the
all-Japan organization.

━ Proactive utilization of such leading-edge research bases
will have an important significance for the pharmaceuticalindustry, won’t it?
● Nishijima

Absolutely yes. According to the latest data of the JPMA,

there were about 610 thousand types of synthetic (extracted) compounds
produced for drug discovery in Japan in 5 years from 2004 to 2008. Amongthem, there were only 24 compounds approved as new drugs. They areso few in 5 years. The probability is 1 : 25,482. It is just like a miracle. The
expenditure of research and development for a new drug is about 70 billion
yen per new drug. I think there are less than 10 pharmaceutical companies
in Japan that can do the development alone from start to finish. This isbecause it is difficult to secure the development cost, so there has been
an increase in cases in which the development project was changed intoa joint development with another company in the middle of the project.
Even if the profit is less, the most important purpose is to launch the drug.
About 70% of this development cost is spent in clinical studies and the stage
thereafter. The cost for nonclinical studies is about 30% , that is, the budgetthat we aim at exploratory drug discovery utilizing leading-edge researchbases accounts for about 30 % of the whole. Of course, the assertiveness ofdivisions involved in clinical studies inside and outside the company may
become bigger. However, I think that the part in which corporate efforts are
sufficiently reflected is before clinical studies, that is, the upstream part of
drug discovery. For example, in the structural analysis and screening testof proteins to discover new compounds, the parts described as searchingsources are very important. The upstream flow is very weak despite being
important, but since we are doing research and development while
imagining that this flow will run into the ocean, we have a high motivation

2 BioSupercomputing Newsletter Vol.3

and are very proactive, although money is limited, so there is a considerable
possibility that the flow will dry up in mid-course. Even so, it is necessary toaddress the issue of drug discovery while promoting efficient searching ofcandidate compounds for development. Therefore, proactive utilization ofleading-edge research bases is required.

■For overcoming the disease of a low degreeof contribution of drugs━ Is the method of creating new drugs changing from day to day?
● Nishijima

In Japan, it has largely changed from the time when the

consortium for structural analysis of proteins was established by the JPMA.
Until then, drug discovery consisted of first searching the cause of thesymptoms of a disease, but the target was completely based on guesswork.
We conducted so-called random screening of a lot of compounds andnatural products thinking they might be related to diseases. We searched
for new drugs in this manner. The difference of new drug discovery is asfollows. First, it became possible to identify receptors and enzymes, thetargets of a drug, by structural and functional analysis instead of guesswork,and searching for new drugs can be carried out in a rational manner. It also
became possible to adjust the expression of a protein based on genome
information, and to verify whether or not it is involved in a disease or is thetarget of a drug. Therefore, it became possible to design new drugs to treat
disease in a rational way. By using molecular imaging, moreover, it is also
possible to confirm the action and therapeutic effect of a drug in the body.
It can be said that the time has changed from the era of symptomatic drug
discovery to that of rational drug discovery aimed at fundamental treatment.
Therefore, it is essential to carry out rational drug discovery by integration ofleading-edge research bases.

━ For what diseases will rational drug discovery be promotedin the future?
●Nishijima Here is data summarizing the degree of satisfaction with thetreatment of various diseases, and the degree of contribution of drugs to
the treatment (Figure 1). This data shows that diseases treated very well withsurgery and drugs have already been differentiated from diseases which heal
poorly and for which there is no good drug. It can be understood that there
have already been good drugs for hypertension, hyperlipidemia, peptic
ulcers, tuberculosis, etc. On the other hand, although there are various drugs
for dementia, complicated diseases like diabetes mellitus, various cancers,etc., the degree of satisfaction is very low. For example, this is because webarely inhibit the progress of dementia and cannot cure it. For diabetes
mellitus, moreover, treatment must be continued indefinitely once it occurs.
That is, since we cannot heal them, it is natural that drugs do not contribute
essentially. Therefore, rational drug discovery in the future will be performed
for overcoming diseases in which the degree of contribution of drugs is low.

━ In the molecular imaging research strategy promotion
program (Phase 2 program) of the Ministry of Education,
Culture, Sports, Science and Technology, it was shown that wewill address the 2 fields of refractory cancers and dementia.
● Nishijima

This is the first reason for specialization in cancer andSPECIAL INTERVIEW
100％

Hyperlipidemia

Degree of contribution of drug to treatment

90％

Peptic ulcer
Tuberculosis
Gout Hypertension

Diabetes mellitus
80％
dementia. In other words,
Epilepsy
the target site of the drug is70％
not clear in these diseases. In
Arrhythmia
Depressiono rd e r to overco m e this , it is,60％
necessar y to implement drug
Parkinson s disease
discovery by integrating leadingChronic hepatitis C
e dge research bases ins tead
50％
Leukemiaof conventional methods.
Prostate cancer
Endometriosis
Fo r e x amp l e, this re quires a
40％ Both the degrees ofsatisfaction with
Breast cancer
breakthrough in brain science,treatment and contribution Cerebral
infarction
deepening and integration of the
Stomach cancer
30％ of drug are low.
AIDS
understanding of the brain andColonic cancer
Diabetic
Uterine myoma
nephropathy
nervous system, and progress in
Chronic renal failure
20％
Uterine cancer The degree of satisfaction with
DiabeticLungcancernerve and brain cell simulation
Hepatic
neuropathy
treatment is diﬀerent for each
Hepatic cancer
cirrhosis
utilizing supercomputers andcancer, but the degree of
10％ Vascular dementia
contribution of drug is generally low.
,
Diabetic retinopathy
the contribution of molecularAlzheimer s disease
imaging to diagnosis and drug0％
d i s c o v e r y. W e b e l i e v e t h a t
0％
10％
20％
30％
40％
50％
60％
70％
80％
90％
100％
all citizens want to introduce
Degree of satisfaction with treatment
leading- edge research bases
into this field for which doctors,
Prepared based on the data of the Doctors Survey Report (fiscal year 2005) by Japan Health Sciences Foundation
patients and pharmaceuticalFigure 1: Degrees of satisfaction with treatment and contribution of drug for various diseases
co m p a n i e s n e e d a s sis t a n ce.
Moreover, it can be said that thisis just where the performance● Nishijima Of course, simulation of the structure of proteins, drugof the ten quadrillion speed computer “Kei” comes in. The mindset of thedesign and disease models will become more important in the future. As
general public is more important than the pull of future science technology
concerns diseases with a low degree of satisfaction with the treatment andor being top in the world. For example, when you or your family members
contribution of drugs, such as dementia, complicated diseases like diabetes
undergo examination, it takes 2 weeks until the result of diagnosis ismellitus and some cancers, described previously, in particular, research byobtained by precise image processing, a huge amount of data processing
simulation may become important. Moreover, the processing speed will also
and comparisons, etc. with a conventional computer. If the ten quadrillion
be important. A demand for the fastest computer, if possible, is common in
speed computer is used, however, it may take 30 minutes to obtain thegovernment, industry and academia. If possible, moreover, it is important toresult. If you are asked which do you choose, anxiously waiting out the 2
develop an environment in which other leading-edge research bases andweeks or acquiring the result quickly on site, everyone would choose getting
supercomputers are integrated, and everything can be used together. If thethe result quickly. I think that the general public will understand that thisuser can use a supercomputer without recognizing it as a supercomputer,needs money. In a brain science such as dementia, moreover, the dimension
it may be better. For example, it will be wonderful if an environment couldof the drug discovery process is different from lowering blood pressure or
be developed so that data can be collected with SPring-8, a structural
killing bacteria invading the body. Because of the problem of recognition, alland functional analysis is immediately performed with a ten quadrillion
the problems cannot be tackled by using experimental animals, neither is it
speed computer, and virtual screening is also carried out. This is because
easy to open the human brain to try drugs. If so, there is no other way thanfuture drug discovery is not possible with individual leading-edge research
simulation utilizing supercomputers. As an extreme case, if you were asked,
bases alone. It is necessary to address this problem by bringing everything“May I open your head or may I use a supercomputer?”, your answer would
together nationwide. In the future, there is no doubt that supercomputers
be obvious (laughing). Actually, there is a field such as dementia, in which it
may be involved in the most important part. Since the data obtained inis necessary to perform simulation.
leading-edge research are all precise, the high processing performance ofsupercomputers is required to utilize the data

■It is important to cultivate human resources
to open up the next generation.
━ Are high-level calculation tools such as supercomputer
very important for the practice of rational drug discovery
carried forward by the pharmaceutical industry?
●Nishijima If Spring-8 is used, for example, the amount of data increases
10- or 20-times in comparison with the X-ray analysis which was doneby our company. The more precise, the clearer the image, so the amountof data does not decrease but increases. Then, we may of course have toconsider choices like upgrading the computers in our company, use of
supercomputers owned by national research organizations, or cooperation
with a university which can use a supercomputer.

━ For the pharmaceutical industry, the 2 main reasons forusing a supercomputer are processing of a huge amount ofdata and simulation as described previously.

━ Finally, please give us your opinion about operation of theten quadrillion speed computer after its completion, if any.
● Nishijima After looking at various leading-edge research bases andtheir operations so far, the matter I feel the most important is cultivationof human resources. I feel that Japanese facilities have no room to expand.
We are good at making facilities themselves, but after starting operation,
the budget to expand and improve it is not available. Therefore, cultivationof human resources there is not well implemented. I think that the facilities
need room for minimal maintainence, as well as for future evolution. To be
specific, we need to cultivate young people more for the next generation.
For example, in choosing research projects, we should consider cultivating
people who will develop the next generation by creating a fund for young
researchers in their 20's and 30's, instead of selecting glamorous projects.
As concerns the present ten quadrillion speed computer, it will probably be
difficult to develop the next generation computer after this with the same
way of thinking. A new breakthrough is required. There is no doubt thatyoung researchers in their 20’s or 30’s may achieve it. We should consider
how to cultivate such human resources.

BioSupercomputing Newsletter Vol.3 3

S

PECIAL INTERVIEW

Future of Life Science Pioneered by Biosupercomputing

Sonic simulation research in the bodywhich is essential for promotion ofultrasound therapy and developmentof therapeutic apparatus
Extraordinary researcher, Department of Mechanical Engineering,
School of Engineering, University of Tokyo

Akira Sasaki■ In order to promote the HIFU treatment
being led by Japan━ Dr. Sasaki, you have been in the industrial world up untilvery recently.
● Sasaki （dispensed with Mr.） I was engaged in the design anddevelopment of an ultrasound diagnostic system in the company called as
Hitachi Medical Corporation for a long time. A digital ultrasound diagnostic
system which appeared in the latter half of the 1980s has evolved at a rapid
pace since the mid-1990s, it became possible to provide more information
for clinical diagnosis, and when its performance improved, its scope becamevery large. About 5 years ago, moreover, ultrasound waves came to be
utilized not only for diagnosis but also for treatment as a global movement,
and because we have to do it in Japan, I was engaged in the developmentof an ultrasound therapy system. I retired from the company at the
mandatory age in March 2010, joined the university in June, and have beenaddressing the development of HIFU (High Intensity Focused Ultrasound)using ultrasound waves. I think that my work is to play the role of interface
between “industry” and “the academic sector” by utilizing my previous
experience in the company.

━ What is the HIFU therapeutic system?
● Sasaki HIFU is a system focusing ultrasound waves on one point in
the body and performing treatment by making only the focused part hightemperature, which is also called a “high Intensity therapeutic ultrasound”
For example, the present cancer treatment consists of drugs and surgery,
both of which are associated with severe suffering and stress. However, HIFU
does not need to cut the body and causes no suffering as with anticancer
drugs. If a patient undergoes treatment in the morning, he/she can return
to home in the afternoon. Moreover, radiation therapy can be done only
once, but HIFU treatment has the advantage that it can be repeatedmany times. The research ongoing now is a DDS (Drug Delivery System)type treatment using ultrasound waves. This is a treatment focusing a
micelle containing a drug on a site such as cancer through a blood vessel,and breaking the particle with faint ultrasound waves to perform topicaltreatment. As described, the HIFU therapeutic system has greater potential.
However, at present, Japanese companies are doing the research, but notcommercialization or manufacture.

━ Why are Japanese manufacturers inactive?
● Sasaki The problem of ensuring safety is a major bottleneck.
Considering the liability issue in failure of treatment, manufacturers cannot
start development so easily. In the case of a drug, it is OK if suitable effects
can be obtained considering the risk and benefit ratio but in the case of atreatment, failure is not permitted, and issues of liability and compensation
may occur. Another issue concerns the market. An ultrasound diagnostic
system is introduced to a lot of medical institutions and has goodmarketability, but the market for treatment is limited, and the cost will behigh. Moreover, a therapeutic apparatus has to undergo clinical evaluation.
Considering the cost, period and manpower involved in a clinical trial, it may
be particularly unprofitable for the manufacturer. Considering the global
movement, however, an Israeli company has already developed this system
in about 2002, which was approved by the FDA in 2004 and launched. In
the U.S.A., the GE company is dealing with it. Philips will launch it in 2011.
Siemens is developing a prototype and will start clinical trials in 2011. In order

4 BioSupercomputing Newsletter Vol.3

to establish the field of HIFU therapy, moreover, the Focused UltrasoundSurgery Foundation was already established in Western countries in2006, and research and development have begun. If Japan does not startdevelopment despite the fact that 3 of the world’s leading companies are
moving ahead with manufacture by shifting from diagnosis to treatment,
100 % of the market will be occupied by overseas companies. Because wehave to promote HIFU therapy from Japan in some way, it was decided toestablish a consortium in Japan. In order that the Japanese HIFU therapeutic
system survives in the future, it is important to build a strategy for Japan to
win the world. This is not a time when one domestic manufacturer can win.
To improve our chances of success, we will work together in an all-Japan
organization.

■Making a bridge between“industry”and the“academic sector”is my job.
━ What is the first issue in developing the HIFU therapeutic
system from Japan?
● SasakiMore than anything else, we have to emphasize the safety oftreatment. HIFU therapy is a method to directly treat only a target site in
the body. In order to perform treatment safely, precise imaging diagnosis,
navigation and biological simulation are important keys. First, in orderto draw up a solid therapeutic plan, a precise preoperational imaging
diagnosis should be made by making effective use of CT, MRI, US (ultrasounddiagnostic system) and RI (nuclear medicine diagnosis system). It is required
to observe in real time during operation, and to conduct appropriate
guided navigation. Unlike surgery which directly opens the body, moreover,this HIFU therapy only looks at images. The efficacy of treatment is also
evaluated with images. In order to observe the progress of treatment, abiological simulation is therefore essentially required.

━ Does a safety issue still remain in the HIFU therapy itself?
● Sasaki Ultrasound waves are characterized in that refraction andreflection occur due to acoustic impedance (density× sound velocity).
Like light, ultrasound waves bend when they enter a different medium.
Therefore, refraction and a change in sound velocity with the fats, muscles
and organs in the body affect the beam characteristics of ultrasound waves
and displacement of the focal point. In the bone, moreover, thermal changes
occur due to absorption of ultrasound waves, and heat diffusion may also
occur at a blood flow-rich site. Moreover, ultrasound waves are influenced
in the body by various factors such as movement of organs such as theheart and presence of air bubbles such as intestinal gas which induce phase
disturbance or sound disturbance. It is never easy. In order to avoid these
influences in the therapeutic plan, it is essential to measure the hurdles
exactly, and to perform optimum control. For this, it is necessary to simulate
the sound characteristics in the body in advance.

━ Does the result of such a biological simulation assist thedesign of HIFU therapy?
● Sasaki One way is optimization design of the ultrasound beamincluding the transducer generating ultrasound waves. In order to irradiateso that the ultrasound waves are precisely focused on the target site, theprocesses of penetration through the skin on the body surface, muscles, fats
and organs will be important. Moreover, procedures for avoiding intestinal

SPECIAL INTERVIEW
Transducer for HIFU

Displacement of the focal point
occurs when ultrasound waves aretransmitted in the body.

Predict the behavior oftransmission of ultrasound waves,and control the focal point
Array-shape transducer

Array-shapetransducer

Bone
Organ

Tumor

An example of a HIFU transducer of concave 56
channel array type◦ Coagulation therapy at a target site at 60 to 90℃ in the focusedregion by increasing the intensity of ultrasound waves◦ Annular Array form: Enlargement of the region of coagulation with
Dynamic Focus

gas and bones which may become large hurdles are also required. In atransducer consisting of multiple elements, each element is limited so as to
avoid irradiation to the place where bones and air bubbles are present inadvance, and refractive correction is performed by giving the delay time. By
these procedures, a method of irradiating ultrasound waves precisely to thetarget site has been studied. Moreover, a method to shorten the treatment
time has also been studied by predicting the increase in temperature at
the coagulation site, and by irradiating while continuously changing theirradiation position. In conventional HIFU therapy, some time to cool offheat after irradiation was required, and it took 2 to 4 hours for treatment,
but this is an attempt to shorten the treatment time largely by continuous
coagulation while moving. In optimization design of HIFU coagulation,
optimization of multi-cauterizing design to shorten the treatment time,and minimization of side effects, simulation will play an important role.

━ In order to establish a HIFU therapy system af ter
overcoming various issues, is biological simulation still
important?
● Sasaki If navigation and simulation are done correctly, the safety of
HIFU therapy will increase. I want to make treatment safe by conducting
experiments based on this. In Europe, research has already progressedto an attempt of treating brain tumors through the cranial bone. By
calculating the refractive index of cranial bone, they are attempting to focus
ultrasound waves on a point in the brain. It is wonderful that treatment canbe performed without opening the brain. The idea is wonderful. I think it isSkin

Beam patternin the focused region

MuscleFat

An example of a method to control
the focal point in the body bysimulation

very difficult to realize it, but simulation will become truly important in suchresearch.

━ In promoting the technical development of such HIFU
therapy, do you think that computational resources suchas a ten quadrillion speed computer will make a significant
contribution?
●Sasaki It is absolutely necessary, and I expect it. In the Organ and Body
Scale Team, development of a focused ultrasound simulator is actuallyongoing, and I would be a fool not to take advantage of this (laughing). As
described previously, since this treatment can be observed only on images,
a simulation is required for monitoring processes. I think that the researchitself cannot be done without simulation.

━ If the safet y of HIFU therapy increases along withthe progress of simulation research, will the Japanesemanufacturer go on to develop or manufacture a HIFU therapy
system?
● Sasaki Yes, it will. Considering the global trend, the time fordevelopment and manufacture has come. For this, if the “academic sector”
researches what degree of safety has been established, “industry” will takeaction, and I think that my mission is to make this possible.

HIFU Transducer for In Vivo Experiment

Example of HIFU Transducer for Prostate

B-mode Image of HIFU Treatment

HIFU Beam Profile

BioSupercomputing Newsletter Vol.3 5

Report on Research Molecular Scale WG

Achievement of a Multiscale
Molecule Simulation of QM/MD/CGM
Institute for Protein Research, Osaka University(From the above) Yasushige Yonezawa, Shusuke Yamanaka,

Hiromitsu Shimoyama, Hideki Yamazaki and Haruki Nakamura
RIKEN, Computational Science Research Program

Ikuo Fukuda

For this achievement, we have developed a multiscale
simulation program, Platypus (PLATform for dYnamic
Protein Unified Simulation ), which couples quantum
mechanics (QM) with molecular dynamics (MD) whichwere developed individually. Quantum mechanics to
calculate electronic state is a computation method
essential for handling enzymatic functions in simulation,and here, computation by the Hartree-Fock (HF) method,
the density functional theory (DFT), CASSCF and CIS areavailable. Molecular dynamics is a simulation method,which reproduces the thermal fluctuation of molecules.
Platypus is an integral of the program which realizes
massive parallelism with the original codes, which has
accelerated performance of up to 8192 parallels in thecomputations of both HF and DFT in the development
so far, and particularly, it shows good scalability up to
1000 to 2000 parallels. In addition, Platypus loads the MDcomputation with an independently developed coarse
graining model (CGM), with which the multiscale molecule
simulation of QM /MD/CGM can b e implemente d.
Moreover, we are developing an algorithm which performs
efficient sampling with the QM/MD computation.

Pyramidality

As one of the applications of Platypus , we introduce
research on the cis-trans isomerization mechanism of theproline residue, which is related to the signal molecular
control of various life activities. In a study of small peptides
including proline in water (reference 1), the transition state
between cis and trans forms the conventionally known
pyramid as well as the inverse pyramid, and it was firstly

Cis

Trans

Cis

Reaction coordinate for the cis-trans isomerization (degrees)

Figure1: Free energy landscape of cis-trans isomerization of a
peptide including a proline residue, which was elucidated by QM/MD
multiscale simulation. A transition state largely fluctuating between
cis and states is observed.

6 BioSupercomputing Newsletter Vol.3

shown that this state fluctuates between these 2 forms(Figure 1). From a study of the Pin1 isomerase, which
accelerates the cis-trans isomerization of the proline
residue, we succeeded in grasping the mechanism, inwhich the strain occurring by binding of the peptide
including proline to the enzyme active site stabilizes
the energy in the transition state so as to accelerateisomerization.
In the molecular dynamics simulation, the time forcomputation of interatomic long-range forces not basedon chemical bonds between molecules accounts for alarge amount. By parallelizing this part, the computation
time can be considerably shortened. The Ewald method
is a general method most often used, but it is known that
this Ewald method is not suitable for parallelization of avery large system. We are therefore pursuing research torevise the long-range force potential recently developedby Wolf et al., and develop our original Force SwitchingWolf method (FSw-Wolf method), by which a consistentand steady simulation can be performed instead of theEwald method. We succeeded in showing by simulationof a fused sodium salt (reference 2 and Figure 2) and ashort peptide in water that the FSw-Wolf method canrealize the computation at a precision comparable to thatof the Ewald method. The FSw-Wolf method is not only avery convenient algorithm, but also it considers only theforce between atoms at a relatively short distance. Thus,
it is very suitable for large scale parallelized molecular
dynamics simulation. Moreover, it is considered that thismethod will become a key method which can realize highspeed parallel computation by combining with otheralgorithms.
Reference 1. Yonezawa Y., Nakata K., Sakakura K., Takada T., Nakamura H., J.
Am. Chem. Soc. 131(12), 4535-4540.
Reference 2. Fukuda I., Yonezawa Y., Nakamura H., J. Phys. Soc. Jpn. 77(11),114301, 2008.

Error rate from the Ewald method

Our group is attempting to elucidate the mechanism offunctions of biological macromolecules, proteins andnucleic acids, at multiple levels including molecular, atomic
and electronic levels using molecular simulation. Actual
molecules in living matter show thermally fluctuating
actions at room temperature, and the fluctuation has theessential roles on molecular functions. Our purpose is toelucidate the mechanism of such biological molecules
including their electronic state while simulating thethermal fluctuation in details.

Cutoff distance (Angstroms)

Figure2: The energy error between the FSw-Wolf method and the Ewald
method, plotted as a function of the cutoff distance and the parameterα in the FSw-Wolf method. This shows that the FSw-Wolf method canreproduce an energy very close to that in the Ewald method.

Report on Research Cell Scale WG

Towards development and experimental
demonstration of liver model basedon large-scale metabolic simulation
at individual cellular level
School of Medicine, Keio University

Ayako Yachie-Kinoshita
Hepatic parenchymal cells (hepatocytes) which occupy a large part of the cellularvolume in liver have very extensive and complex metabolic pathways including mostmetabolic reactions occurring in the body, and play an important role in regulationof vast variety of small molecules. Compartmentation of metabolism by site
specificity, in which an enzyme expression pattern is different between the upstream(portal vein) and downstream (central vein) of sinosidal blood flow, is considered
to be one of the factors that makes the functional switching of metabolism in liver
efficient. However, due to the striking complexity in metabolic dynamics in which
many metabolic functions are intricately involved with each other, it is very difficult
to comprehensively understand the dynamics of hepatic metabolism and its
underlying mechanism, and for many phenomena, analogies are still being drawn
from circumstantial evidence. In such a case, model-based analysis and simulation by
integration of independent kinetic characteristics is very powerful to understand thesystem as a whole.
We therefore established an unprecedented large-scale metabolic model
including approximately 500 defined substances and about 250 dynamic
reactions using the E-Cell Simulation Environment Note1 based on the reaction
kinetics obtained by literature search. With this model, the dynamics of themetabolism in the mitochondria and cytoplasm can be predicted separately andsimultaneously(considering the compartmentation of metabolism in the cells),
and the effects of exchange of small molecules between hepatocytes in portal
vain and central vein regions via a gap junction can be predicted by changing
the enzyme expression pattern to set up the regional heterogeneity of the bothregions (considering the compartmentation of metabolism between cells). We arealso developing the model to reproduce the condition in which hepatocytes withdifferent metabolic properties interlock each other to function by using the Riken
Cell Simulator (RICS)Note 2 (Figure 1).
Using the large-scale metabolic model of hepatocyte, we compared a predicted

dynamics under hypoxic and hypoglycemic condition from a couplet model inwhich two connecting hepatocytes having portal vein and central vein metabolic
properties with those from the models in which both hepatocytes have a property of
portal vein or central vein only. As a result, by coupling cells with different properties,
over-all changes in metabolites and a decrease in ATP energy in response to thesestimulations were suppressed, and it was predicted that the robustness of themetabolism would be improved at an organ level.
This result may contribute not only to understanding how hepatic metabolism is
optimized using heterogeneity, but also to understanding of metabolic failure in theintercellular material exchange disorder such as a case of hepatic cirrhosis. Moreover,the in vivo experiments in our laboratory have clearly showed that the metabolism
changed largely not only in metastatic foci but also the surrounding hepatocytes dueto hepatic metastasis of colon cancer. Our hepatic metabolism simulation model canbe applied to reproduction and discussion of such a disease model, and prediction ofresistance to hepatic ischemia during surgery and spare ability at hepatectomy.
In considering the effects of cell metabolism on organs and the whole body,particularly pathological conditions, on the other hand, it may be essential toestablish an experimental system to observe the metabolic conditions without
destroying the tissue structure.
Our laboratory therefore focus on an experimental technique of “visualization of
metabolism with µm resolution” combining a metabolome analysis with an imaging
mass spectrometryNote3 (Hattori K et al., Antioxid Redox Signal. 13(8): 1157-67 (2010)).
At present, improvement of this method is moving ahead with great urgency, andit has become possible to determine more metabolites including aminoacids at
higher resolution. By this technique, it may be possible to measure and quantify thedifference in metabolism between portal vein and central vein hepatocytes with thein vivo spatial arrangement (Figure 2).
In the future, the study to quantify and observe metabolism as the in vivo spatial
arrangement of tissue is maintained, and to elucidate the results and the meaningof material variation by exhaustive cell simulation (large-scale calculation with asupercomputer) considering spatial information will become important.
Note 1: Simulation environment focuses on phenomena of intracellular molecules, which has been being
developed by Institute for Advanced Biosciences of Keio University, and RIKEN.
Note 2: A platform of cell simulation, which is being developed by RIKEN.
The reactions of small molecules considering the spatial information in the cell and the position
among cells can be simulated by constructing the cellular model in the space (voxel) of a fixed grid,and establishing diffusion and transfer among voxels.
Note 3: The mass distribution is visualized at a resolution of 10 µm by ionizing metabolites by applying a laser
to a section of frozen tissue at fine intervals, by measuring ions with a mass spectrometer connected
to it, and then by reconstructing information on masses of the metabolites determined at therespective positions.

Figure1 : Expansion from exhaustive hepatocellular metabolism model
to liver model

Figure 2 : “Visualization of metabolism” using imaging mass
spectrometry and metabolome analysis

BioSupercomputing Newsletter Vol.3 7

Report on Research Data Analysis Fusion WG

Exhaustive Protein-Protein
Interaction Network
Prediction by Using
MEGADOCK

Graduate School of Information Science and Engineering,Tokyo Institute of Technology(From left, above)Yutaka Akiyama, Yuri Matsuzaki,

Nobuyuki Uchikoga and Masahito Ohue

We are working on prediction of the protein-protein
interaction (PPI), one of the impor tant problems ofsystems biology, by the method of bioinformatics andparallel processing (Figure 1). Usually, the expected roleof the computational method using physical chemistryon PPI analysis was to examine the configuration andaffinity of interactions concerning the known one-to-one
protein-protein interaction in detail. We then developed“MEGADOCK,” a novel PPI prediction system based onlarge-scale parallel calculation, and made it possible topredict a candidate pair of PPI exhaustively from a large
amount of protein groups. This is expected to contribute to
the discovery of new PPI by collaboration with experimentsin the future.
MEGADOCK is a system to predic t the presence orabsence of interaction using information about thetertiary structure of proteins based on various scoresobtained from rigid-body docking. In this calculation, ahigh-speed evaluation is conducted mainly based on the
shape complementarity of the molecular surface without
considering the structural change of the protein. We
introduced the rPSC (real Pairwise Shape Complementarity)
score composed of the terms of shape complementarityand electrostatic interaction assigned to the molecular
structures on the voxel space. With a conventional tool,
ZDOCK, score is calculated using 3 interactions with 3
complex numbers, whereas in the rPSC, score is calculatedusing 2 interactions with 1 complex number by expressing
the shape complementarity in a real number part andintroducing electrostatic interactions into an imaginary
number part. The number of three-dimensional fast
Fourier transformation (FFT) required for convlolution sum
calculation was reduced. When executed by a single CPU,
about four times higher calculation speed was achieved
with the same precision as ZDOCK.

MEGADOCK is parallelized using the MPI library. Whena certain processor was assigned multiple receptor andligand proteins, one ligand is taken sequentially fromthe ligand set, transformed by FFT with the certain angle
increment, and compared as the innermost loop withall the data in the receptors set. A procedure of making
the FFT transformed library concerning known proteins,and read from a hard disk to perform convolution sum
calculations was implemented, and a speed increased of
up to about 3 times was achieved. With appropriate loadbalancing, efficient calculation is possible by hundreds ofprocessors or more.
As a benchmarking of MEGADOCK, we firstly performed
PPI prediction of 44 × 44=1,936 combinations on 44
protein complexes. The predicted (red) and native (green)
structures were consistent (upper part of Figure 2). In theprediction of PPI pairs, many correct complexes werepredicted as shown by the warm color on the diagonalline in the lower par t of Figure 2, and a predic tion
performance (F-measure = 0.415) similar to or higher thanin a related study was obtained. As an actual applicationin systems biology, PPI prediction was performed on thesignal transduction pathway of bacterial chemotaxis (89× 89=7,921) and the human EGFR signal transduction
pathway related to lung cancer(497×497=247,009). Our goal
is to perform the calculationof a 1,000×1,000 (mega) classroutinely.
References(1) Matsuzaki Y., Matsuzaki Y., Sato T. andAkiyama Y., J Bioinform Comput Biol ,7: 991-1012 (2009).
(2) Ohue, Matsuzaki, Matsuzaki, Satoand Akiyama. IPSJ Transactions
on Mathematical Modeling and
its Applications (TOM), 3(3): 91-106(2010).

Figure 1: Estimation of the protein interaction network based on PPI prediction

8 BioSupercomputing Newsletter Vol.3

Figure 2: Result of PPI prediction (44×44 benchmark)Report on Research Brain and Neural WG

Whole Brain Simulationof the Insect Olfactory System

Research Center for Advanced Science and Technology,
The University of Tokyo

Tomoki Kazawa, Stephan Shuichi Haupt
Nerve cells (neurons) are the building blocks necessary for the emergenceof intelligence as they process internal and external information, generally
encoded in sequences of spikes and form networks in which such informationis relayed between them. Input and output parameters of neurons such as
gain can change dynamically depending on prior activity history. Neurons
are present in all metazoan animals from simple coelenterates like Hydraand have the same general properties across the animal kingdom. Though
the basic building blocks are so similar, there is a big difference in the size of
nervous systems, human brains harbour 1011-12 neurons, insects have 105-6 brainneurons, and the somatic nervous system of the nematode Caenorhabditis
elegans contains just 302 neurons. Insects are sufficiently complex to display
many sophisticated behaviours, such as learning floral odors and colors.
Multimodal information is integrated in the insect brain which can generate awide variety of complex and plastic behaviours, making insect brains a highly
suitable system to investigate the emergence of intelligence. Our approachto understanding such an intelligent system shaped by millions of years of
evolution is to attempt to recreate it through simulation. This insect wholebrain simulation has to encompass information processing from sensory input
to behavioural ouput. We currently focus on the odour-source localisation
behaviour of silkmoth (Bombyx mori) males as a convenient model system. We
are analyzing the brain of the silkmoth accumulating numerous data obtainted

with a large grid of methods including molecular genetics, electrophysiology,
imaging, immunohistochemistry, and behavioural experiments. Our methods
cover the full scale of observation levels from the molecular and cellular levels
to the network and behaviour levels. These multi-scale data are integrated inour database, which, for example, contains data on >1600 neurons individually
identified in terms of 3D-morphology and physiology, currently making it thelargest single-species individual neuron database worldwide. An important
insight from these data was the understanding of global and regional
connectivity in the olfactory system in the brain of the silkmoth.
Since insects can exhibit highly complex behaviours despite having a relatively
small number of neurons, it is likely that the relative contribution of eachindividual neuron is more important than for instance in mammals. In our largescale simulation of insect neural circuits, we are therefore performing a detailed
simulation of each individual neuron using multicompartment models (Figure1). The 3D-morphology of neurons is acquired by confocal microscopy and canthen be approximated by sets of connected cylinders. A cylinder per se has asimple equivalent circuit consisting of voltage and impedance to the outside of
the cylinder (membrane resistance and capacitance). Cylinders are connectedby resistors that correspond to axial resistance in neurites. Inputs are describedas chemical synapses having postsynaptic potentials of 5-20ms duration upon
the simulated activation by neurotransmitter. The synaptic activation can
induce spikes of 1-2ms width that are modeled by the conventional sodium
and potassium currents (Figure 1C). By mapping and combining numerous
single neuron simulation models in the brain, a neural circuit simulation canbe constructed (Figure 2).
We estimate that a total of about 10000 neurons in the brain are involved thewhole information processing from reception of olfactory sensory input tothe generation of the control activity patterns for odour-source localisation
behaviour. Using representations of neurons consisting of about 100
compartments, we estimated that the computations necessary to simulate
information processing in the entire insect brain can be performed in realtime on a machine with the performance of a petaflop HPC. If a real-time
simulation of the neural circuit from sensory input to motor output can beachieved, it also becomes possible to investigate information processing by
modification of the circuit properties in ways that are currently not feasiblein actual experiments. Such manipulations are of paramount importance toidentify minimal neural circuits to perform specific information processing
tasks. We expect this approach will have an impact in medical applications,in particular neurorehabilitation and neural protheses.

Figure 1 : Simulation with a multicompartment
model generated by extraction of neuronalmorphology.
A) Double-label image of a GII descending
neuron and the Cv1 motor neuronB) Extracted morphology of the Cv1 motor
neuronC) Multicompartment model and equivalentcircuitD) Single neuron simulation of the Cv1 motor
neuronFigure 2 : Neural circuit simulation of the
premotor center in the silkmoth brain.
A) An example of the spatial distributionof the membrane potentials of local
interneurons (outer side) and bilateral
neurons (inner side)B) Raster plot of spike events of local
inte r n euro ns (gre e n) an d b ilate r al
neurons (red)BioSupercomputing Newsletter Vol.3 9

ReportThe summer school 2010 for the
Integrated Simulation of Living
Matter was held.

RIKEN, Computational Science Research Program

Yasuhiro Ishimine (Organ and Body Scale WG)

The Institute of Medical Science, The University of Tokyo
Teppei Shimamura (Data Analysis WG)
RIKEN, Computational Science Research Program
Yasuhiro Sunaga (Cell Scale WG)
Kyoto University Graduate School of Informatics
Naoki Honda (Brain and Neural WG)
RIKEN, Computational Science Research Program

Gen Masumoto (High-Performance Computing Team)RIKEN, Computational Science Research Program

Kosuke Matsunaga (Molecular Scale WG)(Order of the Japanese syllabary)

At Shonan International Village Center in Hayama Town, Kanagawa
Prefecture, the “Summer school 2010 for the Integrated Simulation of Living
Matter” was held for 3 days from July 5 to 7, 2010. This summer school
was mainly planned and managed by young researchers participatingin the project for the next-generation integrated simulation of living
matter. A total of 57 members including post-doctoral researchers andgraduate school students in related fields, who are participating in thisproject, presented lectures and exchanged opinions concerning numericalsimulation and large-scale data analysis related to life sciences. Here, wewill give an overview of the summer school, interweaving responses toquestionnaires obtained from participants and details of reports submitted
by all participating graduate school students.
The summer school was basically carried forward in a lecture mode. First,
as a “keynote lecture,” Koji Kaya, a director of the Computational Science
Research Program, gave a summary of the research in which the director
himself was engaged, describing his theory concerning the attitude andbackbone for research which a first-class researcher should always strive tomaintain. Then, the latest research achievements were introduced by a totalof 14 researchers representing 6 teams affiliated with the next-generation
integrated simulation research promotion group for living matter for 3 days
(see Table on p. 11 for details of lecturers and lecture titles). In the afternoonof the second day, a time for general discussion was established, the latest
information about the progress and future prospects of the project wasprovided by Ryutaro Himeno, the sub-director of the Computational
Science Research Program, and then a question-and-answer session andexchange of opinions by all the participants was held concerning measuresfor effective use of supercomputers. Extra time was also provided to
exchange information individually, such as for a get-together and poster
sessions. The lunch break on the second day was made slightly longer forthe same purposes, not only information exchange but also voluntaryintercommunion among participants, such as enjoying football outdoors.
According to the results of the questionnaire, the lecturers and content
of lectures were basically satisfactory, and impressions were manifested
such as “I realized that there were research themes at various levels (fromthe level one molecule to the level of the tissue) ,” “since there were somequestions which could not be conceived from an insider's viewpoint - forexample, a question about a theory that we ourselves accept implicitly - I
could appreciate an outsider's viewpoint,” “I found out
which project covers the Petacom plan, what people are
involved, what I can do using Petacom and what are theproblems in using Petacom,” and “I understood that, since
there may be a large computation effort in performing
simulations to understand one factor, next-generation
supercomputers have great significance”. There were also
impressions referring to expansion of future collaborative
research, such as “I understood that a lot of researchers
have so much in common in that we are dealing with acertain problem of optimization”, and “since there are

10 BioSupercomputing Newsletter Vol.3

some common areas among teams as far as concerns not only themes but
also procedures, I expect that better research would be possible if there
were active collaboration”.
As for demands for the future, moreover, there were some opinions suchas “I want you to hold an invitation lecture of a famous researcher in thefield of biology or a person who is doing simulation in the research anddevelopment division of a company”, and “it may be better to hold it at a
meeting like a study session with the people like graduate school students.”
There were also some unique opinions such as “I want to discuss things inview of what goes on in other fields”, and “it might have been interesting
if a scientific contest were held in a team session consisting of roommate
members in the hotel.”
The biggest regret as a secretariat was that there were multiple opinions
that we should have paid attention to participation of graduate school
students. Some graduate school students said, “I thought it was wonderfulthat I did not feel any barrier of position and field at all,” “it was a wonderfulsession which was not too rigid or relaxed, and suitable for the title ofsummer school”, and “I heard opinions from people of quite different
background, approach, experience and age, who are different from thosewith whom I usually interact, and this summer school was a good turning
point for my future research life,” whereas there were some impressions like,“I felt that only a person in a high position or postdoctoral researcher could
ask questions”, and “I felt atrophied because the participants other thanme were postdoctoral researchers.” Moreover, there was an impression,“the story about budget and evaluation of project was stimulating for a
student who wants to purely pursue science in a negative way.” Since there
were some opinions like, “individual self-introduction was required,” as ananswer to the questionnaire, we felt that more significant interchange may
be possible by taking time for orientation at the beginning of the summer
school to shorten the mental distance between each other and to create amood to deal with common subjects.
Based on the above experience in this summer school, we expect that amore fulfilling summer school will be held in and after next year.

ReportAfter participation in the summer
school 2010 for the Integrated
Simulation of Living Matter,
First year of doctor s course,
The University of Tokyo
Graduate School of Science

Ken Saito

I belong to the seminar of Professor Shinya Kuroda of the Universityof Tok yo, a member of the Brain and Neural System Research andDevelopment team which analyzes intracellular signaling pathways using
mathematical models (particularly time-series statistical models). A seniorassociate in the seminar introduced this summer school to me, and I
participated in the summer school because I wanted to meet people indifferent fields who are related to my research theme, but with whom it isdifficult to exchange opinions in my daily research life.
I have been interested in the work of the Data Analysis Fusion Researchand Development Team estimating the structure of gene networks using
time line data about gene expression, such as SiGN and LiSDAS. Because I
have difficulty in appreciating the significance of explanations of signaling
pathways using mathematical models, I wanted to hear other opinions
about it. When I actually heard the lecture at the summer school, it was
impressive that a lot of researchers wanted to apply it in medical practicethrough modeling. I also heard the story of researchers who have the same
directionality as mine, and it was a very valuable experience for me.
Since other lectures handled the theme across various levels from brain
and organs to molecules, I was anxious about keeping up with the contents
before participation, but actually, the lectures were explained so that the
unprofessional people can understand, so I could interestingly hear thelecture of the people far from my specialty to the end. It was particularly
good that the presentation topic was explained carefully, especially the
motivation for the research and why a supercomputer is required. I had
been struggling with the question, “why supercomputers are required foranalyzing the functions of organisms,” but now I could sweep away thatquestion.
Particularly, the presentation by the High-performance Computing Teamwas even more impressive than I had expected. Since the mathematicalmodel that I use now does not require the performance of a computer somuch, I was not so interested in the extra speed of parallel computation,
but I heard the tuning methodology behind this at the summer school,
and this prompted me to have more motivation to study it seriously. In the
future, I want to describe thousands of molecular behaviors in cells with
one model in an integrated manner, and to utilize the knowledge learned at
this summer school.
The matter that I expect from the summer school to be held next year
and so on is aggressive participation of students. In all, only 8 students
including me participated in this summer school. I think that there is no
student who does not know of the “supercomputer project” which cameup in conversation at the screening process for government revitalization,
but I think that there are few students who really understand what is goingon in terms of research themes actually using supercomputers. In orderto understand the positioning of scientific research as a national project, I
thought it would be very meaningful if more students participate in suchan event.
Finally, since not only research, but there were also many recreation events
like football and night networking, etc., at this summer school, I thinkthat participants could have a real opportunity to discuss and exchange
opinions. I would like express my thanks to the people in the Secretariat of
the summer school.

■Program of the summer school 2010
for the Integrated Simulation of Living Matter[Day 1] July 5 (Monday)
Opening speech

Koji Kaya (Director of the Integrated Simulation Software of Living Matter Research and Development Program)“Explanation of purport and keynote lecture”

Yoshinori Tamada (Extraordinary Assistant Professor, Human Genome Center, Institute of Medical
Science, The University of Tokyo)“Estimation of gene network from gene expression data using a
Bayesian networks by nonlinear regression and its parallel algorithm”

Keiji Misawa (Researcher, Data Analysis Fusion Team, Computational Science Research
Program, RIKEN (The Institute of Physical and Chemical Research))“ParaHaplo - Program package to quickly implement analysis related togenome-wide haplotype by parallelization”

Yuri Matsuzaki (Industry-Academia-Government collaborative researcher, Tokyo Institute ofTechnology Graduate School of Information Science and Engineering, Department of Computer Science)“Development of system for estimation of protein-protein interaction
network based on steric structure”

Ryo Yoshida (Assistant Professor, Institute of Statistical Mathematics)“LiSDAS: Life Science Data Assimilation Systems”
Get-together
Poster session[Day 2] July 6 (Tuesday)
Jun Igarashi (Special researcher, Brain and Neural Systems Team, Computational Science Research

Program, RIKEN (The Institute of Physical and Chemical Research))“Basis of realistic neural circuit and large-scale computation”

Naoki Honda (Researcher, Kyoto University Graduate School of Informatics)“Simulation of cytoskeleton-dependent change in cell morphology”

Tomotaka Kasaguchi (Doctor Researcher, Yokohama City University Graduate School of Nanobioscience)“Approach for experimental procedures from an MD”

Tsutomu Yamane (Extraordinary Assistant Professor, Yokohama City University Graduate Schoolof Nanobioscience)“Multiple drug discharging transporter AcrB”

Naoyuki Miyashita (Researcher, Molecular Scale Team, Computational Science Research
Program, RIKEN (The Institute of Physical and Chemical Research))“Sampling method applying molecular dynamics – Development ofReplica Exchange Interface (REIN) –“Yosuke Ohno (Senior Researcher, High-performance Computing Team, Computational Research
Program, RIKEN (The Institute of Physical and Chemical Research))“Hardware and tuning”

Hiroshi Koyama (Senior Researcher, High-performance Computing Team, Computational Research
Program, RIKEN (The Institute of Physical and Chemical Research))“The reason why I hate HPC (High Performance Computing)”
General discussion
Poster session[Day 3] July 7 (Wednesday)
Yasuhiro Sunaga (Researcher, Cell Scale Team, Computational Research Program, RIKEN (TheInstitute of Physical and Chemical Research))“Intracellular biochemical reaction simulator considering organelles”

Youhei Nanazawa (Researcher, Department of Cardiovascular Medicine, Tokai University Hospital)“Development of hemostasis and thrombosis simulator connecting
cells with an organ model”

Kazuyasu Sugiyama (Associate Professor, Faculty of Engineering, The University of Tokyo)“Development of procedures for coupled analysis of fluid structure
based on the fixed mesh method”

Takanori Sugihara (Researcher, High-performance Computing Team, Computational Research
Program, RIKEN (The Institute of Physical and Chemical Research))“Determination of performance for application of next-generation
computers”
Closing speech
Break up

BioSupercomputing Newsletter Vol.3 11

ISLiM Participating Institutions❶ Tohoku University❷ Japan Advanced Instituteof Science and Technology❸ RIKEN❹ The University of Tokyo❺ The Institute of Statistical Mathematics❻ Keio University❼ Chiba University❽ Tokyo Institute of Technology❾ Yokohama City University❷
 Tokai University
 Kyoto University
 Ritsumeikan University
 Osaka University
 Kobe University Hiroshima University


❶

❺

❸
❹
❻
❽
❾

❼



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Event information▪The 3rd BioSupercomputing Symposium●Date : Feb 21 (Mon) and 22 (Tue), 2011 (Reception: night of February 21 (Monday))●Location : RIKEN Advanced Institute for Computational Science (Kobe)※ The program details and registration of participation will be notified on the Web page as soon as they are confirmed.

Topics▪The ten quadrillion speed computer“京(Kei)”was started to built.
The nickname“Kei”in Japanese was chosen from public applicants for the
Next-Generation Supercomputer in July, and RIKEN will refer to the NextGeneration Supercomputer as the K computer in English in the future. The first
8 racks of K computer were set up on Wednesday, September 29 (photographon the right). The computation speed of these 8 racks is about 98.3 TFlops(teraflops) as the theoretical peak performance. More than 800 racks are to bearranged in the computer room at the completion.
The K computer with about 0.5% of its total capacity was ranked 169 among
the Top500 list presented in November, 2010.

BioSupercomputing
Newsletter

3

Vol.

2010.12

Computational Science Research Program,
RIKEN Research Cluster for Innovation

Issued : December 2010

2-1, Hirosawa, Wako, Saitama, 351-0198 Japan
TEL : +81-48-462-1488 FAX : +81-48-462-1220
http ://www.csrp.riken.jp