HPCI magazine vol.10

Consortium for
Industry-Academia-Government
Collaboration and Fugaku
Establish Advanced Platform for
In-Silico Drug Discovery
The FMO Drug Design Consortium (FMODD) was formed at the end of 2014 by volunteers fromindustry, academia, and government. Currently, about 140 members are accessing thesupercomputer Fugaku from all over the country. There are several ways to utilize Fugaku. In
some cases, large-scale calculations are performed using a large number of nodes by a few
people; in other cases many small calculations are done by a large number of members, like thisconsortium. The purpose of the FMODD is to develop the FMO method as a practical meansof drug discovery. To that end, the FMODD is accumulating and disclosing basic data and isdeveloping new methods to generate better results. We asked Prof. Fukuzawa, the group’s chair,about the achievements and future developments.

Kaori Fukuzawa
Professor, Graduate School of Pharmaceutical Sciences, Osaka University

FMO Method for
Rational Drug Design
Many new drugs are currently being developedthat target disease-causing proteins. Newdrug development involves multiple stages. At
the earlier stage, we must find a candidate
compound that binds to the target protein andinhibits (or enhances) its function. After acandidate compound is found, researchers have togradually modify its structure to improve its
efficacy and safety. At these stages, it is necessary to actually synthesize and test candidate
compounds, so the number of compounds
synthesized before a single new drug hits themarket can reach the tens of thousands, and is
one of the factors driving up the time taken andcost of new drug development.
01For this reason, “in silico drug discovery,” inwhich researchers calculate on a computer
how a compound binds to a target protein
and use the results to design a candidate
compound, is gaining popularity. “In silico
drug discovery is efficient because it reduces
the number of experiments, and it also has
the advantage of being able to investigate
the possibility of compounds that have notyet been synthesized,” Prof. Fukuzawa
explains.
There are several methods for calculating
the binding state of a protein-compoundcomplex. Prof. Fukuzawa and hercolleagues use the “fragment molecularorbital” (FMO) method developed by Prof.
Kazuo Kitaura of Osaka Prefecture University (currently Guest Professor of OsakaUniversity) in 1999 (Fig.1). “We want toaccurately understand the binding state ofthe protein-compound complex.” To do this,quantum chemical calculations must be
performed to reveal the electronic structure.
However, the computational cost is too highfor macromolecules such as proteins. TheFMO method was devised to overcome thisproblem.
In the FMO method, a macromolecule isd i v i d e d i n t o s m a l l f r a g m e n t s . Q u a n-(a) Fragmentation of proteinO

R₁HN

H₂NO

R₃O
HNNH
R₂O

R₅OH
N
H

R₄O

(b) Examples of structure-based drug design-O+O

H₃N

Hydrophobicgroup

Hydrophobic
pocketPositivecharge

ONH

Negativecharge

Hydrogen bondO
Tamiﬂu®(active form)

Active site of neuraminidase

Fig. 1

Fragment molecular orbital (FMO)
method and structure-based drug
design(a) In the FMO method, a macromolecule is divided into
small fragments. A protein is divided into amino acid units,
as circled. A compound that binds to a protein is often
treated as a single fragment, but can also be divided intofunctional moieties.
(b) Tamiflu® (generic name: oseltamivir), which is used totreat influenza, binds to the active site of neuraminidase,

vol.10 - Consortium for Industry-Academia-Government Collaboration and Fugaku Establish Advanced Platform for In-Silico Drug Discovery

an enzyme necessary for the replication of influenza
viruses, and suppresses its action. Tamiflu® is designed tobind to the active site through various interactions, such as
electrostatic interactions where positive and negative
charges attract and hydrogen bonding. This strategy iscalled “structure-based drug design.” When the FMO
method is applied to structure-based drug design, it ispossible to precisely know which fragments of the protein
the drug candidate compound interacts with and how
strong the interactions are. That allows researchers toconstruct a candidate compound that interacts morestrongly with the target protein at the appropriate parts.

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tum chemical calculation is done for eachfragment or fragment pair, and the calculation
results are used to reconstruct the electronic
structure of the whole protein. By taking theinfluence of surrounding fragments into
account when calculating each one, theelectronic structure can be calculated
efficiently and precisely.
More importantly, the FMO method provides
a quantitative understanding of various interactions between a protein and a compound.
“When interactions are well understood,
candidate compounds can be designed
rationally. For this reason, the FMO method

is increasingly being used in drug discovery
by pharmaceutical companies, although
it is rarely clearly disclosed,” says Prof.
Fukuzawa, explaining the significance ofusing the FMO method.

Steadily Accumulating DataUsing Large-Scale
Computational Resources“However, no matter how good the FMO
method is, it will not develop into a practical
drug discovery method if researchers
i n academia and pharmaceutical companies are working on their calculations inde-pendently,” Prof. Fukuzawa says. “Wethought it necessary to use large-scalecomputational resources throughindustry - academia - government
collaboration, and to develop and disseminate
databases and methodologies.”
At the end of 2014, she and her colleagues
called on industry, academia, and government researchers to launch a consortium toapply the FMO method project to the K computer. “Just around that time, the HPCI
network began to be used, so members fromall over Japan could access the K computerand perform calculations with the same quality in the same environment. I think it helped
us establish the consortium's foundation,”
Prof. Fukuzawa recalls.
The consortium focused on proteins such as
enzymes and receptors, which are likely
targets for drug discovery, and calculated thebinding sta te s of protein-compoundc o mplexes one after another. Then, the“FMO database (FMODB)” was constructed,
and in February 2019, the data calculated up
to that point was made publicly available foranyone to use. Since then, more and moredata has been added, and as of Oct. 14,2022, there are 15,653 public data points-- 17,625, including private data points.

vol.10 - Consortium for Industry-Academia-Government Collaboration and Fugaku Establish Advanced Platform for In-Silico Drug Discovery

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Considering Fluctuations toObtain More Realistic Data
FMODD not only accumulated data but also
developed new methods for drug discovery.
The background is, “in vivo, the structures ofproteins and compounds are always fluctuating, but the FMO calculation consider only asingle ‘static’ structure, so dynamic interactions that should be occurring in vivo are notknown.” To incorporate protein fluctuations,
Prof. Fukuzawa and her colleagues came up
with the idea of combining the FMO methodwith the molecular dynamics (MD) method,which simulates the movement of molecules(Fig.2). First, the team generates a “movie”
of the fluctuating protein-compound complex
by the MD method, and obtains “snapshots”
at a regular time interval. Then the FMO
calculations are performed for each structure, and the results are averaged. By thismethod, the team is trying to examine theinteractions taking into account molecularfluctuation.

Video snapshot ofMD method“We started this calculation on the K computer around 2017,” Prof. Fukuzawa said.
“Regarding the MD method, we received
the cooperation of the consortium (KBDD)
headed by Prof. Yasushi Okuno of Kyoto
University. The calculations didn't go very

vol.10 - Consortium for Industry-Academia-Government Collaboration and Fugaku Establish Advanced Platform for In-Silico Drug Discovery

FMO calculation

Take the average

FMO calculation
Dynamic interactions
revealed

FMO calculation

Fig. 2Analysis of dynamic interaction
by a combination of the molecular d y n a m i c s ( M D ) m e t h o dand FMO method
FMO calculation

FMO calculation

The MD method is used to track the motion ofatoms exerting forces on each other. First, thefluctuation of the complex is simulated using theMD method, and about 100 snapshots are taken
at a regular interval to perform FMO calculations. By averaging the results of the FMO
calculations, dynamic interactions incorporating protein fluctuations become clear. This is
expected to enable the design of drugs in amore realistic environment. Shown here aresnapshots of the complex of remdesivir, a drugfor treating COVID-19, viral RNA-dependent
RNA polymerase, and RNA, which was generated through the MD method. The structures of thecomplex are slightly different from one other.

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smoothly, partly because we were unfamiliar
with MD,” she added.
“After the K computer ended its operation, wewere able to use the HPCI computational
resources TSUBAME3.0 and Oakforest-PACS,
and finally completed the calculation.” Themethod they established with a struggle atthat time is now demonstrating its power inFugaku. They have elucidated in detail theaction of therapeutic drugs for COVID-19(see Fig. 2). They are also studying membrane proteins, which are important drug

discovery targets, and nucleic acid drugs*1,
which are expected to become new types ofdrugs, using this method.
“Now, members from all over the country areaccessing Fugaku and performing calculations just as they were in the project with theK computer. Fugaku’s computational poweris huge, and I feel that it’s about 100 times
more powerful than the K computer. FMO
calculations of 100 structures obtained by anMD simulation can be done in about 30hours using one rack of Fugaku, and then,we can immediately start scientific discussions to further improve the quality of thecalculations,” Prof. Fukuzawa says. As thenext step, she plans to spread the MD-FMO
combination method to young researchers
and apply it to various complexes.

I Want to Elucidate Life
Phenomena with Quantum
Chemical Calculations
Meanwhile, Prof. Fukuzawa and hercolleagues are also working on utilizing thehuge amount of data they have accumulated. One example is prediction of interaction
strength by machine learning. “There areseveral types of interactions between fragments, such as electrostatic interactions
where positive and negative charges attract
each other, and hydrogen bonds (see Fig. 1b).
By learning the data for each interaction
type, we can get information on the strengthsof the interactions depending on the distance
between fragments. By accumulating suchinformation, we want to eventually predict
the strength of the interaction without
performing FMO calculations,” she explains.
In this way, the FMODD has accumulated
FMO calculation data that forms the interaction information basis of in silico drugvol.10 - Consortium for Industry-Academia-Government Collaboration and Fugaku Establish Advanced Platform for In-Silico Drug Discovery

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discovery, and has developed new
methods and achieved excellent results.
However, this is not Prof. Fukuzawa’s goal.
She has a dream as an expert in quantum
chemical calculations. “Quantum chemical
calculations are first-principles calculations
that do not use assumptions or empiricalparameters. So as long as the calculations
are performed correctly, correct resultsc a n b e o b t a i n e d . I want to use thosequantum chemical calculations to understand
all life phenomena.”

About theResearcherwith people other than scientists, shelearned “it is not necessary to cook exactly
following a recipe, but enough to grasp theflow between the lines with my fivesenses.” She also became aware thatwhen doing research as well as playing
music we begin with the interpretation ofwhat our predecessors left behind, andTo realize this dream, Prof. Fukuzawaadvances her research step by step, by
setting goals to be achieved using the next
supercomputer after Fugaku and the one
after that, such as more accurate calculationof thermal fluctuations, FMO calculation ofenzyme reactions and metalloproteins, andRNA kinetics.

then deepen it. “As a result of seeking a postthat would allow me to do the research I
wanted, I am currently working in Osaka
without my family. I’m worried about my twochildren, a second-grade junior high and asixth-grade elementary school student whomProf. Fukuzawa believes it is important toI left behind in Tokyo, so I return home onlead a fulfilling life as a person, not to sacrifice

weekends as much as possible,” says Prof.

everything other than research. In fact, she

Fukuzawa, showing her mother’s face. Herloves cooking and has taken lessons from amultifaceted nature seems to attract people

Michelin-starred Japanese chef, and she also

and has helped bring together the people ininteracts with artists. Through communication

the consortium.

Associated Research Projects*1: Artificially produced DNA and RNA used as pharmaceuticals. Practical application is progressing, particularly for
drugs for the treatment of genetic diseases.

Construction of platform of FMO-based drug design using HPCI system(hp190133/hp200101/hp210130/hp220143)
Principal Investigator: Kaori Fukuzawa, Graduate School of Pharmaceutical Sciences, Osaka University(Current affiliation from April 2022, Hoshi University until March 2022)

vol.10 - Consortium for Industry-Academia-Government Collaboration and Fugaku Establish Advanced Platform for In-Silico Drug Discovery

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