HPCI magazine vol.1

Using Simulations
to Search
Existing Drugsfor Possible
COVID-19 Treatments
The COVID-19 pandemic has upended our way of life. Pharmaceutical companies andresearch institutes around the world are laboring away to develop drugs to fight it. Running
precision simulations with innovative High Performance Computing Infrastructure
centered on supercomputer Fugaku, researcher Yasushi Okuno was able to find promising
candidate drugs that are potential treatments for COVID-19 from among 2,128 existing
drugs already being used against other diseases.

Yasushi Okuno

Deputy Program Director, Medical Sciences Innovation Hub Program, RCSTI, RIKEN
Professor, Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University“Surprising Results”
from Precision Simulations
Vaccines and pharmaceutical treatments for
COVID-19 are being developed at a breakneck
pace in order to limit the disease's impact andhasten social and economic recovery. A lot of
this activity is focused on identifying drugs
that are potentially effective against this newcoronavirus from among existing drugs,
including antivirals. Since they've already been
proven safe in clinical trials, the time required
to develop treatments based on existing
drugs should be significantly shorter. Yet,despite all the research underway worldwide,from experiments at the cellular level to clinical
trials, effective therapeutics remain elusive.
Given this state of affairs, a lot of hope isriding on supercomputer-based simulations.
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“That's because we can examine theefficacies of many medications in muchless time than it takes for experimental
evaluations, and we can also understandhow these medications work,” explains
Yasushi Okuno. In April 2020, Okuno
began his search for therapeutic drugcandidates among existing drugs. Under
the “Fugaku Preliminary Use Projects”
program, he used the supercomputer
Fugaku, developed and maintained by
RIKEN and other institutes, and under the“High-Performance Computing Infrastructure
COVID-19 Research Access Projects”
program, he used the supercomputer
Cygnus at the University of Tsukuba.
The Fugaku research project searched for
drug candidates among 2,128 existing drugs.
It targeted the “Non-Structural Protein 5”(NSP5) main protease of the coronavirus,
which is critical to coronavirus replication
in infected cells. Okuno's research teamconstructed models of the main proteaseand existing drug molecules in Fugaku,
and ran molecular dynamics simulations
to investigate their behaviors. “Thesecomputations allowed us to faithfully
reproduce the molecular behaviors,
showing the conformational transition of
the protein’s active site pocket *1 between
the closed and open states, and thetransition of the drug from an unboundvol.1 - Using Simulations to Search Existing Drugs for Possible COVID-19 Treatments

state to a bound state at the active site
pocket or other sites on the molecularsurface (Fig.1).”
Then, sorting by how long the drug molecules being evaluated remain in the main
protease active pocket and other factors,
they were able to find dozens of promising
candidates from the existing drugs studied(Fig.2). “These drugs are expected tohave a strong binding affinity to the main
protease, and may be effective in fighting
the new coronavirus. Before we ran thesimulations, I was concerned that we might
not find enough promising drugs like these,or might even find too many. But we founda suitable number of candidates. And 12 ofthese are being used in clinical studies andclinical trials as new coronavirus treatments
in other countries. I was surprised how good
the results were,” said Okuno. The factthat 12 of the drug candidates discovered
through these simulations are already atthe clinical study or clinical trial stages for
COVID-19 speaks well to the reliability ofthe simulations.

Fig. 1

Molecular Dynamics
Simulated on Fugaku

This is a still from a movie based on the Fugaku simulations
investigating the molecular interactions between the mainprotease critical to the coronavirus replication (gray) and theexisting drug Niclosamide (pink). One of the drug molecules
has settled into an active site pocket (yellow), others havebound elsewhere, and still others have not bound to theprotein. These simulations were performed on 2,128 existingdrugs.

Fig. 2

Identifying Therapeutic Drug
Candidates

The simulations shown in Fig. 1 examined how long a drug
molecule stays in the active pocket of the protein (verticalaxis) and how long it stays anywhere along the surface of theprotein (horizontal axis). Each dot in Fig. 2 represents one of
the 2,128 existing drugs evaluated in this research. Drugs
undergoing clinical studies or clinical trials in other countries
are marked with a red “X”. The closer to the upper right a drug
is located, the better its expected ability to bind with theprotein. Those in the upper right quadrant were considered
suitable candidates for COVID-19 therapeutic drugs.
Niclosamide*1 Active site pocket: Some proteins have pocket-like indentations
on their surface where certain molecules bind to them to startworking. These indentations are called “active site pockets” or“active pockets”. A molecule that occupies the active pocket
instead of the usual molecule can prevent that protein fromfunctioning. Thus, discovering such a molecule is the first step indrug development.

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Among the 12 candidates, the drug
Niclosamide is expected to have aparticularly strong tendency to bind to theactive site pocket. Not yet approved inJapan, it is inexpensive and has been
confirmed safe overseas, where it is usedto treat parasitic infections. Given theseresults, clinical research is expected togain momentum.

Taking Full Advantage ofFugaku's Processing
Capabilities
Okuno and his team began runningsimulations on Fugaku at the end of April
2020. Despite having less than a month toprepare, everything went smoothly andthey had treatment candidates in hand by
the end of June. He says they pulled thisoff thanks to “previous experience on theK computer, and because Fugaku wasvery easy to use.”
Okuno and his team had previously run drug
discovery simulations on the K computer.
But for simulations at this level of detail,the K computer was only able to examine afew dozen existing drug types. “In the earlystages of drug discovery, it's important to‘choose from many’. Although a huge
number of candidates is evaluated at thisstage in the experimental approach, the K

vol.1 - Using Simulations to Search Existing Drugs for Possible COVID-19 Treatments

computer hadn't quite reached the point
where it's realistic to fully simulate thoseprocesses. But, Fugaku could run calculations
for more than 2,000 kinds of drugs, which ismuch more practicable.” Identifying viabledrug candidates from over 2,000 types ofexisting drugs through these precise
molecular dynamics simulations was a‘world's first’ achievement. It was of greatsignificance both as a computational
technique and from an academic perspective.
What's more, these simulations were doneusing only 5,500 nodes, which are a fractionof Fugaku's total processing power.
In addition to Fugaku's raw calculating
power, this achievement was also the resultof several endeavors and innovations in thecomputational approach. One of those isrunning each simulation with hundreds more
drug molecules present, so interactions withthe proteins become a more common
occurrence. This can reduce the run timeneeded for the simulations. Too many drug
molecules, on the other hand, could preventthe simulations from executing properly.
Thus, the number of drug molecules present

had to be carefully controlled. The teamalso confirmed that the length of time thevirtual drug molecules remained in theactive pockets was consistent with actuallaboratory test results. Because theFugaku simulations can produce suchmassive amounts of data, they also needed
to devise ways to analyze all that data.

Using the Power of Cygnus
to Simulate Another Protein
Using the University of Tsukuba's Cygnus
supercomputer, the team investigatedwhether the therapeutic drug candidates
selected from the Fugaku simulations
would also bind to NSP16, another protein
produced by the new coronavirus. NSP16
inhibitors, which bind to NSP16 to suppress
its function, haven't been studied as muchas the main protease inhibitors. Runningsimulations to explore the therapeuticpotential of existing drugs against NSP16
is an ambitious experiment.
The Cygnus computer is outfitted with anabundance of modern GPUs *2, which areoften used for artificial intelligence
research, and can quickly execute moleculardynamics simulations. “Since Cygnus was
already fully up and running, it didn't takeas long to pre-process the data for thesesimulations, and they ran reliably.”03

Cygnus ran simulations with higher
concentrations of the drug molecules toefficiently capture the molecular interactions(Fig.3), like those run on the Fugaku,
evaluating each drug molecule's ability tobind to the NSP16 active site pockets. The
results are still being analyzed, butdifferent drugs are expected to bind moreeasily to different proteins. It will beinteresting to see if the findings bear thatout.

*2 GPU: Short for “Graphics Processing Unit”, a special type ofcomputer chip optimized in design for image processing. For
certain types of calculations, GPUs can be much faster than theCPUs (Central Processing Unit) commonly used for doing math.

Fig. 3

About theResearcher
The approach that Yasushi Okuno took inthis battle against COVID-19 can be appliedin the search for drugs for other diseases. In
fact, with Fugaku operating at full capacity,
Okuno intends to search for drug candidates
for cancer and other challenging diseases.
His research work places the priority on thepatients. “I hope to use the power of Fugaku
to quickly identify a suitable drug for eachpatient’s particular cancer, and to search

existing drugs for those effective against
diseases that currently lack medications.” In
addition to his supercomputing work, he isalso involved in a consortium that brings
together pharmaceutical companies andresearchers from different fields to accelerate
drug discovery. Driven to provide the patients
he encounters with suitable medications assoon as possible, Okuno continues to leadin the field of computational drug discovery.

Molecular Dynamics
Simulated on Cygnus

Theinteractions
betweenthemainprotease-targeting candidate drug Niclosamide
and NSP16 were computed on Cygnus the same
way Niclosamide and main protease interactions
were computed on Fugaku.

Associated Research Projects• “Promotion of Innovative Drug Discovery Infrastructure for Acceleration of Precision Medicine” (hp200129)• “MD-based Screening of Drugs with Novel Action Mechanism Against COVID-19” (hp200155)

vol.1 - Using Simulations to Search Existing Drugs for Possible COVID-19 Treatments

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