The Resistance Part II:
Fighting HIV Resistance At Home and in the Laboratory
By Jason Socrates
Bardi
"All
must work together or the Body will go to pieces."
—Aesop,
The Belly and The Members, circa 600 B.C.
It was early summer, lunchtime at the Scripps Research Institute
(TSRI), and the monthly meeting of scientists who are funded
by a program project grant from the National Instuitutes of
Health called Drug Design Cycle Targeting HIV-Protease
Drug Resistance was about to begin.
There were over a dozen people in the room from all parts
of the TSRI campus and beyond—organic chemists, molecular
biologists, computer scientists, protein chemists, and cell
biologists.
TSRI Associate Professor Bruce Torbett, one of the investigators
in the room, delighted at being able to have biologists at
the same table with modelers, crystallographers, and chemists.
"It forces us to think differently," he says.
At 5 minutes after the hour, TSRI Professor John Elder rushed
in and grabbed an open seat across from the other biologists.
"I think I'll sit on the computational side today," he said.
The meeting lasts over an hour. One person describes the
latest "phage display" experiments. Another discusses cloning
a mutant only to find it to be a wild type. There were reports
on data mining; shuttle and expression vectors; the chemistry
and synthesis of small molecule HIV inhibitors; selecting
D-amino acid peptides as inhibitors; and an upcoming conference
in Washington, D.C.
Also during the meeting, Molecular Biology Professor Arthur
Olson discusses the status of the FightAIDS@Home project.
FightAIDS@Home is a distributed computer project that is integral
to the research consortium that Olson leads.
"Scripps is a highly collaborative place," says Olson. "That's
why I've stayed here for 20 years."
Computing for a Cause
Twenty years ago, AIDS was still a relatively unknown disease.
TSRI was at that time called the Research Institute of the
Scripps Clinic, and there was no Department of Chemistry.
The institute had no computational research program at all,
Olson adds. There were not even any computers, outside of
the few in administrative offices and those that were hooked
up to one scientific instrument or another.
Over the years, computers and chemists have both arrived
at TSRI, and now Olson directs a program project grant that
has brought these two groups together with biologists to take
a multidisciplinary approach to addressing the problem of
HIV protease drug resistance.
"Nobody knows how to do everything, so you really need these
kinds of collaborations," says Olson.
See:
The Resistance
Part I: From Petri Dishes to Population Dynamics
Olson's FightAIDS@Home project is one of a growing number
of "distributed computing" projects that seek to make use
of the vast untapped computational resource that exists in
the form of personal home computers. In fact, Olson's was
the first such project involving biomedical research.
"The idea is that with a large enough computing source,
you can look at all the mutations that may arise during the
evolution of drug resistance," says Olson.
The procedure is simple. Any person with a computer and
an internet connection can sign up by logging onto http://fightaidsathome.scripps.edu/
and downloading the program—the "client" in computer
software parlance. Once the client is installed on the individual's
computer, it is designed to conduct some set of calculations
that may be one tiny part of a larger computation.
The computations basically take a known or candidate drug
and simulate docking it into the HIV protease enzyme—or
one of many mutant forms of this enzyme.
The client, designed by the company Entropia, Inc.ª, runs
so that the computations take place without disturbing normal
computer use. The program runs when the machine is not in
use, and runs until the computation is finished—usually
after several dedicated hours of computing time.
The process is further made unobtrusive by what is known
as pull scheduling. In this system, when the client finishes
with one computation, the program waits until the user connects
to the internet. Then the program wakes up, sends the results
to the server at TSRI, and requests another job. The server
then sends another computation.
"It's as simple as that," says Olson.
AutoDock and the Source Code
FightAIDS@Home was originally managed by Entropia, but it
is now a nonprofit venture managed by TSRI. TSRI investigators
are now in direct communication with the users.
In May, investigators at TSRI sent out an email to some
30,000 previous FightAIDS@Home users. Each email went to an
individual who has expressed an interest in donating some
of his/her computer time for the cause, and invited him/her
to upload the new client application and continue under TSRI's
management.
At a meeting a few days later, a research associate describes
how in the first week of the sign-up they had received a flood
of emails from countries in Europe, Japan, and even Turkey.
In the first 48 hours of TSRI-managed operations, they had
received 1,000 emails. And by the end of May, there were about
2,500 people who had uploaded the new client.
"We're thrilled about this," says Olson
The real advantage of local management of the project, says
Olson, is that the investigators have access to the source
code. This means that Olson and the other investigators can
build improvements directly into their docking software.
The docking software they use is called AutoDock, and it
was designed by Olson's group in the 1980s. This software
basically takes a computer representations of a protein like
the HIV protease and assays how well it binds to a computer
representation of a flexible molecule like any protease inhibitor.
Originally the TSRI investigators had to supply Entropia
with the source code for AutoDock, which locked them into
using the one version of AutoDock they had when the project
started.
They can now use different variations of the AutoDock code
for different computations, and they can also upgrade the
FightAIDS@Home client as the AutoDock software improves.
In fact, improvements to the AutoDock software have been
made nearly every year since the program first came out in
1989. Version 4 of the software—the next major release—is
currently waiting in the wings for beta-testing.
"It has a lot of enhanced functionality," says Olson.
All Mutants Great and Small
Now that the project has moved to TSRI, Olson and his colleagues
have done a lot of thinking about how best to schedule and
run calculations. This has resulted in redundant jobs to multiple
clients and statistical analysis to make sure that the data
returned is not corrupted—if someone were to unplug a
computer during the middle of a calculation, for instance.
"We don't have to worry about losing a job or two," says
Olson.
They have also done a lot of thinking about the sort of
jobs they want to send to people who are donating their computer
time.
Originally, the questions were rather simple. Investigators
took the known structures of the wild type and mutant proteases
and docked clinically approved drugs to them to see if they
could detect resistance.
"In fact, we could detect resistance," says Olson.
Now they are asking somewhat more complicated questions,
such as whether they can predict the resistance in a mutant
protease without a known structure. Not all the structures
of the mutants that arise clinically in patients who take
HIV drugs have been solved.
Investigators can expand the types of calculations that
are used, changing the way in which the computer models the
proteins and the inhibitors. They can increase the grid size—something
akin to resolution—and make more accurate computations.
They can make parts of the modeled molecules more or less
flexible as they see fit as flexibility directly affects the
complexity of a calculation.
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