2009-ASCB-Press-Book - page 7

T h e A m e r i c a n s o c i e t y f o r C e l l B i o l o g y
5
News from
The American Society
for Cell Biology
49th Annual Meeting
San Diego, CA
December 5–9, 2009
Fragments from old drugs match
new virus threats
EMBARGOED
FOR RELEASE
10:00 am, U.S. Pacific Time
Sunday, December 6, 2009
Contact
Daniel B. Dadon
University of California,
San Diego
Department of Chemistry
and Biochemistry
MC 0332
9500 Gilman Dr.
La Jolla, CA 92093-0332
(818) 665-6448
Author presents
Sunday, December 6, 2009
12:30–2:00 pm
Poster Session 1:
New and Emerging Technologies
for Cell Biology I
Program 771
Board B718
Exhibit Halls D–H
The Rational Design of
Predicted Neuraminidase
Inhibitors for the Treatment of
Swine and Avian Influenza
D.B. Dadon, J. Durrant,
J. McCammon
Department of Chemistry and
Biochemistry
University of California, San
Diego, La Jolla, CA
J. McCammon
Howard Hughes Medical
Institute, La Jolla, CA
A new “rational drug design”
project identifies fragments
of older FDA-approved
compounds that might
counter drug resistance
in emerging avian and
swine influenzas
A
massive, data-crunching
computer search program
that matches fragments
of potential drug molecules to
prospective pandemic viruses has
identified several U.S. Food and
Drug Administration–approved
drugs that could be the basis for
new medicines if emerging viruses
such as the so-called avian or
swine flu strains develop resis-
tance to current antiviral agents.
This identification of new
targets for old drugs completely by
computer is a perfect demonstra-
tion of “rational drug design.” Like
fitting a key to a lock, computer
search algorithms take the known shapes
of drugs and match them, one after an-
other, to the known shapes of disease-re-
lated proteins. That’s the theory. In prac-
tice, rational drug design requires jiggling
a ring holding hundreds of thousands
of keys while wrestling with a lock that
doesn’t stay still. Yet few research groups
have had greater success at rational drug
design aimed at viruses than Andrew
McCammon’s Howard Hughes Medical
Institute–funded computational group at
the University of California, San Diego.
Among other triumphs, the McCammon
lab honed the search algorithms that
helped identify the second generation of
anti-HIV drugs.
Now with worldwide concerns about
rapidly emerging influenza strains, the
McCammon lab is searching for new
antiviral agents to counter potential
pandemics. Influenza viruses have two
major sets of glycoproteins on their outer
surface. The researchers are targeting the
second set, the neuraminidase proteins.
Neuraminidase is the N in H5N1, a.k.a.
avian flu, and in H1N1/09, the former
“swine” flu.
The problem with targeting any pro-
tein is that biomolecules don’t sit still. To
hit a moving target, you need to consider
how the protein can slightly shift posi-
tion or shape, explains Daniel Dadon, a
member of the McCammon lab. “A single
picture of a sleeping cheetah, for example,
might suggest that the animal is always
lethargic,” he says. “In reality, a cheetah
is dynamic, spending much of its time
sitting, running, climbing, attacking, and
walking.” To capture cheetahs, or influ-
enza viruses, you have to understand their
motions over time.
A search algorithm that accounts
for the flexibility of the molecular dock-
ing sites is at the core of the McCammon
group’s “relaxed complex scheme” (RCS).
After studying neuraminidase flexibility,
the researchers created a virtual library
of druglike molecules by mixing and
matching parts of various FDA-approved
drugs. They used the information gained
from the RCS simulations to test which
molecules from this new library would
best inhibit neuraminidase function. Six
compounds were predicted to inhibit
neuraminidase better than FDA-approved
drugs such as oseltamivir, peramivir, and
zanamivir. The computer data also sug-
gest that some of these compounds may
target other parts of the neuraminidase
protein—an ability that could prove use-
ful if the new viruses develop resistance to
current therapies.
The “N1” in H1N1, the neuraminidase (N1) monomer: The “mo-
lecular dynamics” simulation was clustered into 27 nonredundant
conformational structures and aligned to show the flexible regions
of the N1 protein. Great flexibility is evident in the loop regions.
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