It doesn’t matter if you ask a pharmaceutical
company executive, an overbooked doctor or a patient seeking treatment,
when it comes to discovering new drugs to treat illness, everyone
agrees. We need better drugs faster.
Robert Pearlman’s drug discovery software is used by
pharmaceutical companies across the world.
The drug discovery process, however,
is notoriously time-consuming and expensive, requiring scientists
to synthesize and test tens to
hundreds of thousands—sometimes millions—of compounds
in the hopes of finding one that will interact with the body in
the desired way. Fortunately, advances in computer-assisted drug
(CADD) are improving the way scientists do their work. Dr. Robert
Pearlman, Coulter R. Sublett Regents Chair in Pharmacy at The University
of Texas at Austin, is a pioneer in the field.
CADD software is used at almost every pharmaceutical company on
the planet. One of his first programs, Concord™,
has been distributed commercially since 1986, and new products
continue to issue from his newly established software company Optive
Each software product serves a different purpose, but they are
all designed to help scientists make better decisions about which
to synthesize and test.
“Understanding how molecules interact with one another is
the key to drug discovery,” Pearlman explains. “Drug
discovery boils down to finding a small molecule—the drug—that
interacts in an optimal fashion with a large biomolecular ‘target’
or ‘receptor,’ often
a protein. What makes drug discovery so difficult is that there
are a near-infinite number of small molecules that could be synthesized
and tested as potential ligands for each target.”
assist scientists by enabling computer-based predictions of how
well a small molecule might interact with a given biomolecular
target even before that small molecule has been synthesized. By
synthesizing and testing only those compounds that are predicted
to be active,
scientists can greatly reduce the number of small molecules they
actually synthesize and test.
CADD predictions greatly improve
the odds for drug discovery. This makes the drug development process
more effective and predictable
and ultimately means savings of both time and money.
buying is a useful analogy when considering drug discovery.
If your friend were choosing a new car, how would you help
her choose among all possible options? You could begin by finding
out what attributes were most important to her in a car, such
as body style and color.
begins with biology. Once doctors identify a physiological condition
they would like to modify, biologists work to determine
the molecular biochemistry that controls the condition. They may
find an enzyme they want to inhibit, as is the case with recent
arthritis research and the new class of arthritis drugs called
Cox II inhibitors.
Or when the objective is to cure a particular type of infection,
biologists must discover a way to disrupt some process within the
bacteria they want to kill without simultaneously killing the cells
of our own bodies.
Once biologists discover the biomolecular “target” which
controls the biochemical process they want to modify, drug discovery
shifts from biology to chemistry. This isn’t surprising,
once you recognize that the human body is an elaborate system of
checks and balances.
“Chemical reactions drive our physiological processes, our mental
processes, our emotional processes,” says Pearlman. “The
body is an amazing balance of chemical reactions, and it has all
sorts of mechanisms for controlling the chemical equilibria which
constitute a normal physiological or emotional state.
“Why do you get hungry? Because some chemical equilibrium
has gotten out of balance. And you restore that balance—often
just a matter of blood sugar—by ingesting some additional
chemicals which we call food. Depression is due to a neurochemical
You treat it by administering drugs that affect the concentrations
of those neurochemicals.”
Discovering a new drug requires
taking the biological target, or receptor, that the biologists
identified and discovering a compound
that will fit that target and thus alter the body’s chemical
The needle in a haystack idiom is appropriate here. The number
of drug-sized organic compounds that can be synthesized is as close
as it gets, far, far beyond a trillion. Before computer-based methods
were developed, scientists basically proceeded by trial and error.
On average, a pharmaceutical company would synthesize 8,000 to
12,000 compounds in a single discovery effort. This could take
help your friend choose what cars to test drive, you might
begin by narrowing the field to only cars close to the ones
your friend already likes. For example, she might like small
sedans in gray, so she should begin testing small sedans in
gray. Her perfect car is probably among them.
In the meantime, pharmaceutical companies were amassing samples
of compounds they had synthesized and tested. In the mid 1980s,
pharmaceutical company might have had a database of half a million
compounds, represented as the familiar two-dimensional chemical
structures we see in chemistry textbooks. This was useful for inventory
data tracking, but not necessarily for future drug discovery efforts.
The world, as we know, is rendered in three dimensions.
“People dreamed of performing calculations on three-dimensional
structures to identify those which would fit into a particular receptor,” says
Pearlman. “But as late as the mid-80s, it would take anywhere
from several minutes to half an hour to generate the 3D structure
of just one drug-sized molecule. Faced with the daunting task of
converting databases of hundreds of thousands of compounds, pharmaceutical
companies never seriously considered large-scale conversion to
Pearlman’s first commercially distributed CADD
changed all that. It was the first program in the world to rapidly
and automatically convert two-dimensional chemical representations
into three-dimensional chemical structures. The current version
of the program can convert half a million drug-sized compounds
3D structures in less than an hour. Nearly two decades after its
creation, it remains the industry-standard tool for this critically
Concord™ enabled exciting new strategies
for computer-assisted drug discovery, the first of which was 3D-searching.
3D structures of compounds in a database, 3D-searching software
enables scientists to quickly search through that database looking
with the right size and shape for optimal interaction with the
3D structure of a particular target. Purchasing and testing only
that are most likely to interact with the target provides obvious
savings of both dollars and time.
Pearlman and his team soon started
thinking about how they could use the computer to generate structures
of compounds that had not
yet been synthesized. A number of programs followed, including
a large, multi-purpose package called DiverseSolutions™.
to a consumer choosing a car, scientists can find the next
drug most efficiently by only testing compounds with a good
chance of being viable. Compounds can be plotted on
a plane using structural descriptors on each axis.
DiverseSolutions™ software helps scientists choose which compounds to synthesize
from a subset of possible compounds by assigning
descriptors to specific elements of chemical structures. In
many cases, scientists
find a number of compounds that bind to a target but don’t
bind well enough to actually become drugs. These compounds
are termed “leads.” DiverseSolutions™ enables scientists to use structural descriptors for these
leads and plot them in a descriptor plane. The scientists can
see where those leads are clustered in the descriptor plane,
a subset of possible molecules to synthesize future compounds.
Pharmaceutical companies responded to its introduction with
great excitement and
have remained enthusiastic ever since.
From the beginning, Pearlman’s
goal in creating the software has been the same as that of
the university: to make sure it is used.
“First and foremost, we want to see the results of the university’s
research being used by the people it can really benefit,” says
Neil Iscoe, who directs the university’s Office of Technology
overall goal is the distribution of technology, and the vehicle
for that is commercialization.”
Since the mid-80s, Pearlman’s
software has been distributed on behalf of the university by
the St. Louis company Tripos Inc.
Tripos pays royalties back to the university and to Pearlman’s
Over time, the lab grew and started morphing into a software
company of its own.
“Once you’ve got commercial software of commercial interest
and you’ve got a commercial user base, you’ve got
commercial expectations regarding quality and user interface
Reluctant to put the pressure of such commercial expectations
and round-the-clock support on graduate students and post-doctoral
students, Pearlman’s lab group evolved and is now staffed
entirely by full-time employees. Its ties with industry collaborators
scenarios where industry partners had unlimited access to the
software in exchange for critical feedback and financial support.
25 years with the university, Pearlman started thinking
about how to keep the software updated, distributed and developed
after he eventually retired.
The obvious solution was to spin
out a software company that could be self-sustaining outside
of the university. Optive
introduced in July 2003.
compounds are plotted on a plane, scientists can test only
those compounds similar to known leads, or compounds close
to viable, as highlighted in red. This
saves time and expense and makes use of existing data.
Optive’s success is good news
for everyone involved. The five programs originally licensed
to Tripos are now licensed to Optive
but continue to be distributed by Tripos and to generate royalties
to the university. The investment dollars paid by pharmaceutical
industry into research at the university are returned many
times over by successful commercialization.
Optive will at the
same time develop new software and maintain its relationships with
industry partners. Pharmaceutical companies
get the software that makes their job easier. Even the Austin
“Most of the time drug development goes to the east or the
west coast,” says
Iscoe. “Optive is an example of a company that sells
technology both nationally and internationally and does it
from Austin. This
can really help our community.”
It’s rare to find
a situation in which everyone wins, but this is one. And
perhaps the ultimate winner is the patient, the consumer,
the individual hoping for relief from a malady or even a
“The primary benefit of CADD is that you can actually develop better
drugs,” says Pearlman. “CADD methodology enables
scientists to devote more time to search for even better
drug candidates. Rather
than rushing to market with the first promising candidate,
companies are now saying, ‘You know, if this compound
works so well, maybe that compound would work even better.’ This
leads to better drugs with fewer side effects, and it may
mean drugs that
you can dose once a day instead of four times a day.”
“Optive Research is not about software distribution. It’s about
scientific research into improved CADD methods. We are excited
about the impact our software has had and will continue to have on the
drug discovery process, and we are gratified by the notion
that these benefits to society are rooted in the ‘technology incubator’ which
is The University of Texas at Austin.”
Graphics generated by DiverseSolutions™ software package