Featuring Dr. Jay Ponder
The development of new therapeutic drugs is not simple, often requiring gathering extracts from exotic plants and animals and going through many rounds of trial-and-error experimentation, mixing hundreds of compounds together in hope that a handful will yield a useful new compound. Augmented with digital technology, biomedical researchers hope to synthesize new compounds from scratch with little more than computer-generated models and contribute into the therapeutic drug industry, a major niche in healthcare technology with an estimated global market of $252 billion by 2017 and an annual growth rate of 7%.
Synthetic drugs are not a recent innovation. The first synthetic drugs arose mostly as a consequence of altering existing active compounds (e.g. morphine from opium) in the hope of increasing its efficacy or to discover new uses. The idea to create synthetic drugs from the ground up mostly originated with the exponential increases in computational power over the past few decades. These technological developments pointed researchers toward a tantalizing possibility: would it be possible to design drugs by computer, creating molecules that bind efficiently to their target? Starting in the 1990s, this idea took off at universities and drug companies everywhere, but unfortunately success has been woefully limited. Despite having been designed according to the most accurate computer models available at the time, the newly synthesized compounds often failed to bind to their cellular and molecular targets. Some researchers suggested that computers were not yet powerful enough to accurately simulate all the conditions and chemical interactions that exist at the atomic scale. Dr. Jay Ponder of the Department of Chemistry (a post-doctoral researcher at the time) argued the contrary. He held that computers were not the culprit, but rather the computer models which he claimed were not accurate enough. Over the past two decades, Dr. Ponder and his lab have been working to improve these models with the ultimate hope that computer-aided design of new, synthetic drugs and compounds will become commercially feasible in the near-future.
Calculating the binding strength between molecules is no easy task. Although it is easy to conceptualize drug binding as two puzzle pieces or a lock and a key fitting snugly together without much give, in reality the structure of proteins are highly dynamic. This means that drugs end up binding to the protein in many different ways, with varying degrees of efficacy. In essence to calculate the correct binding efficacy at a point, one needs to perform thousands, if not millions, of different individual energy calculations. For this reason, quantum mechanical models of binding, while much more accurate than any current model, take too much time and computing power to implement. Instead, scientists must rely on models based on the classical principles of electrical attraction. Despite being 100,000 times faster to calculate than quantum models, classical models are just not precise enough to be used calculate binding energy accurately enough for use in the synthesis of effective compounds.
Dr. Ponder and his lab have made several improvements to earlier models, including improving assumptions on charge distribution and fluidity. In doing this, the lab was assisted by a surprising source of help – graphics processing units (GPUs), which gaming consoles and computers use extensively to generate animations and smooth, high-fidelity renders of an in-game world. It turns out that the calculations necessary to generate a realistic graphical field-of-view in a video game are similar to those used by the Ponder lab to simulate molecular binding. This, combined with the unique and massively parallel nature of GPUs, means that Dr. Ponder lab’s simulation runs faster on a single, average-quality GPU than a 12-core, high-end Mac Pro.
The lab hopes to test its ever-improving model by entering a worldwide competition in which various labs attempt to accurately calculate binding energy values of several molecules with a specific target molecule, called a “host.”. In their past outings in the competition, the Ponder lab has stood out as one of the top contenders, but Dr. Ponder recognizes that there is still much room for improvement. Even in their best showings, the lab was only able to calculate energies accurate to within acceptable bounds for about half of the molecules. For the upcoming competition, Dr. Ponder and his lab aim to accurately predict binding energies for a much higher percentage of the molecules.
In addition to the competition, the lab also hopes to use its model in the fight against HIV. Currently, HIV/AIDS patients take a cocktail of anti-retroviral drugs in order to treat their disease. However, patients must consistently take these drugs for the rest of their lives in order to keep the virus and the disease dormant. If they stop the regimen at any time, the virus will inevitably return in full force and progress into the invariably terminal AIDS. Researchers hypothesize that this happens because a portion of the virus ‘hides’ in an area or enters dormancy, making them immune to anti-retroviral drugs.
In their research, a group at the Washington University School of Medicine has identified a protein, a member of the histone deacetylase family, that may play a key role in the virus’ ability to ‘hide’. The group believes inhibiting this protein would reactivate or release the previously unreachable virus, which can now be eliminated using existing treatments. If this procedure is effective and successful, it will be the first ever cure for HIV and a major breakthrough for humanity, now able to cure what was once incurable, terminal, and feared around the world. With their improved models, the Ponder lab hopes to help develop a drug that could inhibit the protein while leaving other types of histone deacetylases, which are very similar in structure and essential for life, completely unscathed.
The unprecedented boom in computational power and technological progress since the turn of the millennium has granted us new opportunities to study life and fight disease. New techniques now allow researchers to gather data and perform calculations at such dizzying rates that we often have more data than we know what to do with. Dr. Ponder and his lab demonstrate the important idea that a sound model necessarily begins with a solid understanding of foundational principles, no matter how fast computers get.
For more information about Dr. Ponder :
E-mail : firstname.lastname@example.org
Website : http://www.chemistry.wustl.edu/faculty/ponder
Phone : (314) 935-4275
Lab Address :
Washington University in St. Louis
1 Brookings Dr
St. Louis, MO 63130
Edited by Jeff Bai, Brett Gao