Monoclonal antibodies are increasingly popular therapies for diseases such as cancer, arthritis and multiple sclerosis. They are also very expensive, due in part to the requirement that they are given intravenously at high concentrations to achieve their therapeutic benefits. Attempts to redesign the therapies to allow for easier and cheaper subcutaneous delivery have been stymied by the tendency of the antibodies to clump together, producing an unusably viscous solution. While experimental studies have identified some of the reasons for this viscosity, fully understanding these protein-protein interactions requires zooming in to a scale that's currently beyond the ability of experiments.
Enter computational modeling, which can help scientists determine why some antibodies aggregate and others don't, pointing the way to designing better treatments. While a postdoctoral scholar with the Center for Multiscale Theory and Simulation, Anuj Chaudhri worked with CMTS director Gregory Voth and scientists Dan Zarraga, Steve Shire and Tom Patapoff from the Late & Early Stage Pharmaceutical Development teams at Genentech to construct a model of what exactly happens when you put a lot of these antibodies into close proximity. The work was published by The Journal of Physical Chemistry.