Project Summary for The Development and Experimental Verification of Computational
Methods to Design Therapeutic Proteins
Therapeutic proteins are an important tool in modern medicine, and their use in treating serious illnesses
such as cancer and autoimmune diseases continues to grow annually. Antibodies are one of the most important
classes of therapeutic proteins. They occur naturally in the immune system, where they bind strongly and
specifically to foreign molecules, acting as flags to the rest of the immune system by indicating the presence of
materials that should be eliminated from the body. The use of antibodies by medical professionals allows them
to guide patients’ immune responses to improve their health outcomes.
Although antibodies offer tremendous benefits, they are not without their limitations. They are large, delicate
proteins that are relatively expensive to produce, difficult to formulate at high concentrations, and sensitive to
the conditions at which they are stored. Additionally, the experimental methods that are currently used to
develop new antibodies are time consuming and while they can control the molecule the antibodies bind (i.e.
antigens), it is extremely difficult to target specific regions (i.e. epitopes) of those molecules. Finally, there are
many experimental and clinical applications where antibodies are currently used despite not being the most
appropriate protein for the purpose because there are not convenient alternatives available.
Advances in computational protein design over the last decade are poised to revolutionize the development
of antibodies and other therapeutic proteins. Recently, the Pantazes Lab at Auburn University has created
software capable of designing antibodies or any of 50+ other binding proteins in as little as a few minutes on a
personal computer to bind any target epitope of any desired antigen. Preliminary experimental results of this
method appear very promising. Over the next five years, the lab plans on building on this foundation to create a
therapeutic protein development workflow with unprecedented flexibility. Proposed research includes: 1)
Improving the computational design and selection criteria to enhance experimental viability, thereby providing
end users confidence that what they design will function as predicted; 2) Expanding the design capabilities to
include specific interactions, permitting the design of pH-sensitive binding proteins and enzymes; 3) Extending
the design principles from binding proteins to peptides, enabling the design of any amino acid based binding
moiety; and 4) Designing a synthetic binding protein with all of the benefits of antibodies and none of the
drawbacks. Each project will involve both computational development as well as experimental validation.
Altogether, this research will allow for the rapid design of an optimized binding protein for therapeutic
applications. Whether it is developing personalized cancer treatments, fighting an antibiotic-resistant bacteria,
or countering an emerging pandemic, doctors will be able to develop novel treatments in a timely manner.