Chemistry professor Kathryn Muratore has received a $44,993 grant from the Research Corporation for Science Advancement for her project, entitled "Knowledge-based Redesign of Enzymes to Identify Substrate Specificity Determinants." In addition to helping pay for supplies, the grant will cover research stipends for Muratore and her student assistants, and for some equipment.
The project involves analyzing genetic codes of enzymes—proteins that catalyze cell reactions. DNA consists of a long pair sequence of 4 chemical bases: adenine (A), guanine (G), thymine (T), and cytosine (C). Combinations of these base pairs code for specific enzymes. Muratore is identifying patterns in these enzyme-producing sequences that will help Muratore identify how enzymes work. According to Muratore, identifying the general genetic pattern of an enzyme will ultimately allow scientists to predict what a newly-discovered enzyme will do.
These predictions can be relevant in medicine. For example, protein kinases are a type of enzyme. A particular type of protein kinase is involved in 90% of a kind of leukemia.
"So if we knew more about how that enzyme worked, or didn't work, in cancer patients, that information would be really helpful," says Muratore.
Currently, the most essential component of the project is creating a software program that will identify patterns in strings of genetic code. Each organism's DNA can have millions of base pairs, making it difficult for a single scientist to identify patterns. The program will identify enzyme codes as they differ across organisms, even if there are multiple changes in the base pairs of two different organisms for a single enzyme – a process known as co-variation.
Muratore has created a rough version of the software, and her student assistants, Sam Sheftel (BS/MS biochemistry '10) and Shannon Christie (BS environmental science, '11) are currently upgrading it. Muratore ultimately aims to make a more user-friendly version of the program available to other scientists on a public research server.
Sheftel is also creating software that will visually show how the co-variation patterns occur by mapping them onto a virtual 3-dimensional model.
"Just like there is a genomic database with all of the gene sequences, there is a database of protein 3D structures," says Muratore. "This is the spatial arrangement of all the atoms in the protein. If we want to know whether two atoms in a protein are near each other and might interact, we can know this by looking at the 3D model."