Intellectual Merit – Research outcomes and significance: Enzymes are proteins that serve as nature’s catalysts. They are vitally important in all living organisms and are also used in a variety of industrial processes. This project was focused on improving our understanding of how enzymes work, using computational predictions and experimental tests. Enzymes are made up of a string of amino acids that fold into a globular structure. Their catalytic activity occurs in a small cavity on the globule. For each enzyme, a specific set of amino acids in or near the cavity are involved in the catalytic activity. We have developed highly accurate computational methods to predict which amino acids of an enzyme are important to activity. In this project, our computational methods predicted that, for many enzymes, amino acids in the second and third layers outside the cavity also are important for catalysis. Experiments were performed to test these predictions. Nitrile hydratase, an enzyme that is used in the industrial production of acrylamide, was predicted to have a double-layer catalytic site. Of the five distal amino acids predicted, four proved to be important for catalysis. Three distal amino acids that were not predicted were also tested; all three were confirmed not to contribute directly to catalysis. Our calculations predicted that the enzyme phosphoglucose isomerase (PGI) also has a spatially extended catalytic site. On the other hand, the enzyme ketosteroid isomerase (KSI), which catalyzes a reaction similar to that of PGI, was predicted to have a very compact, single-layer catalytic site. Experiments confirmed that indeed, distant amino acids, those predicted by our computational methods, play very important roles in the catalytic process of PGI. KSI was confirmed to have a single-layer active site with no significant participation by distant amino acids, as predicted. Thus we have shown that it is possible to predict, by computation, which distant amino acids are important for catalysis. Broader impacts of research results: The demonstration of predictability of participation of distal amino acids in catalysis is very valuable in efforts to design artificial enzymes that catalyze specific reactions that are commercially important. Enzyme-catalyzed chemical processes produce far fewer unwanted by-products, consume less energy, and generate less waste than conventional industrial chemical processes. As demand for “green” industrial processes increases, these research findings will prove to be important to the development of such processes and, in turn, important to our future economic growth. Broader impacts – Education and training: A new experiment based on this project has been developed and implemented for the Molecular Modeling course and another experiment has been developed and implemented for the Chemical Biology laboratory course at Northeastern University. Dozens of students in the Chemical Biology course and in the Molecular Modeling course have participated and learned from this NSF sponsored project. Six doctoral students and five undergraduate students have worked directly on this project and learned valuable laboratory and computational skills. In addition, a total of seven Master’s students and one doctoral student in the Biology department have performed one-semester projects in our research group, learning new skills in computational biology. In the course of this project, four students have graduated with the Ph.D. degree. Two are currently in postdoctoral research positions and two are in industrial positions. The training of highly skilled and knowledgeable scientists in these areas of research is critically important to the high-tech regional economy and to the U.S. national economy.

Last Modified: 01/08/2013
Modified by: Mary...

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