Ensemble-function Studies of Enzyme Mechanism

Stanford University, Stanford CA

Investigators

Abstract

Enzymes are the catalysts underlying all of biology, allowing reactions—that otherwise would take decades, millennia or longer—to occur in less than a second and providing catalysis for just the right reactions needed for biology. Given their remarkable capabilities and their centrality to biology, enzymes have been an intense subject of research for nearly a century. Resulting from this research are many drugs and enzymes engineered to have practical value. Nevertheless, understanding how enzymes achieve their extraordinary abilities has remained elusive. Such an understanding should be quantitative, as quantitative models are more complete, more readily tested, and more powerfully used in practical applications. This proposal integrates a well-recognized concept in physics into the study of enzymes, conformational ensembles. In particular, there has been enormous progress at obtaining and now predicting “the” structure of proteins. Yet, proteins do not exist as a single structure but rather a complex “ensemble” of conformational states. These multiple states are often involved in function, such as motor proteins that allow our heart and other muscles to work, and, even when not directly involved, ensemble properties are the missing linking in relating molecules to free energies, the energy values that determine the probabilities of molecular events such as binding and catalysis. This proposal links enzyme conformational properties to the ability of the enzyme to catalyze (or speed) reactions, and, in the course of these analysis, the molecular features that are responsible for catalysis will be identified. Most broadly, this information will yield fundamental understanding and provide hints and guidelines that may aid in the design of new enzymes for practical use. This project will train graduate and undergraduate students. The overarching goal of this proposal is to develop quantitative models for enzyme catalysis that are rooted in fundamental physics and chemistry. Ensemble–function analysis provides the paradigm needed to achieve this goal. Critically, ensembles, rather than static structures, are needed to obtain free energies and thus reaction probabilities, based on the laws of statistical mechanics. Ensembles are also needed to evaluate whether conformational states and interactions observed in static structures are representative of the population of molecules. This research will leverage existing structural data and recent advances in obtaining crystallographic data at physiological temperatures to obtain ensemble information using pseudo- ensembles and multi-temperature (MT) X-ray crystallography. EnsemblePDB will be developed to rapidly build pseudo-ensembles from the vast trove of existing Protein Data Bank structures and to assess two fundamental aspects of catalysis: (1) What changes occur across the reaction states? –thereby providing a minimal model for the enzymatic reaction path; and (2) What are the energetic consequences of these changes? –thereby providing quantitative models for the enzyme features responsible for catalysis. To account for catalytic contributions from enzyme features, the enzyme reaction is compared to the corresponding solution reaction, using solution reaction paths obtained from quantum mechanical calculations and the energetics of enzyme and solution interactions obtained from energy functions derived from crystallographic data and from molecular dynamics. This proposal will first apply this approach to serine proteases, the near-universal textbook example for enzyme catalysis. Deliverables of the proposal include: (1) A quantitative, atomic-level model of serine protease catalysis; (2) Determination of catalytic features shared among evolutionarily-related and evolutionarily-distinct enzymes and across enzymes carrying out reactions with different chemical constraints; (3) Tests of evolutionary mechanisms of enzyme cold-adaptation; and (4) In-depth determination of temperature-dependent changes in enzyme conformational ensembles, information that may be foundational for studying allostery and designing new enzymes. Most broadly, the scientific achievements from this proposal have the potential to catalyze a paradigm shift—from the currently dominant structure–function approaches to ensemble–function studies that link structure to the energetics that underlie function. They also have the potential to revolutionize the teaching of enzyme mechanisms and unify teaching across scientific disciplines, changing textbook descriptions from general and descriptive to specific models based on fundamental chemistry and physics principles that are taught in chemistry classes. This project was funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.