Enzymes perform the designated function of catalyzing chemical reactions by serving more than a scaffold for bringing together the reactants. The role of structure in enzyme function has been known for more than a century now; however, more recent evidence suggests that a functioning enzyme exists in an ensemble of conformations under ambient physiological conditions. The ensemble view of enzyme structure suggests that it can sample conformational sub-states that exhibit function promoting structural and dynamical features. Further, evidence from experiments and computational modeling suggest that transitions between these conformational sub-states enable substrate recognition and catalysis. Quantitative insights into these functionally relevant sub-states remains challenging, particularly due to the wide range of time-scales involved, limited window of resolution for individual techniques and the fact that some of the sub-states can be potentially short-lived. We address these issues by developing a joint computational-experimental framework to identify and characterize such functionally relevant sub-states in the context of enzyme function. In addition to identifying structural intermediates, our framework will quantify the relative population of the conformations in various sub-states as well as enable their linkage to kinetics of enzyme function through the catalytic cycle. This integrated approach will be used to investigate the bio-medically relevant ribonuclease (RNase) family of proteins and enzymes. In particular, we will: (1) Develop a theoretical framework to identify and characterize the multi-scale hierarchy in the conformational landscape of proteins; (2) Utilize the developed framework to investigate the RNase fold members and their ability to access distinct conformational sub-states, including functionally relevant sub-states along the catalytic cycle; (3) Validate the developed model and predicted sub- states by integrating nuclear magnetic resonance (NMR) relaxation dispersion experiments. The developed methodology and models will be improved by iterative interaction between the 3 PIs with different expertise spanning theoretical biophysics, computational simulations and experimental techniques. Overall, our studies will have implications in the design of novel inhibitors of RNase function in the context of neurotoxicity, angiogenesis and anti-pathogenicity.

Public Health Relevance

The proposed research will have direct impact on human health. The theoretical foundation, and the modeling and software framework developed will allow automated characterization of biomolecular systems involved in enzyme catalysis. In particular the multi-scale hierarchy of conformational motions and sub-state analysis has important implications for obtaining the knowledge of protein structure, folding, dynamics, and function. The results from investigations of ribonuclease family members could potentially help in designing novels medicine for diseases associated with neurotoxicity, angiogenesis and anti-pathogenicity. Further, the developed tools and software will be distributed free to the wider community.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM105978-04
Application #
9284477
Study Section
Macromolecular Structure and Function E Study Section (MSFE)
Program Officer
Barski, Oleg
Project Start
2014-04-01
Project End
2019-03-31
Budget Start
2017-04-01
Budget End
2018-03-31
Support Year
4
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Biology
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Shukla, Shantanu; Bafna, Khushboo; Gullett, Caeley et al. (2018) Differential Substrate Recognition by Maltose Binding Proteins Influenced by Structure and Dynamics. Biochemistry 57:5864-5876
Duff Jr, Michael R; Borreguero, Jose M; Cuneo, Matthew J et al. (2018) Modulating Enzyme Activity by Altering Protein Dynamics with Solvent. Biochemistry 57:4263-4275
Narayanan, Chitra; Bernard, David N; Bafna, Khushboo et al. (2018) Ligand-Induced Variations in Structural and Dynamical Properties Within an Enzyme Superfamily. Front Mol Biosci 5:54
Dionne, Ugo; Chartier, François J M; López de Los Santos, Yossef et al. (2018) Direct Phosphorylation of SRC Homology 3 Domains by Tyrosine Kinase Receptors Disassembles Ligand-Induced Signaling Networks. Mol Cell 70:995-1007.e11
Parvatikar, Akash; Vacaliuc, Gabriel S; Ramanathan, Arvind et al. (2018) ANCA: Anharmonic Conformational Analysis of Biomolecular Simulations. Biophys J 114:2040-2043
Narayanan, Chitra; Bernard, David N; Bafna, Khushboo et al. (2018) Conservation of Dynamics Associated with Biological Function in an Enzyme Superfamily. Structure 26:426-436.e3
O'Dell, William B; Agarwal, Pratul K; Meilleur, Flora (2017) Oxygen Activation at the Active Site of a Fungal Lytic Polysaccharide Monooxygenase. Angew Chem Int Ed Engl 56:767-770
Gagné, Donald; Narayanan, Chitra; Bafna, Khushboo et al. (2017) Sequence-specific backbone resonance assignments and microsecond timescale molecular dynamics simulation of human eosinophil-derived neurotoxin. Biomol NMR Assign 11:143-149
Bhojane, Purva P; Duff Jr, Michael R; Bafna, Khushboo et al. (2017) Small Angle Neutron Scattering Studies of R67 Dihydrofolate Reductase, a Tetrameric Protein with Intrinsically Disordered N-Termini. Biochemistry 56:5886-5899
Narayanan, Chitra; Gagné, Donald; Reynolds, Kimberly A et al. (2017) Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily. Sci Rep 7:3207

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