This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. RG13 is a 637-aminoacid engineered allosteric molecular switch between beta-lactamase (BLA) and maltose binding protein (MBP) [Gutas G, Mitchell SF, Ostermeier M, (2004) Chem Biol 11:1483-1487;Guntas G, Mansell TJ, Kim JR, Ostermeier M, (2005) Proc Natl Acad Sci USA 102:11224-11229]. In the absence of maltose, MBP exists in an open form. Maltose binding is concomitant with a 35 degree bending motion about the hinge, resulting in the closed form of the protein [Sharff AJ, Rodseth LE, Spurlino JC, Quiocho FA, (1992) Biochemistry 31:10657-10663]. BLA is a monomeric enzyme that hydrolyzes the amide bond of the beta-lactam ring of beta-lactam antibiotic such as penicillin. The circularly permuted BLA was inserted into the MBP, and a switch (RG13) was identified in which its beta-lactam hydrolysis activity was compromised in the absence of maltose but increased 25-fold in the presence of maltose. We reasoned that in the switch the conformational change in the MBP domain upon maltose binding would propagates to the active site of the BLA domain and alter its catalytic properties, a mechanism analogous to natural allosteric effects. RG13 was identified from a combinational library rather than rationally designed, and thus, the molecular mechanism by which switching occurs is not known. Our goal is to develop a structural understanding of the switching mechanism in order to guide generation of further hypotheses such as optimizing and creating novel allosteric switch molecules for various applications. In order to achieve the goal, Dr. Ostermeier and co-workers are conducting NMR experiments including residual dipolar coupling (RDC), nuclear Overhauser enhancement (NOE), and paramagnetic relaxation enhancement (PRE) measurements. These measurements provide orientation and distance constraints for structural modeling RG13. We would first predict the structures of the switch using Rosetta NMR [Raman S, Lange OF, Rossi P, Tyka M, Wang X, et al. (2010) Science 327:1014-1018;Raman S, Huang YJ, Mao B, Rossi P, Aramini JM, et al. (2010) J Am Chem Soc 132:202-207;Shen Y, Vernon R, Baker D, Bax A, (2009) J Biomol NMR 43:63-78] and domain insertion [Berrando M, Ostermeier M, Gray JJ, (2008) Structure 16:513-527] approaches. Our previous NMR studies (15N, 1H-TROSY-HSQC) indicate that the individual domain structures of RG13 are substantially conserved from MBP and BLA [Wright CM, Majumdar A, Tolman JR, Ostermeier M, (2010) Proteins 78:1423-1430]. Therefore we can get good starting structures from Monte Carlo (MC) simulations with NMR constraints. Proteins, however, are flexible and dynamic. In order to achieve our goal to understand the allosteric switching mechanism of RG13, we have to understand conformational changes upon fusion of two parent proteins (BLA and MBP) and binding of maltose and their propagation from MBP to BLA through the flexible linkers. This dynamic process will be investigated by running molecular dynamics (MD) simulations. Structural model and its dynamics will be compared and tested with NMR relaxation data by running long time MD simulations (>60 ns) [Bhattacharya N, Yi M, Zhou HX, Logan TM, (2007) J Mol Biol 374:977-992]. We would model the structure in the presence of antibiotic molecules such as penicillin, which has not been parameterized for MD simulations. In order to prepare the parameters compatible to CHARMM force field format, we would perform quantum chemistry calculations with Gaussian03.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Biotechnology Resource Grants (P41)
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Carnegie-Mellon University
Biostatistics & Other Math Sci
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