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Computational examination of the electronic properties of 2-cyanophenylalanine, 3-cyanophenylalanine , and 4-cyanophenylalanine
Metzroth, Lucy
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Denver, CO
Metropolitan State University of Denver
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Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Matthew Mariner.
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Faculty mentor: Joshua P. Martin

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C OMPUTATIONAL E XAMINATION OF THE E LECTRONIC P ROPERTIES OF 2 C YANOPHENYLALANINE , 3 C YANOPHENYLALANINE , AND 4 C YANOPHENYLALANINE Lucy Metzroth and Joshua P. Martin Department of Chemistry and Biochemistry, Metropolitan State University of Denver Abstract We present an in depth computational examination of the electronic properties of 2 cyanophenylalanine, 3 cyanophenylalanine, and 4 cyanophenylalanine. Electronic structures of these biologically relevant spectroscopic probes give insight into the observed photophysical properties and use of these chromophores as participants in Förster Resonance Energy Transfer (FRET) and protein folding studies. Computational chemistry calculations using high level ab initio methods were performed to determine minimum energy geometries and examine the molecular orbitals of a model chromophore ( cyanotoluene ) and the cyanophenyalanine derivatives. Results suggest that, in the ground state, most of the electron density is situated in bonding orbitals around t he ring structure in all three amino acids. However, upon excitation to a singlet excited state, the molecular orbitals become more antibonding in character. In analyzing these c han ges, we discuss the utility of these reporters in studies of protein dynamics that require spectroscopic selectivity. Background I nfo rmation Big picture: Real time observation of protein folding and dynamics. This can be accomplished using Förster Resonance Energy Transfer (FRET) Below: The donor (D) is electronically excited and transfers energy to an acceptor (A) with a distance dependent efficiency. The distance between A and D can then show if the protein is folded or unfolded. Figure adapted from Ref. 1 Cyanophenylalanine Probes Computational Computational chemistry uses methods , which approximate the quantum mechanical Schrodinger equation through different treatment of electronic wavefunctions, and basis sets , a finite number of well defined functions that describe the atomic orbitals for each atom. power needed. Results: Geometry Model the chromophore of the Phe CN derivatives with cyanotoluene . Calculated 4 cyanotoluene geometries match previously reported 6 results confirming accuracy. 2 cyanotoluene and 3 cyanotoluene show little difference in geometry Location of the nitrile group on the ring has little effect on geometry. However the electron density may change correlating to differences in the photophysical properties. Results: Molecular Orbitals Electronic structure does not change with the addition of the amino group Highest occupied molecular orbital localized on chromophore (ring structure), not amino group Conclusions and Future Work Cyanotoluene is an excellent chromophore benchmark for studying Phe CN photophysics and can be used to determine best methods/basis sets with lower computational cost. 0 state Phe CN and the model chromophores show extended conjugation from the addition of the nitrile group improving their F , and making them superior for spectroscopic investigations, such as FRET processes within peptides and proteins. Future work: Calculate excited state energies and molecular orbitals Calculate ground and excited state conformers, and how their electronic structures differ Calculate ground and excited state energetics in various solvent environments Calculate vertical excitation energy from oscillator strengths and transition dipole moments to compare with absorption and fluorescence spectroscopy results Place Phe CN in a peptide and calculate electronic structure changes 1.409 1.411 1.401 1.412 1.410 1.403 1.096 1.094 1.512 1.101 1.103 1.103 1.444 1.188 1.096 1.094 4 cyanotoluene 2 cyanotoluene 1.103 1.103 1.100 1.511 1.417 1.445 1.188 1.413 1.094 1.400 1.094 1.406 1.095 1.403 1.096 1.409 1.417 3 cyanotoluene 1.095 1.096 1.512 1.411 1.403 1.404 1.406 1.412 1.410 1.103 1.103 1.101 1.095 1.444 1.188 1.094 Figure adapted from Ref. 6 Cyanotoluene electron density Increasing cost of calculation Method Basis Set Hartree Fock Assume electrons move independently and uses atomic solutions to solve for molecules Density Functional Theory ( e.g . B3LYP) Electrons are a gas of uniform density while the exchange energy term is replaced with exchange/correlation energy Möller Plesset ( e.g . MP2) Improves on Hartree Fock by adding in electron correlation using perturbation theory Coupled Cluster ( e.g . CCSD) Improves on Hartree Fock by adding in electron correlation using multi electron wavefunctions Exact Solution Exact, analytical solution Minimal Basis Set Minimum number of basis functions required to model spherical nature of atom Split Valence ( e.g . 6 311G) Represents core atomic orbitals with one set of functions and valence orbitals with another Correlation Consistent ( e.g . cc pVDZ ) Uses polarization functions and extrapolation to converge systematically to the complete basis set limit Complete Basis Set Limit Limit where an infinite number of functions are used in the basis set. Limits Geometries calculated using MP2/cc pVDZ level for the S 0 minimum; Bond lengths in 2 Phe CN 3 Phe CN 4 Phe CN 2 cyanophenylalanine (2 Phe CN ), 3 cyanophenylalanine (3 Phe CN ), and 4 cyanophenylalanine (4 Phe CN ) are useful spectroscopic probes in structural and dynamics studies 2 of peptides/proteins because Phe CN derivatives are easily incorporated into peptides and proteins 2 using Fmoc or solid phase peptide synthesis ) and fluorescence quantum F ) is increased by a factor of four compared to phenylalanine with the addition of the nitrile group probe of the local environment to determine the hydration status of protein core hydrogen bonding ability of solvent 3,4 of peptide/protein geometries allowing for studies of native structures (240 nm) and (280 nm) allows for selective excitation of a specific derivative References 1 Lemar , E., et al., Science, 2018, 359 (6373), 288. 2 Martin, J.P.; Fetto , N.R.; Tucker, M.J., Phys. Chem. Chem. Phys., 2016, 18 , 20750. 3 Getahun , Z.; Huang, C. y.; Wang, T.; De Leon, B.; Degrado , W.F.; Gai, F., J. Am. Chem. Soc. , 2003, 125 , 405. 4 Adhikary , R.; Zimmermann, J.; Dawson, P.E.; Romesberg , F. E., ChemPhysChem , 2014, 15 , 849. 5 Tucker, M.J.; Oyola , R.; Gai, F., J. Phys. Chem. B , 2005, 109 , 4788. 6 Meloni , S. L.; Matsika , S., Theor . Chem. Acc. 2014, 133 (7), 1. Acknowledgements We would like to gratefully acknowledge Natalie R. Fetto (University of Nevada, Reno), Dr. Matthew J. Tucker (University of Nevada, Reno), Austin J. Haider (MSU Denver), Andrew Melendrez Zerwekh (MSU Denver), and Roman J. Martinez (MSU Denver) for their continued collaboration. Funding: MSU Denver Provost Startup Funds Phe CN derivatives with commonly used probes ( e.g. tryptophan) demonstrates the utility of the cyanophenylalanine species for use in FRET studies 2,5 of peptides/proteins at short distances. MP2/cc pVDZ CCSD/cc pVDZ Phe CN electron density MP2/cc pVDZ B3LYP/cc pVDZ