Arginine52 Controls the Photoisomerization Process in Photoactive Yellow Protein

Groenhof, Gerrit; Schaefer, L.; Boggio‐Pasqua, Martial; Grubmueller, Helmut; Robb, MA

doi:10.1021/ja078024u

Cited by 87 publications

(125 citation statements)

References 11 publications

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“…Examples occur in the conical intersections involved in a lone pair photoexcitation, [89][90][91][92][93][94][95] in the conical intersections involved where an isolated negative charge occurs as the result of a charge transfer, 65,[96][97][98][99][100][101][102][103][104][105][106][107] or in the conical intersections involved as a result of the charge transfer and a proton transfer. Examples occur in the conical intersections involved in a lone pair photoexcitation, [89][90][91][92][93][94][95] in the conical intersections involved where an isolated negative charge occurs as the result of a charge transfer, 65,[96][97][98][99][100][101][102][103][104][105][106][107] or in the conical intersections involved as a result of the charge transfer and a proton transfer.…”

Section: Qualitative Vb Analysis Of Conical Intersections Involving Cmentioning

confidence: 99%

In This Molecule There Must Be a Conical Intersection

Robb¹

2014

Advances in Physical Organic Chemistry

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Section: Qualitative Vb Analysis Of Conical Intersections Involving Cmentioning

confidence: 99%

In This Molecule There Must Be a Conical Intersection

Robb¹

2014

Advances in Physical Organic Chemistry

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“…(2) In previous works we have used mixed quantum/classical (QM/MM) simulations to reveal the detailed sequence of structural changes that follows photon absorption in both wild-type PYP(3) and the Arg52Gln mutant. (4) The first step is a photoisomerization of the chromophore of the double (wt-PYP) or single bond (Arg52Gln). In the protein radiationless decay from the excited state is very efficient because the intersection seam between the ground- (S 0 ) and excited-state (S 1 ) surfaces lies near the excited-state minima.…”

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confidence: 99%

“…Snapshots from an excited-state trajectory of the Arg52Gln mutant:(4) (a) at photoexcitation, (b) twisted configuration without H-bonds to the carbonyl oxygen, and (c) at conical intersection seam. Image (c) shows how two backbone amino groups and a bulk water molecule donate the three H-bonds required for excited-state decay from the single-bond twisted structure.…”

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confidence: 99%

Hydrogen Bonding Controls Excited-State Decay of the Photoactive Yellow Protein Chromophore

2009

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We have performed excited-state dynamics simulations of a Photoactive Yellow Protein chromophore analogue in water. The results of the simulations demonstrate that in water the chromophore predominantly undergoes single-bond photoisomerization, rather than double-bond photoisomerization. Despite opposite charge distributions in the chromophore, excited-state decay takes place very efficiently from both single- and double-bond twisted minima in water. Radiationless decay is facilitated by ultrafast solvent reorganization, which stabilizes both minima by specific hydrogen bond interactions. Changing the solvent to the slightly more viscous D2O leads to an increase of the excited-state lifetime. Together with previous simulations, the present results provide a complete picture of the effect of the protein on the photoisomerization of the chromophore in PYP: the positive guanidinium group of Arg52 favors double-bond isomerization over single-bond isomerization by lowering the barrier for double-bond isomerization, while the hydrogen bonds with Tyr42 and Glu46 enhance deactivation from the double-bond twisted minimum.

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“…For such ultrafast excited state processes, "on the fly" ab initio nonadiabatic dynamics simulations in combination with the QM/MM method should be more useful. 7,12,13,26,37,80,81,92 However, time scale of "on the fly" ab initio nonadiabatic dynamics is rather limited, always within or near picoseconds, due to expensive evaluations of gradient difference and nonadiabatic coupling vectors and small time steps. However, relatively slow reactions, more than hundreds of picoseconds, remain ubiquitous in solution photochemistry and biophotochemistry.…”

Section: B Averaged Conical Intersections On Potential Of Mean Forcementioning

confidence: 99%

“…Thus, they are mainly used to simulate ultrafast, nonequilibrium nonadiabatic processes in small-and medium-size polyatomic molecules. 7,12,13,26,37,80,81,92 However, relatively slow reactions, more than hundreds of picoseconds, remain ubiquitous in solution photochemistry and biophotochemistry, where topological structures, such as conical intersections of potential of mean force surfaces, could be more useful and can provide valuable insights into mechanisms. 27,28,[74][75][76][77] In this work, we have combined our sequential optimization technique with the QM/MM and QM/MM-MFEP methods and developed two conical intersection optimization methods for small-and medium-size molecules in solution or macromolecules on potential energy surfaces and potential of mean force surfaces, respectively.…”

Section: Introductionmentioning

confidence: 99%

Conical intersections in solution: Formulation, algorithm, and implementation with combined quantum mechanics/molecular mechanics method

Cui

Yang

2011

The Journal of Chemical Physics

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The significance of conical intersections in photophysics, photochemistry, and photodissociation of polyatomic molecules in gas phase has been demonstrated by numerous experimental and theoretical studies. Optimization of conical intersections of small-and medium-size molecules in gas phase has currently become a routine optimization process, as it has been implemented in many electronic structure packages. However, optimization of conical intersections of small-and medium-size molecules in solution or macromolecules remains inefficient, even poorly defined, due to large number of degrees of freedom and costly evaluations of gradient difference and nonadiabatic coupling vectors. In this work, based on the sequential quantum mechanics and molecular mechanics (QM/MM) and QM/MM-minimum free energy path methods, we have designed two conical intersection optimization methods for small-and medium-size molecules in solution or macromolecules. The first one is sequential QM conical intersection optimization and MM minimization for potential energy surfaces; the second one is sequential QM conical intersection optimization and MM sampling for potential of mean force surfaces, i.e., free energy surfaces. In such methods, the region where electronic structures change remarkably is placed into the QM subsystem, while the rest of the system is placed into the MM subsystem; thus, dimensionalities of gradient difference and nonadiabatic coupling vectors are decreased due to the relatively small QM subsystem. Furthermore, in comparison with the concurrent optimization scheme, sequential QM conical intersection optimization and MM minimization or sampling reduce the number of evaluations of gradient difference and nonadiabatic coupling vectors because these vectors need to be calculated only when the QM subsystem moves, independent of the MM minimization or sampling. Taken together, costly evaluations of gradient difference and nonadiabatic coupling vectors in solution or macromolecules can be reduced significantly. Test optimizations of conical intersections of cyclopropanone and acetaldehyde in aqueous solution have been carried out successfully.

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Arginine52 Controls the Photoisomerization Process in Photoactive Yellow Protein

Cited by 87 publications

References 11 publications

In This Molecule There Must Be a Conical Intersection

In This Molecule There Must Be a Conical Intersection

Hydrogen Bonding Controls Excited-State Decay of the Photoactive Yellow Protein Chromophore

Conical intersections in solution: Formulation, algorithm, and implementation with combined quantum mechanics/molecular mechanics method

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