Thursday, October 19, 2017

Analyzing Reaction Rates with the Distortion/Interaction-Activation Strain Model

Bickelhaupt, F. M.; Houk, K. N.,  Angew. Chem. Int. Ed. 2017, 56, 10070-10086
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Bickelhaupt and Houk present a nice review of their separately developed, but conceptually identical model for assessing reactivity.1 Houk termed this the “distortion/interaction” model,2 while Bickelhaupt named it “activation strain”.3 The concept is that the activation barrier can be dissected in a distortion or stain energy associated with bringing the reactants into the geometry of the transition state, and the interaction energy is the stabilization energy afforded by the molecular orbital interactions of the reactant components with each other in the transition state.

The review discusses a broad range of applications, including SN2 and Ereactions, pericyclic reactions (including Diels-Alder reactions of enones and the dehdydro Diels-Alder reaction that I have discussed in this blog), a click reaction, a few examples involving catalysis, and the regioselectivity of indolyne (see this post). They also discuss the role of solvent and the relationship of this model to Marcus Theory.

I also want to mention in passing a somewhat related article by Jorgensen and co-authors published in the same issue of Angewandte Chemie as the above review.4 This article discusses the paucity of 10 electron cycloaddition reactions, especially in comparison to the large number of very important cycloaddition reactions involving 6 electrons, such as the Diels-Alder reaction, the Cope rearrangement, and the Claisen rearrangement. While the article does not focus on computational methods, computations have been widely used to discuss 10-electron cycloadditions. The real tie between this paper and the review discussed above is Ken Houk, whose graduate career started with an attempt to perform a [6+4] cycloaddition, and he has revisited the topic multiple times throughout his career.


1. Bickelhaupt, F. M.; Houk, K. N., "Analyzing Reaction Rates with the Distortion/Interaction-Activation Strain Model." Angew. Chem. Int. Ed. 201756, 10070-10086, DOI: 10.1002/anie.201701486.
2. Ess, D. H.; Houk, K. N., "Distortion/Interaction Energy Control of 1,3-Dipolar Cycloaddition Reactivity." J. Am. Chem. Soc. 2007, 129, 10646-10647, DOI: 10.1021/ja0734086
3. Bickelhaupt, F. M., "Understanding reactivity with Kohn-Sham molecular orbital theory: E2-SN2 mechanistic spectrum and other concepts." J. Comput. Chem. 1999, 20, 114-128
4. Palazzo, T. A.; Mose, R.; Jørgensen, K. A., "Cycloaddition Reactions: Why Is It So
Challenging To Move from Six to Ten Electrons?" Angew. Chem. Int. Ed. 2017, 56, 10033-10038, DOI: 10.1002/anie.201701085.

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Monday, October 9, 2017

Benzophenone Ultrafast Triplet Population: Revisiting the Kinetic Model by Surface-Hopping Dynamics

Marco Marazzi, Sebastian Mai, Daniel Roca-Sanjuán, Mickaël G. Delcey, Roland Lindh, Leticia González, and Antonio Monari (2016)
Highlighted by Ravi Kumar Venkatraman

In 1967, Norrish and Porter were honoured with Nobel prize for their seminal work on understanding the fast chemical reactions using flash photolysis technique.1 Since then benzophenone (Bzp) serves as an archetypal system for understanding the photochemistry of various aromatic ketones. Aromatic ketones find their use in various technologically significant applications like sunscreen, photocatalysis, etc., apart from their fundamental interest.2 Efficacy of aromatic ketones for use in various applications relies upon their photophysics and photochemistry. Therefore, understanding the photophysics and photochemistry of Bzp has attracted several experimental and theoretical investigations.2 Despite these myriads of investigations, pathways for populating the lowest triplet state (T1) after photoexcitation to the S1 state remains still elusive. There are two plausible pathways: i) a direct ISC from S1(nπ*) to T1(nπ*); or ii) an indirect process, involving ISC from S1(nπ*) to T1(ππ*) with subsequent internal conversion (IC) to T1(nπ*). The latter pathway is more efficient, according to El-Sayed’s rule, because it entails a change in the orbital character during the spin-orbit coupling mediated process.3

Reproduced with permission from Marco Marazzi, Sebastian Mai, et. al., J. Phys. Chem. Lett., 7, 622 (2016) under Creative Commons Attribution (CC-BY) License

In this work, authors have employed ab initio surface-hopping dynamics simulation for Bzp in gas phase to explore the pathways for the lowest triplet state (T1) population after photo-excitation to the S1 state. This study clearly demonstrates that the dominant mechanism for populating the T1 state is the indirect pathway invoking T2 state as an intermediate. This study urges reinvestigation of spectroscopic assignment for Bzp in various time-resolved spectroscopic techniques. Furthermore, the mechanism for the photoinduced energy transfer in photocatalysis and DNA damage studies must be revisited as in principle now both channels involving T2 and T1 states are available.

1.) F. Ariese, K. Roy, V. R. Kumar, H. C. Sudeeksha, S. Kayal, S. Umapathy, Time-Resolved Spectroscopy: Instrumentation and Applications in Encyclopedia of Analytical Chemistry, edited by R. A. Meyers, 1-55, (2017) John Wiley & Sons, Ltd.
2.) M. C. Cuquerella, V. L-Vallet, J. Cadet, and M. A. Miranda, Benzophenone Photosensitized DNA Damage, Acc. Chem. Res., 45, 1558 (2012).
3.) Elsayed, M. A., Spin-Orbit Coupling and Radiationless Processes in Nitrogen Heterocyclics. J. Chem. Phys., 38, 2834 (1963).

Friday, October 6, 2017

More applications of computed NMR spectra

Grimblat, N.; Kaufman, T. S.; Sarotti, A. M., "Computational Chemistry Driven Solution to Rubriflordilactone B." Org. Letters 2016, 18, 6420-6423
Reddy, D. S.; Kutateladze, A. G., "Structure Revision of an Acorane Sesquiterpene Cordycepol A." Org. Letters 2016, 18, 4860-4863
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

In this post I cover two papers discussing application of computed NMR chemical shifts to structure identification and (yet) another review of computational techniques towards NMR structure prediction.
Grimblat, Kaufman, and Sarotti1 take up the structure of rubriflordilactone B 1, which was isolated from Schisandra rubriflora. The compound was then synthesized and its x-ray structure reported, however its NMR did not match with the natural extract. It was suggested that there were actually two compounds in the extract, the minor one was less soluble and is the crystallized 1, and a second compound responsible for the NMR signal.
The authors looked at all stereoisomers of this molecule keeping the three left-most rings intact. The low energy rotamers of these 32 stereoisomers were then optimized at B3LYP/6-31G* and the chemical shifts computed at PCM(pyridine)/mPW1PW91/6-31+G**. To benchmark the method, DP4+ was used to identify which stereoisomer best matches with the observed NMR of authentic 1; the top fit (92.6% probability) was the correct structure.

The 32 stereoisomers were then tested against the experimental NMR of the natural extract. DP4+ with just the proton shifts suggested structure 2 (99.8% probability); however, the 13C chemical shifts predicted a different structure. Re-examination of the reported chemical shifts identifies some mis-assigned signals, which led to a higher C-DP4+ prediction. When all 128 stereoisomers were tested, structure 2 had the highest DP4+ prediction (99.5%), but the C-DP4+ prediction remained problematic (10.8%). Analyzing the geometries of all reasonable alternative for agreement with the NOESY spectrum confirmed 2. These results underscore the importance of using all data sources.
Reddy and Kutateladze point out the importance of using coupling constants along with chemical shifts in structure identification.2 They examined cordycepol A 3, obtained from Cordyceps ophioglossoides. They noted that the computed chemical shifts and coupling constants of originally proposed structure 3adiffered dramatically from the experimental values.

They first proposed that the compound has structure 3b. The computed coupling constants using their relativistic force field.3 The experimental coupling constants for the proton H1 are 13.4 and 7.1 Hz. The computed values for 3a are 8.9 and 1.6 Hz, and this structure is clearly incorrect. The coupling constants are improved with 3b, but the 13C chemical shifts are in poor agreement with experiment. So, they proposed structure 3c, the epimer at both C1 and C11 of the original structure.

They optimized four conformations of 3c at B3LYP/6-31G(d) and obtained Boltzmann-weighted chemical shifts at mPW1PW91/6-311+G(d,p). The RMS deviation of the computed 13C chemical shifts relative to the experiment is only 1.54 ppm, and more importantly, the computed coupling constants of 13.54 and 6.90 Hz are in excellent agreement with the experiment values.

Lastly, Grimblat and Sarotti present a review of a number of methods for using computed NMR chemical shifts towards structure prediction.4 These methods include CP3DP4DP4+ (all of which I have posted on in the past) and an artificial neural network approach of their own design. They discuss a number of interesting cases where each of these methods has been crucial in identifying the correct chemical structure.


1. Grimblat, N.; Kaufman, T. S.; Sarotti, A. M., "Computational Chemistry Driven Solution to Rubriflordilactone B." Org. Letters 201618, 6420-6423, DOI: 10.1021/acs.orglett.6b03318.
2. Reddy, D. S.; Kutateladze, A. G., "Structure Revision of an Acorane Sesquiterpene Cordycepol A." Org. Letters 201618, 4860-4863, DOI: 10.1021/acs.orglett.6b02341.
3. (a) Kutateladze, A. G.; Mukhina, O. A., "Minimalist Relativistic Force Field: Prediction of Proton–Proton Coupling Constants in 1H NMR Spectra Is Perfected with NBO Hybridization Parameters." J. Org. Chem.201580, 5218-5225, DOI: 10.1021/acs.joc.5b00619; (b) Kutateladze, A. G.; Mukhina, O. A., "Relativistic Force Field: Parametrization of 13C–1H Nuclear Spin–Spin Coupling Constants." J. Org. Chem. 201580, 10838-10848, DOI: 10.1021/acs.joc.5b02001.
4. Grimblat, N.; Sarotti, A. M., "Computational Chemistry to the Rescue: Modern Toolboxes for the Assignment of Complex Molecules by GIAO NMR Calculations." Chem. Eur. J. 201622, 12246-12261, DOI: h10.1002/chem.201601150.


1: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19+,20-,21-,22+,24-,25-,28+/m0/s1
2: InChI=1S/C28H30O6/c1-13-9-20(32-26(13)30)25-14(2)24-17-6-5-15-12-28-21(8-7-16(15)18(17)10-19(24)31-25)27(3,4)33-22(28)11-23(29)34-28/h5-9,14,19-22,24-25H,10-12H2,1-4H3/t14-,19-,20-,21-,22+,24+,25-,28+/m0/s1
3c: InChI=1S/C16H28O2/c1-6-11(2)9-14-16(5)12(3)7-8-13(16)15(4,17)10-18-14/h9,12-14,17H,6-8,10H2,1-5H3/b11-9-/t12-,13-,14-,15-,16+/m0/s1

This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.