Wednesday, March 25, 2015

Thermodynamic Evaluation of Aromatic CH/π Interactions and Rotational Entropy in a Molecular Rotor

Pérez-Estrada, S.; Rodrı́guez-Molina, B.; Xiao, L.; Santillan, R.; Jiménez-Osés, G.; Houk, K. N.; Garcia-Garibay, M. A. J. Am. Chem. Soc. 2015, 137, 2175
Contributed by Steven Bachrach.
Reposted from Computational Organic Chemistry with permission

Molecular rotors remain a fascinating topic – the idea of creating a miniature motor just seems to capture the imagination of scientists. Garcia-Garibay and his group have synthesized the interesting rotor 1, and in collaboration with the Houk group, they have utilized computations to help understand the dynamics of this rotor.1

The x-ray structure of this compound, shown in Figure 1, displays two close interactions of a hydrogen on the central phenyl ring with the face of one of the steroidal phenyl rings. Rotation of the central phenyl ring is expected to then “turn off” one or both of these C-Hπ interactions. The authors argue this as a competition between the molecule sampling an enthalpic region, where the molecule has one or two favorable C-Hπ interactions, and the large entropic region where these C-Hπ interactions do not occur, but this space is expected to have a large quantity of energetically similar conformations.



Figure 1. X-ray and M06-2x/6-31G(d) optimized structures of 1.

Variable temperature NMR finds the central phenyl hydrogen with a chemical shift of 6.55ppm at 295 K but at 6.32 ppm at 222 K. This suggest as freezing of the conformations at low temperature favoring those conformations possessing the internal C-Hπ interactions. M06-2X/6-31G(d) optimization finds two low-energy conformations with a single C-Hπ interaction. These are shown in Figure 1. No competing conformation was found to have two such interactions. Computations of the chemical shifts of these conformations show the upfield shift of the central phenyl hydrogens. Fitting these chemical shifts to the temperature data gives ΔH = -1.74 kcal mol-1, ΔS = -5.12 esu and ΔG = -0.21 kcal mol-1 for the enthalpic region to entropic region transition.


(1) Pérez-Estrada, S.; Rodrı́guez-Molina, B.; Xiao, L.; Santillan, R.; Jiménez-Osés, G.; Houk, K. N.; Garcia-Garibay, M. A. "Thermodynamic Evaluation of Aromatic CH/π Interactions and Rotational Entropy in a Molecular Rotor," J. Am. Chem. Soc. 2015137, 2175-2178, DOI: 10.1021/ja512053t.


1: InChI=1S/C48H54O4/c1-45-23-19-39-37-15-11-35(51-3)29-33(37)9-13-41(39)43(45)21-27-47(45,49)25-17-31-5-7-32(8-6-31)18-26-48(50)28-22-44-42-14-10-34-30-36(52-4)12-16-38(34)40(42)20-24-46(44,48)2/h5-8,11-12,15-16,29-30,39-44,49-50H,9-10,13-14,19-24,27-28H2,1-4H3

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

Sunday, March 22, 2015

A Case Study of the Mechanism of Alcohol-Mediated Morita Baylis- Hillman Reactions. The Importance of Experimental Observations.

R. Erik Plata, and Daniel A. Singleton Journal of the American Chemical Society 2015, ASAP.
Contributed by +Jan Jensen

This excellent and unusually well-written paper has already been discussed quite a bit including a blog post at In the Pipeline, (including a lively discussion in the comments section), a Reddit thread, and a C&EN highlight, not to mention a lot of twittering. Here are my 2 cents.

To summarize: the authors picked a somewhat challenging (by their own admission) reaction and show that published computational studies as well as their own calculations (using standard approaches) yield mechanistic conclusions that in many cases are "not even wrong" as Pauli once said.

The study offers some important lessons and some of the lessons are quite fundamental and, judging by the literature, often needed.

* Don't ignore the experimental data.  If your calculations predict an overall increase in standard free energy for a reaction that is observed to proceed, there's something wrong.  The same goes for calculated free energy barriers that suggest reaction rates on the order of years.

* Life is often complicated. Don't just pick the simplest or computationally most tractable reaction mechanism.

* Thermodynamics requires just as much attention as the electronic structure theory. ZPE or enthalpy is not a substitute for the free energy (especially for bimolecular reactions) and the thermodynamic terms should not be corrected in an ad hoc fashion. Oh, and use the correct standard state.

* If you want to compare your computed enthalpies and entropies to experiments, you must include the entropy enthalpy of solvation in your calculations.

* The paper suggests that the largest error comes from the enthalpy of solvation due to the implicit solvent model.  You may have to include explicit solvent molecules to get accurate results.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Tuesday, March 10, 2015

Reinvestigation of the Stereochemistry of the C-Glycosidic Ellagitannins, Vescalagin and Castalagin

Matsuo, Y.; Wakamatsu, H.; Omar, M.; Tanaka, T.  Org. Lett. 2014, 17, 46-49
Contributed by Steven Bachrach.
Reposted from Computational Organic Chemistry with permission

Vescalagin 1 and castalagin 2 are found in plants and also in wine and whisky. They possess some intriguing stereochemistry and the topic of interest in the paper by Tanaka and coworkers is the stereochemistry of the triphenyl fragment.1 The original proposed structure indicated a (S,S) (1a and 2a) configuration, yet a molecular mechanics study suggest the (S,R) (1b and 2b) configuration would be lower in energy.
1a: R1 = OH, R2 = H
2a: R1 = H, R2 = OH
1b: R1 = OH, R2 = H
2b: R1 = H, R2 = OH

Recognizing the power of DFT computations in resolving this type of structural problem, Tanaka measured the ECD spectrum of the hydrolyzed forms of 1 and 2, namely 3 and 4. The (S,S) and (S,R) isomers of 3and 4 were subjected to a Monte Carlo search using MM. Low-lying conformers were reoptimized at B3LYP/6-31G(d,p) including PCM, modeling methanol as the solvent. The ECD spectrum was then predicted using all conformations with a population over 1%. The computed spectrum for the (S,R) isomer reproduced the negative Cotton effect at 218 nm observed in the experiment.

3a: R1 = OH, R2 = H
4a: R1 = H, R2 = OH
3b: R1 = OH, R2 = H
3b: R1 = H, R2 = OH

The structures of 1 and 2 of both stereoisomers were next optimized at B3LYP/6-31G(d,p) including PCM. The lowest energy conformation of each is shown in Figure 1. The 1H and 13C chemical shifts were computed at this level, again using all conformations with a population greater than 1%. The correlation coefficient for the fit between the experimental values of the chemical shifts and 1a and 2a are significantly lower for both proton and carbon, while the correlation coefficients compared to 1b and 2bare larger, 0.93 or better. Therefore, the structures of vescalagin is 1b and castalagin is 2b.


Figure 1. B3LYP/6-31G(d,p) optimized geometries of the lowest energy conformers of 1b and 2b.


(1) Matsuo, Y.; Wakamatsu, H.; Omar, M.; Tanaka, T. "Reinvestigation of the Stereochemistry of the C-Glycosidic Ellagitannins, Vescalagin and Castalagin," Org. Lett. 201417, 46-49, DOI: 10.1021/ol503212v.


1: InChI=1S/C41H26O26/c42-8-1-5-12(24(48)21(8)45)13-6(2-9(43)22(46)25(13)49)39(60)65-34-11(4-63-37(5)58)64-38(59)7-3-10(44)23(47)26(50)14(7)15-18-16(28(52)32(56)27(15)51)17-19-20(30(54)33(57)29(17)53)31(55)35(66-41(19)62)36(34)67-40(18)61/h1-3,11,31,34-36,42-57H,4H2/t11-,31-,34+,35+,36-/m0/s1
2: InChI=1S/C41H26O26/c42-8-1-5-12(24(48)21(8)45)13-6(2-9(43)22(46)25(13)49)39(60)65-34-11(4-63-37(5)58)64-38(59)7-3-10(44)23(47)26(50)14(7)15-18-16(28(52)32(56)27(15)51)17-19-20(30(54)33(57)29(17)53)31(55)35(66-41(19)62)36(34)67-40(18)61/h1-3,11,31,34-36,42-57H,4H2/t11-,31+,34+,35+,36-/m0/s1

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

Monday, March 9, 2015

Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: computing infrastructure and collective properties

Tamara Husch, Nusret Duygu Yilmazer, Andrea Balducci and Martin Korth, Phys. Chem. Chem. Phys., 2015,17, 3394-3401
Contributed by Tobias Schwabe

If you are among those who (like me) follow from time to time what is going on in volunteer computing for Computational Chemistry, you might be well aware of the first projects in this field: QMC@home (see: It's been a little bit quiet around there lately but now it seems Martin Korth and his team are setting the stage for a new project for the QMC@home community: The foundations for that are laid out in their recent PCCP paper. aims at supporting the development of better batteries for electric cars. As a first starting point, finding new electrolytes has been chosen as target – certainly a good choice as this idea is quite in vogue right now: e.g. see this JPC/C Feature Article (which, by the way, also shows the usage of the very interesting projected WFT-in-DFT embedding method to get accurate results for large complex systems)[1]. And for a more general overview, you can check some recent reviews about Computational Chemistry in this field [2,3].

Husch et al. make an interesting contribution here because they attack the problem by virtual HTS, one of the few studies where this idea is not “just” applied for drug discovery. Especially, they tackle the problem of collective properties. Their pilot studies show already some promising results. For example, they found nitriles to be potential electrolytes, which have also attracted some interest from experimental side.


[1] Taylor A. Barnes, Jakub W. Kaminski, Oleg Borodin, and Thomas F. Miller, III, J. Phys. Chem. C 2015, 119, 3865−3880, DOI: 10.1021/jp510882g

[2] Mahesh Datt Bhatt and Colm O’Dwyer, Phys. Chem. Chem. Phys., 2015, 17, 4799—4844, DOI: 10.1039/c4cp05552g

[3] Martin Korth, in Specialist Periodical Reports: Chemical Modeling: Applications and Theory, ed. M. Springborg and J.-O. Joswig, Royal Society of Chemistry, London, UK, 2014

Wednesday, March 4, 2015

Selected publications of Stefan Grimme, Leibniz prize winner 2015

Contributed by Martin Korth

Yesterday, Stefan Grimme received a Leibniz prize, which is awarded by the German Research Foundation DFG every year to ten outstanding German scientists across all(!) fields and including a research grant of 2.5 million Euro each (probably the reason why it is called the 'German Nobel prize'):

Only a handful of theoretical chemists can boast to have one dangling over their Victorian fireplace; S. Peyerimhoff (1989), H.-J. Werner (2000), J. Gauß (2005), F. Neese (2010) - probably a club few would mind to join. Other chemists who have received the prize include H. Michel, G. Ertl, H. Schwarz, F. Schüth, ... - again not the usual bunch. (Like Philosophy? J. Habermas got one in 1986, Historical Science? J. Osterhammel did it in 2010, ... just look up the list on Wikipedia)

In honor of Grimme winning the prize, this highlight is devoted to a selection of his papers, with a focus on method development. He is of course already a well-known figure in our community (being amongst the 200 most cited chemists now), but not everyone might be aware of the breadth also of his methodological work - though CCH did it's best with no less than 7 Highlights devoted to his work over the last 3 years!

Here's the list:

DFT/MRCI 1996 1998
Spin-scaled methods 2003a 2003b (2012 review)
DFT-D 2004 2006 2010 - see CompChemHighlight (2011 review)
Double Hybrid functionals 2006a 2006b 2007a 2007b (2014 review)
gCP 2012 - see CompChemHighlight
Supramolecular binding 2012 - see CompChemHighlight
HF-3c 2013 - see  CompChemHighlight
QCEIMS 2013 - see CompChemHighlight 2014
simplified TDA 2013 2014
QMDFF 2014 - see CompChemHighlight
Crystal structure prediction 2014a 2014b

And the bonus numbers are:

Do special pi-pi interactions exist? 2008
Why not to use B3LYP/6-31G* 2012
Dispersion effects 2013 (amongst many other papers on this topic) - see CompChemHighlight
GMTKN benchmark databases 2010 2011 - is anyone NOT using them?

Congratulations to Stefan Grimme, we're looking forward to extend the list!