Sunday, February 12, 2017

Conformer-specific hydrogen atom tunnelling in trifluoromethylhydroxycarbene

Mardyukov, A.; Quanz, H.; Schreiner, P. R., Nat. Chem. 2017, 9, 71–76
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

The Schreiner group has again reported an amazing experimental and computational study demonstrating a fascinating quantum mechanical tunneling effect, this time for the trifluoromethylhydroxycarbene (CF3COH) 2.1 (I have made on a number of posts discussing a series of important studies in this field by Schreiner.) Carbene 2 is formed, in analogy to many other hydroxycarbenes, by flash vapor pyrolysis of the appropriate oxoacid 1 and capturing the products on a noble gas matrix.

Carbene 2t is observed by IR spectroscopy, and its structure is identified by comparison with the computed CCSD(T)/cc-pVTZ frequencies. When 2t is subjected to 465 nm light, the signals for 2t disappear within 30s, and two new species are observed. The first species is the cis conformer 2c, confirmed by comparison with its computed CCSD(T)/cc-pVTZ frequencies. This cis conformer remains even with continued photolysis. The other product is determined to be trifluoroacetaldehyde 3. Perhaps most interesting is that 2t will convert to 3 in the absence of light at temperatures between 3 and 30 K, with a half-life of about 144 h. There is little rate difference at these temperatures. These results are quite indicative of quantum mechanical tunneling.

To aid in confirming tunneling, they computed the potential energy surface at CCSD(T)/cc-pVTZ. The trans isomer is 0.8 kcal mol-1 lower in energy that the cis isomer, and this is much smaller than for other hydroxycarbenes they have examined. The rotational barrier TS1 between the two isomer is quite large, 26.4 kcal mol-1, precluding their interchange by classical means at matrix temperatures. The barrier for conversion of 2t to 3 (TS2) is also quite large, 30.7 kcal mol-1, and insurmountable at 10K by classical means. No transition state connecting 2c to 3 could be located. These geometries and energies are shown in Figure 1.





Figure 1. Optimized geometries at CCSD(T)/cc-pVTZ. Relative energies (kcal mol-1) of each species are listed as well.

WKB computations at M06-2X/6-311++G(d,p) predict a half-life of 172 h, in nice agreement with experiment. The computed half-life for deuterated 2t is 106 years, and the experiment on the deuterated analogue revealed no formation of deuterated 3.

The novel component of this study is that tunneling is conformationally selective. The CF3 group stabilizes the cis form probably through some weak HF interaction, so that the cis isomer can be observed, but no tunneling is observed from this isomer. Only the trans isomer has the migrating hydrogen atom properly arranged for a short hop over to the carbon, allowing the tunneling process to take place.


1) Mardyukov, A.; Quanz, H.; Schreiner, P. R., "Conformer-specific hydrogen atom tunnelling in trifluoromethylhydroxycarbene." Nat. Chem. 20179, 71–76, DOI: 10.1038/nchem.2609.


1: =1S/C3HF3O3/c4-3(5,6)1(7)2(8)9/h(H,8,9)
2: InChI=1S/C2HF3O/c3-2(4,5)1-6/h6H
3: InChI=1S/C2HF3O/c3-2(4,5)1-6/h1H

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Sunday, January 22, 2017

Crystal Structure Determination of the Pentagonal-Pyramidal Hexamethylbenzene Dication C6(CH3)62+

Malischewski, M.; Seppelt, K., Angew. Chem. Int. Ed. 2017, 56, 368-370
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Hypercoordinated carbon has fascinated chemists since the development of the concept of the tetravalent carbon. The advent of superacids has opened up the world of hypercoordinated species and now a crystal structure of a hexacoordinated carbon has been reported for the C6(CH3)62+ species 1.1

The molecule is prepared by first epoxidation of hexamethyl Dewar benzene, followed by reaction with Magic acid, and crystallized by the addition of HF. The crystal structure shows a pentamethylcyclopentadienyl base capped by a carbon with a methyl group. The x-ray structure is well reproduced by the B3LYP/def2-TZVP structure shown in Figure 1. (While this DFT method predicts a six-member isomer to be slightly lower in energy, MP2 does predict the cage as the lowest energy isomer.)

Figure 1. B3LYP/def2-TZVP optimized geometry of 1.

The Wiberg bond order for the bond between the capping carbon and each carbon of the five-member base is about 0.54, so the sum of the bond orders to the apical carbon is less than 4. The carbon is therefore not hypervalent, but it appears to truly be hypercoordinate. (A topological electron density analysis (AIM) study would have been interesting here.) NICS analysis indicates the cage formed by the apical carbon and the five-member ring expresses 3-D aromaticity. This can be thought of as coming from the C5(CH3)5+ fragment with its 4 electrons and the CCH3+ fragment with two electrons, providing 4+ 2 = 6 electrons for the aromatic cage.


1) Malischewski, M.; Seppelt, K., "Crystal Structure Determination of the Pentagonal-Pyramidal Hexamethylbenzene Dication C6(CH3)62+Angew. Chem. Int. Ed. 2017, 56, 368-370, DOI: 10.1002/anie.201608795.

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Acetyl-CoA carboxylase inhibition by ND-630 reduces hepatic steatosis, improves insulin sensitivity, and modulates dyslipidemia in rats

Harriman, G., Greenwood, J., Bhat, S., Huang, X., Wang, R., Paul, D., Tong, L., Saha, A.K., Westlin, W.F., Kapeller, R. and Harwood, H.J., (2016)
Contributed by Jan Jensen

This paper describes the development of ND-630 (aka NDI-010976) which is currently in Phase 2 clinical trials and could help cure a serious liver disease called non-alcoholic steatohepatitis and potentially other diseases. I am highlighting it here because computational chemistry had a lot to do with its discovery both directly and indirectly.

The development of ND-630 is spearheaded by Nimbus Therapeutics, which is basically an off-shoot of Schrödinger, i.e. a company that uses Schrödinger's software to discover new drugs. One of the co-founders (at the VC company Atlas) writes:
Back in the spring of 2009, Atlas (where I'm a partner) founded the company with Schrödinger, a leading computational chemistry software company, after almost a year-long dialogue between myself and Ramy Farid, Schrödinger’s president. At this time, Schrödinger was launching a novel computational tool called WaterMap, an apt name for a technology that maps the energetics of water sites at the receptor-ligand interface, providing a potential roadmap for efficient ligand-receptor interactions. As this cutting-edge technology catalyzed some of our initial thinking, we called it Project Troubled Water Inc (PTW) for the first year or so. 
So in a way, this is also highlight of this article. To summarise: the company was founded because these people believed in computational chemistry as the main driving force behind drug discovery. Did the success of ND-630 prove them right?

Here's how they discovered ND-630 according to the article. They started with the crystal structure of Acetyl-CoA carboxylase with the natural product Soraphen A bound and identified two pockets with high-energy hydration sites using SiteMap and then WaterMap. Then they did a structure-based virtual screen of commercially available compounds using GlideXP and kept only compounds that hit the high-energy hydration sites in both pockets. Soraphen A and these compounds where then used to build two pharmacophore models, which, in turn, where used for a ligand-based virtual screen with hits further refined with GlideXP. "A combined virtual hit-list of a few thousand compounds was clustered to maximize diversity, and 300 representatives were chosen after visualization of the poses. This process led to the identification of ND-022 ... Subsequently, lead optimization proceeded rapidly, guided by WaterMap and Prime/MM-GBSA v. 2.2 estimates of binding free energy." Which finally led to ND-630.

So not exactly Derek Lowe's unicorn dream come true, but I think it's fair to call this computer aided drug design.

Thanks to Victor Guallar for bringing the article to my attention.

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Saturday, January 7, 2017

A Thermally Populated, Perpendicularly Twisted Alkene Triplet Diradical

Wentrup, C.; Regimbald-Krnel, M. J.; Müller, D.; Comba, P., Angew. Chem. Int. Ed. 2016, 55, 14600-1460
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Wentrup and co-workers examined the strained, non-planar aromatic 1.1

The UKS-BP86-D3BJ/def2-TZVP optimized geometry of the singlet 1 is shown in Figure 1. The molecule is decidedly twisted, with an angle of about 52°. This large twist, weakening the π-bond between the two aromatic fragments, suggests that the triplet state of 1 might be easily accessible. The geometry of 31 is also shown in Figure 1, and the two aromatic portions are orthogonal.


Figure 1. UKS-BP86-D3BJ/def2-TZVP optimized geometries of 11 and 31.

The proton and 13C NMR studies of 1 show increasing paramagnetism, observed as line broadening, with increasing temperature. Confirming this is ESR which shows increasing signal with increasing temperature. The triplet state is clearly present. The experimental ΔEST=9.6 kcal mol-1 and the computed singlet-triplet gap is 9.3 kcal mol-1. This is in excellent agreement, and much better than previous computations which predict a gap of 3.4 kcal mol-1, but omitted the D3 correction. This dispersion correction stabilizes the singlet state over the triplet state, as might be expected. (The triplet has the two aromatic components orthogonal and so they have minimal dispersion interactions, while the aromatic planes are much closer in the singlet state.)

For comparison, the computed ΔEST of isomer 2 is much larger: 17.9 kcal mol-1. The energies of the triplet states of 1 and 2 are nearly identical. Both of these structures have orthogonal, non-interacting aromatic moieties. However, the energy of 12 with the twist angles of 11 is 8.2 kcal mol-1 lower than that of 11. This the twisting causes a significant strain to the singlet state, but not to the triplet, and that gives rise to its small singlet-triplet gap.


1) Wentrup, C.; Regimbald-Krnel, M. J.; Müller, D.; Comba, P., "A Thermally Populated, Perpendicularly Twisted Alkene Triplet Diradical." Angew. Chem. Int. Ed. 2016, 55, 14600-14605, DOI: 10.1002/anie.201607415.


1: InChI=1S/C42H24/c1-5-13-29-25(9-1)17-21-33-34-22-18-26-10-2-6-14-30(26)38(34)41(37(29)33)42-39-31-15-7-3-11-27(31)19-23-35(39)36-24-20-28-12-4-8-16-32(28)40(36)42/h1-24H
2: InChI=1S/C42H24/c1-5-13-29-21-37-33(17-25(29)9-1)34-18-26-10-2-6-14-30(26)22-38(34)41(37)42-39-23-31-15-7-3-11-27(31)19-35(39)36-20-28-12-4-8-16-32(28)24-40(36)42/h1-24H

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Wednesday, December 28, 2016

Ultra-fast computation of electronic spectra for large systems by tight-binding based simplified Tamm-Dancoff approximation (sTDA-xTB)

Stefan Grimme and Christoph Bannwarth (2016)
Contributed by Jan Jensen

Grimme and Bannwarth presents the xTB method, a modified DFTB2 (SCC-DFTB) method combined with Grimme's simplified Tamm-Dancoff  approximated (sTDA) TD-DFT procedure for the rapid calculations of electronic spectra.  The two main modifications are 1) the addition of diffuse basis functions for some elements to accurately describe Rydberg states and 2) the SCF is replaced by a single diagonalization and the atomic-charge dependent term is evaluated only once using specifically designed charges. The method is parameterized against CC and DFT calculations for all elements up to Zn and more elements are in the works.

SCS-CC2/aug-cc-VXZ (X = T or D depending on molecule size) vertical singlet-singlet excitation energies are reproduced with a MAE of 0.27 eV.  For comparison, the corresponding MAEs for TD-PBE/def2-TZVP and TD-PBE0/def2-SV(P) are 0.67 and 0.31 eV.  The method also yields reasonably accurate ECD spectra.  

The method is quite fast requiring only a few minutes of CPU time for molecules with 500-1000 atoms. A very recent paper uses an as-yet-unpublished variant called GFN-xTB to perform an single point calculation on a P450 enzyme (7,500 atoms) without recourse to fragmentation.

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Friday, December 16, 2016

Evidence of a Nitrene Tunneling Reaction: Spontaneous Rearrangement of 2-Formyl Phenylnitrene to an Imino Ketene in Low-Temperature Matrixes

Nunes, C. M.; Knezz, S. N.; Reva, I.; Fausto, R.; McMahon, R. J.,  J. Am. Chem. Soc. 2016, 138, 15287-15290
Contributed by Steven Bachrach
Reposted from Computational Organic Chemistry with permission

Reva and McMahon report a very nice experimental and computational study implicating hydrogen atom tunneling in the rearrangement of the nitrene 1 into the ketene 2.1 The reaction is carried out by placing azide 3 in an argon matrix and photolyzing it. The IR shows that at first a new compound A is formed and that over time the absorptions of A erode and those of a second compound B grow in. This occurs whether the photolysis continues or not over time.

IR spectra were computed at B3LYP/6-311++G(d,p) for compounds 31 and 2 and they match up very well with the recorded spectra of A and B, respectively. The triplet state of nitrenes are typically about 20 kcal mol-1 lower in energy than the singlet states. The EPR spectrum confirms that 1 is a triplet.
So how does the conversion of 31 into 2 take place, especially at 10 K? The rate constant for this conversion at 10 K is estimated as 1 x 10-5 s-1, which implies a barrier from classical transition state theory of only 0.2 kcal mol-1. That low a barrier seems preposterous, and suggests that the reaction may proceed via tunneling. This notion is supported by the experiment on the deuterated analogue, which shows no conversion of 1D into 2D.

The authors propose that 31 undergoes a hydrogen migration on the triplet surface through transition state 34 to give 32, which then undergoes intersystem crossing to give singlet 2. The structures of these critical points calculated at B3LYP/6-311++G(d,p) are shown in Figure 1. The computed activation barrier is 20.7 kcal mol-1. (The barrier height ranges from 16.7 to 23.0 with a variety of different computational methods.) This large barrier precludes a classical over-the-top reaction and points towards tunneling. The barrier width is estimated at about 2.1 Å. WKB computations estimate the tunneling half time of about 21 min, somewhat smaller than in the experiments, and the estimate for the deuterated species is 150,000 years.



Figure 1. B3LYP/6-311++G(d,p) optimized structures of 3132, and the TS 34.


1) Nunes, C. M.; Knezz, S. N.; Reva, I.; Fausto, R.; McMahon, R. J., "Evidence of a Nitrene Tunneling Reaction: Spontaneous Rearrangement of 2-Formyl Phenylnitrene to an Imino Ketene in Low-Temperature Matrixes." J. Am. Chem. Soc. 2016, 138, 15287-15290, DOI: 10.1021/jacs.6b07368.


1: InChI=1S/C7H5NO/c8-7-4-2-1-3-6(7)5-9/h1-5H
2: InChI=1S/C7H5NO/c8-7-4-2-1-3-6(7)5-9/h1-4,8H

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Wednesday, November 30, 2016

ANI-1: An extensible neural network potential with DFT accuracy at force field computational cost

Justin S. Smith, Olexandr Isayev, Adrian E. Roitberg (2016)
Contributed by Jan Jensen

This paper basically presents a neural network force field, which the authors call a neural network potential (NNP).  The authors heavily modify the Behler-Parinello symmetry functions (also used in this CCH) to improve the transferability and train it against 13.8 million ωB97X/6-31G(d) energies computed for CHON-containing molecules with 8 or less non-hydrogen atoms. This huge training set made it possible to parameterise a neural net with three hidden layers with a total of 320 nodes and 124,033 optimisable parameters.  Deep learning indeed.  

What makes this work particularly exiting is that the NNP appears to be transferable to larger molecules. For example, the figure above shows that the NNP can reproduce the relative ωB97X/6-31G(d) energies of retinol conformers with en RMSE of 0.6 kcal/mol.  For comparison the corresponding value for DFTB (not clear if it's DFTB2 or DFTB3) is 1.2 kcal/mol, although ωB97X/6-31G(d) is not the definitive reference by which to judge DFTB accuracy.

I think this work holds a lot of promise. One of the key challenges is to reduce the size of the training set to a point where high level calculations can be used to compute the energies. Alternatively, perhaps approaches like ∆-machine learning can be used to correct the NNP using a smaller representative training set.

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