Wednesday, July 19, 2017

The Structure of the Elusive Simplest Dipeptide Gly-Gly

Cabezas, C.; Varela, M.; Alonso, J. L., Angew. Chem. Int. Ed. 2017, 56, 6420-6425
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Continuing their application of laser ablation molecular beam Fourier transform microwave (LA-MB-FTMW) spectroscopy and computational chemistry to biochemical molecules (see these previous posts), the Alonso group reports on the structure of the glycine-glycine dipeptide 1.1 The microwave spectrum shows three different conformers. MP2/6-311++G(d,p) computations, the same method they have previously utilized for predicting geometries, revealed a number of different conformations. By matching the spectroscopic parameters obtained from the spectrum with those of the computed structures, they proposed the three conformations 1a1b, and 1c, shown in Figure 1.

1a

1b

1c
Figure 1. ωb97xd/6-31G(d) optimized structures of the three conformers of 1.
Note that the authors did not report their structures in their supporting materials(!) so I have optimized them.

The structures of conformers 1a and 1b are nearly planar. MP2 predicts a non-planar rotomer of 1a, which brings the carboxyl group out of plane, to be the lowest conformation in terms of electronic energy. With the M06-2x functional, this non-planar rotomer is about isoenergetic with 1a. With all computational levels 1a is the lowest in free energy. The barrier for rotation between the non-planar rotomer and 1a is very small, and this explains why it is not observed in the supersonic expansion.

References

1) Cabezas, C.; Varela, M.; Alonso, J. L., "The Structure of the Elusive Simplest Dipeptide Gly-Gly." Angew. Chem. Int. Ed. 2017, 56, 6420-6425, DOI: 10.1002/anie.201702425.

InChIs

1: InChI=1S/C4H8N2O3/c5-1-3(7)6-2-4(8)9/h1-2,5H2,(H,6,7)(H,8,9)
InChIKey=YMAWOPBAYDPSLA-UHFFFAOYSA-N


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Tuesday, July 18, 2017

Development of a 13C NMR Chemical Shift Prediction Procedure Using B3LYP/cc-pVDZ and Empirically Derived Systematic Error Correction Terms: A Computational Small Molecule Structure Elucidation Method

Xin, D.; Sader, C. A.; Chaudhary, O.; Jones, P.-J.; Wagner, K.; Tautermann, C. S.; Yang, Z.; Busacca, C. A.; Saraceno, R. A.; Fandrick, K. R.; Gonnella, N. C.; Horspool, K.; Hansen, G.; Senanayake, C. H., J. Org. Chem. 2017, ASAP
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission


Here’s another take on automating a procedure for using computer 13C chemical shifts to assess chemical structure.1 (Have a look at these previous posts for some alternative methods and applications.) The approach here is to benchmark a few computational methods against a conformationally flexible drug-like molecule, in this case 1. A variety of conformations were optimized using the different computational methods, and 13C chemical shifts evaluated from a Boltzmann-weighted distribution. While the best agreement with the experimental chemical shifts (based on the root-mean-squared deviation) is with ωB97XD/cc-pVDZ, the authors opt for B3LYP/cc-pVDZ for its computational efficiency with only slightly poorer performance. (It should be note that WC04/cc-pVDZ, a functional designed for computing 13chemical shifts,2 is almost as good as ωB97XD/cc-pVDZ. Also, not mentioned in the article is the dramatically poorer performance of the pcS-2 basis set, despite the fact that it was parametrized3 for NMR computation!)
They apply the procedure to a number of test cases. For example, the HIV-1 reverse transcriptase inhibitor nevirapine hydrolyzes to a compound whose structure has been difficult to identify. The four proposed structures 2a-d were subjected to the computational method, and the 13C chemical shift RMSD for 2d is only 2.3ppm, significantly smaller than for the other 3 structures. Compound 2d was then synthesized and its NMR matches that of the nevirapine hydrolysis product.


References

1) Xin, D.; Sader, C. A.; Chaudhary, O.; Jones, P.-J.; Wagner, K.; Tautermann, C. S.; Yang, Z.; Busacca, C. A.; Saraceno, R. A.; Fandrick, K. R.; Gonnella, N. C.; Horspool, K.; Hansen, G.; Senanayake, C. H., "Development of a 13C NMR Chemical Shift Prediction Procedure Using B3LYP/cc-pVDZ and Empirically Derived Systematic Error Correction Terms: A Computational Small Molecule Structure Elucidation Method." J. Org. Chem. 2017, ASAP, DOI: 10.1021/acs.joc.7b00321.
2) Wiitala, K. W.; Hoye, T. R.; Cramer, C. J., “Hybrid Density Functional Methods Empirically Optimized for the Computation of 13C and 1H Chemical Shifts in Chloroform Solution,” J. Chem. Theory Comput. 20062, 1085-1092, DOI: 10.1021/ct6001016.
3) Jensen, F., “Basis Set Convergence of Nuclear Magnetic Shielding Constants Calculated by Density Functional Methods,” J. Chem. Theory Comput.20084, 719-727, DOI: 10.1021/ct800013z.


InChIs

1: InChI=1S/C24H26F4N2O4S/c1-4-35(33,34)18-7-8-20-15(10-18)9-17(30-20)13-23(32,24(26,27)28)22(2,3)12-14-5-6-16(25)11-19(14)21(29)31/h5-11,30,32H,4,12-13H2,1-3H3,(H2,29,31)/t23-/m0/s1
InChIKey=ILKZCEOVIFOUBJ-QHCPKHFHSA-N
2d: InChI=1S/C15H16N4O2/c1-9-6-8-17-14(18-10-4-5-10)12(9)19-13-11(15(20)21)3-2-7-16-13/h2-3,6-8,10H,4-5H2,1H3,(H,16,19)(H,17,18)(H,20,21)
InChIKey=ZLFOGBWAZNUXAD-UHFFFAOYSA-N

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Monday, July 10, 2017

Does Proton Conduction in the Voltage-Gated H+ Channel hHv1 Involve Grotthuss-Like Hopping via Acidic Residues?

Siri C. van Keulen, Eleonora Gianti, Vincenzo Carnevale, Michael L. Klein, Ursula Rothlisberger, and Lucie Delemotte (2017)
Contributed by Dries Van Rompaey



Voltage gated proton channels are membrane channels that are are regulated by both the pH gradient and the voltage. In most cases these channels only open when the electrochemical proton gradient is outwards, functioning as a passive acid extrusion mechanism. They have an exquisite selectivity for protons, prompting Delemotte and coworkers to investigate the mechanism of proton transport and the origin of this selectivity.

The mechanism for proton transport was explored using an integrative approach, combining classical simulations with QM/MM. Three separate cation binding sites can be observed in the channel, each consisting of a pair of negatively charged residues. QM/MM simulations were used to examine binding and unbinding of the proton, while conformational rearrangements were sampled using classical simulation. In contrast to the classic Grotthus mechanism, where the proton is transported through a water wire by subsequent bond formation and bond breaking, simulations indicated that the proton may traverse the channel by jumping between the acidic residues, assisted by a water molecule. As shown by classical MD, structural rearrangements occur upon proton binding, orienting the residues for the next proton jump, allowing for the proton to move through the channel. This integrative modelling study provides an interesting and novel mechanism for the transfer of a proton across a membrane. It will be interesting to see where future work on this channel leads.

Sunday, June 25, 2017

A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models

Highlighted by Jan Jensen

Figure 1: The key difference in using deep learning algorithms as a machine learning tool as opposed to a “machine intelligence” tool is the assistance, augmentation and possible replacement, for human-led tasks like feature engineering in computational chemistry.

A lot of machine learning research in chemistry is focussed on finding the best descriptors for the property of interest.  This paper shows that simply using 2D images of molecules leads to similarly accurate predictions of solvation free energies, in vitro HIV activity, and in vivo toxicity. 

This seems to me an appropriate "null-model" that all machine learning studies should include. Another option would be SMILES strings or some representation thereof. If your fancy descriptor doesn't lead to significantly better predictions then it's back to the drawing board.

The manuscript doesn't mention code availability but one of the co-authors tells me that they plan to make to code available when it is ready.

Saturday, June 24, 2017

London Dispersion Enables the Shortest Intermolecular Hydrocarbon H···H Contact.

Rösel, S.; Quanz, H.; Logemann, C.; Becker, J.; Mossou, E.; Cañadillas-Delgado, L.; Caldeweyher, E.; Grimme, S.; Schreiner, P. R.,  J. Am. Chem. Soc. 2017, 139, 7428–7431
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Following on previous work (see these posts on ladderane and hexaphenylethane), Schreiner, Grimme and co-workers have examined the structure of the all-meta tri(di-t-butylphenyl)methane dimer 12.1 In the study of hexaphenylethane,2 Schreiner and Grimme note that t-butyl groups stabilize highly congested structures through dispersion, identifying them as “dispersion energy donors”.3 The idea here is that the dimer of 1 will be stabilized by these many t-butyl groups. In fact, the neutron diffraction study of the crystal structure of 12 shows an extremely close approach of the two methane hydrogens of only 1.566 Å, the record holder for the closest approach of two formally non-bonding hydrogen atoms.


To understand the nature of this dimeric structure, they employed a variety of computational techniques. (Shown in Figure 1 is the B3LYPD3ATM(BJ)/def2-TZVPP optimized geometry of 12.) The HSE-3c (a DFT composite method) optimized crystal structure predicts the HH distance is 1.555 Å. The computed gas phase structure lengthens the distance to 1.634 Å, indicating a small, but essential, role for packing forces. Energy decomposition analysis of 12 at B3LYP-D3ATM(BJ)/def2-TZVPP indicates a dominant role for dispersion in holding the dimer together. While 12 is bound by about 8 kcal mol-1, the analogue of 12lacking all of the t-butyl groups (the dimer of triphenylmethane 22) is unbound by over 8 kcal mol-1. Topological electron density analysis does show a bond critical point between the two formally unbound hydrogen atoms, and the noncovalent interaction plot shows an attractive region between these two atoms.

Figure 1ATM(BJ)/def2-TZVPP optimized geometry of 12, with most of the hydrogens suppressed for clarity. (Selecting the molecule will launch Jmol with the full structure, including the hydrogens.)


References

1) Rösel, S.; Quanz, H.; Logemann, C.; Becker, J.; Mossou, E.; Cañadillas-Delgado, L.; Caldeweyher, E.; Grimme, S.; Schreiner, P. R., "London Dispersion Enables the Shortest Intermolecular Hydrocarbon H···H Contact." J. Am. Chem. Soc. 2017139, 7428–7431, DOI: 10.1021/jacs.7b01879.
2) Grimme, S.; Schreiner, P. R., "Steric Crowding Can Stabilize a Labile Molecule: Solving the Hexaphenylethane Riddle." Angew. Chem. Int. Ed. 2011, 50 (52), 12639-12642, DOI: 10.1002/anie.201103615.
3) Grimme, S.; Huenerbein, R.; Ehrlich, S., "On the Importance of the Dispersion Energy for the Thermodynamic Stability of Molecules." ChemPhysChem 2011, 12 (7), 1258-1261, DOI: 10.1002/cphc.201100127.


InChIs

1: InChI=1S/C43H64/c1-38(2,3)31-19-28(20-32(25-31)39(4,5)6)37(29-21-33(40(7,8)9)26-34(22-29)41(10,11)12)30-23-35(42(13,14)15)27-36(24-30)43(16,17)18/h19-27,37H,1-18H3
InChIKey=VFNQDWKFTWSJAU-UHFFFAOYSA-N

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Saturday, June 10, 2017

Dynamic Effects Responsible for High Selectivity in a [3,3] Sigmatropic Rearrangement Featuring a Bispericyclic Transition State

Villar López, R.; Faza, O. N.; Silva López, C., J. Org. Chem. 2017, 82 (9), 4758-4765
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Bispericyclic reactions occur when two different pericyclic reactions merge to have a single transition state. An example of this is the joining of two [3,3]-sigmatopic rearrangements of 1 that merge to have a single transition state. Lopez, Faza, and Lopez have examined the dynamics of this reaction.1


Because of the symmetry of the species along this reaction pathway, the products of the two different rearrangements are identical, and will be formed in equal amounts, though they are produced from a single transition state with the reaction pathway bifurcating due to a valley-ridge inflection post TS.

The interesting twist that is explored here is when 1 is substituted in order to break the symmetry. The authors have examined 3x with either fluorine, chlorine, or bromine. The critical points on the reactions surface were optimized at M06-2X/Def2TZVPP. In all three cases a single bispericyclic transition state 3TS1x is found, which leads to products 4a and 4b. A second transition state 4TSx corresponds to the [3,3]-rearrangement that interconverts the two products. The structures of 1TS3TS1F, and 3TS1Cl are shown in Figure 1.

1TS

3TS1F

3TS1Cl
Figure 1. M06-2X/Def2TZVPP optimized geometries of 1TS3TS1F, and 3TS1Cl.

The halogen substitution breaks the symmetry of the reaction path. This leads to a number of important changes. First, the C4-C5 and C7-C8 distances, which are identical in 1TS, are different in the halogen cases. Interestingly, the distortions are dependent on the halogen: in 3TS1F C4-C5 is 0.2 Å longer than C7-C8, but in 3TS1Cl C7-C8 is much longer (by 0.65 Å) than C4-C5. Second, the products are no longer equivalent with the halogen substitution. Again, this is halogen dependent: 4bF is 4.0 kcal mol-1 lower in energy than 4aF, while 4aCl is 8.2 kcal mol-1 lower than 4bCl.

These difference manifest in very different reaction dynamics. With trajectories initiated at the first (bispericyclic) transiting state, 89% end at 4bF and 9% end at 4aF, a ratio far from unity that might be expected from both products resulting from passage through the same TS. The situation is even more extreme for the chlorine case, where all 200 trajectories end in 4aCl. This is yet another example of the role that dynamics play in reaction outcomes (see these many previous posts).


References

1) Villar López, R.; Faza, O. N.; Silva López, C., "Dynamic Effects Responsible for High Selectivity in a [3,3] Sigmatropic Rearrangement Featuring a Bispericyclic Transition State." J. Org. Chem. 2017, 82 (9), 4758-4765, DOI: 10.1021/acs.joc.7b00425.


InChIs

1: InChI=1S/C9H12/c1-3-9-6-4-8(2)5-7-9/h1-2,4-7H2
InChIKey=RRXCPJIEZVQPSZ-UHFFFAOYSA-N
2: InChI<=1S/C9H12/c1-7-4-5-8(2)9(3)6-7/h1-6H2
InChIKey=AMBNQWVPTPHADI-UHFFFAOYSA-N
3F: InChI=1S/C9H8F4/c1-3-7-5-4-6(2)8(10,11)9(7,12)13/h1-2,4-5H2
InChIKey=VZFAQFJKHDWJDN-UHFFFAOYSA-N
3Cl: InChI=1S/C9H8Cl4/c1-3-7-5-4-6(2)8(10,11)9(7,12)13/h1-2,4-5H2
InChIKey=AIVUHFMHIMNOJB-UHFFFAOYSA-N
4aF: InChI=1S/C9H8F4/c1-5-4-6(8(10)11)2-3-7(5)9(12)13/h1-4H2
InChIKey=NAUUHIHYMAOMIF-UHFFFAOYSA-N
4aCl: InChI=1S/C9H8Cl4/c1-5-4-6(8(10)11)2-3-7(5)9(12)13/h1-4H2
InChIKey=MMCKDJXQYSGQEH-UHFFFAOYSA-N
4bF: InChI=1S/C9H8F4/c1-5-4-6(2)8(10,11)9(12,13)7(5)3/h1-4H2
InChIKey=LMFNAIRCNARWSX-UHFFFAOYSA-N
4bCl: InChI=1S/C9H8Cl4/c1-5-4-6(2)8(10,11)9(12,13)7(5)3/h1-4H2
InChIKey=NOFFASDSCUGRTP-UHFFFAOYSA-N

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Saturday, May 27, 2017

Synthesis of a carbon nanobelt

Povie, G.; Segawa, Y.; Nishihara, T.; Miyauchi, Y.; Itami, K. Science 2017, 356, 172-175
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

The synthesis of components of nanostructures (like fullerenes and nanotubes) has dramatically matured over the past few years. I have blogged about nanohoops before, and this post presents the recent work of the Itami group in preparing the nanobelt 1.1

1

The synthesis is accomplished through a series of Wittig reactions with an aryl-aryl coupling to stitch together the final rings. The molecule is characterized by NMR and x-ray crystallography. The authors have also computed the structure of 1 at B3LYP/6-31G(d), shown in Figure 1. The computed C-C distances match up very well with the experimental distances. The strain energy of 1, presumably estimated by Reaction 1,2 is computed to be about 119 kcal mol-1.

1
Figure 1. B3LYP/6-31G(d) optimized structure of 1.
Rxn 1
NICS(0) values were obtained at B3LYP/6-311+G(2d,p)//B3LYP/6-31G(d); the rings along the middle of the belt have values of -7.44ppm and are indicative of normal aromatic 6-member rings, while the other rings have values of -2.00ppm. This suggests the dominant resonance structure shown below:

References

1) Povie, G.; Segawa, Y.; Nishihara, T.; Miyauchi, Y.; Itami, K., "Synthesis of a carbon nanobelt." Science 2017, 356, 172-175, DOI: 10.1126/science.aam8158.
2) Segawa, Y.; Yagi, A.; Ito, H.; Itami, K., "A Theoretical Study on the Strain Energy of Carbon Nanobelts." Org. Letters 2016, 18, 1430-1433, DOI: 10.1021/acs.orglett.6b00365.

InChIs:

1: InChI=1S/C48H24/c1-2-26-14-40-28-5-6-31-20-44-32(19-42(31)40)9-10-34-24-48-36(23-46(34)44)12-11-35-21-45-33(22-47(35)48)8-7-30-17-41-29(18-43(30)45)4-3-27-15-37(39(26)16-28)25(1)13-38(27)41/h1-24H
InChIKey=KJWRWEMHJRCQKK-UHFFFAOYSA-N



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