Friday, October 12, 2018

Teaching an old carbocation new tricks: Intermolecular C–H insertion reactions of vinyl cations

Popov, S.; Shao, B.; Bagdasarian, A. L.; Benton, T. R.; Zou, L.; Yang, Z.; Houk, K. N.; Nelson, H. M., Science 2018, 361, 381
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

A recent paper by Papov, Shao, Bagdasarian, Benton, Zou, Yang, Houk, and Nelson uncovers a vinyl cation insertion reaction that once again involves dynamic effects.1

They find that vinyl triflates and cyclic vinyl triflates will react with [Ph3C]+[HCB11Cl11] and triethylsilane to generate vinyl cations that can then be trapped through a C-H insertion reaction. For example, cyclohexenyl triflate 1 reacts in a cyclohexane solvent to give the insertion product 2.


The reactions of isomers 3 and 4 give different ratios of the two products 5 and 6. In both cases, the cyclohexyl is trapped predominantly at the site of the triflate substituent. This means that the mechanism cannot involve a cyclohexene intermediate, since then the two ratios should be identical.


They performed molecular dynamic trajectory analysis at the M062X/6-311+G(d,p) level, starting with the two transition states leading from 3 (TS3) and 4 (TS4), the only transition states located for the insertion reaction. The structures of these TSs are shown in Figure 1.


TS3

TS4
Figure 1. M062X/6-311+G(d,p) optimized geometries of TS3 and TS4.

The trajectories end up in two product basins associated with 5 and 6 starting with either TS3 or TS4. Thus, these transition states are ambimodal, and typical of reactions where dynamic effects dominate. For the reaction of 3, the majority of the trajectories starting at TS3 end up as 5, consistent with the experiments. Similarly, for the trajectories that start at TS4, the majority end up as 6, consistent with experiments.

Once again, we see that relatively simple organic reactions do not follow simple reaction mechanisms, that a single transition state leads to two different products and the product distributions are dependent on reaction dynamics. This may not be too surprising for the vinyl cation insertions given the many examples provide by the Tantillo group of cation rearrangements that are controlled by reaction dynamics (see for examples, this post and this post).


References

1. Popov, S.; Shao, B.; Bagdasarian, A. L.; Benton, T. R.; Zou, L.; Yang, Z.; Houk, K. N.; Nelson, H. M., "Teaching an old carbocation new tricks: Intermolecular C–H insertion reactions of vinyl cations." Science2018361, 381-387, DOI: 10.1126/science.aat5440.


InChIs

1: InChI=1S/C7H10F3O3S/c8-7(9,10)14(11,12,13)6-4-2-1-3-5-6/h4H,1-3,5H2,(H,11,12,13)
InChIKey=CMPVYBNXADJVOM-UHFFFAOYSA-N
2: InChI<=1S/C12H22/c1-3-7-11(8-4-1)12-9-5-2-6-10-12/h11-12H,1-10H2
InChIKey=WVIIMZNLDWSIRH-UHFFFAOYSA-N
3: InChI=1S/C9H14F3O3S/c1-8(2)5-3-7(4-6-8)16(13,14,15)9(10,11)12/h3H,4-6H2,1-2H3,(H,13,14,15)
InChIKey=XDWBLRRAHKBZJR-UHFFFAOYSA-N
4: InChI=1S/C9H14F3O3S/c1-8(2)5-3-4-7(6-8)16(13,14,15)9(10,11)12/h4H,3,5-6H2,1-2H3,(H,13,14,15)
InChIKey=YHVCPSRICQJFDT-UHFFFAOYSA-N
5: InChI=1S/C14H26/c1-14(2)10-8-13(9-11-14)12-6-4-3-5-7-12/h12-13H,3-11H2,1-2H3
InChIKey=BZQBWUOXOYWYJC-UHFFFAOYSA-N
6: InChI=1S/C14H26/c1-14(2)10-6-9-13(11-14)12-7-4-3-5-8-12/h12-13H,3-11H2,1-2H3
InChIKey=AENMAOBTECURBO-UHFFFAOYSA-N


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

Sunday, September 30, 2018

DeepSMILES: An adaptation of SMILES for use in machine-learning of chemical structures

Highlighted by Jan Jensen



There's been a lot of work in the last few years on machine learning methods for suggesting molecules (see here and here for examples). Most of these "generative models" are trained using  SMILES representations of the molecules. But SMILES was never designed with machine learning in mind and contain features that can cause problems when doing so. The end result is that generative models suggest a lot of SMILES strings with the wrong syntax. For example CC(C(C instead of CC(C)C.

Noel and Andrew suggest a different SMILES syntax (DeepSMILES) that addresses many of these problems. Have a look at the figure above to see if you can deduce the conversion-rules and read the paper to see close you got. It will be very interesting to see whether DeepSMILES will lead to significant improvements in machine learning applications.


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

Thursday, September 27, 2018

Curved Aromatic molecules – 4 new examples

Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

I have recently been interested in curved aromatic systems – see my own paper on double helicenes.1 In this post, I cover four recent papers that discuss non-planar aromatic molecules.

The first paper2 discusses the warped aromatic 1 built off of the scaffold of depleiadene 3. The crystal structure of 1 shows the molecule to be a saddle with near C2v symmetry. B3LYP/6-31G computations indicate that the saddle isomer is 10.5 kcal mol-1 more stable than the twisted isomer, and the barrier between them is 16.0 kcal mol-1, with a twisted saddle intermediate as well.


The PES is significantly simpler for the structure lacking the t-butyl groups, 2. The B3LYP/6-31G PES of 2has the saddle as the transition state interconverting mirror images of the twisted saddle isomer, and this barrier is only 1.8 kcal mol-1. Figure 1 displays the twisted saddle and the saddle transition state. Clearly, the t-butyl groups significantly alter the flexibility of this C86 aromatic surface. One should be somewhat concerned about the small basis set employed here, especially lacking polarization functions, and a functional that lacks dispersion correction. However, the computed geometry of 1 is quite similar to that of the x-ray structure.


2 twisted saddle (ground state)

2 saddle (transition state)
Figure 1. B3LYP/6-31G optimized geometries of the isomer of 2.

The second paper presents 4, a non-planar aromatic based on [8]circulene 6.3 (See this post for a general study of circulenes.) [8]circulene has a tub-shape, but is flexible and can undergo tub-to-tub inversion. The expanded aromatic 4 is found to have a twisted shape in the x-ray crystal structure. A simplified model 5 was computed at B3LYP/6-31G(d) and the twisted isomer is 4.1 kcal mol-1 lower in energy than the saddle (tub) isomer (see Figure 2). The barrier for interconversion of the two isomers is only 6.2 kcal mol-1, indicating a quite labile structure.


5 twisted
0.0

5 TS
6.2

5 saddle
4.1
Figure 2. B3LYP/6-31G(d) optimized geometries and relative energies (kcal mol-1) of the isomers of 5.

The third paper presents a geodesic molecule based on 1,3,5-trisubstitued phenyl repeat units.4 The authors prepared 7, and its x-ray structure shows a saddle-shape. The NMR indicate a molecule that undergoes considerable conformational dynamics. To address this, they did some computations on the methyl analogue 8. The D7h structure is 309 kcal mol-1 above the local energy minimum structure, which is way too high to be accessed at room temperature. PM6 computations identified a TS only 0.6 kcal mol-1above the saddle ground state. (I performed a PM6 optimization starting from the x-ray structure, which is highly disordered, and the structure obtained is shown in Figure 3. Unfortunately, the authors did not report the optimized coordinates of any structure!)

Figure 3. PM6 optimized structure of 8.

The fourth and last paper describes the aza-buckybowl 9.5 The x-ray crystal structure shows a curved bowl shape with Cs symmetry. NICS(0) values were computed for the parent molecule 10 B3LYP/6-31G(d). These values are shown in Scheme 1 and the geometry is shown in Figure 4. The 6-member rings that surround the azacylopentadienyl ring all have NICS(0) near zero, which suggests significant bond localisation.

Scheme 1. NICS(0) values of 10
Figure 4. B3LYP/6-31G(d) optimized structure of 10.

Our understanding of what aromaticity really means is constantly being challenged!


References

1. Bachrach, S. M., "Double helicenes." Chem. Phys. Lett. 2016666, 13-18, DOI: 10.1016/j.cplett.2016.10.070.
2. Ho, P. S.; Kit, C. C.; Jiye, L.; Zhifeng, L.; Qian, M., "A Dipleiadiene-Embedded Aromatic Saddle Consisting
of 86 Carbon Atoms." Angew. Chem. Int. Ed. 201857, 1581-1586, DOI: 10.1002/anie.201711437.
3. Yin, C. K.; Kit, C. C.; Zhifeng, L.; Qian, M., "A Twisted Nanographene Consisting of 96 Carbon Atoms." Angew. Chem. Int. Ed. 201756, 9003-9007, DOI: 10.1002/anie.201703754.
4. Koki, I.; Jennie, L.; Ryo, K.; Sota, S.; Hiroyuki, I., "Fluctuating Carbonaceous Networks with a Persistent
Molecular Shape: A Saddle-Shaped Geodesic Framework of 1,3,5-Trisubstituted Benzene (Phenine)." Angew. Chem. Int. Ed. 201857, 8555-8559, DOI: 10.1002/anie.201803984.
5. Yuki, T.; Shingo, I.; Kyoko, N., "A Hybrid of Corannulene and Azacorannulene: Synthesis of a Highly Curved Nitrogen-Containing Buckybowl." Angew. Chem. Int. Ed. 201857, 9818-9822, DOI: 10.1002/anie.201805678.


InChIs

1: InChI=1S/C134H128/c1-123(2,3)57-37-65-66-38-58(124(4,5)6)42-70-74-46-62(128(16,17)18)50-82-94(74)110-106(90(66)70)105-89(65)69(41-57)73-45-61(127(13,14)15)49-81-93(73)109(105)119-113-97(81)85(131(25,26)27)53-77-78-54-87(133(31,32)33)99-83-51-63(129(19,20)21)47-75-71-43-59(125(7,8)9)39-67-68-40-60(126(10,11)12)44-72-76-48-64(130(22,23)24)52-84-96(76)112-108(92(68)72)107(91(67)71)111(95(75)83)121-115(99)103(78)118-104-80(56-88(134(34,35)36)100(84)116(104)122(112)121)79-55-86(132(28,29)30)98(82)114(120(110)119)102(79)117(118)101(77)113/h37-56H,1-36H3
InChIKey=GKUTUWMASUJSFD-UHFFFAOYSA-N
2: InChI=1S/C86H32/c1-9-33-34-10-2-14-38-42-18-6-22-46-50-26-30-55-56-32-28-52-48-24-8-20-44-40-16-4-12-36-35-11-3-15-39-43-19-7-23-47-51-27-31-54-53-29-25-49-45-21-5-17-41-37(13-1)57(33)73-74(58(34)38)78(62(42)46)84-70(50)66(55)81(65(53)69(49)83(84)77(73)61(41)45)82-67(54)71(51)85-79(63(43)47)75(59(35)39)76(60(36)40)80(64(44)48)86(85)72(52)68(56)82/h1-32H
InChIKey=MXCDWJZMTKLBDM-UHFFFAOYSA-N
3: InChI=1S/C18H12/c1-2-6-14-11-12-16-8-4-3-7-15-10-9-13(5-1)17(14)18(15)16/h1-12H
InChIKey=KVJJNMIHWIRGRP-UHFFFAOYSA-N
4: InChI=1S/C132H108O4/c1-125(2,3)53-29-65-66-30-54(126(4,5)6)34-70-74-38-58(130(16,17)18)42-78-86-46-82-63-51-91(135-27)92(136-28)52-64(63)84-48-88-80-44-60(132(22,23)24)40-76-72-36-56(128(10,11)12)32-68-67-31-55(127(7,8)9)35-71-75-39-59(131(19,20)21)43-79-87-47-83-62-50-90(134-26)89(133-25)49-61(62)81-45-85-77-41-57(129(13,14)15)37-73-69(33-53)93(65)109-110(94(66)70)114(98(74)78)122-106(86)118-103(82)104(84)120-108(88)124-116(100(76)80)112(96(68)72)111(95(67)71)115(99(75)79)123(124)107(87)119(120)102(83)101(81)117(118)105(85)121(122)113(109)97(73)77/h29-52H,1-28H3
InChIKey=ZLPRACZKLACDHX-UHFFFAOYSA-N
5: InChI=1S/C108H60O4/c1-37-13-49-50-14-38(2)18-54-58-22-42(6)26-62-70-30-66-47-35-75(111-11)76(112-12)36-48(47)68-32-72-64-28-44(8)24-60-56-20-40(4)16-52-51-15-39(3)19-55-59-23-43(7)27-63-71-31-67-46-34-74(110-10)73(109-9)33-45(46)65-29-69-61-25-41(5)21-57-53(17-37)77(49)93-94(78(50)54)98(82(58)62)106-90(70)102-87(66)88(68)104-92(72)108-100(84(60)64)96(80(52)56)95(79(51)55)99(83(59)63)107(108)91(71)103(104)86(67)85(65)101(102)89(69)105(106)97(93)81(57)61/h13-36H,1-12H3
InChIKey=ZSIVUKSPPZUSQL-UHFFFAOYSA-N
6: InChI=1S/C32H16/c1-2-18-5-6-20-9-11-22-13-15-24-16-14-23-12-10-21-8-7-19-4-3-17(1)25-26(18)28(20)30(22)32(24)31(23)29(21)27(19)25/h1-16H
InChIkey=BASWMOIVIHXTRC-UHFFFAOYSA-N
7: InChI=1S/C224H210/c1-211(2,3)197-99-169-85-183(113-197)184-86-170(100-198(114-184)212(4,5)6)157-66-149-67-158(79-157)172-88-187(117-200(102-172)214(10,11)12)188-90-174(104-202(118-188)216(16,17)18)161-70-151-71-162(81-161)176-92-191(121-204(106-176)218(22,23)24)193-95-179(109-207(123-193)221(31,32)33)165-74-153-75-166(83-165)180-96-195(125-208(110-180)222(34,35)36)196-98-182(112-210(126-196)224(40,41)42)168-77-154-76-167(84-168)181-97-194(124-209(111-181)223(37,38)39)192-94-178(108-206(122-192)220(28,29)30)164-73-152-72-163(82-164)177-93-190(120-205(107-177)219(25,26)27)189-91-175(105-203(119-189)217(19,20)21)160-69-150-68-159(80-160)173-89-186(116-201(103-173)215(13,14)15)185-87-171(101-199(115-185)213(7,8)9)156-65-148(64-155(169)78-156)141-50-127-43-128(51-141)130-45-132(55-143(150)53-130)134-47-136(59-145(152)57-134)138-49-140(63-147(154)61-138)139-48-137(60-146(153)62-139)135-46-133(56-144(151)58-135)131-44-129(127)52-142(149)54-131/h43-126H,1-42H3
InChIKey=ZDDKJXIESSWTIA-UHFFFAOYSA-N
8: InChI=1S/C182H126/c1-99-15-113-43-127(29-99)141-57-142-65-155(64-141)162-78-169-92-170(79-162)172-82-164-83-174(94-172)176-85-166-87-178(96-176)180-89-168-91-182(98-180)181-90-167-88-179(97-181)177-86-165-84-175(95-177)173-81-163(80-171(169)93-173)156-66-143(128-30-100(2)16-114(113)44-128)58-144(67-156)130-32-103(5)19-117(47-130)118-20-104(6)34-132(48-118)147-60-148(71-158(165)70-147)134-36-107(9)23-121(51-134)123-25-109(11)39-137(53-123)151-62-152(75-160(167)74-151)138-40-111(13)27-125(55-138)126-28-112(14)42-140(56-126)154-63-153(76-161(168)77-154)139-41-110(12)26-124(54-139)122-24-108(10)38-136(52-122)150-61-149(72-159(166)73-150)135-37-106(8)22-120(50-135)119-21-105(7)35-133(49-119)146-59-145(68-157(164)69-146)131-33-102(4)18-116(46-131)115-17-101(3)31-129(142)45-115/h15-98H,1-14H3
InChIKey=FJHGGHOTCCNJNI-UHFFFAOYSA-N
9: InChI=1S/C44H23N/c1-44(2,3)21-16-28-24-8-4-6-22-26-14-19-12-10-18-11-13-20-15-27-23-7-5-9-25-29(17-21)41(28)45-42(33(22)24)39-35(26)37-31(19)30(18)32(20)38(37)36(27)40(39)43(45)34(23)25/h4-17H,1-3H3
InChIKey=QHBWEZKXFSKCSM-UHFFFAOYSA-N
10: InChI=1S/C40H15N/c1-4-19-23-8-3-9-24-20-5-2-7-22-26-15-18-13-11-16-10-12-17-14-25-21(6-1)30(19)39-36-32(25)34-28(17)27(16)29(18)35(34)33(26)37(36)40(31(20)22)41(39)38(23)24/h1-15H
InChIKey=XWSUADIIRLXSBY-UHFFFAOYSA-N

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

Tuesday, September 18, 2018

Rearrangement of Hydroxylated Pinene Derivatives to Fenchone-Type Frameworks: Computational Evidence for Dynamically-Controlled Selectivity

Blümel, M.; Nagasawa, S.; Blackford, K.; Hare, S. R.; Tantillo, D. J.; Sarpong, R., J. Am. Chem. Soc. 2018, 140, 9291-9298
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Sarpong and Tantillo have examined the acid-catalyzed Prins/semipinacol rearrangement of hydroxylated pinenes, such as Reaction 1.1
Rxn 1
Interestingly, only the fenchone scaffold products, like 1, are observed and the camphor scaffold products, like 2, are not observed. Cation intermediates are likely, and this means that a primary alkyl shift is taking place in preference to a tertiary alkyl shift, see Scheme 1.

Scheme 1.

Primary alkyl shift

Tertiary alkyl shift

They proposed the following key steps in the reaction mechanism:

ωB97X-D/6-31+G(d,p) computations find a flat surface around cation intermediate 4: the TS leading to 5and 6 are only 1.3 and 3.3 kcal mol-1, respectively. Since these small barriers are quite susceptible to changes in basis set and functional, and since Tantillo has found many examples of post-transition state bifurcations in cation systems, the authors reasonably decided to conduct molecular dynamics trajectories originating at the TS connecting 3 and 4. The geometries of the critical points are shown in Figure 1.

The trajectory study shows all the usual characteristics of reactions that are under dynamic control. A third of the trajectories show recrossing of the barrier, typical of very flat surfaces. Nearly all of the remaining trajectories led to 5, with only 2 trajectories (~1%) leading to 6. The dynamics are understandable in terms of favoring the primary alkyl shift over the tertiary since a significantly smaller mass needs to move in the former case.


TS 3 → 4

4

TS 4 → 5

TS 4 → 6
Figure 1. ωB97X-D/6-31+G(d,p) optimized geometries.

This is yet another study that implicates dynamic effects in routine reactions, one of many I have discussed over the years.

References

1. Blümel, M.; Nagasawa, S.; Blackford, K.; Hare, S. R.; Tantillo, D. J.; Sarpong, R., "Rearrangement of Hydroxylated Pinene Derivatives to Fenchone-Type Frameworks: Computational Evidence for Dynamically-Controlled Selectivity." J. Am. Chem. Soc. 2018140, 9291-9298, DOI: 10.1021/jacs.8b05804.

InChIs

1: InChI=1S/C17H20O2/c1-16-9-12-8-13(16)14(11-6-4-3-5-7-11)19-10-17(12,2)15(16)18/h3-7,12-14H,8-10H2,1-2H3/t12?,13?,14-,16?,17?/m0/s1
InChIKey=LTTUIPPXEHHMJS-XWTIBIIYSA-N
2: InChI=1S/C17H20O2/c1-16-10-19-15(11-6-4-3-5-7-11)13-8-12(16)9-14(18)17(13,16)2/h3-7,12-13,15H,8-10H2,1-2H3/t12?,13?,15-,16?,17?/m0/s1
InChIKey=GCKIOHNLJYVWKL-CMESGNGWSA-N


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

Wednesday, August 29, 2018

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians

Haichen Li, Christopher Collins, Matteus Tanha, Geoffrey J. Gordon, David J. Yaron (2018)
Highlighted by Jan Jensen


There are increasingly many papers on predicting the molecular energy and other properties using machine learning (ML). Most, if not all, use some similarity measure of the molecular structure to structures in the training set when training. This paper uses DFTB Hamiltonian matrix elements instead and treats the short-range matrix elements as adjustable parameters (weights) to be trained. To make this happen, DFTB is implemented as a layer for deep learning, using the TensorFlow deep learning framework, by recasting the DFTB equations in terms of tensor operations. In this way domain knowledge is incorporated into the ML model. Since the starting values are the "conventional" DFTB parameters one can also view this as refining the DFTB method.

This DFTB-ML approach is evaluated on 15,700 hydrocarbons by comparing the RMSE in energy per heavy atom (Eatom) relative to ωB97X/6-31G(d) reference values. Training on up to 7 heavy atoms and testing on 8 heavy atoms, leads to RMS errors in Eatom of 0.72 kcal/mol, compared to 1.80 using conventional DFTB. Training on up to 4 heavy atoms gives an Eatom RMSE of 1.08 kcal/mol. The results can be further improved by using neural networks to allow the matrix elements to depend on the molecular environment of the atoms.

As the authors point out the performance on the training data remained above chemical accuracy (0.5 kcal/mol) for the total molecular energy, but they offer several interesting ideas on how to improve the performance.


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

Nano-Saturn: Experimental Evidence of Complex Formation of an Anthracene Cyclic Ring with C60

Yuta, Y.; Eiji, T.; Kan, W.; Shinji, T., Angew. Chem. Int. Ed. 2018, 57, 8199-8202
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

It never hurts to promote one’s science through clever names – think cubane, buckminsterfullerene, bullvalene, etc. Host-guest chemistry is not immune to this cliché too, and this post discusses the latest synthesis and computations of a nano-Saturn; nano-Saturns are a spherical guest molecule captured inside a ring host molecule. I discussed an example of this a number of years ago – the nano-Saturn comprised of C60 fullerene surrounded by [10]cycloparaphenylene.

Yamamoto, Tsurumaki, Wakamatsu, and Toyota have prepared a nano-Saturn complex with the goal of making a flatter ring component.1 The inner planet is modeled again by C60 and the ring is the [24]circulene analogue 1. The x-ray crystal structure of this nano-Saturn complex is shown in Figure 1.

1: R = 2,4,6-tri-iso-propylphenyl
2: R = H
Figure 1. X-ray crystal structure of the nano-Saturn complex of 1 with C60.

Variable temperature NMR experiments gave the binding values of ΔH = -18.1 ± 2.3 kJ mol-1 and TΔS = 0.8 ± 2.2 kJ mol-1 at 298 K. To gauge this binding energy, they computed the complex of C60 with the parent compound 2 at B3LYP/6-1G(d)//M05-2X/6-31G(d), unfortunately without publishing the coordinates in the supporting materials. The computed binding enthalpy is ΔH = -50.6 kJ mol-1, but this computation is for the gas phase. The computed structure shows close contacts of 0.29 nm between the fullerene and the C9-proton of the anthracenyl groups, in excellent agreement with the x-ray structure. These weak C-Hπ interactions undoubtedly help stabilize the complex, especially given that the fullerene carries a very tiny Mulliken charge of +0.08 e.

References

1) Yuta, Y.; Eiji, T.; Kan, W.; Shinji, T., "Nano-Saturn: Experimental Evidence of Complex Formation of an Anthracene Cyclic Ring with C60." Angew. Chem. Int. Ed. 2018, 57, 8199-8202, DOI: 10.1002/anie.201804430.

InChIs

1: InChI=1S/C174H180/c1-91(2)121-78-150(97(13)14)164(151(79-121)98(15)16)163-90-128-71-139-70-127-59-109(37-38-120(127)77-162(139)163)110-39-49-140-129(60-110)72-130-61-111(40-50-141(130)165(140)170-152(99(17)18)80-122(92(3)4)81-153(170)100(19)20)112-41-51-142-131(62-112)73-132-63-113(42-52-143(132)166(142)171-154(101(21)22)82-123(93(5)6)83-155(171)102(23)24)114-43-53-144-133(64-114)74-134-65-115(44-54-145(134)167(144)172-156(103(25)26)84-124(94(7)8)85-157(172)104(27)28)116-45-55-146-135(66-116)75-136-67-117(46-56-147(136)168(146)173-158(105(29)30)86-125(95(9)10)87-159(173)106(31)32)118-47-57-148-137(68-118)76-138-69-119(128)48-58-149(138)169(148)174-160(107(33)34)88-126(96(11)12)89-161(174)108(35)36/h37-108H,1-36H3
InChIKey=AMDNULXMAMDTMX-UHFFFAOYSA-N
2: InChI=1S/C84H48/c1-13-61-25-62-15-3-51-33-75(62)43-73(61)31-49(1)50-2-14-63-26-64-16-4-52(34-76(64)44-74(63)32-50)54-6-18-66-28-68-20-8-56(38-80(68)46-78(66)36-54)58-10-22-70-30-72-24-12-60(42-84(72)48-82(70)40-58)59-11-23-71-29-69-21-9-57(39-81(69)47-83(71)41-59)55-7-19-67-27-65-17-5-53(51)35-77(65)45-79(67)37-55/h1-48H
InChIKey=ZYXXLAYETADMDM-UHFFFAOYSA-N


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Thursday, August 16, 2018

Readily Accessible Ambiphilic Cyclopentadienes for Bioorthogonal Labeling

Levandowski, B. J.; Gamache, R. F.; Murphy, J. M.; Houk, K. N., J. Am. Chem. Soc. 2018, 140, 6426-6431
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

I recently posted on a paper proposing 1,2-benzoquinone and related compounds as the diene component for bioorthogonal labeling. Levandowski, Gamache, Murphy, and Houk report on tetrachlorocyclopentadiene ketal 1 as an active ambiphilic diene component.1
1 is sterically congested to diminish self-dimerization and will react with both electron-rich and electron-poor dienes. To test it as an active diene in bioorthogonal labeling applications, they optimized the structures of the transition states at CPCM(water)/M06-2X/6-311+G(d,p)//CPCM(water)/M06-2X/6-31G(d) for the Diels-Alder reaction of 1 with a variety of dienophiles including trans-cyclooctene 2 and endo-bicyclononyne 3. These transition states are shown in Figure 1. The activation free energy is quite low for each: 18.1 kcal mol-1 with 2 and 18.9 kcal mol-1 with 3.

TS(1+2)

TS(1+3)
Figure 1. CPCM(water)/M06-2X/6-31G(d) optimized geometries for the TSs of the reaction of 1 with 2and 3.

Experiments were successfully run using 1 as a label on a neuropeptide.

References

1) Levandowski, B. J.; Gamache, R. F.; Murphy, J. M.; Houk, K. N., "Readily Accessible Ambiphilic Cyclopentadienes for Bioorthogonal Labeling." J. Am. Chem. Soc. 2018140, 6426-6431, DOI: 10.1021/jacs.8b02978.

InChIs

1:InChI=1S/C7H4Cl4O2/c8-3-4(9)6(11)7(5(3)10)12-1-2-13-7/h1-2H2
InChIkey=DXQQKKGWMVTLOJ-UHFFFAOYSA-N



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Sunday, July 29, 2018

Error-Controlled Exploration of Chemical Reaction Networks with Gaussian Processes

Gregor N. Simm and Markus Reiher (2018)
Highlighted by Jan Jensen



See if you recognise this scenario: you benchmark a cheap method against an accurate, but expensive, method for a set of molecules and get a mean error that you can use to correct the results obtained with the cheap method. But sooner or later you  start using the cheap method on molecules that look increasingly different from your benchmark set. At what point should you do another benchmark calculation against your expensive method? Simm and Reiher use Gaussian Processes (GP) to provide a quantitative answer.

GP is a way to fit a numerical function to a set of data points with uncertainties of the fit for every point in the fit. Simm and Reiher's basic idea is to arrange the benchmark points on the x-axis by computing a distance between pairs of molecular structures and performing a GP fit. Now compute the x-coordinate of the molecule you're uncertain about: if the uncertainty in the GP fit for that point is larger than the standard deviation of the mean error of your cheap method computed for the benchmark set, then you need to benchmark your cheap method against the more expensive method for that molecule.

Wednesday, July 25, 2018

Spectroscopic Evidence for Aminomethylene (H−C̈−NH2)—The Simplest Amino Carbene

Eckhardt, A. K.; Schreiner, P. R., Angew. Chem. Int. Ed. 2018, 57, 5248-5252
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Eckhardt and Schreiner have spectroscopically characterized the aminomethylene carbene 1.1 Their characterization rests on IR spectra, with comparison to the computed AE-CCSD(T)/cc-pCVQZ anharmonic vibrational frequencies, and the UV-Vis spectra, with comparison to the computed B3LYP/6–311++G(2d,2p) transitions.


1 can be converted to 2 by photolysis. Interestingly, 1 does not convert to 2 after 5 days on the matrix in the dark. This is in distinct contrast to hydroxycarbene and related other carbene which undergo quantum mechanical tunneling (see this post and this post). Examination of the potential energy surface for the reaction of 1 to 2 at AE-CCSD(T)/cc-pCVQZ (see Figure 1) identifies that the lowest barrier is 45.8 kcal mol-1, about 15 kcal mol-1 larger than the barrier for the hydroxycarbene rearrangement. Additionally, the barrier width for 1 → 2 is 25% larger than for the hydroxycarbenes. Both of these suggest substantially reduced tunneling, and WKB analysis predicts a tunneling half-life of more than a billion years. The stability of 1 is attributed to the strong π-donor ability of nitrogen to the electron-poor carbene. This is reflected in a very short C-N bond (1.27 Å).

Figure 1. Structures and energies of 1 and 2 and the transition states that connect them. The relative energies (kcal mol-1) are computed at AE-CCSD(T)/cc-pCVQZ.


References

1) Eckhardt, A. K.; Schreiner, P. R., "Spectroscopic Evidence for Aminomethylene (H−C̈−NH2)—The
Simplest Amino Carbene." Angew. Chem. Int. Ed. 201857, 5248-5252, DOI: 10.1002/anie.201800679.


InChIs

1: InChI=1S/CH3N/c1-2/h1H,2H2
InChIKey=KASBEVXLSPWGFS-UHFFFAOYSA-N
2: InChI=1S/CH3N/c1-2/h2H,1H2
InChIKey=WDWDWGRYHDPSDS-UHFFFAOYSA-N

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Wednesday, July 18, 2018

Longest C–C Single Bond among Neutral Hydrocarbons with a Bond Length beyond 1.8 Å

Ishigaki, Y.; Shimajiri, T.; Takeda, T.; Katoono, R.; Suzuki, T., Chem 2018, 4, 795-806
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

This is a third post in a series dealing with very short or very long distances between atoms. Ishigaki, Shimajiri, Takeda, Katoono, and Suzuki have prepared three related analogues of hexaphenylethane that all have long C-C bonds.1 The idea is to create a core by fusing two adjacent phenyls into a naphylene, and then protect the long C-C bond through a shell made up of large aryl groups, 1. Fusing another 5-member ring opposite to the stretched C-C bond (2) creates a scissor effect that should stretch that bond further, even more so in the unsaturated version 3.

Their M062-x/6-31G* computations predict an increasing longer C-C bond (highlighted in blue in the above drawing): 1.730 Å in 1, 1.767 Å in 2, and 1.771 Å in 3. The structure of 3 is shown in Figure 3.

Figure 1. M06-2x/6-31G(d) optimized structure of 3.

These three compounds were synthesized, and characterized by IR and Raman spectroscopy. Their x-ray crystal structures at 200 K and 400K were also determined. The C-C distances are 1.742 Å (1), 1.773 Å (2) and 1.798 Å (3) with distances slightly longer at 400 K. These rank as the longest C-C bonds recorded.


References

1) Ishigaki, Y.; Shimajiri, T.; Takeda, T.; Katoono, R.; Suzuki, T., "Longest C–C Single Bond among Neutral Hydrocarbons with a Bond Length beyond 1.8 Å." Chem 20184, 795-806, DOI: 10.1016/j.chempr.2018.01.011.


InChIs

1: InChI=1S/C40H26/c1-5-17-32-27(11-1)23-24-28-12-2-6-18-33(28)39(32)36-21-9-15-31-16-10-22-37(38(31)36)40(39)34-19-7-3-13-29(34)25-26-30-14-4-8-20-35(30)40/h1-26H
InChIKey=IFIFQLGAOZULMX-UHFFFAOYSA-N
2: InChI=1S/C42H28/c1-5-13-33-27(9-1)17-18-28-10-2-6-14-34(28)41(33)37-25-23-31-21-22-32-24-26-38(40(37)39(31)32)42(41)35-15-7-3-11-29(35)19-20-30-12-4-8-16-36(30)42/h1-20,23-26H,21-22H2
InChIKey=HSJDZFLRPWJAGF-UHFFFAOYSA-N
3: InChI=1S/C42H26/c1-5-13-33-27(9-1)17-18-28-10-2-6-14-34(28)41(33)37-25-23-31-21-22-32-24-26-38(40(37)39(31)32)42(41)35-15-7-3-11-29(35)19-20-30-12-4-8-16-36(30)42/h1-26H
InChIKey=QQYNKBIOZSXWGD-UHFFFAOYSA-N

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Saturday, June 30, 2018

Triplet-Tuning: A Novel Non-Empirical Construction Scheme of Exchange Functionals

Highlighted by Jan Jensen


The absolute error of the optical band gap computed with the CC-PVDZ basis set

The difference between the lowest triplet and singlet energy (ET) can be calculated both by UDFT and TDDFT but give different results because we don't know the exact density functional. So the authors suggest that functional can be improved by minimising this difference, i.e. without comparison to experimental data. 

Indeed, such a triplet tuned (TT) functional "provide more accurate predictions for key observables in photochemical measurements, including but not limited to ET, optical band gaps (ES), singlet–triplet gaps (∆EST), and ionization potentials (I)" for a set of 100 organic molecules. Two parameters in the PBE exchange functional, the fraction of short-range HF exchange and the range-separation parameter, were adjusted.

One thing that is not clear to me is if the equivalence of UDFT and TDDFT is valid only for the exact density. If so, this would only be valid in the complete basis set limit. Either way, the results clearly improve using the CC-PVDZ basis set.


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Tuesday, June 26, 2018

Intramolecular London Dispersion Interaction Effects on Gas-Phase and Solid-State Structures of Diamondoid Dimers

Fokin, A. A.; Zhuk, T. S.; Blomeyer, S.; Pérez, C.; Chernish, L. V.; Pashenko, A. E.; Antony, J.; Vishnevskiy, Y. V.; Berger, R. J. F.; Grimme, S.; Logemann, C.; Schnell, M.; Mitzel, N. W.; Schreiner, P. R., J. Am. Chem. Soc. 2017, 139, 16696-16707
Contributed by Steven Bacharach
Reposted from Computational Organic Chemistry with permission

Schreiner and Grimme have examined a few compounds (see these previous posts) with long C-C bonds that are found in congested systems where dispersion greatly aids in stabilizing the stretched bond. Their new paper1 continues this theme by examining 1 (again) and 2, using computations, and x-ray crystallography and gas-phase rotational spectroscopy and electron diffraction to establish the long C-C bond.


The distance of the long central bond in 1 is 1.647 Å (x-ray) and 1.630 Å (electron diffraction). Similarly, this distance in 2 is 1.642 Å (x-ray) and 1.632 Å (ED). These experiments discount any role for crystal packing forces in leading to the long bond.

A very nice result from the computations is that most functionals that include some dispersion correction predict the C-C distance in the optimized structures with an error of no more than 0.01 Å. (PW6B95-D3/DEF2-QZVP structures are shown in Figure 1.) Not surprisingly, HF and B3LYP without a dispersion correction predict a bond that is too long.) MP2 predicts a distance that is too short, but SCS-MP2 does a very good job.


1

2
Figure 1. PW6B95-D3/DEF2-QZVP optimized structures of 1 and 2.


References

1) Fokin, A. A.; Zhuk, T. S.; Blomeyer, S.; Pérez, C.; Chernish, L. V.; Pashenko, A. E.; Antony, J.; Vishnevskiy, Y. V.; Berger, R. J. F.; Grimme, S.; Logemann, C.; Schnell, M.; Mitzel, N. W.; Schreiner, P. R., "Intramolecular London Dispersion Interaction Effects on Gas-Phase and Solid-State Structures of Diamondoid Dimers." J. Am. Chem. Soc. 2017139, 16696-16707, DOI: 10.1021/jacs.7b07884.


InChIs

1: InChI=1S/C28H38/c1-13-7-23-19-3-15-4-20(17(1)19)24(8-13)27(23,11-15)28-12-16-5-21-18-2-14(9-25(21)28)10-26(28)22(18)6-16/h13-26H,1-12H2
InChIKey=MMYAZLNWLGPULP-UHFFFAOYSA-N
2: InChI=1S/C26H34O2/c1-11-3-19-15-7-13-9-25(19,21(5-11)23(27-13)17(1)15)26-10-14-8-16-18-2-12(4-20(16)26)6-22(26)24(18)28-14/h11-24H,1-10H2
InChIKey=VPBJYHMTINJMAE-UHFFFAOYSA-N


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