Diatomic densities from DFT

I recently blogged about a paper arguing that modern density functional development has strayed from the path of improving density description, in favor of improved energetics. The Medvedev paper¹ was met with a number of criticisms. A potential “out” from the conclusions of the work was that perhaps molecular densities do not fare so poorly with more modern functionals, following the argument that better energies might reflect better densities in bonding regions.

The Hammes-Schiffer group have now examined 14 diatomic molecules with the goal of testing just this hypothesis.² They subjected both homonuclear diatomics, like N₂, Cl₂, and Li₂, and heteronuclear diatomics, like HF, LiF, and SC, to 90 different density functionals using the very large aug-cc-pCVQZ basis set. Using the CCSD density as a reference, they examined the differences in the densities predicted by the various functional both along the internuclear axis and perpendicular to it.

The 20 functionals that do the best job in mimicking the CCSD density are all hybrid GGA functionals, along with the sole double hybrid functional included in the study (B2PLYP). These functionals date from 1993 to 2012. The 20 functionals that do the poorest job include functionals from all rung-types, and date from 1980-2012. A very slight upward trend can be observed in the density error increasing with development year, while the error in the dissociation energy clearly is decreasing over time.

They note that six functionals of the Minnesota-type, those that are highly parameterized and of recent vintage, perform very poorly at predicting atomic densities, but do well with the diatomic densities.

Hammes-Schiffer concludes that their diatomic results support the general trend noted by Medvedev’s atomic results, that density description is lagging in more recently developed functionals. I’d add that this trend is not as dramatic for the diatomics as for atoms.

They pose what is really the key question: “Is the purpose to approximate the exact functional or simply to provide chemists with a useful tool for exploring chemical systems?” Since, as they note, the modern highly parameterized functionals have worked so well for predicting energies and geometries, “the observation that many modern functionals produce incorrect densities could be of no great consequence for many studies”. Nonetheless, “the ultimate goal is still to obtain both accurate densities and accurate energies”.

References

1) Medvedev, M. G.; Bushmarinov, I. S.; Sun, J.; Perdew, J. P.; Lyssenko, K. A., "Density functional theory is straying from the path toward the exact functional." Science 2017, 355, 49-52, DOI: 10.1126/science.aah5975.

2) Brorsen, K. R.; Yang, Y.; Pak, M. V.; Hammes-Schiffer, S., "Is the Accuracy of Density Functional Theory for Atomization Energies and Densities in Bonding Regions Correlated?" J. Phys. Chem. Lett. 2017, 8, 2076-2081, DOI: 10.1021/acs.jpclett.7b00774.

from Computational Organic Chemistry http://ift.tt/2wqOs1n

I recently blogged about a paper arguing that modern density functional development has strayed from the path of improving density description, in favor of improved energetics. The Medvedev paper¹ was met with a number of criticisms. A potential “out” from the conclusions of the work was that perhaps molecular densities do not fare so poorly with more modern functionals, following the argument that better energies might reflect better densities in bonding regions.

The Hammes-Schiffer group have now examined 14 diatomic molecules with the goal of testing just this hypothesis.² They subjected both homonuclear diatomics, like N₂, Cl₂, and Li₂, and heteronuclear diatomics, like HF, LiF, and SC, to 90 different density functionals using the very large aug-cc-pCVQZ basis set. Using the CCSD density as a reference, they examined the differences in the densities predicted by the various functional both along the internuclear axis and perpendicular to it.

The 20 functionals that do the best job in mimicking the CCSD density are all hybrid GGA functionals, along with the sole double hybrid functional included in the study (B2PLYP). These functionals date from 1993 to 2012. The 20 functionals that do the poorest job include functionals from all rung-types, and date from 1980-2012. A very slight upward trend can be observed in the density error increasing with development year, while the error in the dissociation energy clearly is decreasing over time.

They note that six functionals of the Minnesota-type, those that are highly parameterized and of recent vintage, perform very poorly at predicting atomic densities, but do well with the diatomic densities.

Hammes-Schiffer concludes that their diatomic results support the general trend noted by Medvedev’s atomic results, that density description is lagging in more recently developed functionals. I’d add that this trend is not as dramatic for the diatomics as for atoms.

They pose what is really the key question: “Is the purpose to approximate the exact functional or simply to provide chemists with a useful tool for exploring chemical systems?” Since, as they note, the modern highly parameterized functionals have worked so well for predicting energies and geometries, “the observation that many modern functionals produce incorrect densities could be of no great consequence for many studies”. Nonetheless, “the ultimate goal is still to obtain both accurate densities and accurate energies”.

References

1) Medvedev, M. G.; Bushmarinov, I. S.; Sun, J.; Perdew, J. P.; Lyssenko, K. A., "Density functional theory is straying from the path toward the exact functional." Science 2017, 355, 49-52, DOI: 10.1126/science.aah5975.

2) Brorsen, K. R.; Yang, Y.; Pak, M. V.; Hammes-Schiffer, S., "Is the Accuracy of Density Functional Theory for Atomization Energies and Densities in Bonding Regions Correlated?" J. Phys. Chem. Lett. 2017, 8, 2076-2081, DOI: 10.1021/acs.jpclett.7b00774.

from Computational Organic Chemistry http://ift.tt/2wqOs1n

Bispericyclic reaction involving two [6+4] cycloadditions

Bispericyclic transition states arise when two pericyclic reactions merge to a common transition state. This leads to a potential energy surface with a bifurcation such that reactions that traverse this type of transition state will head towards two different products. The classic example is the dimerization of cyclopentadiene, involving two [4+2] Diels-Alder reactions. Unusual PESs are discussed in my book and in past blog posts.

Houk and coworkers have now identified a bispericyclic transition state involving two [6+4] cycloadditions.¹ Reaching back to work Houk pursued as a graduate student with Woodward for inspiration, these authors examined the reaction of tropone 1 with dimethylfulvene 2. Each moiety can act as the diene or triene component of a [6+4] allowed cycloaddition:

The product with fulvene 2 as the 6 π-e component and tropone as the 4 π-e component [6_F+4_T] is 3, while reversing their participation in the [6_T+4_F] cycloaddition leads to 4. A variety of [4+2] reactions are also possible. All of these reactions were investigated at PCM/M06-2X/6-311+G(d,p)//B3LYP-D3/6-31G(d). The reaction leading to 3 is exothermic by 3.0 kcal mol^-1, while the reaction to 4 endothermic by 1.3 kcal mol^-1.

Interestingly, there is only one transition state that leads to both 3 and 4, the first known bispericyclic transition state for two conjoined [6+4] cycloadditions. The barrier is 27.9 kcal mol^-1. The structures of the two products and the transition state leading to them are shown in Figure 1. 3 and 4 can interconvert through a Cope transition state, also shown in Figure 1, with a barrier of 26.3 kcal mol^-1 (for 4 → 3).

3	4
TS [6+4]	TS Cope

Figure 1. B3LYP-D3/6-31G(d) optimized geometries.

Given that a single transition leads to two products, the product distribution is dependent on the molecular dynamics. A molecular dynamics simulation at B3LYP-D3/6-31G(d) with 117 trajectories indicates that 4 is formed 91% while 3 is formed only 9%. Once again, we are faced with the reality of much more complex reaction mechanisms/processes than simple models would suggest.

References

1) Yu, P.; Chen, T. Q.; Yang, Z.; He, C. Q.; Patel, A.; Lam, Y.-h.; Liu, C.-Y.; Houk, K. N., "Mechanisms and Origins of Periselectivity of the Ambimodal [6 + 4] Cycloadditions of Tropone to Dimethylfulvene." J. Am. Chem. Soc. 2017, 139 (24), 8251-8258, DOI: 10.1021/jacs.7b02966.

InChIs

1: InChI=1S/C7H6O/c8-7-5-3-1-2-4-6-7/h1-6H
InChIKey=QVWDCTQRORVHHT-UHFFFAOYSA-N

2: InChI=1S/C8H10/c1-7(2)8-5-3-4-6-8/h3-6H,1-2H3
InChIKey=WXACXMWYHXOSIX-UHFFFAOYSA-N

3:InChI=1S/C15H16O/c1-15(2)10-6-8-12(14(16)9-7-10)11-4-3-5-13(11)15/h3-12H,1-2H3
InChIKey=SEKRUGIZAIQCDA-UHFFFAOYSA-N

4: InChI=1S/C15H16O/c1-9(2)14-10-7-8-11(14)13-6-4-3-5-12(10)15(13)16/h3-8,10-13H,1-2H3
InChIKey=AQQAMUGJSGJKLC-UHFFFAOYSA-N

from Computational Organic Chemistry http://ift.tt/2vIgLs0

Bispericyclic transition states arise when two pericyclic reactions merge to a common transition state. This leads to a potential energy surface with a bifurcation such that reactions that traverse this type of transition state will head towards two different products. The classic example is the dimerization of cyclopentadiene, involving two [4+2] Diels-Alder reactions. Unusual PESs are discussed in my book and in past blog posts.

Houk and coworkers have now identified a bispericyclic transition state involving two [6+4] cycloadditions.¹ Reaching back to work Houk pursued as a graduate student with Woodward for inspiration, these authors examined the reaction of tropone 1 with dimethylfulvene 2. Each moiety can act as the diene or triene component of a [6+4] allowed cycloaddition:

The product with fulvene 2 as the 6 π-e component and tropone as the 4 π-e component [6_F+4_T] is 3, while reversing their participation in the [6_T+4_F] cycloaddition leads to 4. A variety of [4+2] reactions are also possible. All of these reactions were investigated at PCM/M06-2X/6-311+G(d,p)//B3LYP-D3/6-31G(d). The reaction leading to 3 is exothermic by 3.0 kcal mol^-1, while the reaction to 4 endothermic by 1.3 kcal mol^-1.

Interestingly, there is only one transition state that leads to both 3 and 4, the first known bispericyclic transition state for two conjoined [6+4] cycloadditions. The barrier is 27.9 kcal mol^-1. The structures of the two products and the transition state leading to them are shown in Figure 1. 3 and 4 can interconvert through a Cope transition state, also shown in Figure 1, with a barrier of 26.3 kcal mol^-1 (for 4 → 3).

3	4
TS [6+4]	TS Cope

Figure 1. B3LYP-D3/6-31G(d) optimized geometries.

Given that a single transition leads to two products, the product distribution is dependent on the molecular dynamics. A molecular dynamics simulation at B3LYP-D3/6-31G(d) with 117 trajectories indicates that 4 is formed 91% while 3 is formed only 9%. Once again, we are faced with the reality of much more complex reaction mechanisms/processes than simple models would suggest.

References

1) Yu, P.; Chen, T. Q.; Yang, Z.; He, C. Q.; Patel, A.; Lam, Y.-h.; Liu, C.-Y.; Houk, K. N., "Mechanisms and Origins of Periselectivity of the Ambimodal [6 + 4] Cycloadditions of Tropone to Dimethylfulvene." J. Am. Chem. Soc. 2017, 139 (24), 8251-8258, DOI: 10.1021/jacs.7b02966.

InChIs

1: InChI=1S/C7H6O/c8-7-5-3-1-2-4-6-7/h1-6H
InChIKey=QVWDCTQRORVHHT-UHFFFAOYSA-N

2: InChI=1S/C8H10/c1-7(2)8-5-3-4-6-8/h3-6H,1-2H3
InChIKey=WXACXMWYHXOSIX-UHFFFAOYSA-N

3:InChI=1S/C15H16O/c1-15(2)10-6-8-12(14(16)9-7-10)11-4-3-5-13(11)15/h3-12H,1-2H3
InChIKey=SEKRUGIZAIQCDA-UHFFFAOYSA-N

4: InChI=1S/C15H16O/c1-9(2)14-10-7-8-11(14)13-6-4-3-5-12(10)15(13)16/h3-8,10-13H,1-2H3
InChIKey=AQQAMUGJSGJKLC-UHFFFAOYSA-N

from Computational Organic Chemistry http://ift.tt/2vIgLs0

A few review articles

A few nice review/opinion pieces have been piling up in my folder of papers of interest for this Blog. So, this post provides a short summary of a number of review articles that computationally-oriented chemists may find of interest.

Holy Grails in computational chemistry

Houk and Liu present a short list of “Holy Grails” in computationally chemistry.¹ They begin by pointing out a few technical innovations that must occur for the Grails to be found: development of a universal density functional; an accurate, generic force field; improved sampling for MD; and dealing with the combinatorial explosion with regards to conformations and configurations. Their list of Grails includes predicting crystal structures and structure of amorphous materials, catalyst design, reaction design, and device design. These Grails overlap with the challenges I laid out in my similarly-themed article in 2014.²

Post-transition state bifurcations and dynamics

Hare and Tantillo review the current understanding of post-transition state bifurcations (PTSB).³ This type of potential energy surface has been the subject of much of Chapter 8 of my book and many of my blog posts. What is becoming clear is the possibility of a transition state followed by a valley-ridge inflection leads to reaction dynamics where trajectories cross a single transition state but lead to two different products. This new review updates the state-of-the-art from Houk’s review⁴ of 2008 (see this post). Mentioned are a number of studies that I have included in this Blog, along with reactions involving metals, and biochemical systems (many of these examples come from the Tantillo lab). They close with the hope that their review might “inspire future studies aimed at controlling selectivity for reactions with PTSBs” (italics theirs). I might offer that controlling selectivity in these types of dynamical systems is another chemical Grail!

The Hase group has a long review of direct dynamics simulations.⁵ They describe a number of important dynamics studies that provide important new insight to reaction mechanism, such as bimolecular S_N2 reactions (including the roundabout mechanism) and unimolecular dissociation. They write a long section on post-transition state bifurcations, and other dynamic effects that cannot be interpreted using transition state theory or RRKM. This section is a nice complement to the Tantillo review.

Benchmarking quantum chemical methods

Mata and Suhm look at our process of benchmarking computational methods.⁶ They point out the growing use of high-level quantum computations as the reference for benchmarking new methods, often with no mention of any comparison to experiment. In defense of theoreticians, they do note the paucity of useful experimental data that may exist for making suitable comparisons. They detail a long list of better practices that both experimentalists and theoreticians can take to bolster both efforts, leading to stronger computational tools that are more robust at helping to understand and discriminate difficult experimental findings.

References

1) Houk, K. N.; Liu, F., "Holy Grails for Computational Organic Chemistry and Biochemistry." Acc. Chem. Res. 2017, 50 (3), 539-543, DOI: 10.1021/acs.accounts.6b00532.

2) Bachrach, S. M., "Challenges in computational organic chemistry." WIRES: Comput. Mol. Sci. 2014, 4, 482-487, DOI: 10.1002/wcms.1185.

3) Hare, S. R.; Tantillo, D. J., "Post-transition state bifurcations gain momentum – current state of the field." Pure Appl. Chem. 2017, 89, 679-698, DOI: 0.1515/pac-2017-0104.

4) Ess, D. H.; Wheeler, S. E.; Iafe, R. G.; Xu, L.; Çelebi-Ölçüm, N.; Houk, K. N., "Bifurcations on Potential Energy Surfaces of Organic Reactions." Angew. Chem. Int. Ed. 2008, 47, 7592-7601, DOI: 10.1002/anie.200800918

5) Pratihar, S.; Ma, X.; Homayoon, Z.; Barnes, G. L.; Hase, W. L., "Direct Chemical Dynamics Simulations." J. Am. Chem. Soc. 2017, 139, 3570-3590, DOI: 10.1021/jacs.6b12017.

6) Mata, R. A.; Suhm, M. A., "Benchmarking Quantum Chemical Methods: Are We Heading in the Right Direction?" Angew. Chem. Int. Ed. 2017, ASAP, DOI: 10.1002/anie.201611308.

from Computational Organic Chemistry http://ift.tt/2tGUSIW

A few nice review/opinion pieces have been piling up in my folder of papers of interest for this Blog. So, this post provides a short summary of a number of review articles that computationally-oriented chemists may find of interest.

Holy Grails in computational chemistry

Houk and Liu present a short list of “Holy Grails” in computationally chemistry.¹ They begin by pointing out a few technical innovations that must occur for the Grails to be found: development of a universal density functional; an accurate, generic force field; improved sampling for MD; and dealing with the combinatorial explosion with regards to conformations and configurations. Their list of Grails includes predicting crystal structures and structure of amorphous materials, catalyst design, reaction design, and device design. These Grails overlap with the challenges I laid out in my similarly-themed article in 2014.²

Post-transition state bifurcations and dynamics

Hare and Tantillo review the current understanding of post-transition state bifurcations (PTSB).³ This type of potential energy surface has been the subject of much of Chapter 8 of my book and many of my blog posts. What is becoming clear is the possibility of a transition state followed by a valley-ridge inflection leads to reaction dynamics where trajectories cross a single transition state but lead to two different products. This new review updates the state-of-the-art from Houk’s review⁴ of 2008 (see this post). Mentioned are a number of studies that I have included in this Blog, along with reactions involving metals, and biochemical systems (many of these examples come from the Tantillo lab). They close with the hope that their review might “inspire future studies aimed at controlling selectivity for reactions with PTSBs” (italics theirs). I might offer that controlling selectivity in these types of dynamical systems is another chemical Grail!

The Hase group has a long review of direct dynamics simulations.⁵ They describe a number of important dynamics studies that provide important new insight to reaction mechanism, such as bimolecular S_N2 reactions (including the roundabout mechanism) and unimolecular dissociation. They write a long section on post-transition state bifurcations, and other dynamic effects that cannot be interpreted using transition state theory or RRKM. This section is a nice complement to the Tantillo review.

Benchmarking quantum chemical methods

Mata and Suhm look at our process of benchmarking computational methods.⁶ They point out the growing use of high-level quantum computations as the reference for benchmarking new methods, often with no mention of any comparison to experiment. In defense of theoreticians, they do note the paucity of useful experimental data that may exist for making suitable comparisons. They detail a long list of better practices that both experimentalists and theoreticians can take to bolster both efforts, leading to stronger computational tools that are more robust at helping to understand and discriminate difficult experimental findings.

References

1) Houk, K. N.; Liu, F., "Holy Grails for Computational Organic Chemistry and Biochemistry." Acc. Chem. Res. 2017, 50 (3), 539-543, DOI: 10.1021/acs.accounts.6b00532.

2) Bachrach, S. M., "Challenges in computational organic chemistry." WIRES: Comput. Mol. Sci. 2014, 4, 482-487, DOI: 10.1002/wcms.1185.

3) Hare, S. R.; Tantillo, D. J., "Post-transition state bifurcations gain momentum – current state of the field." Pure Appl. Chem. 2017, 89, 679-698, DOI: 0.1515/pac-2017-0104.

4) Ess, D. H.; Wheeler, S. E.; Iafe, R. G.; Xu, L.; Çelebi-Ölçüm, N.; Houk, K. N., "Bifurcations on Potential Energy Surfaces of Organic Reactions." Angew. Chem. Int. Ed. 2008, 47, 7592-7601, DOI: 10.1002/anie.200800918

5) Pratihar, S.; Ma, X.; Homayoon, Z.; Barnes, G. L.; Hase, W. L., "Direct Chemical Dynamics Simulations." J. Am. Chem. Soc. 2017, 139, 3570-3590, DOI: 10.1021/jacs.6b12017.

6) Mata, R. A.; Suhm, M. A., "Benchmarking Quantum Chemical Methods: Are We Heading in the Right Direction?" Angew. Chem. Int. Ed. 2017, ASAP, DOI: 10.1002/anie.201611308.

from Computational Organic Chemistry http://ift.tt/2tGUSIW

Structure of GlyGly

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 1a, 1b, 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

from Computational Organic Chemistry http://ift.tt/2uv7xhk

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 1a, 1b, 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

from Computational Organic Chemistry http://ift.tt/2uv7xhk

Another procedure for computing NMR chemical shifts

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 ¹³ chemical 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. 2006, 2, 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., 2008, 4, 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

from Computational Organic Chemistry http://ift.tt/2ual12m

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 ¹³ chemical 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. 2006, 2, 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., 2008, 4, 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

from Computational Organic Chemistry http://ift.tt/2ual12m

A record short H…H non-bonding interaction

Dynamics in a [3,3]-rearrangement

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 1TS, 3TS1F, and 3TS1Cl are shown in Figure 1.

1TS

3TS1F

3TS1Cl

Figure 1. M06-2X/Def2TZVPP optimized geometries of 1TS, 3TS1F, 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

from Computational Organic Chemistry http://ift.tt/2rt2R9I

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 1TS, 3TS1F, and 3TS1Cl are shown in Figure 1.

1TS

3TS1F

3TS1Cl

Figure 1. M06-2X/Def2TZVPP optimized geometries of 1TS, 3TS1F, 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

from Computational Organic Chemistry http://ift.tt/2rt2R9I

Nanobelt

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

from Computational Organic Chemistry http://ift.tt/2qMTX70

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

from Computational Organic Chemistry http://ift.tt/2qMTX70

Progress in DFT development and the density they predict

“Getting the right answer for the right reason” – how important is this principle when it comes to computational chemistry? Medvedev and co-workers argue that when it comes to DFT, trends in functional development have overlooked this maxim in favor of utility.¹ Specifically, they note that

There exists an exact functional that yields the exact energy of a system from its exact density.

Over the past two decades a great deal of effort has gone into functional development, mostly in an empirical way done usually to improve energy prediction. This approach has a problem:

[It], however, overlooks the fact that the reproduction of exact energy is not a feature of the exact functional, unless the input electron density is exact as well.

So, these authors have studied functional performance with regards to obtaining proper electron densities. Using CCSD/aug-cc-pwCV5Z as the benchmark, they computed the electron density for a number of neutral and cationic atoms having 2, 4, or 10 electrons. Then, they computed the densities with 128 different functionals of all of the rungs of Jacob’s ladder. They find that accuracy was increasing as new functionals were developed from the 1970s to the early 2000s. Since then, however, newer functionals have tended towards poorer electron densities, even though energy prediction has continued to improve. Medvedev et al argue that the recent trend in DFT development has been towards functionals that are highly parameterized to fit energies with no consideration given to other aspects including the density or constraints of the exact functional.

In the same issue of Science, Hammes-Schiffer comments about this paper.² She notes some technical issues, most importantly that the benchmark study is for atoms and that molecular densities might be a different issue. But more philosophically (and practically), she points out that for many chemical and biological systems, the energy and structure are of more interest than the density. Depending on where the errors in density occur, these errors may not be of particular relevance in understanding reactivity; i.e., if the errors are largely near the nuclei but the valence region is well described then reactions (transition states) might be treated reasonably well. She proposes that future development of functionals, likely still to be driven by empirical fitting, might include other data to fit to that may better reflect the density, such as dipole moments. This seems like a quite logical and rational step to take next.

A commentary by Korth³ summarizes a number of additional concerns regarding the Medvedev paper. The last concern is the one I find most striking:

Even if there really are (new) problems, it is as unclear as before how they can be overcome…With this in mind, it does not seem unreasonable to compromise on the quality of the atomic densities to improve the description of more relevant properties, such as the energetics of molecules.

Korth concludes with

In the meantime, while theoreticians should not rest until they have the right answer for the right reason, computational chemists and experimentalists will most likely continue to be happy with helpful answers for good reasons.

I do really think this is the correct take-away message: DFT does appear to provide good predictions of a variety of chemical and physical properties, and it will remain a widely utilized tool even if the density that underpins the theory is incorrect. Functional development must continue, and Medvedev et al. remind us of this need.

References

1) Medvedev, M. G.; Bushmarinov, I. S.; Sun, J.; Perdew, J. P.; Lyssenko, K. A., "Density functional theory is straying from the path toward the exact functional." Science 2017, 355, 49-52, DOI: 10.1126/science.aah5975.

2) Hammes-Schiffer, S., "A conundrum for density functional theory." Science 2017, 355, 28-29, DOI: 10.1126/science.aal3442.

3) Korth, M., "Density Functional Theory: Not Quite the Right Answer for the Right Reason Yet." Angew. Chem. Int. Ed. 2017, 56, 5396-5398, DOI: 10.1002/anie.201701894.

from Computational Organic Chemistry http://ift.tt/2pnbtdI

“Getting the right answer for the right reason” – how important is this principle when it comes to computational chemistry? Medvedev and co-workers argue that when it comes to DFT, trends in functional development have overlooked this maxim in favor of utility.¹ Specifically, they note that

There exists an exact functional that yields the exact energy of a system from its exact density.

Over the past two decades a great deal of effort has gone into functional development, mostly in an empirical way done usually to improve energy prediction. This approach has a problem:

[It], however, overlooks the fact that the reproduction of exact energy is not a feature of the exact functional, unless the input electron density is exact as well.

So, these authors have studied functional performance with regards to obtaining proper electron densities. Using CCSD/aug-cc-pwCV5Z as the benchmark, they computed the electron density for a number of neutral and cationic atoms having 2, 4, or 10 electrons. Then, they computed the densities with 128 different functionals of all of the rungs of Jacob’s ladder. They find that accuracy was increasing as new functionals were developed from the 1970s to the early 2000s. Since then, however, newer functionals have tended towards poorer electron densities, even though energy prediction has continued to improve. Medvedev et al argue that the recent trend in DFT development has been towards functionals that are highly parameterized to fit energies with no consideration given to other aspects including the density or constraints of the exact functional.

In the same issue of Science, Hammes-Schiffer comments about this paper.² She notes some technical issues, most importantly that the benchmark study is for atoms and that molecular densities might be a different issue. But more philosophically (and practically), she points out that for many chemical and biological systems, the energy and structure are of more interest than the density. Depending on where the errors in density occur, these errors may not be of particular relevance in understanding reactivity; i.e., if the errors are largely near the nuclei but the valence region is well described then reactions (transition states) might be treated reasonably well. She proposes that future development of functionals, likely still to be driven by empirical fitting, might include other data to fit to that may better reflect the density, such as dipole moments. This seems like a quite logical and rational step to take next.

A commentary by Korth³ summarizes a number of additional concerns regarding the Medvedev paper. The last concern is the one I find most striking:

Even if there really are (new) problems, it is as unclear as before how they can be overcome…With this in mind, it does not seem unreasonable to compromise on the quality of the atomic densities to improve the description of more relevant properties, such as the energetics of molecules.

Korth concludes with

In the meantime, while theoreticians should not rest until they have the right answer for the right reason, computational chemists and experimentalists will most likely continue to be happy with helpful answers for good reasons.

I do really think this is the correct take-away message: DFT does appear to provide good predictions of a variety of chemical and physical properties, and it will remain a widely utilized tool even if the density that underpins the theory is incorrect. Functional development must continue, and Medvedev et al. remind us of this need.

References

1) Medvedev, M. G.; Bushmarinov, I. S.; Sun, J.; Perdew, J. P.; Lyssenko, K. A., "Density functional theory is straying from the path toward the exact functional." Science 2017, 355, 49-52, DOI: 10.1126/science.aah5975.

2) Hammes-Schiffer, S., "A conundrum for density functional theory." Science 2017, 355, 28-29, DOI: 10.1126/science.aal3442.

3) Korth, M., "Density Functional Theory: Not Quite the Right Answer for the Right Reason Yet." Angew. Chem. Int. Ed. 2017, 56, 5396-5398, DOI: 10.1002/anie.201701894.

from Computational Organic Chemistry http://ift.tt/2pnbtdI

Tetrabenzo[7]circulene

I have discussed the circulenes in a few previous posts. Depending on their size, they can be bowls, flat disks, or saddles. A computational study of [7]circulene noted that C₂ structure is slightly higher in energy than the C_s form,¹ though the C₂ form is found in the x-ray structure.²

Now, Miao and co-workers have synthesized the tetrabenzo[7]circulene 1 and also examined its structure using DFT.³

As with the parent compound, a C₂ and C_s form were located at B3LYP/6-31G(d,p), and are shown in Figure 1. The C₂ form is 7.6 kcal mol^-1 lower in energy than the C_s structure, and the two are separated by a transition state (also shown in Figure 1) with a barrier of 12.2 kcal mol^-1. The interconversion of these conformations takes place without going through a planar form. The x-ray structure contains only the C₂ structure. It should be noted that the C₂ structure is chiral, and racemization would take place by the path: 1-C_s &lrarr; 1-C_s &lrarr; 1-C₂*, where 1-C₂* is the enantiomer of 1-C₂.

1-C2

1-TS

1-Cs

Figure 1. B3LYP/6-31G(d,p) optimized structures of 1.

References

1) Hatanaka, M., "Puckering Energetics and Optical Activities of [7]Circulene Conformers." J. Phys. Chem. A 2016, 120 (7), 1074-1083, DOI: 10.1021/acs.jpca.5b10543.

2) Yamamoto, K.; Harada, T.; Okamoto, Y.; Chikamatsu, H.; Nakazaki, M.; Kai, Y.; Nakao, T.; Tanaka, M.; Harada, S.; Kasai, N., "Synthesis and molecular structure of [7]circulene." J. Am. Chem. Soc. 1988, 110 (11), 3578-3584, DOI: 10.1021/ja00219a036.

3) Gu, X.; Li, H.; Shan, B.; Liu, Z.; Miao, Q., "Synthesis, Structure, and Properties of Tetrabenzo[7]circulene." Org. Letters 2017, DOI: 10.1021/acs.orglett.7b00714.

InChIs

1: InChI=1S/C44H22/c1-5-13-28-24(9-1)32-19-17-23-18-20-33-25-10-2-6-14-29(25)38-31-16-8-4-12-27(31)35-22-21-34-26-11-3-7-15-30(26)37(28)43-39(32)36(23)40(33)44(38)42(35)41(34)43/h1-22H
InChIKey=KVMXYGAVHDZMNP-UHFFFAOYSA-N

from Computational Organic Chemistry http://ift.tt/2pyvuQ0

I have discussed the circulenes in a few previous posts. Depending on their size, they can be bowls, flat disks, or saddles. A computational study of [7]circulene noted that C₂ structure is slightly higher in energy than the C_s form,¹ though the C₂ form is found in the x-ray structure.²

Now, Miao and co-workers have synthesized the tetrabenzo[7]circulene 1 and also examined its structure using DFT.³

As with the parent compound, a C₂ and C_s form were located at B3LYP/6-31G(d,p), and are shown in Figure 1. The C₂ form is 7.6 kcal mol^-1 lower in energy than the C_s structure, and the two are separated by a transition state (also shown in Figure 1) with a barrier of 12.2 kcal mol^-1. The interconversion of these conformations takes place without going through a planar form. The x-ray structure contains only the C₂ structure. It should be noted that the C₂ structure is chiral, and racemization would take place by the path: 1-C_s &lrarr; 1-C_s &lrarr; 1-C₂*, where 1-C₂* is the enantiomer of 1-C₂.

1-C2

1-TS

1-Cs

Figure 1. B3LYP/6-31G(d,p) optimized structures of 1.

References

1) Hatanaka, M., "Puckering Energetics and Optical Activities of [7]Circulene Conformers." J. Phys. Chem. A 2016, 120 (7), 1074-1083, DOI: 10.1021/acs.jpca.5b10543.

2) Yamamoto, K.; Harada, T.; Okamoto, Y.; Chikamatsu, H.; Nakazaki, M.; Kai, Y.; Nakao, T.; Tanaka, M.; Harada, S.; Kasai, N., "Synthesis and molecular structure of [7]circulene." J. Am. Chem. Soc. 1988, 110 (11), 3578-3584, DOI: 10.1021/ja00219a036.

3) Gu, X.; Li, H.; Shan, B.; Liu, Z.; Miao, Q., "Synthesis, Structure, and Properties of Tetrabenzo[7]circulene." Org. Letters 2017, DOI: 10.1021/acs.orglett.7b00714.

InChIs

1: InChI=1S/C44H22/c1-5-13-28-24(9-1)32-19-17-23-18-20-33-25-10-2-6-14-29(25)38-31-16-8-4-12-27(31)35-22-21-34-26-11-3-7-15-30(26)37(28)43-39(32)36(23)40(33)44(38)42(35)41(34)43/h1-22H
InChIKey=KVMXYGAVHDZMNP-UHFFFAOYSA-N

from Computational Organic Chemistry http://ift.tt/2pyvuQ0

SpnF revisited

Medvedev, et al. have examined the cyclization step in the formation of Spinosyn A, which is catalyzed by the putative Diels-Alderase enzyme SpnF.¹ This work follows on the computational study done by Houk, Singleton and co-workers,² which I have discussed in this post (Dynamics in a reaction where a [6+4] and [4+2] cycloadditons compete). In fact, I recommend that you read the previous post before continuing on with this one. In summary, Houk, et al. found that a single transition state connects reactant 1 to both 2 and 3. The experimental product with the enzyme SpnF is 3. In the absence of enzyme, Houk, et al. suggest that reactions will cross the bispericyclic transition state TS-BPC (TS1 in the previous post) leading primarily to 2, which then undergoes a Cope rearrangement to get to product 3. Some molecules will follow pathways that go directly to 3.

The PCM(water)/M06-2x/6-31+G(d) study by Medvedev, et al. first identifies 560 conformations of 3. Next, they identified 384 TSs lying within 30 kcal mol^-1 from the lowest TS. These can be classified as either TS-DA (leading directly to 3) or TS-BPC (which may lead to 2 by steepest descent, but can bifurcate towards 3). They opt to utilize the Atoms-in-Molecules theory to identify bond critical points to categorize these TS, and find that 144 are TS-BPC and 240 are TS-DA. (The transition state found by Houk, et al. is the second lowest energy TS found in this study, 0.29 kcal mol^-1 higher in energy that the lowest TS and also of TS-BPC type.)

They also examined two alternative routes. First, they propose a path that first takes 1 to 4 via an alternative Diels-Alder reaction, and a second Cope rearrangement (TS-Cope2) takes this to 2, which can then convert to 3 via TS-Cope1. The other route involves a biradical pathway to either A or B. These alternatives prove to be non-competitive, with transition state energies significantly higher than either TS-DA or TS-BPC.

Returning to the set of TS-DA and TS-BPC transition states, while the former are more numerous, the latter are lower in energy. In summary, this study further complicates the complex situation presented by Houk, et. al. In the absence of catalyst, 1 can undergo either a Diels-Alder reaction to 3, or pass through a bispericyclic transition state that can lead to 3, but principally to 2 and then undergo a Cope rearrangement to get to 3. The question that ends my previous post on this subject — “ just what role does the enzyme SpnF play?” — remains to be answered.

References

1) Medvedev, M. G.; Zeifman, A. A.; Novikov, F. N.; Bushmarinov, I. S.; Stroganov, O. V.; Titov, I. Y.; Chilov, G. G.; Svitanko, I. V., "Quantifying Possible Routes for SpnF-Catalyzed Formal Diels–Alder Cycloaddition." J. Am. Chem. Soc. 2017, 139, 3942-3945, DOI: 10.1021/jacs.6b13243.

2) Patel, A.; Chen, Z.; Yang, Z.; Gutiérrez, O.; Liu, H.-w.; Houk, K. N.; Singleton, D. A., "Dynamically Complex [6+4] and [4+2] Cycloadditions in the Biosynthesis of Spinosyn A." J. Am. Chem. Soc. 2016, 138, 3631-3634, DOI: 10.1021/jacs.6b00017.

InChIs

1: InChI=1S/C24H34O5/c1-3-21-15-12-17-23(27)19(2)22(26)16-10-7-9-14-20(25)13-8-5-4-6-11-18-24(28)29-21/h4-11,16,18-21,23,25,27H,3,12-15,17H2,1-2H3/b6-4+,8-5+,9-7+,16-10+,18-11+/t19-,20+,21-,23-/m0/s1
InChIKey=JEKALMRMHDPSQK-ZTRRSECRSA-N

2: InChI=1S/C24H34O5/c1-3-19-8-6-10-22(26)15(2)23(27)20-12-11-17-14-18(25)13-16(17)7-4-5-9-21(20)24(28)29-19/h4-5,7,9,11-12,15-22,25-26H,3,6,8,10,13-14H2,1-2H3/b7-4-,9-5+,12-11+/t15-,16-,17-,18-,19+,20+,21-,22+/m1/s1
InChIKey=AVLPWIGYFVTVTB-PTACFXJJSA-N

3: InChI=1S/C24H34O5/c1-3-19-5-4-6-22(26)15(2)23(27)11-10-20-16(9-12-24(28)29-19)7-8-17-13-18(25)14-21(17)20/h7-12,15-22,25-26H,3-6,13-14H2,1-2H3/b11-10+,12-9+/t15-,16+,17-,18-,19+,20-,21-,22+/m1/s1
InChIKey=BINMOURRBYQUKD-MBPIVLONSA-N

from Computational Organic Chemistry http://ift.tt/2nZnhlN

Medvedev, et al. have examined the cyclization step in the formation of Spinosyn A, which is catalyzed by the putative Diels-Alderase enzyme SpnF.¹ This work follows on the computational study done by Houk, Singleton and co-workers,² which I have discussed in this post (Dynamics in a reaction where a [6+4] and [4+2] cycloadditons compete). In fact, I recommend that you read the previous post before continuing on with this one. In summary, Houk, et al. found that a single transition state connects reactant 1 to both 2 and 3. The experimental product with the enzyme SpnF is 3. In the absence of enzyme, Houk, et al. suggest that reactions will cross the bispericyclic transition state TS-BPC (TS1 in the previous post) leading primarily to 2, which then undergoes a Cope rearrangement to get to product 3. Some molecules will follow pathways that go directly to 3.

The PCM(water)/M06-2x/6-31+G(d) study by Medvedev, et al. first identifies 560 conformations of 3. Next, they identified 384 TSs lying within 30 kcal mol^-1 from the lowest TS. These can be classified as either TS-DA (leading directly to 3) or TS-BPC (which may lead to 2 by steepest descent, but can bifurcate towards 3). They opt to utilize the Atoms-in-Molecules theory to identify bond critical points to categorize these TS, and find that 144 are TS-BPC and 240 are TS-DA. (The transition state found by Houk, et al. is the second lowest energy TS found in this study, 0.29 kcal mol^-1 higher in energy that the lowest TS and also of TS-BPC type.)

They also examined two alternative routes. First, they propose a path that first takes 1 to 4 via an alternative Diels-Alder reaction, and a second Cope rearrangement (TS-Cope2) takes this to 2, which can then convert to 3 via TS-Cope1. The other route involves a biradical pathway to either A or B. These alternatives prove to be non-competitive, with transition state energies significantly higher than either TS-DA or TS-BPC.

Returning to the set of TS-DA and TS-BPC transition states, while the former are more numerous, the latter are lower in energy. In summary, this study further complicates the complex situation presented by Houk, et. al. In the absence of catalyst, 1 can undergo either a Diels-Alder reaction to 3, or pass through a bispericyclic transition state that can lead to 3, but principally to 2 and then undergo a Cope rearrangement to get to 3. The question that ends my previous post on this subject — “ just what role does the enzyme SpnF play?” — remains to be answered.

References

1) Medvedev, M. G.; Zeifman, A. A.; Novikov, F. N.; Bushmarinov, I. S.; Stroganov, O. V.; Titov, I. Y.; Chilov, G. G.; Svitanko, I. V., "Quantifying Possible Routes for SpnF-Catalyzed Formal Diels–Alder Cycloaddition." J. Am. Chem. Soc. 2017, 139, 3942-3945, DOI: 10.1021/jacs.6b13243.

2) Patel, A.; Chen, Z.; Yang, Z.; Gutiérrez, O.; Liu, H.-w.; Houk, K. N.; Singleton, D. A., "Dynamically Complex [6+4] and [4+2] Cycloadditions in the Biosynthesis of Spinosyn A." J. Am. Chem. Soc. 2016, 138, 3631-3634, DOI: 10.1021/jacs.6b00017.

InChIs

1: InChI=1S/C24H34O5/c1-3-21-15-12-17-23(27)19(2)22(26)16-10-7-9-14-20(25)13-8-5-4-6-11-18-24(28)29-21/h4-11,16,18-21,23,25,27H,3,12-15,17H2,1-2H3/b6-4+,8-5+,9-7+,16-10+,18-11+/t19-,20+,21-,23-/m0/s1
InChIKey=JEKALMRMHDPSQK-ZTRRSECRSA-N

2: InChI=1S/C24H34O5/c1-3-19-8-6-10-22(26)15(2)23(27)20-12-11-17-14-18(25)13-16(17)7-4-5-9-21(20)24(28)29-19/h4-5,7,9,11-12,15-22,25-26H,3,6,8,10,13-14H2,1-2H3/b7-4-,9-5+,12-11+/t15-,16-,17-,18-,19+,20+,21-,22+/m1/s1
InChIKey=AVLPWIGYFVTVTB-PTACFXJJSA-N

3: InChI=1S/C24H34O5/c1-3-19-5-4-6-22(26)15(2)23(27)11-10-20-16(9-12-24(28)29-19)7-8-17-13-18(25)14-21(17)20/h7-12,15-22,25-26H,3-6,13-14H2,1-2H3/b11-10+,12-9+/t15-,16+,17-,18-,19+,20-,21-,22+/m1/s1
InChIKey=BINMOURRBYQUKD-MBPIVLONSA-N

from Computational Organic Chemistry http://ift.tt/2nZnhlN

Automated chemical drawings

Making a good drawing of a chemical structure can be a difficult task. One wants to prepare a drawing that provides a variety of different information in a clean and clear way. We tend to want equal bond lengths, angles that are representative of the atom’s hybridization, symmetrical rings, avoided bond crossings, and the absence of overlapping groups. These ideals may be difficult to manage. Sometimes we might also want to represent something about the actual 3-dimensional shape. So for example, the drawing on the left of Figure 1 properly represents the atom connectivity with no bond crossing, but the figure on the right is probably the image all organic chemists would want to see for cubane.

Figure 1. Two drawing of cubane

For another example, the drawing on the left of Figure 2 nicely captures the relative stereo relationships within D-glucose, but the drawing on the right adds in the fact that the cyclohexyl ring is in a chair conformation. Which drawing is better? Well, it likely is in the eye of the beholder, and the context of the chemistry at hand.

Figure 2. Two drawings of D-glucose.

Frączek has reported on an automated procedure for creating aesthetically pleasing 2-D drawings of chemical structures.¹ The method involves optimizing distances between atoms projected onto a 2-D plane, along with rules to try to keep atom lengths and angles similar, and symmetrical rings, and minimize overlapping bonds. He shows a number of nice examples, especially of natural products, where his automated procedure PSM (physical simulation method) provides some very nice drawings, often noticeably superior to those generated by previously proposed schemes for preparing drawings.

Using the web site he has developed (http://ift.tt/2mLrFnO), I recreated the structures of some of the molecules I have discussed in this blog. In Figure 3, these are shown side-by-side to my drawings. My drawings were generally done with MDL/Isis/Accelrys/Biovia Draw (available for free for academic users) with an eye towards representing what I think is a suitable view of the molecule based on what I am discussing in the blog post. For many molecules, PSM does a very nice job, sometimes better than what I have drawn, but in some cases PSM produces an inferior drawing. Nonetheless, creating nice chemical drawings can be tedious and PSM offers a rapid option, worthy of at least trying out. Ultimately, what we decide to draw and publish is often an aesthetic choice and each individual must decide on one’s own how best to present one’s work.

My Drawing	PSM

Figure 3. Comparison of my drawings vs. drawing made by PSM.

References

1) Frączek, T., "Simulation-Based Algorithm for Two-Dimensional Chemical Structure Diagram Generation of Complex Molecules and Ligand–Protein Interactions." J. Chem. Inform. Model. 2016, 56, 2320-2335, DOI: 10.1021/acs.jcim.6b00391.

from Computational Organic Chemistry http://ift.tt/2mLs0H2

Making a good drawing of a chemical structure can be a difficult task. One wants to prepare a drawing that provides a variety of different information in a clean and clear way. We tend to want equal bond lengths, angles that are representative of the atom’s hybridization, symmetrical rings, avoided bond crossings, and the absence of overlapping groups. These ideals may be difficult to manage. Sometimes we might also want to represent something about the actual 3-dimensional shape. So for example, the drawing on the left of Figure 1 properly represents the atom connectivity with no bond crossing, but the figure on the right is probably the image all organic chemists would want to see for cubane.

Figure 1. Two drawing of cubane

For another example, the drawing on the left of Figure 2 nicely captures the relative stereo relationships within D-glucose, but the drawing on the right adds in the fact that the cyclohexyl ring is in a chair conformation. Which drawing is better? Well, it likely is in the eye of the beholder, and the context of the chemistry at hand.

Figure 2. Two drawings of D-glucose.

Frączek has reported on an automated procedure for creating aesthetically pleasing 2-D drawings of chemical structures.¹ The method involves optimizing distances between atoms projected onto a 2-D plane, along with rules to try to keep atom lengths and angles similar, and symmetrical rings, and minimize overlapping bonds. He shows a number of nice examples, especially of natural products, where his automated procedure PSM (physical simulation method) provides some very nice drawings, often noticeably superior to those generated by previously proposed schemes for preparing drawings.

Using the web site he has developed (http://ift.tt/2mLrFnO), I recreated the structures of some of the molecules I have discussed in this blog. In Figure 3, these are shown side-by-side to my drawings. My drawings were generally done with MDL/Isis/Accelrys/Biovia Draw (available for free for academic users) with an eye towards representing what I think is a suitable view of the molecule based on what I am discussing in the blog post. For many molecules, PSM does a very nice job, sometimes better than what I have drawn, but in some cases PSM produces an inferior drawing. Nonetheless, creating nice chemical drawings can be tedious and PSM offers a rapid option, worthy of at least trying out. Ultimately, what we decide to draw and publish is often an aesthetic choice and each individual must decide on one’s own how best to present one’s work.

My Drawing	PSM

Figure 3. Comparison of my drawings vs. drawing made by PSM.

References

1) Frączek, T., "Simulation-Based Algorithm for Two-Dimensional Chemical Structure Diagram Generation of Complex Molecules and Ligand–Protein Interactions." J. Chem. Inform. Model. 2016, 56, 2320-2335, DOI: 10.1021/acs.jcim.6b00391.

from Computational Organic Chemistry http://ift.tt/2mLs0H2