Archive for the 'Cramer' Category

Benchmarked Dispersion corrected DFT and SM12

This is a short post mainly to bring to the reader’s attention a couple of recent JCTC papers.

The first is a benchmark study by Hujo and Grimme of the geometries produced by DFT computations that are corrected for dispersion.1 They use the S22 and S66 test sets that span a range of compounds expressing weak interactions. Of particular note is that the B3LYP-D3 method provided the best geometries, suggesting that this much (and justly) maligned functional can be significantly improved with just the simple D3 fix.

The second paper entails the description of Truhlar and Cramer’s latest iteration on their solvation model, namely SM12.2 The main change here is the use of Hirshfeld-based charges, which comprise their Charge Model 5 (CM5). The training set used to obtain the needed parameters is much larger than with previous versions and allows for treating a very broad set of solvents. Performance of the model is excellent.

References

(1) Hujo, W.; Grimme, S. "Performance of Non-Local and Atom-Pairwise Dispersion Corrections to DFT for Structural Parameters of Molecules with Noncovalent Interactions," J. Chem. Theor. Comput. 2013, 9, 308-315, DOI: 10.1021/ct300813c

(2) Marenich, A. V.; Cramer, C. J.; Truhlar, D. G. "Generalized Born Solvation Model SM12," J. Chem. Theor. Comput. 2013, 9, 609-620, DOI: 10.1021/ct300900e

Cramer &DFT &Grimme &Solvation &Truhlar Steven Bachrach 14 Jan 2013 No Comments

Indolyne regioselectivity explained

The nature of reactions of indolynes is the subject of two recent computational/experimental studies. There are three isomeric indolynes 1a-c which are analogues of the more famous benzyne (which I discuss in significant detail in Chapter 4.4 of my book).

One might anticipate that the indolynes undergo comparable reactions as benzyne, like Diels-Alder reactions and nucleophilic attack. In fact the indolynes do undergo these reactions, with unusual regiospecificity. For example, the reaction of the substituted 6,7-indolyne undergoes regioselective Diels-Alder cycloaddition with substituted furans (Scheme 1), but the reaction with the other indolynes gives no regioselection. 1 Note that the preferred product is the more sterically congested adduct.

Scheme 1

In the case of nucleophilic addition, the nucleophiles add specifically to C6 with substituted 6,7-indolynes (Scheme 2), while addition to 4,5-indolynes preferentially gives the C5-adduct (greater than 3:1) while addition to the 5,6-indolynes preferentially gives the C5-adduct), but with small selectivity (less than 3:1).2

Scheme 2

The authors of both papers – Chris Cramer studied the Diels-Alder chemistry and Ken Houk studied the nucleophilic reactions – employed DFT computations to examine the activation barriers leading to the two regioisomeric products. So for example, Figure 1 shows the two transition states for the reaction of 2c with 2-iso-propyl furan computed at MO6-2X/6-311+G(2df,p).

ΔG = 9.7

ΔG = 7.6

Figure 1. MO6-21/6-311+G(2df,p) optimized TSs for the reaction of 2-iso-propylfuran with 2c. Activation energy (kcal mol-1) listed below each structure.1

The computational results are completely consistent with the experiments. For the Diels-Alder reaction of 2-t-butylfuran with the three indolynes 2a-c, the lower computed TS always corresponds with the experimentally observed major product. The difference in the energy of the TSs leading to the two regioisomers for reaction with 2a and 2b is small (less than 1 kcal mol-1), consistent with the small selectivity. On the other hand, no barrier could be found for the reaction of 2-t-butylfuran with 2c that leads to the major product. Similar results are also obtained for the nucleophilic addition – in all cases, the experimentally observed major product corresponds with the lower computed activation barrier.

So what accounts for the regioselectivity? Both papers make the same argument, though couched in slightly different terms. Houk argues in terms of distortion energy – the energy needed to distort reactants to their geometries in the TS. As seen in Figure 2, the benzyne fragment of 2a is distorted, with the C-C-C angle at C4 of 125° and at C5 of 129°. In the transition states, the angle at the point of nucleophilic attack widens. Since the angle starts out wider at C5, attack there is preferred, since less distortion is needed to achieve the geometry of the TS.

2a

TS at C4
ΔG = 12.9

TS
at C5

ΔG = 9.9

Figure 2. B3LYP/6-31G(d) optimized structures of 2a and the TSs for the reaction of aniline with 2a. Activation energy in kcal mol-1.2

Cramer argues in terms of the indolyne acting as an electrophile. Increasing substitution at the furan 2-position makes is better at stabilizing incipient positive charge that will build up there during a (very) asymmetric Diels-Alder transition state. This explains the increasing selectivity of the furan with increasing substitution. The indolyne acting as an electrophile means that the attack will lead from the center will lesser charge. In 2c, the C-C-C angle at C6 is 135.3°, while that at C7 is 117.2°. This makes C7 more carbanionic and C6 more carbocationic; therefore, the first bond made is to C6, leading to the more sterically congested product. Note that Houk’s argument applies equally well, as C6 is predistorted to the TS geometry.

References

(1) Garr, A. N.; Luo, D.; Brown, N.; Cramer, C. J.; Buszek, K. R.; VanderVelde, D., "Experimental and Theoretical Investigations into the Unusual Regioselectivity of 4,5-, 5,6-, and 6,7-Indole Aryne Cycloadditions," Org. Lett., 2010, 12, 96-99, DOI: 10.1021/ol902415s

(2) Cheong, P. H. Y.; Paton, R. S.; Bronner, S. M.; Im, G. Y. J.; Garg, N. K.; Houk, K. N., "Indolyne and Aryne Distortions and Nucleophilic Regioselectivites," J. Am. Chem. Soc., 2010, 132, 1267-1269, DOI: 10.1021/ja9098643

InChIs

1a: InChI=1/C8H5N/c1-2-4-8-7(3-1)5-6-9-8/h2,4-6,9H
InChIKey=RNDHGGYOIRREHC-UHFFFAOYAU

1b: InChI=1/C8H5N/c1-2-4-8-7(3-1)5-6-9-8/h3-6,9H
InChIKey=WWZQFJXNXMIWCD-UHFFFAOYAO

1c: InChI=1/C8H5N/c1-2-4-8-7(3-1)5-6-9-8/h1,3,5-6,9H
InChIKey=UHIRLIIPIXHWLT-UHFFFAOYAH

2a: InChI=1/C9H7N/c1-10-7-6-8-4-2-3-5-9(8)10/h3,5-7H,1H3
InChIKey=VTVUPAJGRVFCKI-UHFFFAOYAJ

2b: InChI=1/C9H7N/c1-10-7-6-8-4-2-3-5-9(8)10/h4-7H,1H3
InChIKey=KKPOWDDYMOXTFW-UHFFFAOYAN

2c: InChI=1/C9H7N/c1-10-7-6-8-4-2-3-5-9(8)10/h2,4,6-7H,1H3
InChIKey=MDAHOGWZOBLIEX-UHFFFAOYAZ

Aromaticity &benzynes &Cramer &Houk Steven Bachrach 29 Mar 2010 3 Comments

Solubility in olive oil

Here’s a nice example of the application of computed solvation energies in non-aqueous studies. Cramer and Truhlar have employed their latest SM8 technique, which is parameterized for organic solvents and for water, to estimate solvation energies in olive oil.1 Now you may wonder why solvation in olive oil of all things? But the partitioning of molecules between water and olive oil has been shown to be a good predictor of lipophilicity and therefore bioavailability of drugs! The model works reasonably well in reproducing experimental solvation energies and partition coefficients. They do make the case that fluorine substitution which appears to improve solubility in organics,originates not to more favorable solvation in organic solvents (like olive oil) but rather that fluorine substitution dramatically decreases solubility in water.

References

(1) Chamberlin, A. C.; Levitt, D. G.; Cramer, C. J.; Truhlar, D. G., "Modeling Free Energies of Solvation in Olive Oil," Mol. Pharmaceutics, 2008, 5, 1064-1079, DOI: 10.1021/mp800059u

Cramer &Solvation &Truhlar Steven Bachrach 17 Feb 2009 1 Comment

SM8 performance

Cramer and Truhlar have tested their latest solvation model SM8 against a test set of 17 small, drug-like molecules.1 Their best result comes with the use of SM8, the MO5-2X functional, the 6-31G(d) basis set and CM4M charge model. This computational model yields a root mean squared error for the solvation free energy of 1.08 kcal mol-1 across this test set. This is the first time these authors have recommended a particular computational model. Another interesting point is that use of solution-phase optimized geometries instead of gas-phase geometries leads to only marginally improved solvation energies, so that the more cost effective use of gas-phase structures is encouraged.

These authors note in conclusion that further improvement of solvation prediction rests upon “an infusion of new experimental data for molecules characterized by high degrees of functionality (i.e. druglike)”.

References

(1) Chamberlin, A. C.; Cramer, C. J.; Truhlar, D. G., “Performance of SM8 on a Test To Predict Small-Molecule Solvation Free Energies,” J. Phys. Chem. B, 2008, 112, 8651-8655, DOI: 10.1021/jp8028038.

Cramer &Solvation &Truhlar Steven Bachrach 21 Oct 2008 No Comments

Review of SM8

Cramer and Truhlar1 have published a nice review of their SM8 approach to evaluated solvation energy. Besides a quick summary of the theoretical approach behind the model, they detail a few applications. Principle among these is (a) the very strong performance of SM8 relative to some of the standard approaches in the major QM codes (see my previous blog post), (b) modeling interfaces, and (c) computing pKa values of organic compounds.

References

(1) Cramer, C. J.; Truhlar, D. G., "A Universal Approach to Solvation Modeling," Acc. Chem. Res. 2008, 41, 760-768, DOI: 10.1021/ar800019z.

Cramer &Solvation &Truhlar Steven Bachrach 23 Jul 2008 No Comments

New solvation model: SM8

Truhlar and Cramer have updated their Solvation Model to SM8.1 This model allows for any solvent to be utilized (both water and organic solvents) and treats both neutral and charged solutes. While there are some small theoretical changes to the model, the major change is in how the parameters are selected, the number of parameters, and a much more extensive data set is used for the fitting procedure.

Of note is how well this new model works. Table 1 compares the errors in solvation free energies computed using the new SM8 model against some other popular continuum methods. Clearly, SM8 provides much better results. As they point out, what is truly discouraging is the performance of the 3PM model against the continuum methods. 3PM stands for “three-parameter model”, where the solvation energies of all the neutral solute in water is set to their average experimental value (-2.99 kcal mol-1), and the same for the neutral solutes in organic solvents (-5.38 kcal mol-1), and for ions (-65.0 kcal mol-1). The 3PM outperforms most of the continuum methods!

Table 1. Mean unsigned error (kcal mol-1) for the solvation
free energies computed with different methods.1


Method

Aqueous neutrala

Organic neutralsb

Ionsc

SM8d

0.55

0.61

4.31

IEF-PCM/UA0e

4.87

5.99

9.73

IEF-PCM/UAHFf

1.18

3.94

8.15

C-PCM/GAMESSg

1.57

2.78

8.39

PB/Jaguarh

0.86

2.28

6.72

3PM

2.65

1.49

8.60


a274 data points. b666 data points spread among 16 solvents. c332 data points spread among acetonitrile, water, DMSO, and methanol. dUsing mPW1PW/6-31G(d). eUsing mPW1PW/6-31G(d) and the UA0 atomic radii in Gaussian. fUsing mPW1PW/6-31G(d) and the UAHF atomic radii in Gaussian. gUsing B3LYP/6-31G(d) and conductor-PCM in GAMESS. hUsing B3LYP/6-31G(d) and the PB method in Jaguar.

References

(1) Marenich, A. V.; Olson, R. M.; Kelly, C. P.; Cramer, C. J.; Truhlar, D. G., "Self-Consistent Reaction Field Model for Aqueous and Nonaqueous Solutions Based on Accurate Polarized Partial Charges," J. Chem. Theory Comput., 2007, 3, 2011-2033. DOI: 10.1021/ct7001418.

Cramer &Solvation &Truhlar Steven Bachrach 19 Nov 2007 1 Comment

Predicting NMR chemical shifts of penam β-lactams

Cramer and Hoye have applied DFT computations to the predictions of both protons and carbon NMR chemical shifts in penam β-lactams1 using the procedure previously described in my blog post Predicting NMR chemical shifts. They examined the compounds 1-8 by optimizing low energy conformers at B3LYP/6-31G(d) with IEFPCM (solvent=chloroform). The chemical shifts were then computed using these geometries with the larger 6-311+G(2d,p) basis set and four different functionals: B3LYP, PBE1 and the two specific functionals designed to produce proton and carbon chemical shifts: WP04 and WC04.

A number of interesting results are reported. First, all three functionals do a fine job in predicting the proton chemical shifts of 1-8, with WP04 slightly better than the other two.On the other hand, all three methods fail to predict the carbon chemical shifts of 1-3, though B3LYP and PBE1 do correctly identify 5-8. The failure of WC04 is surprising, especially since dimethyl disulfide was used in the training set. They also noted that WP04 using just the minimum energy conformation (as opposed to a Boltzmann averaged chemical shift sampled from many low energy conformers) did correctly identify lactams 1-4. This is helped by the fact that the lowest energy conformer constituted anywhere form 37% to 68% of the energy-weighted population.

References


(1) Wiitala, K. W.; Cramer, C. J.; Hoye, T. R., “Comparison of various density functional methods for distinguishing stereoisomers based on computed 1H or 13C NMR chemical shifts using diastereomeric penam ?-lactams as a test set,” Mag. Reson. Chem., 2007, 45, 819-829, DOI: 10.1002/mrc.2045.

InChIs

1: InChI=1/C18H17NO5S/c1-18(2)14(17(23)24-3)19-15(22)11(16(19)25-18)10-12(20)8-6-4-5-7-9(8)13(10)21/h4-7,10-11,14,16H,1-3H3/t11-,14+,16+/m0/s1

5: InChI=1/C17H15NO5S/c1-17(2)13(16(22)23)18-14(21)10(15(18)24-17)9-11(19)7-5-3-4-6-8(7)12(9)20/h3-6,9-10,13,15H,1-2H3,(H,22,23)/t10-,13+,15+/m0/s1

Cramer &DFT &NMR Steven Bachrach 22 Oct 2007 No Comments

Predicting NMR chemical shifts

Another three applications of computed NMR chemical shifts towards structure identification have appeared, dealing with carbohydrates and natural products.

Prediction of NMR Signals of Carbohydrates

The study by Cramer and Hoye1 investigates identification of diastereomers with NMR, in particular, identification of cis and trans isomers of 2-methyl- (1), 3-methyl- (2), and 4-methylcyclohexanol (3). The study discusses the ability of different DFT methods to predict the chemical shifts of these alcohols in regard to distinguishing their different configurations. An interesting twist is that they have developed a functional specifically suited to predict proton chemical shifts and a second functional specifically for predicting carbon chemical shifts.2

The approach they take was first to optimize the six different conformations for each diastereomer including solvent (chloroform). They chose to optimize the structures at B3LYP/6-311+G(2d,p) with PCM. The six conformers (notice the axial/equatorial relationships, along with the position of the alcohol hydrogen) of 1c are presented in Figure 1. Chemical shifts were then obtained with a number of different methods, weighting them according to a Boltzmann distribution.

0.0
xyz

0.20
xyz

0.73
xyz

1.23
xyz

1.56
xyz

1.85
xyz

Figure 1. PCM/B3LYP/6-311+G(2d,p) optimized structures of the conformers of 1c. Relative energies (kcal mol-1) are listed for each isomer.

Now a brief digression into how they developed their modified functional.2 They define the exchange-correlation functional (see Chapter 1.3.1 of my book – or many other computational chemistry books!) as

      Exc = P2Ex(HF) + P3ΔEx(B) + P4Ex(LSDA) + P5ΔEc(LYP) + P6Ec(LSDA)

where the Ps are parameters to be fit and Ex(HF) is the Hartree-Fock exchange energy, ΔEx(B) is the Becke gradient correction to the local spin-density approximation (LSDA), Ex(LSDA) is the exchange energy, ΔEc(LYP) is the Lee-Yang-Parr correction to the LSDA correlation energy, and Ec(LSDA) is the LSDA correlation energy. Chemical shifts were computed for proton and carbon, and the parameters P were adjusted (between 0 and 1) to minimize the error in the predicted chemical shifts from the experimental values. A total of 43 different molecules were used for this fitting procedure. The values of the parameters are given for the carbon functional (WC04), the proton functional (WP04) and B3LYP (as a reference) in Table 1. Note that there is substantial difference in the values of the parameter among these three different functionals.

Table 1. Values of the parameters P for the functionals WC04, WP04, and B3LYP.


 

P2

P3

P4

P5

P6


WC04

0.7400

0.9999

0.0001

0.0001

0.9999

WP04

0.1189

0.9614

0.999

0.0001

0.9999

B3LYP

0.20

0.72

0.80

0.81

1.00


Now, the computed proton and carbon chemical shifts using 4 different functions (B3LYP, PBE1, MP04, and WC04) for 1-3 were compared with the experiment values. This comparison was made in a number of different ways, but perhaps most compellingly by looking at the correlation coefficient of the computed shifts compared with the experimental shifts. This was done for each diastereomer, i.e. the computed shifts for 2c and 2t were compared with the experimental shifts of both 2c and 2t. If the functional works well, the correlation between the computed and experimental chemical shifts of 2c (and 2t) should be near unity, while the correlation between the computed shifts of 2c and the experimental shifts of 2t should be dramatically smaller than one. This is in fact the case for all three functionals. The results are shown in Table 2 for B3LYP and WP04, with the later performing slightly better. The results for the carbon shifts are less satisfactory; the correlation coefficients are roughly the same for all comparisons with B3LYP and PBE1, and WC04 is only slightly improved.
Nonetheless, the study clearly demonstrates the ability of DFT-computed proton chemical shifts to discriminate between diasteromers.

Table 2. Correlation coefficients between the computed and experimental proton chemical shifts.a


 

2ccomp
(1.06)
xyz

2tcomp
(0.0)
xyz


2cexp
 

2texp

0.9971
0.9985

0.8167
0.8098

0.8334
0.9050

0.9957
0.9843


 

3c
(0.0)
xyz

3t
(0.63)
xyz


3cexp
 

3texp

0.9950
0.9899

0.8856
0.9310

0.8763
0.8717

0.9990
0.9979


 

4c
(0.54)
xyz

4t
(0.0)
xyz


4cexp
 

4texp

0.9993
0.9975

0.8744
0.8675

0.8335
0.9279

0.9983
0.9938


aPCM/B3LYP/6-311+G(2d,p)//PCM/ B3LYP/6-31G(d) in regular type and PCM/WP04/6-311+G(2d,p)//PCM/ B3LYP/6-31G(d) in italic type. Relative energy (kcal mol-1) of the most favorable conformer of each diastereomer is given in parenthesis.

Predicting NMR of Natural Products

Bagno has a long-standing interest in ab initio prediction of NMR. In a recent article, his group takes on the prediction of a number of complex natural products.3 As a benchmark, they first calculated the NMR spectra of strychnine (4) and compare it with its experimental spectrum. The optimized PBE1PBE/6-31G(d,p) geometry of 4 is drawn in Figure 2. The correlation between the computed NMR chemical shifts for both 1H and 13C is quite good, as seen in Table 3. The corrected mean average errors are all very small, but Bagno does point out that four pairs of proton chemical shifts and three pairs of carbon chemical shifts are misordered.

Strychnine
4

Figure 2. PBE1PBE/6-31G(d,p) geometry of strychnine 4.3

Table 3. Correlation coefficient and corrected mean average error
(CMAE) between the computed and experiment chemical shifts of 4.


 

δ(1H)

δ(13C)

method

r2

CMAE

r2

CMAE

B3LYP/cc-pVTZ

0.9977

0.07

0.9979

1.4

PBE1PBE/cc-pVTZ

0.9974

0.08

0.9985

0.9


The study of the sesquiterpene carianlactone (5) demonstrates the importance of including solvent in the NMR computation. The optimized B3LYP/6-31G(d,p) geometry of 5 is shown in Figure 3, and the results of the comparison of the computed and experimental chemical are listed in Table 4. The correlation coefficient is unacceptable when the x-ray structure is used. The agreement improves when the gas phase optimized geometry is employed, but the coefficient is still too far from unity. However, optimization using PCM (with the solvent as pyridine to match experiments) and then computing the NMR chemical shifts in this reaction field provides quite acceptable agreement between the computed and experimental chemical shifts.

Corianlactone 5

Figure 3. B3LYP/6-31G(d,p) geometry of carianlactone 5.3

Table 4. Correlation coefficient and corrected mean average error (CMAE) between
the computed and experiment chemical shifts of 5.


 

δ(1H)

δ(13C)

geometry

r2

CMAE

r2

CMAE

X-ray

0.9268

0.23

0.9942

3.1

B3LYP/6-31G(d,p)

0.9513

0.19

0.9985

1.6

B3LYP/6-31G(d,p) + PCM

0.9805

0.11

0.9990

1.2


Lastly, Bagno took on the challenging structure of the natural product first identified as boletunone B (6a).4 Shortly thereafter, Steglich reinterpreted the spectrum and gave the compound the name isocyclocalopin A (6b).5 A key component of the revised structure was based on the δ 0.97 ppm signal that they assigned to a methyl above the enone group, noting that no methyl in 6a should have such a high field shift.

Bagno optimized the structures of 6a and 6b at B3LYP/6-31G(d,p), shown in Figure 4. The NMR spectra for 6a and 6b were computed with PCM (modeling DMSO as the solvent). The correlation coefficients and CMAE are much better for the 6b model than for the 6a model., supporting the reassigned structure. However, the computed chemical shift for the protons of the key methyl group in question are nearly identical in the two proposed structures: 1.08 ppm in 6a and 1.02 ppm in 6b. Nonetheless, the computed chemical shifts and coupling constants of 6b are a better fit with the experiment than those of 6a.

boletunone B 6a

isocyclocalopin A 6b

Figure 4. B3LYP/6-31G(d,p) geometry of the proposed structures of Boletunone B, 6a and 6b.3

Table 5. Correlation coefficient and corrected mean average error (CMAE) between the computed (B3LYP/6-31G(d,p) + PCM) and experiment chemical shifts of 6a and 6b.


 

δ(1H)

δ(13C)

structure

r2

CMAE

r2

CMAE

6a

0.9675

0.22

0.9952

3.7

6b

0.9844

0.15

0.9984

1.9


In a similar vein, Nicolaou and Frederick has examined the somewhat controversial structure of maitotxin.6 For the sake of brevity, I will not draw out the structure of maitotxin; the interested reader should check out its entry in wikipedia. The structure of maitotoxin has been extensively studied, but in 2006, Gallimore and Spencer7 questioned the stereochemistry of the J/K ring juncture. A fragment of maitotoxin that has the previously proposed stetreochemistry is 7. Gallimore and Spencer argued for a reversed stereochemistry at this juncture (8), one that would be more consistent with the biochemical synthesis of the maitotoxin. Nicolaou noted that reversing this stereochemistry would lead to other stereochemical changes in order for the structure to be consistent with the NMR spectrum. Their alternative is given as 9.

7

8

9

Nicolaou and Freferick computed 13C NMR of the three proposed fragments 7-9 at B3LYP/6-31G*; unfortunately they do not provide the coordinates. They benchmark this method against brevetoxin B, where the average error is 1.24 ppm, but they provide no error analysis – particularly no regression so that corrected chemical shift data might be employed. The best agreement between the computed and experimental chemical shifts is for 7, with average difference of 2.01 ppm. The differences are 2.85 ppm for 8 and 2.42 ppm for 9. These computations support the original structure of maitotoxin. The Curious Wavefunction blog discusses this topic, with an emphasis on the possible biochemical implication.

References

(1) Wiitala, K. W.; Al-Rashid, Z. F.; Dvornikovs, V.; Hoye, T. R.; Cramer, C. J., "Evaluation of Various DFT Protocols for Computing 1H and 13C Chemical Shifts to Distinguish Stereoisomers: Diastereomeric 2-, 3-, and 4-Methylcyclohexanols as a Test Set," J. Phys. Org. Chem. 2007, 20, 345-354, DOI: 10.1002/poc.1151

(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) Bagno, A.; Rastrelli, F.; Saielli, G., "Toward the Complete Prediction of the 1H and 13C NMR Spectra of Complex Organic Molecules by DFT Methods: Application to Natural Substances," Chem. Eur. J. 2006, 12, 5514-5525, DOI: 10.1002/chem.200501583

(4) Kim, W. G.; Kim, J. W.; Ryoo, I. J.; Kim, J. P.; Kim, Y. H.; Yoo, I. D., "Boletunones A and B, Highly Functionalized Novel Sesquiterpenes from Boletus calopus," Org. Lett. 2004, 6, 823-826, DOI: 10.1021/ol049953i

(5) Steglich, W.; Hellwig, V., "Revision of the Structures Assigned to the Fungal Metabolites Boletunones A and B," Org. Lett. 2004, 6, 3175-3177, DOI: 10.1021/ol048724t.

(6) Nicolaou, K. C.; Frederick, M. O., "On the Structure of Maitotoxin," Angew. Chem. Int. Ed., 2007, 46, 5278-5282, DOI: 10.1002/anie.200604656.

(7) Gallimore, A. R.; Spencer, J. B., "Stereochemical Uniformity in Marine Polyether Ladders - Implications for the Biosynthesis and Structure of Maitotoxin," Angew. Chem. Int. Ed. 2006, 45, 4406-4413, DOI: 10.1002/anie.200504284.

InChI

1: InChI=1/C7H14O/c1-6-4-2-3-5-7(6)8/h6-8H,2-5H2,1H3
2: InChI=1/C7H14O/c1-6-3-2-4-7(8)5-6/h6-8H,2-5H2,1H3
3: InChI=1/C7H14O/c1-6-2-4-7(8)5-3-6/h6-8H,2-5H2,1H3
4: InChI=1/C21H22N2O2/c24-18-10-16-19-13-9-17-21(6-7-22(17)11-12(13)5-8-25-16)14-3-1-2-4-15(14)23(18)20(19)21/h1-5,13,16-17,19-20H,6-11H
5: InChI=1/C14H14O6/c1-12-2-6(15)8-13(4-18-13)9-10(19-9)14(8,20-12)7-5(12)3-17-11(7)16/h5,7-10H,2-4H2,1H3/t5-,7-,8?,9+,10+,12+,13?,14-/m1/s1
6a: InChI=1/C15H20O6/c1-7-4-5-14(3)12(17)9-8(2)6-20-15(14,11(7)16)21-10(9)13(18)19/h4,8-10,12,17H,5-6H2,1-3H3,(H,18,19)/t8-,9+,10+,12+,14-,15-/m1/s1
6b: InChI=1/C15H20O6/c1-7-4-5-15(12(17)10(7)16)9-8(2)6-20-14(15,3)21-11(9)13(18)19/h4,8-9,11-12,17H,5-6H2,1-3H3,(H,18,19)/t8?,9-,11?,12+,14-,15-/m1/s1

Cramer &DFT &NMR Steven Bachrach 01 Aug 2007 No Comments

More on Asymmetric 1,2-Additions

Addition of enolboranes to α-substituted aldehydes

In Chapter 5.2, we discussed a number of computation studies of the origins of asymmetry in 1,2-additions. We discussed the importance of the Felkin-Anh model, but that modifications of this model are needed to rationalize the broad range of addition reactions.

One modification was presented by Frenking,1 who noted that in the addition of LiH to propanal, it was the conformation of the aldehyde that dictated the energy of the possible transition states. The lowest energy transition state is 1a, lying 1.3 kcal mol-1 below 1b and 1.6 kcal mol-1 below 1c (computed at MP2/6-31G(d)//HF/6-31G(d)). When the LiH fragment is removed and all other atoms kept frozen in their positions in the three transition states, 1a remains the lowest in energy.

A recent article by Cramer and Evans2 examined the addition of enolboranes to aldehydes and also noted the importance of the aldehyde conformation in dictating the stereochemical outcome. The main thrust was, however, that the Cram-Conforth type model for 1,2-addition is more appropriate for some enolborane additions.

This work derives from Evans’ earlier experimental study of the addition of the boron enolate of 2-methyl-3-pentanone to a-alkoxyaldehydes (Scheme 1).3 Evans suggested that there were four transition state models that give a 3,4-anti relationship in the product (Scheme 2). The Felkin-Anh model favors B, since it avoids the syn interaction, and so E enolates will have a greater anti selectivity than Z enolates. On the other hand, the Conforth model favors transition state C, and predicts that Z enolates will have greater anti selectivity. The addition of Z enolates in fact gives large anti selectivity, while addition of E enolates gives poor anti selectivity. These results are consistent with the Cram-Cornforth model.

Scheme 1.

Scheme 2.

Cee, Cramer and Evans2 examined the addition of enolborane to a number of a-substituted propanal compounds. They located six transition states (Figure 1) for the reaction of 2-fluoropropanal, three leading to the (R,S) product (2A-C) and three leading to the (S,S) product (2A’-C’). The lowest energy transition states, 2A and 2A’, both have the fluorine atom positioned anti to the carbonyl, consistent with the Cornforth model. This reflects the stability of 2-fluoropropanal. Similar results are found for addition to 2-chloropropanal

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2A (0.0)

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2B (2.4)

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2C (2.6)

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2A’ (0.8)

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2B’ (1.4)

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2C’ (3.7)

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Figure 1. Optimized transition states and relative energies (kcal mol-1) for the reaction of 2-fluoropropanal with enolborane computed at B3LYP/6-31G(d).2

For the reaction of enolborane with 2-methoxypropanal, the lowest energy transition state, 3, also has the methoxy group anti to the carbonyl (see Figure 2). However, the lowest energy transition state for the reaction of 2-methylthiopropanal, 4, has the MeS group perpendicular to the carbonyl, as predicted by the Felkin-Anh model. Similarly, the lowest energy transition states for the addition to 2-dimethylaminopropanal (5) and to 2-dimenthylphosphinopropanal (6) follow the Felkin-Anh model.

The lowest energy conformer of propanal with F, Cl, or OMe as the 2-substituent has the substituent anti to the carbonyl. All three of these aldehydes undergo addition of enolborane through the Cornforth TS. The lowest energy conformer with SMe2 or PMe2 has the substituent perpendicular to the carbonyl, which mimics its location in the enolborane transition state. Only 2-dimethylaminopropanal falls outside this pattern; its lowest energy conformer positions the substituent about 150° from the carbonyl, but rotation to a perpendiculat (Felkin-Anh) position requires only 2 kcal mol-1, half of that need for F, Cl, or methoxy rotation. Cee, Cramer, and Evans draw two conclusions. First, the stereochemistry 1,2-addition of enolborane parallels the conformation of the aldehyde itself, and second, this implies that the Cornforth pathway can be preferred over the Felkin-Anh for those aldehydes where the anti conformation is particularly stable.

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3

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4

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5

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6

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References

(1) Frenking, G.; F., K. K.; Reetz, M. T., “On the Origin of π-Facial Diastereoselectivity in Nucleophilic Additions to Chiral Carbonyl Compounds. 2. Calculated Transition State Structures for the Addition of Nucleophiles to Propionaldehyde 1, Chloroacetyldehyde 2, and 2-Chloropropionaldehyde 3.,” Tetrahedron 1991, 47, 9005-9018, DOI: 10.1016/S0040-4020(01)86505-4.

(2) Cee, V. J.; Cramer, C. J.; Evans, D. A., “Theoretical Investigation of Enolborane Addition to α-Heteroatom-Substituted Aldehydes. Relevance of the Cornforth and Polar Felkin-Anh Models for Asymmetric Induction,” J. Am. Chem. Soc. 2006, 128, 2920-2930, DOI: DOI: 10.1021/ja0555670

(3) Evans, D. A.; Siska, S. J.; Cee, V. J., “Resurrecting the Cornforth Model for Carbonyl Addition: Studies on the Origin of 1,2-Asymmetric Induction in Enolate Additions to Heteroatom-Substituted Aldehydes,” Angew. Chem. Int. Ed. 2003, 42, 1761-1765, DOI: 10.1002/anie.200350979.

1,2-addition &Cramer &DFT Steven Bachrach 09 Jul 2007 1 Comment