Effect of Hydrogen Bonds on pKa Values: Importance of Networking

Shokri, A.; Abedin, A.; Fattahi, A.; Kass, S. R.  J. Am. Chem. Soc. 2012, 134, 10646 (Paywall)

Contributed by Steven Bachrach.
Reposted from Computational Organic Chemistry with permission

Can a hydrogen bonding network affect acidity? Kass has examined the polyol 1 whose conjugate base1cb can potentially be stabilized by a large hydrogen bonding network.¹ Kass had previously found a significant acidy enhancement in comparing t-butanol (ΔG(deprotonation) = 369.2 kcal mol^-1) with that of 2 (ΔG(deprotonation) = 334.4 kcal mol^-1).²

Table 1 lists the computed and experimental free energies of deprotonation of 1. The experimental values are computed at M06-2x/maug-cc-pVT(+d)Z. The structure of 1cb is drawn in Figure 1.

Table 1. Computed and experimental free energies (kcal mol^-1 of deprotonation of some alcohols.

	MO6-2x	Expt
t-butanol	368.6	369.3
2	335.0	334.4
1	320.2	313.5

The difference in the acidity of t-butanol and 2, some 30 kcal mol^-1, reflects the stability afforded by three intramolecular hydrogen bonds to the oxyanion. In going from 2cb to 1cb, each of the hydroxyl groups that donate to the oxyanion act as the acceptor of a hydrogen bond from the more removed hydroxyl groups. There is in effect a first and second layer of hydrogen bond network in 1cb. These secondary hydrogen bonds lead to further stabilization of the anion, as reflected in the diminished DPE of 1 over 2: 320.2 vs. 335.0 kcal mol^-1. Note that this secondary layer does not stabilize the anion to the same degree as the primary layer, but nonetheless its effect is large and quite striking.

1cb

Figure 1. M06-2x/maug-cc-pVT(+d)Z optimized structure of 1cb.

Even in solution these more remote hydrogen bonds can stabilize the anion. So, using the CPCM approach and modeling DMSO, 2 is predicted have a pK_a that is 15 units below that of t-butanol, and 1is predicted to be 3 pK_a units more acidic than 2. Experiments verify this prediction with the pK_as of 16.1 for 2 and 11.4 for 1.

References

(1) Shokri, A.; Abedin, A.; Fattahi, A.; Kass, S. R. "Effect of Hydrogen Bonds on pKa Values: Importance of Networking," J. Am. Chem. Soc. 2012, 134, 10646-10650, DOI: 10.1021/ja3037349

(2) Tian, Z.; Fattahi, A.; Lis, L.; Kass, S. R. "Single-Centered Hydrogen-Bonded Enhanced Acidity (SHEA) Acids: A New Class of Brønsted Acids," J. Am. Chem. Soc. 2009, 131, 16984-16988, DOI:10.1021/ja9075106

InChIs

1: InChI=1S/C13H28O7/c14-4-1-10(17)7-13(20,8-11(18)2-5-15)9-12(19)3-6-16/h10-12,14-20H,1-9H2
InChIKey=HGTVPOTWAYDRSM-UHFFFAOYSA-N

1cb: InChI=1S/C13H27O7/c14-4-1-10(17)7-13(20,8-11(18)2-5-15)9-12(19)3-6-16/h10-12,14-19H,1-9H2/q-1
InChIKey=UQPPTNIHRICITD-UHFFFAOYSA-N

2: InChI=1S/C7H16O4/c8-4-1-7(11,2-5-9)3-6-10/h8-11H,1-6H2
InChIKey=FAQWYKIIWYVDPQ-UHFFFAOYSA-N

2cb: InChI=1S/C7H15O4/c8-4-1-7(11,2-5-9)3-6-10/h8-10H,1-6H2/q-1
InChIKey=WSCPTRIAWKZJFZ-UHFFFAOYSA-N

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Refinement of protein structure homology models via long, all-atom molecular dynamics simulations

Alpan Raval, Stefano Piana, Michael P. Eastwood, Ron O. Dror, and David E. Shaw, Proteins 2012, 80, 2071-2079 (Paywall)

Contributed by Victor Guallar

Many theoretical chemists work routinely on biological systems and, in particular, on proteins. While it might not be their main interest, predicting the conformational sampling associated to these systems is certainly a concern.  Those who have been around for a while have seen how the necessary conformational sampling has moved from few picoseconds to hundreds of nanoseconds and even microseconds (while I do not agree, molecular dynamics has almost the exclusivity as a sampling technique). Clearly the latest development of special-purpose computers, such as the remarkable effort from the D. E. Shaw Research group, together with the development of molecular dynamics for graphical processing units, have contributed to this time expansion. Along these advances we surely had the following questions: are the force fields up to it?, how meaningful are these long molecular dynamics simulations?

The Shaw group has probably already answered these questions for us. In a comprehensive study¹ they produce at least a hundred microseconds simulation for 24 proteins used in recent CASP competitions. They frame their study under the capabilities of molecular dynamics (and force fields) in refining homology models. Thus, for each system they produce a trajectory from both an initial homology model and from the native X-ray structure (or NMR). This study followed a previous one where the simulations were capable of accurately reproducing the native state on several fast-folders. The results this time, however, are quite surprising and even worrisome. For most of the systems the structures drift away from the native state. Furthermore, this drift occurs even when starting from the native state. Overall the results indicate that for most systems the force field minimum is not consistent with the X-ray or NMR experimental structures. While the authors only used two force fields (considered to be the best ones), they conclude that most likely this is a limitation for all available force fields.

The authors obtain better results when imposing constraints to the simulation (limiting the drift away from the native structure). Thus, one can conclude from this work that brute force molecular dynamics simulations are still far away from being accurate. Obviously similar conclusion could be applied to other sampling techniques using the same force fields (for example Monte Carlo techniques). While we wait for better force fields (maybe polarizable ones such AMOEBA?), we probably should use molecular dynamics as a local exploration rather than to predict novel conformations, or to score significantly different ones. Of course these limitations might not apply to those systems with a strong preference for a state, such as fast-folder proteins.

References

1 Alpan Raval, Stefano Piana, Michael P. Eastwood,1 Ron O. Dror, and David E. Shaw, Proteins 2012, 80, 2071-2079 

Transition states of native and drug-resistant HIV-1 protease are the same

D. Randal Kippa, Jennifer S. Hirschia, Aya Wakataa, Harris Goldstein, and Vern L. Schramm Proceedings of the National Academy of Sciences 2012, 109, 6543 (Paywall)

What is the rate determining step?
The general features of the HIV-1 protease mechanism appear to be 1) nucleophilic attack on the amide carbonyl group by a water molecule to form a gem-diol intermediate, 2) protonation of the amide nitrogen, and 3) cleavage of the amide C-N bond.

As pointed out in the introduction, computational studies such as Okimoto et al. and. Piana et al. both  seem to indicate that Step 2 is the rate limiting step.

However, a closer look at these studies suggest that the issue is not well settled.  Okimoto et al.'s (small gas phase) model suggests that the gem-diol intermediate is more stable than the enzyme-substrate complex and computed the barrier of the second step relative to this intermediate.  Piana et al.'s (QM/MM) model suggests that the gem-diol intermediate is less stable than the enzyme-substrate complex and computed the barrier of the second step relative to this enzyme substrate.

If one switches the reference state in both studies Okimoto et al.'s model would predict the first two steps to have essentially the same barrier, while Piana et al.'s model would predict the first step to be rate determining.  Furthermore, the primary $^{15}$N isotope effect computed by Piana et al. (0.97$\pm$0.2) is larger than the experimental value obtained by Rodrigez et al. (0.995$\pm$0.002) (large isotope effects mean significant deviations from 1).

Kinetic isotope effects confirm the rate limiting step and the transition state structure

Schramm and co-workers have used labelled substrates to measure primary $^{14}$C and $^{15}$N and secondary $^3$H and $^{18}$O isotope effects.  Furthermore, they used small gas phase models to compute the corresponding isotope effects for all five stationary points at the ONIOM (M06-2X/6-31+G**:am1) level of theory.

Overall the measured isotope effects best match the computed values for the transition state for Step 2, which is therefore likely to be the rate determining step.  This isotope effect was computed relative to the enzyme-substrate complex; it would be interesting to recompute this value relative to the gem-diol intermediate, which is sufficiently stable to be observed experimentally at low-pH conditions (Das et al.)

Transition states and drug design
Very similar isotope effects was also measured for a mutant (I84V) which has displayed resistance to all nine FDA approved-inhibitors, indicating that the transition state structure in this mutant is quite similar to that of the wild-type.  Thus, transition state-mimics would likely inhibit both forms of the enzyme and may lead to new inhibitors that are less prone to resistance.

Acknowledgement: Thanks to Luca De Vico for alerting me to this paper

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Aromatic Transition States in Nonpericyclic Reactions: Anionic 5-Endo Cyclizations Are Aborted Sigmatropic Shifts

Gilmore, K.; Manoharan, M.; Wu, J. I. C.; Schleyer, P. v. R.; Alabugin, I. V. J. Am. Chem. Soc.2012, 134, 10584–10594 (Paywall)
Contributed by Steven Bachrach.
Reposted from Computational Organic Chemistry with permission

The activation energy for the 5-endo-dig reaction of the anion 1 is anomalously low compared to its 4-endo-dig and 6-endo-dig analogues. Furthermore, the TS is quite early, earlier than might be expected based on the Hammond Postulate. Alabugin and Schleyer have examined this reaction and found some interesting results.¹

First, NICS(0) values for a series of related intermolecular anionic attack at alkynes show some interesting trends (Table 1). Two of the transition states look like they might be aromatic: the TSs for the 3-exo-dig and the 5-endo-dig reaction have NICS(0) values that are quite negative. However, given the geometry of these TSs, particularly the close proximity of the σ bonds to the ring center, one might be concerned about contamination of these orbitals. So, NICS(0)_MOzz computations, which look at the tensor component perpendicular to the ring using just the π-MOs, shows that the 3-exo-dig is likely non-aromatic (NICS(0)_MOzz is near zero), the TS for the 4-endo-dig reaction is antiaromatic (NICS(0)_MOzz very positive) and the TS for the 5-endo-dig reaction is aromatic (NICS(0)_MOzz is very negative. So this last reaction is the first example of an aromatic transition that is not for a pericyclic reaction!

Table 1. NICS(0) and NICS(0)_MOzz for the TS of some anionic alkyne cyclizations.

	NICS(0)	NICS(0)MOzz
3-exo-dig	-19.3	-1.6
4-endo-dig	1.8	23.9
5-endo-dig (1)	-15.2	-20.5

These authors argue that the reaction of 1 is an “aborted” sigmatropic shift. A normal pericyclic reaction is a single step with a single (concerted) transition state. An interrupted sigmatropic shift has an intermediate that lies higher in energy than the reactants, such as in the Bergman cyclization of an enediyne. The aborted sigmatropic shift has an intermediate that lies lower in energy than the reactants, such as in the cyclization of 1.

References

(1) Gilmore, K.; Manoharan, M.; Wu, J. I. C.; Schleyer, P. v. R.; Alabugin, I. V. "Aromatic Transition States in Nonpericyclic Reactions: Anionic 5-Endo Cyclizations Are Aborted Sigmatropic Shifts," J. Am. Chem. Soc.2012, 134, 10584–10594, DOI: 10.1021/ja303341b

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Chemical Networks (Triple Header!)

1. Rewiring Chemistry: Algorithmic Discovery and Experimental Validation of One-Pot Reactions in the Network of Organic Chemistry 
2. Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry Chemical
3. Network Algorithms for the Risk Assessment and Management of Chemical Threats 

A back-to-back-to-back (!) set of three papers in Angewandte Chemie from Bartosz Grzybowski and co-workers. All three articles concern the development of Chemical Networks and their application in synthetic chemistry, of which more later. It is often said that the realm of synthesis is both art and science, however, the wealth of empirical observations made over centuries of making molecules underpin the field. As Grzybowski remarks here, “it is simply beyond cognition of any individual human to understand and analyze all this collective chemical knowledge”, and most chemists already search online synthesis databases to perform individual steps, but perhaps the role of automated computational synthetic route selection, and reaction design is set to grow? Also see Dean Tantillo's recent post on CCH.

Grzybowksi’s group has constructed a network of organic chemistry (NOC) from reactions in the chemical literature since 1779 until present day: reactants and products are represented by nodes in this graph and known chemical interconversions by edges. From this NOC containing seven million reactions, the first paper of the series seeks to discover new ways of performing consecutive reactions in the same vessel (so-called “one pot” reactions). From known reactions that interconvert A to B and B to C, the authors have coded filters that check for compatability between solvents, reagents, catalysts etc so that the two steps may be performed in the same reaction vessel, thus creating a novel way to prepare C from A in one step. Typically synthetic organic protocols are the result of much tinkering and optimization studies in the lab: in contrast the NOC predictions have yield a number of two, three and four step one-pot reactions that give moderate to good yields without any human optimization.

In the second paper the group turn their attention to designing “optimal” reaction pathways to synthesise a given target molecule. Again the NOC is used, this time to propagate backwards from the target via an initial synthetic plan to starting materials. A Metropolis Monte Carlo algorithm is used to randomly sample alternative routes in order to minimize a penalty function associated with the cost of performing each step. Impressively this approach has been used already by a synthesis company to reduce their costs. Additional costs such as waste disposal or energy costs associated with heating/cooling are undoubtedly important for chemistry on the process scale, and perhaps these could be incorporated in future implementations of the optimization.

The third application of a chemical network considers the synthesis of chemical warfare agents. Reaction networks are explored starting from commonly available household chemicals. Thankfully the paper is careful not to disclose any of the synthetic steps involved, and the authors propose strengthening existing regulation of substances by not only regulating single molecules but also combinations of reagents that have been ranked according to game theory as more likely to be used. 

A Paramagnetic Bonding Mechanism for Diatomics in Strong Magnetic Fields

Kai K. Lange, E. I. Tellgren, M. R. Hoffmann and T. Helgaker Science 2012, 337, 327 (Paywall)

A new bonding mechanism
As chemists we are familiar with two types of strong bonds occurring between atoms, covalent and ionic. This paper shows that when very strong magnetic fields (of the order of 10⁵ T) are applied, a third bonding mechanism arrises. Helgaker and co-workers term this perpendicular paramagnetic bonding.


Binding triplet H₂
Whilst previous Hartree-Fock calculations have shown that the lowest triplet state of H₂ becomes bound in strong magnetic fields, this investigation uses the recently developed LONDON code to demonstrate the same phenomena at the Full-CI level. Similar calculations (again, with a very strong magnetic field) on the triplet state of He₂ show a considerable strengthening of the interaction between the constituent atoms.

The nature of this bonding
By examining the behaviour of the molecular orbitals under different orientations relative to the external magnetic field, the authors note a stabilisation of antibonding orbitals in the perpendicular orientation, leading to a new type of bonding interaction. Although the potential of a new chemical bonding mechanism is undoubtably exciting, the magnetic fields required are beyond those that can be currently generated in a lab. However, such fields are present on some stellar objects and the findings of this paper are likely to aid in the spectroscopy of such bodies.

Dynamic Origin of the Stereoselectivity of a Nucleophilic Substitution Reaction

Bogle, X. S.; Singleton, D. A. Org. Lett., 2012, 14, 2528-2531 (Paywall)
Contributed by Steven Bachrach.
Reposted from Computational Organic Chemistry with permission

I think most organic chemists hold dear to their hearts the notion that selectivity is due to crossing over different transition states. Readers of my book and this blog know of the many examples where this notion simply is not true (see here). This post discusses yet another example taking place in a seemingly simple reaction.

Singleton has examined the nucleophilic substitution reaction of 1 with sodium tolylsulfide.¹ The mono substitution gives potentially two different stereoproducts 2 and 3. The experimental ratio of these products 2:3 is 81:19. (Note that things are a bit more complicated because disubstitution can also occur, but this has been factored into the product ratio.)

Based on previous literature, this reaction is likely to proceed in a concerted fashion, and so one might anticipate running computations to locate a transition state leading to 2 and a transition state leading to3. In fact, Singleton finds six different TSs (the lowest energy TS 4 is shown in Figure 1), all within 2 kcal mol^-1 of each other at PCM(ethanol)/B3LYP/6-31+G**. However, the intrinsic reaction coordinate going forward from each of these six TSs leads solely to 2; no TS could be located that connects to 3! (Computations were also performed at PCM(ethanol)/M06-2x/6-31+G** which give very similar results.) Classical transition state theory would lead one to conclude that only 2 should be formed, inconsistent with experiment.

4

5

Figure 1. PCM/B3LYP/6-31+G** optimized structures of TSs 4 and 5.

Furthermore, no intermediate could be located. This is consistent with a concerted mechanism. A second transition state was located which interconverts 2 and 3 with the involvement of a chloride – a sort of addition/rotation/elimination process. This TS 5 is also shown in Figure 1.

A direct dynamics study was performed, and 197 trajectories were computed. Of these, 185 trajectories went to product: 156 to 2 and 29 to 3, for a ratio of 84:16 – in amazing agreement with experiment! The product selectivity is due entirely to dynamic effects. In fact, it is one vibrational mode that dictates the product distribution. Essentially, the nature of the rotation about the C=C bond differentiates the eventual route, with a clockwise rotation leading always to 2 and a counterclockwise rotation leading about a third of the time to 3.

References

(1) Bogle, X. S.; Singleton, D. A. "Dynamic Origin of the Stereoselectivity of a Nucleophilic Substitution Reaction," Org. Lett., 2012, 14, 2528-2531, DOI: 10.1021/ol300817a.

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