Reaction development: A checklist (Part 2)

Citation:

Tyler, J.L.; Trauner, D.; Glorius, F. Reaction development: a student's checklist. Chem. Soc. Rev. ASAP. https://pubs.rsc.org/en/content/articlelanding/2025/cs/d4cs01046a

Summary Figure:

Background:

Continuing to go through this "checklist" about how to turn a discovered reaction into a paper. Today's section will focus on how to identify interesting mechanistic features of the reaction, which covers parts of steps 2, 3, and 5 on their checklist:

2. Kinetics and Thermodynamics

(a) Can the rate law be determined?

In most cases, kinetic data is not collected for a given reaction because it is moderately difficult and gives fairly specific information. The authors make a good point that collecting rate data could give highly valuable information about stoichiometry that can inform optimization of the reaction. If you have a reaction that is first order with respect to a given additive (say, a halide salt), then you can increase the quantity of that additive to enhance the rate of the reaction. For example, Suzuki reactions often require the use of a base (often an alkoxide or fluoride salt) to improve transmetalation from the boronic acid. If you determine the reaction is first order with respect to the base, you can add more to improve the reaction. I think the proposal by the authors to try collecting kinetic data early on in reaction discovery interesting, but unlikely to be practiced. The amount of effort to get high quality kinetic data is often higher than the effort necessary to optimize the reaction via brute force, especially when the pre-optimized reaction may not be amenable to collecting kinetic data. It's hard to get kinetics on a 7% yield. 

(b) Can you increase the rate?

Next, the authors ask if there are was to increase the rate of reaction, which in some ways is the opposite of the scope. Instead of finding the limits of reactivity, the goal here is to find the best case reaction, by activating the substrate more. The authors give the example of using hydrogen bonding interactions or activating Lewis acids or bases to make a substrate more reactive. Going back to the Suzuki cross-coupling example, if transmetalation from the boronic acid is difficult, the addition of a Lewis base (like an alkoxide or fluoride) could form the more activated boronate, increasing the rate of transmetalation. Another example would be changing functional groups, such as using an aryl bromide instead of an aryl chloride in a cross-coupling reaction, because the aryl bromide has a weaker C-X bond and is therefore more activated. 

(b) Have you identified the catalytically active species?

Technically, this is in section 5, but I think it appropriately fits with these points. If you can identify the true catalyst, then you can avoid induction periods, or even discover other reactivity. For example, there have been multiple recent cases where bisphosphine ligands have been shown to be oxidized to the mono-oxidized phosphine ligand (See: https://chemrxiv.org/engage/chemrxiv/article-details/66aeabbd5101a2ffa809a6fa). Personally, I've tried to synthesize a nickel catalyst directly instead of throwing a nickel salt and ligand together, and ended up introducing a 4 hour induction period, because the catalyst I made wasn't the active catalyst!

(c) Have you established the steric sensitivity?

In contrast, this is more directly a scope question. More on this is later. 

(d) Have you identified the reaction driving force?

(e) Can you bias an equilibrium?

(f) Is the intended product stable?

I find it interesting that they ask these questions here, because in my opinion these are questions about reaction design. If you don't know what the reaction driving force is, then why would you expect the reaction to work? If the reaction seems thermodynamically infeasible, and you don't know why it would work, then why are you doing it? Finding a way to bias the equilibrium is a tool you can use to improve the driving force. Similarly, if the intended product is not stable, some solution needs to be found before anything else, or you're never going to collect meaningful data. For example, if you are planning to study a conjugate addition with a cuprate reagent and want to know more about the cuprate being formed, finding a way to titrate or otherwise measure the reactivity of the cuprate has to be part of the initial experimental design. Otherwise you're just chucking reagents in a flask and praying. 

(a) Can the reaction be catalysed?

Once again, this is the kind of question that needs to be asked in the design phase of method development. If you are using stoichiometric reagents, but the hypothesized mechanism does not need it, you should have a good reason to be trying it stoichiometrically. 

3. Mechanism

(a) Does the proposed mechanism require evidence?

(b) Can the intermediates be identified?

(c) Can the reaction pathway be computed?

(d) Is there an alternative route to the active species?

I'm biased here. I love looking at mechanisms in papers, and often will skip straight to the proposed catalytic cycle. I hate it when authors use mechanisms by analogy instead of doing the work themselves. However, in many cases, the utility of a new method is that it expands the scope of previously discovered reactions to new partners. In these cases, one or two quick mechanistic experiments to check that the intermediates seem to be consistent is usually fine. I do wish that more authors drew multiple plausible mechanisms when appropriate. 

I am also biased in favor of experimental mechanistic work over computational work. If you can isolate or at least provide evidence for certain intermediates in your proposed mechanism, then that helps verify the entire proposal. I really like how they use this section to list a number of choice mechanistic experiments. The examples don't necessarily fit each section, but the important part is that they list a ton of fan-favorites from your standard physical organic class, which I'm listing below with some of the possible information they give:

-Hammett plot (cation or anion formation)

-Kinetic isotope effect (is this carbon involved in the rate determining step)

*Don't forget that there's also 13C KIE, which isn't mentioned here but is very useful!

-Stern-Volmer (identifies key species in photochem)

-cyclic voltammetry (identifies key oxidation/reduction species)

-radical clocks (identifies if a radical forms at a given carbon)

-radical traps (identifies if a cage-unbound radical forms)

The best mechanistic experiment is always going to be synthesizing a given intermediate from an alternate pathway (or at least something close to it. One classic example is studying oxidative addition by swapping phenyl halides with o-tolyl halides (they're even stable enough to be precatalysts: https://www.nature.com/articles/s41570-017-0025). For many oxidative addition complexes, the Ar-M-X species are unstable end up forming biphenyl dimers. Using the o-tolyl halides enables the isolation of the Ar-M-X species because the steric hindrance of the o-tolyl prevents reductive elimination. 

Finally, I love the authors' take on the utility of computed mechanisms. Computation can support or disprove competing mechanisms, but they can never prove a mechanism. If you propose a species forms based on experimental data, computation can support that proposal by showing that the species is energetically accessible. If a proposed mechanism would go through an extremely high energy intermediate, it means that pathway is likely less feasible. If every pathway goes through infeasible high energy intermediates, it means you did your computations wrong, because experimentally you know the reaction works. 

Computation can also support selectivity by assigning numerical values to things we "know" as chemists. For example, if we "know" that adding a Lewis acid to a reaction makes a carbonyl more electrophilic, using computation we can measure the energy of an addition into that carbonyl. 

5. Catalysis

(c) Can you catalyse the reaction enantioselectively?

Often, figuring out if a reaction can be asymmetric is built into the reaction design. Depending on the relevant elementary steps, there may be a way to either introduce chirality (stereoselective) or use built-in chirality to construct enantioenriched products (stereospecific). However, at some point in the reaction process this question should be asked. 

(d) Is the catalyst turnover optimal?

I think the authors don't go far enough in explaining why it might be beneficial to identify the turnover number (TON) of the catalyst. Usually, the TON is found by dividing the amount of product by the amount of catalyst, and the way to increase TON is to use less catalyst. However, I think the most important thing to optimize with this is identifying how the catalyst is deactivated. If you can prevent the catalyst from being deactivated, it can keep doing reactions. For a great example, see: https://pubs.acs.org/doi/abs/10.1021/acs.oprd.7b00342

Key takeaways:

This is ending up being mostly my commentary on the paper. 

I am a big believer in designing reactions around a mechanism. You should have some proposed mechanism in mind for a reaction that is feasible, and use that to propose reasonable optimizations. 

Later on, you should do careful mechanistic work (mostly experimental) to verify your hypothesis. This enables other researchers to build on your work. 

 

(Part 3: https://alwaysbecoupling.blogspot.com/2025/02/reaction-development-checklist-part-3.html)