We all know about allylic strain. Today I want to talk about Inomata’s syn-effect (see the graphic below), which is on display in certain base-promoted isomerization reactions. I have seen Professor Inomata’s thought-provoking work for many years and I think it stands as a very useful example of stereoelectronic balance in acyclic stereocontrol. The peculiar aspect here is that the Z-olefin is favoured. I don’t think cases like this belong to the usual repertoire of topics we discuss while teaching the foundations of acyclic stereocontrol. Indeed, the syn-effect seems to run counter to some of our intuition regarding the build-up of unfavourable steric interactions in transition states. The effect is neat, yet I am kind of happy that there is not too many instances of it out there. I, for one, would not want to mention it when I teach allylic strain. Why confuse all those bright young minds?

In syn-effect, the electronic contribution made when CH sigma orbitals interact with the pi-system, overrides the unfavourable A(1,3) interaction that develops when the R group is forced to be coplanar with the vinyl C-H bond. At least this is what the authors propose, although I have not seen theoretical papers dealing with this phenomenon. It is exceptional cases like this that keep chemistry rolling. There might be other outliers out there and we need to find them.

https://www.jstage.jst.go.jp/article/yukigoseikyokaishi/67/11/67_11_1172/_pdf

I just realized that there is something in common between chemical science and economics. Surprised? Hear me out. I will name two important concepts: risk management and exit strategy.

Risk management. When I discuss chemistry ideas with students who are new to research, I often hear questions such as “Do you think this idea will work?”. It takes time to realize that this question has no place in research. This question is irrelevant because nobody has a crystal ball. Very few ideas actually work. The only relevant question is: “Is this idea worth the risk?”. Students who are passionate about science get this really well and are driven to work hard once they realize that the return on their time/effort could be substantial.

Exit strategy. Once we commit to pursuing interesting, yet risky ideas in the lab, we encounter another parallel with economics. I refer to having an “exit strategy”, or abandoning your project because your efforts are best spent elsewhere. In my view, acquiring a good exit strategy is very difficult and I honestly cannot pretend that I have mastered this myself. When do you say that a given research project needs to be stopped? Yet, this knowledge is critical to any research undertaking. I will provide an example that has been articulated by Richard Nisbett, a social psychologist at the University of Michigan (http://www-personal.umich.edu/~nisbett/):

An aging hospital needs to be replaced. Detailed cost estimates suggest that it would be as expensive to remodel this old hospital as to demolish it and build a new one. The proponents of remodelling say that the original hospital was very expensive to build and that it would be wasteful to simply reduce it to rubble. On the other hand, the proponents of building the new hospital say that it would inevitably be more modern. Which path is wiser – remodel the old hospital or build a new one? If you are of the opinion that the old hospital should be remodeled, you have fallen into the “sunk-cost trap” shorthand abstraction (SHA) known to economists. The money spent on the old hospital is irrelevant – it’s sunk – and has no bearing on the present choice. To draw a parallel to research, I submit that this is one of the most difficult lessons to learn when running a lab – how to have an exit strategy and know when to stop pouring resources into a given area. We need to trust our instincts and not fall into the “sunk-cost trap”.

I have not written about my sabbatical work for a while. As my sabbatical stint involving protein crystallization approaches the finish line at the end of December, I realize that I have learned a lot of new things. Take, for instance, what we did today with Elena (I blogged about our joint work on several occasions). We recently got some exciting new crystals of a protein I won’t disclose right now (it is just too early in the process). The nature of the protein is not that relevant as I just want to cover an interesting process related to improving crystal quality. We have struggled to crystallize this particular protein for some time. The crystals we have produced prior to today did not diffract well. To improve their quality, we resorted to seeding, which started by us fishing out our imperfect crystals under the microscope, followed by grinding them using a simple device shown on the left side below.

What you see is an Eppendorf vial with a small polystyrene ball in it. When you add to this vial the mother liquor together with your low-quality crystals and vortex them, the ball breaks them up into tiny pieces. Under the microscope, you can actually see them as sharp little fragments suspended in liquid. We made this “crystal slush” last Friday. Today we set up the hanging drops that you see above. Each location is sealed by grease and contains an aqueous buffer (with some additives) at the bottom. Using 0.1microliter volumes you set up hanging drops that have various combinations of the protein of interest and the buffer. Most importantly, to each drop you add 0.3 microliters of the “crystal slush” suspension. That’s it. You do all of this on a thin round piece of glass, invert it, and place it above the buffer solution in each of the 8 locations shown above. Despite gravity, the drops do not fall because of the high surface tension of water… I think we need to take a lot of these protein crystallization tricks into the synthetic organic domain. Personally, I have never tried careful concentration adjustment as a means to drive crystal formation. For Elena, though, there is an enormous difference between 1.25M, 1.3M, and 1.35M protein solutions. Apparently, such spectrum of concentrations can play a huge role in determining the success of crystallization. We’ll see what happens. The main lesson for me is that progress is slow and you just have to be patient. Alas, this is one skill I left behind in my postdoc days… Elena keeps me in check, though!