[graphene]

Super interesting.

If you read the Feynman speech that he references at the beginning, he actually mentions that as you scale machines down, things like mechanical rigidity will degrade and you will need to change your design rules accordingly. I always assumed that when you reach the molecular level, thermal motion and the constant bombardment by water molecules would mean that the only viable option is to use proteins, just like nature does, so it's very interesting to see that this guy is aiming to use more rigid structures at the molecular level. I guess this is a way to reduce the complexity (degrees of freedom) compared to designing protein tertiary structure. I wonder if this is too constraining though, he admits he has yet to figure out how to build mechanical machines using this approach, and intuitively I'd expect that to be very difficult with this degree of rigidity. You might need the additional flexibility of peptide chains to do many of the interesting things that are possible.

He does point out the advantage of durability, but this raises the obvious issue that one of the questioners alluded to, namely toxicity/pollution risk. I'd think degredation by biological or other means would be a feature, not a bug, since as he points out, even conventional plastics are a huge pollution problem.

Fascinating stuff nonetheless.

[drmeister]

Christian Schafmeister here - thanks! You make some very good points that I can address: (1) Things made with "Molecular Lego" still move, but they keep their shape just enough to organize atoms/groups to do things like speed up reactions and bind other molecules. We've explored dynamics in several of our papers. They aren't too constrained - they are constrained "just enough"; and we can build in flexibility and hinges where ever we want. (2) We don't know how to make mechanical molecular machines with them yet; we need to start making a lot of them and explore their properties to figure that out. The first folks who smelted iron didn't know how to build motors with it - it took a lot of people playing around with iron for a long time to figure that out. I think we can get there in less time but it will take work. (3) Re: toxicity/pollution - this is the first non-natural molecular technology that contains the solution to any problems that it generates. We need to learn how to make catalysts well and then we can build catalysts that break these molecules down. Conceivably, we could build materials that contain the catalysts that break them down and are activated by an external signal. Or we make materials out of bigger bricks (built from Molecular Lego) and we fish them out of the environment, tear them apart from each other, check them for defects and build new materials with the good ones and recycle the broken ones. We can also build catalysts that break down every other indestructable material that we've been dumping into the environment for 100 years. Regarding toxicity, these molecules are made out of carbon, nitrogen, oxygen and hydrogen - the same atoms you are made out of. They are inherently non-toxic (there are qualifiers on this).

[graphene]

Hi Christian, great to have you replying directly like this; I hope my criticism came across as constructive, since I'm super excited about and impressed with this work, as someone also chasing the dream of molecular nanotechnology.

Re: rigidity; I'm curious (apologies for not having read your papers) how you define "just enough" flexibility, and how your design tools take freely moving components into account. Would you agree with my intuitive feeling that there's a tradeoff between designability and functionality, and that your spiroligomer work sits between rationally designed protein structures (very hard problem) and Drexlerian molecular-scale gears and ratchets (similar, determinsitic design rules as in macroscopic systems)? Or, do you feel that anything protein "machines" can do, spiroligomer machines can do too?

I recently started a startup that has molecular nanotechnology as the end goal, and my thinking has been that the flexibility of proteins is an essential element in achieving the capability to design and manufacture with atomic precision, and that the concomitant complexity of the large numbers of degrees of freedom can be tamed with a data-driven approach leveraging machine learning algorithms. I'd love to hear if you have any thoughts on this, and how it relates to the spiroligomer approach.