De-novo protein engineering
Proteins are nourishing (so long they are not poisonous) but that's not what makes them interesting for technological development.
What makes Proteins interesting (on the longer term) is that they can form decent engineering materials like e.g. horn and spider silk. Silk is inferior to say nanotube cables but still better than even steel (in terms of specific strength and toughness). Proteins can be the engineering materials that in turn will be used to form stiff structural frameworks in the nanoscale that open up the path to even more advanced productive nanosystems.
The by far greatest part of current interest (state 2017) though stems from the near term objective of massively improving medicine. But that's not the focus of this wiki. There are plenty of other good sources for things like targeted cancer drug delivery for making the horrible treatment methods of chemo-therapy and radiation-therapy obsolete and a thing of the past.
What proteins are
Proteins are chains of aminoacids. They are assembled by the ribosomes in the cells of all living organisms on earth under the instructions from a copy of DNA (so called: transfer-RNA). This was a monumental discovery when it was made.
Small proteins are called peptides. Big peptides are called proteins.
Proteins vs Polymers
Superficially proteins are chain molecules like plastics but the analogy breaks down immediately. Here is a comparison of polymers (plastics) with proteins:
- plastics (like polystyrene) usually have very simple monomers while proteins have the set of ~20 basic amino acids as monomers
- plastics are not folded up "permanently" by thermal motion. Especially not to complex predefined shapes.
- plastics may contain branches in the chain proteins may not
- plastics assemble in a statistical fashion while proteins are assembled almost deterministically in the ribosomes.
"Almost deterministically" because error rates are quite high when compared to digital electronics. A lot of quality control and repair mechanisms in the host organisms cell keep everything from going to utter chaos.
Hijacking lifes nanomachinery – The first step
The story of artificial proteins (not de-novo proteins yet!) started when we learned to hijack the molecular machinery of the cells of organisms (often cyanobacteria but also other organisms - even goats). This works by injecting synthetic DNA into the DNA of the organism using phages (viruses that attack bacteria) as transport vehicle.
Some limitations of lifes nanomachinery
Natural proteins have several disadvantages:
The the (dreaded) folding problem:
Given the DNA for a protein (a gene) and thus the sequence of aminoacids it's extremely difficult to predict how the protein will fold. (By including the molecular biological context - the environment the protein "lives" in - some progress has been made) Institutional supercomputers & distributed citizen science Fold@Home are crunching such problems.
There are various complex reasons why natural proteins
- often are in configurations that are on the verge of falling apart – See: Evolution
- are often highly susceptible to single mutations
- are often highly susceptible to environmental conditions
- often have low symmetry
Note: In cells there are redestabilisation proteins present (which are called (TODO: find and add name here)). These are nudging proteins in a way to get them out of bad states where they fell in the wrong energy minima. That is when they ended up in an incorrectly folded state. If nothing helps they are marked as garbage and recycled by a complex protein system that literally looks like a bucket.
Sidenote: The presence of the many dynamic equilibria of assembly repair and recycling in biological nanosystems was and still is a major contribution factor for the persistent misconceptions that
- every nanosystem must work this way and that
- having every atom in place for longer periods of time is fundamentally in conflict with thermodynamics.
Avoiding these limitations of lifes nanomachinery
>>> De-novo protein engineering <<<
This is about ascending a small step beyond the limitations of lifes nanomachinery.
Despite the issue that the goal that may sound presumptuous to some readers the topic is quite mundane.
To solve the folding problem (for artificial protein design - not for natural protein analysis) one avoids it.
One breaks it into smaller pieces and combines them to larger solutions. Sounds a bit like divide and conquer approach in programming.
- (1) Solving the folding problem for small stable motives building up a library.
- (2) Building up a bigger shape by putting those base motives together again in a way where folding is reliably predictable and stable.
This approach is also known as the inverse folding problem. Taking an superficial analogy to cryptography where the inverse problem (multiplication) is much simper than the forward problem (factorization).
One may want to create overall proteins with high symmetry e.g. allowing self assembly of the final folded proteins into rods shests and such. (TODO: find and link related paper). An abstraction to much higher symmetry has already successfully been performed in the related area of structural DNA nanotechnology.
Upgrading the deepest core of lifes machinery
There are efforts to adding a new basepair to the letters of the DNA. This allows for the encoding of a lot more aminoacids. Extending the toolset of foldamers.
Ending the dependence on the machinery of life
Going away fro hijacking ribosomes.
On the path to advanced productive nanosystems one wants to get away from dependence on and limitation by systems of molecular biology ASAP.
There are already experimental instances of complete independence:
- oglionucleotide only structural DNA nanotechnology
- foldamers that are not made with ribosomes like e.g. spiroligomers
Artificial building blocks are hard to degrade or undegradable by biological organisms. This brings the advantage of robustness and longevity of the products but the the problem of persistent "organic" waste.
The fundamental problem with conventional chemical synthesis involving long sequences of steps is that one suffers an exponential drop in yield. Every step multiplies its (usually not too high) yield. (A chain multiplication).