This is a wish list for protein folding and engineering. It contains some speculation and brain storming and shouldn't be considered completely viable for now.

Wishlist

• Given a 3d shape (of some nanostructure), produce a protein's amino acid sequence that will consistently create that shape. (done as of 2023?)

• Control over protein functional properties, such as catalytic domains and sites, as well as designing specific confirmational changes and control over conformation changes.

• DNA data storage: faster polymerases

• Proteins that make molecular display techniques easier (simplifying lab bench protocols) -- like mRNA display and ribosome display; easier molecular display would be very valuable for projects using directed evolution techniques.

• Better protein-based nanopores for DNA sequencing, amino acid sequencing, and protein sensing.

• Human-controlled DNA polymerase synthesis activity (choose each nucleotide), or an instrumented ribosome to control protein production regardless of mRNA content

• Molecular protein lego: connect multiple legos together to build large-scale protein structures. This is generally useful for modeling and nanostructures. Binding by DNA addresses or other high affinity ligand specific techniques, for a stable toolbox of known protein structures and shapes and building up larger structures from small parts.

• Protein mechanical logic: protein structures that have internal logic and state, based on mechanical motion or other catalytic reactions and interactions.

• Generalized, fully-programmable molecular nanotechnology: programmable nanomachines and nanofactories that can produce other nanostructures to exact specifications, without uncertainty regarding protein folding.

TODO

• What were those long-tube protein molecular-chemistry factories called? (non-ribosomal peptide synthetases or NRPS). They are apparently natural, and they have multiple points of interest inside the tube that modify a molecule as it progresses along the protein.

Other interesting targets

• gene editing proteins (see gene-editing)
• enzymes for DNA synthesis
• molecular recording (like in vivo DNA-based recording devices, for debugging or otherwise, lineage tracing techniques, "of toasters and molecular ticker tapes")
• protein binding affinity stuff (protein-protein interaction)
• catalytic activity, enhancement of catalysis or reduction of catalysis
• synthetic metabolisms
• biosensors

Structural protein design with machine learning

Well, it's probably time to update this page... lots of recent progress in machine learning for protein design.

• AlphaFold2: Highly accurate protein structure prediction with AlphaFold
• RoseTTAFold: Accurate prediction of protein structures and interactions using a three-track neural network
• RFdiffusion: Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models
• A new protein design era with protein diffusion
• A high-level programming language for generative protein design
• Codon language embeddings provide strong signals for protein engineering
• openfold (ref)
• De novo design of high-affinity protein binders to bioactive helical peptides
• Illuminating protein space with a programmable generative model

References

See https://diyhpl.us/~bryan/papers2/bio/protein-engineering/

• https://en.wikipedia.org/wiki/Protein_design
• https://en.wikipedia.org/wiki/Protein_engineering
• https://en.wikipedia.org/wiki/Protein_foldng
• https://en.wikipedia.org/wiki/Protein_structure_prediction_software