Applications of DNA-Functionalized Proteins

As an important component that constitutes all the cells and tissues of the human body, protein is involved in most of the biological processes. Inspired by natural protein systems, considerable efforts covering many discipline fields were made to design artificial protein assemblies and put them into application in recent decades. The rapid development of structural DNA nanotechnology offers significant means for protein assemblies and promotes their application. Owing to the programmability, addressability and accurate recognition ability of DNA, many protein assemblies with unprecedented structures and improved functions have been successfully fabricated, consequently creating many brand-new researching fields. In this review, we briefly introduced the DNA-based protein assemblies, and highlighted the limitations in application process and corresponding strategies in four aspects, including biological catalysis, protein detection, biomedicine treatment and other applications.

Artificial protein assemblies with well-defined supramolecular protein nanostructures

Nature uses a wide range of well-defined biomolecular assemblies in diverse cellular processes, where proteins are major building blocks for these supramolecular assemblies. Inspired by their natural counterparts, artificial protein-based assemblies have attracted strong interest as new bio-nanostructures, and strategies to construct ordered protein assemblies have been rapidly expanding. In this review, we provide an overview of very recent studies in the field of artificial protein assemblies, with the particular aim of introducing major assembly methods and unique features of these assemblies. Computational de novo designs were used to build various assemblies with artificial protein building blocks, which are unrelated to natural proteins. Small chemical ligands and metal ions have also been extensively used for strong and bio-orthogonal protein linking. Here, in addition to protein assemblies with well-defined sizes, protein oligomeric and array structures with rather undefined sizes (but with definite repeat protein assembly units) also will be discussed in the context of well-defined protein nanostructures. Lastly, we will introduce multiple examples showing how protein assemblies can be effectively used in various fields such as therapeutics and vaccine development. We believe that structures and functions of artificial protein assemblies will be continuously evolved, particularly according to specific application goals.

Protein interface redesign facilitates the transformation of nanocage building blocks to 1D and 2D nanomaterials

Although various artificial protein nanoarchitectures have been constructed, controlling the transformation between different protein assemblies has largely been unexplored. Here, we describe an approach to realize the self-assembly transformation of dimeric building blocks by adjusting their geometric arrangement. Thermotoga maritima ferritin (TmFtn) naturally occurs as a dimer; twelve of these dimers interact with each other in a head-to-side manner to generate 24-meric hollow protein nanocage in the presence of Ca2+ or PEG. By tuning two contiguous dimeric proteins to interact in a fully or partially side-by-side fashion through protein interface redesign, we can render the self-assembly transformation of such dimeric building blocks from the protein nanocage to filament, nanorod and nanoribbon in response to multiple external stimuli. We show similar dimeric protein building blocks can generate three kinds of protein materials in a manner that highly resembles natural pentamer building blocks from viral capsids that form different protein assemblies.

Deep neural language modeling enables functional protein generation across families

Bypassing nature's evolutionary trajectory, de novo protein generation - defined as creating artificial protein sequences from scratch - could enable breakthrough solutions for biomedical and environmental challenges. Viewing amino acid sequences as a language, we demonstrate that a deep learning-based language model can generate functional artificial protein sequences across families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. Our protein language model is trained by simply learning to predict the next amino acid for over 280 million protein sequences from thousands of protein families, without biophysical or coevolutionary modeling. We experimentally evaluate model-generated artificial proteins on five distinct antibacterial lysozyme families. Artificial proteins show similar activities and catalytic efficiencies as representative natural lysozymes, including hen egg white lysozyme, while reaching as low as 44% identity to any known naturally-evolved protein. The X-ray crystal structure of an enzymatically active artificial protein recapitulates the conserved fold and positioning of active site residues found in natural proteins. We demonstrate our language model's ability to be adapted to different protein families by accurately predicting the functionality of artificial chorismate mutase and malate dehydrogenase proteins. These results indicate that neural language models successfully perform de novo protein generation across protein families and may prove to be a tool to shortcut evolution.

Artificial Protein Coronas Enable Controlled Interaction with Corneal Epithelial Cells: New Opportunities for Ocular Drug Delivery

Topical administration is the most convenient route for ocular drug delivery, but only a minor fraction is retained in the precorneal pocket. To overcome this limitation, numerous drug delivery systems (DDS) have been developed. The protein corona (PC) is the layer of biomolecules (e.g., proteins, sugars, lipids, etc.) that forms around DDS in physiological environments by non-covalent interaction. The PC changes the DDS physical–chemical properties, providing them with a completely novel biological identity. The specific involvement of PC in ocular drug delivery has not been addressed so far. To fulfill this gap, here we explored the interaction between a library of four cationic liposome-DNA complexes (lipoplexes) and mucin (MUC), one of the main components of the tear film. We demonstrate that MUC binds to the lipoplex surface shifting both their size and surface charge and reducing their absorption by primary corneal epithelial cells. To surpass such restrictions, we coated lipoplexes with two different artificial PCs made of Fibronectin (FBN) and Val-Gly-Asp (VGA) tripeptide that are recognized by receptors expressed on the ocular surface. Both these functionalizations remarkedly boosted internalization in corneal epithelial cells with respect to pristine (i.e., uncoated) lipoplexes. This opens the gateway for the exploitation of artificial protein corona in targeted ocular delivery, which will significantly influence the development of novel nanomaterials.

Light-Driven CO2 Reduction by Co-Cytochrome b562

The current trend in atmospheric carbon dioxide concentrations is causing increasing concerns for its environmental impacts, and spurring the developments of sustainable methods to reduce CO2 to usable molecules. We report the light-driven CO2 reduction in water in mild conditions by artificial protein catalysts based on cytochrome b562 and incorporating cobalt protoporphyrin IX as cofactor. Incorporation into the protein scaffolds enhances the intrinsic reactivity of the cobalt porphyrin toward proton reduction and CO generation. Mutations around the binding site modulate the activity of the enzyme, pointing to the possibility of further improving catalytic activity through rational design or directed evolution.

Recent Progress Using De Novo Design to Study Protein Structure, Design and Binding Interactions

De novo protein design is a powerful methodology used to study natural functions in an artificial-protein context. Since its inception, it has been used to reproduce a plethora of reactions and uncover biophysical principles that are often difficult to extract from direct studies of natural proteins. Natural proteins are capable of assuming a variety of different structures and subsequently binding ligands at impressively high levels of both specificity and affinity. Here, we will review recent examples of de novo design studies on binding reactions for small molecules, nucleic acids, and the formation of protein-protein interactions. We will then discuss some new structural advances in the field. Finally, we will discuss some advancements in computational modeling and design approaches and provide an overview of some modern algorithmic tools being used to design these proteins.