Synthetic biology principles for the design of protein with novel structures and functions

Modeling reveals the strength of weak interactions in stacked-ring assembly

Cells employ many large macromolecular machines for the execution and regulation of processes that are vital for cell and organismal viability. Interestingly, cells cannot synthesize these machines as functioning units. Instead, cells synthesize the molecular parts that must then assemble into the functional complex. Many important machines, including chaperones such as GroEL and proteases such as the proteasome, comprise protein rings that are stacked on top of one another. While there is some experimental data regarding how stacked-ring complexes such as the proteasome self-assemble, a comprehensive understanding of the dynamics of stacked-ring assembly is currently lacking. Here, we developed a mathematical model of stacked-trimer assembly and performed an analysis of the assembly of the stacked homomeric trimer, which is the simplest stacked-ring architecture. We found that stacked rings are particularly susceptible to a form of kinetic trapping that we term "deadlock," in which the system gets stuck in a state where there are many large intermediates that are not the fully assembled structure but that cannot productively react. When interaction affinities are uniformly strong, deadlock severely limits assembly yield. We thus predicted that stacked rings would avoid situations where all interfaces in the structure have high affinity. Analysis of available crystal structures indicated that indeed the majority-if not all-of stacked trimers do not contain uniformly strong interactions. Finally, to better understand the origins of deadlock, we developed a formal pathway analysis and showed that, when all the binding affinities are strong, many of the possible pathways are utilized. In contrast, optimal assembly strategies utilize only a small number of pathways. Our work suggests that deadlock is a critical factor influencing the evolution of macromolecular machines and provides general principles for understanding the self-assembly efficiency of existing machines.

Molecular basis for curvature formation in SepF polymerization

The self-assembly of proteins into curved structures plays an important role in many cellular processes. One good example of this phenomenon is observed in the septum-forming protein (SepF), which forms polymerized structures with uniform curvatures. SepF is essential for regulating the thickness of the septum during bacteria cell division. In Bacillus subtilis, SepF polymerization involves two distinct interfaces, the β-β and α-α interfaces, which define the assembly unit and contact interfaces, respectively. However, the mechanism of curvature formation in this step is not yet fully understood. In this study, we employed solid-state NMR (SSNMR) to compare the structures of cyclic wild-type SepF assemblies with linear assemblies resulting from a mutation of G137 on the β-β interface. Our results demonstrate that while the sequence differences arise from the internal assembly unit, the dramatic changes in the shape of the assemblies depend on the α-α interface between the units. We further provide atomic-level insights into how the angular variation of the α2 helix on the α-α interface affects the curvature of the assemblies, using a combination of SSNMR, cryo-electron microscopy, and simulation methods. Our findings shed light on the shape control of protein assemblies and emphasize the importance of interhelical contacts in retaining curvature.

PROTHON: A Local Order Parameter-Based Method for Efficient Comparison of Protein Ensembles

The comparison of protein conformational ensembles is of central importance in structural biology. However, there are few computational methods for ensemble comparison, and those that are readily available, such as ENCORE, utilize methods that are sufficiently computationally expensive to be prohibitive for large ensembles. Here, a new method is presented for efficient representation and comparison of protein conformational ensembles. The method is based on the representation of a protein ensemble as a vector of probability distribution functions (pdfs), with each pdf representing the distribution of a local structural property such as the number of contacts between C_β atoms. Dissimilarity between two conformational ensembles is quantified by the Jensen-Shannon distance between the corresponding set of probability distribution functions. The method is validated for conformational ensembles generated by molecular dynamics simulations of ubiquitin, as well as experimentally derived conformational ensembles of a 130 amino acid truncated form of human tau protein. In the ubiquitin ensemble data set, the method was up to 88 times faster than the existing ENCORE software, while simultaneously utilizing 48 times fewer computing cores. We make the method available as a Python package, called PROTHON, and provide a GitHub page with the Python source code at https://github.com/PlotkinLab/Prothon.

Understanding a protein fold: the physics, chemistry, and biology of α-helical coiled coils

Protein science is being transformed by powerful computational methods for structure prediction and design: AlphaFold2 can predict many natural protein structures from sequence, and other AI methods are enabling the de novo design of new structures. This raises a question: how much do we understand the underlying sequence-to-structure/function relationships being captured by these methods? This perspective presents our current understanding of one class of protein assembly, the α-helical coiled coils. At first sight, these are straightforward: sequence repeats of hydrophobic (h) and polar (p) residues, (hpphppp)_n, direct the folding and assembly of amphipathic α helices into bundles. However, many different bundles are possible: they can have two or more helices (different oligomers); the helices can have parallel, antiparallel or mixed arrangements (different topologies); and the helical sequences can be the same (homomers) or different (heteromers). Thus, sequence-to-structure relationships must be present within the hpphppp repeats to distinguish these states. I discuss the current understanding of this problem at three levels: First, physics gives a parametric framework to generate the many possible coiled-coil backbone structures. Second, chemistry provides a means to explore and deliver sequence-to-structure relationships. Third, biology shows how coiled coils are adapted and functionalized in nature, inspiring applications of coiled coils in synthetic biology. I argue that the chemistry is largely understood; the physics is partly solved, though the considerable challenge of predicting even relative stabilities of different coiled-coil states remains; but there is much more to explore in the biology and synthetic biology of coiled coils.

From peptides to proteins: coiled-coil tetramers to single-chain 4-helix bundles

The design of completely synthetic proteins from first principles-de novo protein design-is challenging. This is because, despite recent advances in computational protein-structure prediction and design, we do not understand fully the sequence-to-structure relationships for protein folding, assembly, and stabilization. Antiparallel 4-helix bundles are amongst the most studied scaffolds for de novo protein design. We set out to re-examine this target, and to determine clear sequence-to-structure relationships, or design rules, for the structure. Our aim was to determine a common and robust sequence background for designing multiple de novo 4-helix bundles. In turn, this could be used in chemical and synthetic biology to direct protein-protein interactions and as scaffolds for functional protein design. Our approach starts by analyzing known antiparallel 4-helix coiled-coil structures to deduce design rules. In terms of the heptad repeat, abcdefg -i.e., the sequence signature of many helical bundles-the key features that we identify are: a = Leu, d = Ile, e = Ala, g = Gln, and the use of complementary charged residues at b and c. Next, we implement these rules in the rational design of synthetic peptides to form antiparallel homo- and heterotetramers. Finally, we use the sequence of the homotetramer to derive in one step a single-chain 4-helix-bundle protein for recombinant production in E. coli. All of the assembled designs are confirmed in aqueous solution using biophysical methods, and ultimately by determining high-resolution X-ray crystal structures. Our route from peptides to proteins provides an understanding of the role of each residue in each design.

Configurational entropy, transition rates, and optimal interactions for rapid folding in coarse-grained model proteins

Under certain conditions, the dynamics of coarse-grained models of solvated proteins can be described using a Markov state model, which tracks the evolution of populations of configurations. The transition rates among states that appear in the Markov model can be determined by computing the relative entropy of states and their mean first passage times. In this paper, we present an adaptive method to evaluate the configurational entropy and the mean first passage times for linear chain models with discontinuous potentials. The approach is based on event-driven dynamical sampling in a massively parallel architecture. Using the fact that the transition rate matrix can be calculated for any choice of interaction energies at any temperature, it is demonstrated how each state's energy can be chosen such that the average time to transition between any two states is minimized. The methods are used to analyze the optimization of the folding process of two protein systems: the crambin protein and a model with frustration and misfolding. It is shown that the folding pathways for both systems are comprised of two regimes: first, the rapid establishment of local bonds, followed by the subsequent formation of more distant contacts. The state energies that lead to the most rapid folding encourage multiple pathways, and they either penalize folding pathways through kinetic traps by raising the energies of trapping states or establish an escape route from the trapping states by lowering free energy barriers to other states that rapidly reach the native state.

One, two, many: Strategies to alter the number of carbohydrate binding sites of lectins

Carbohydrates are more than an energy-storage. They are ubiquitously found on cells and most proteins, where they encode biological information. Lectins bind these carbohydrates and are essential for translating the encoded information into biological functions and processes. Hundreds of lectins are known, and they are found in all domains of life. For half a century, researchers have been preparing variants of lectins in which the binding sites are varied. In this way, the traits of the lectins such as the affinity, avidity and specificity towards their ligands as well as their biological efficacy were changed. These efforts helped to unravel the biological importance of lectins and resulted in improved variants for biotechnological exploitation and potential medical applications. This review gives an overview on the methods for the preparation of artificial lectins and complexes thereof and how reducing or increasing the number of binding sites affects their function.

Functionalization of a symmetric protein scaffold: Redundant folding nuclei and alternative oligomeric folding pathways

Successful de novo protein design ideally targets specific folding kinetics, stability thermodynamics, and biochemical functionality, and the simultaneous achievement of all these criteria in a single step design is challenging. Protein design is potentially simplified by separating the problem into two steps: (a) an initial design of a protein "scaffold" having appropriate folding kinetics and stability thermodynamics, followed by (b) appropriate functional mutation-possibly involving insertion of a peptide functional "cassette." This stepwise approach can also separate the orthogonal effects of the "stability/function" and "foldability/function" tradeoffs commonly observed in protein design. If the scaffold is a protein architecture having an exact rotational symmetry, then there is the potential for redundant folding nuclei and multiple equivalent sites of functionalization; thereby enabling broader functional adaptation. We describe such a "scaffold" and functional "cassette" design strategy applied to a β-trefoil threefold symmetric architecture and a heparin ligand functionality. The results support the availability of redundant folding nuclei within this symmetric architecture, and also identify a minimal peptide cassette conferring heparin affinity. The results also identify an energy barrier of destabilization that switches the protein folding pathway from monomeric to trimeric, thereby identifying another potential advantage of symmetric protein architecture in de novo design.

Inhibition of lung microbiota-derived proapoptotic peptides ameliorates acute exacerbation of pulmonary fibrosis

Idiopathic pulmonary fibrosis is an incurable disease of unknown etiology. Acute exacerbation of idiopathic pulmonary fibrosis is associated with high mortality. Excessive apoptosis of lung epithelial cells occurs in pulmonary fibrosis acute exacerbation. We recently identified corisin, a proapoptotic peptide that triggers acute exacerbation of pulmonary fibrosis. Here, we provide insights into the mechanism underlying the processing and release of corisin. Furthermore, we demonstrate that an anticorisin monoclonal antibody ameliorates lung fibrosis by significantly inhibiting acute exacerbation in the human transforming growth factorβ1 model and acute lung injury in the bleomycin model. By investigating the impact of the anticorisin monoclonal antibody in a general model of acute lung injury, we further unravel the potential of corisin to impact such diseases. These results underscore the role of corisin in the pathogenesis of acute exacerbation of pulmonary fibrosis and acute lung injury and provide a novel approach to treating this incurable disease.

Systems biology–the transformative approach to integrate sciences across disciplines

Life science is the study of living organisms, including bacteria, plants, and animals. Given the importance of biology, chemistry, and bioinformatics, we anticipate that this chapter may contribute to a better understanding of the interdisciplinary connections in life science. Research in applied biological sciences has changed the paradigm of basic and applied research. Biology is the study of life and living organisms, whereas science is a dynamic subject that as a result of constant research, new fields are constantly emerging. Some fields come and go, whereas others develop into new, well-recognized entities. Chemistry is the study of composition of matter and its properties, how the substances merge or separate and also how substances interact with energy. Advances in biology and chemistry provide another means to understand the biological system using many interdisciplinary approaches. Bioinformatics is a multidisciplinary or rather transdisciplinary field that encourages the use of computer tools and methodologies for qualitative and quantitative analysis. There are many instances where two fields, biology and chemistry have intersection. In this chapter, we explain how current knowledge in biology, chemistry, and bioinformatics, as well as its various interdisciplinary domains are merged into life sciences and its applications in biological research.

Development of mammalian cell logic gates controlled by unnatural amino acids

Mammalian cell logic gates hold great potential for wide-ranging applications. However, most of those currently available are controlled by drug(-like) molecules with inherent biological activities. To construct truly orthogonal circuits and artificial regulatory pathways, biologically inert molecules are ideal molecular switches. Here, we applied genetic code expansion and engineered logic gates controlled by two biologically inert unnatural amino acids. Genetic code expansion relies on orthogonal aminoacyl-tRNA synthetase/tRNA pairs for co-translational and site-specific unnatural amino acid incorporation conventionally in response to an amber (UAG) codon. By screening 11 quadruplet-decoding pyrrolysyl tRNA variants from the literature, we found that all variants decoding CUAG or AGGA tested here are functional in mammalian cells. Using a quadruplet-decoding orthogonal pair together with an amber-decoding pair, we constructed logic gates that can be successfully controlled by two different unnatural amino acids, expanding the scope of genetic code expansion and mammalian cell logic circuits.

How Coiled-Coil Assemblies Accommodate Multiple Aromatic Residues

Rational protein design requires understanding the contribution of each amino acid to a targeted protein fold. For a subset of protein structures, namely, α-helical coiled coils (CCs), knowledge is sufficiently advanced to allow the rational de novo design of many structures, including entirely new protein folds. Current CC design rules center on using aliphatic hydrophobic residues predominantly to drive the folding and assembly of amphipathic α helices. The consequences of using aromatic residues-which would be useful for introducing structural probes, and binding and catalytic functionalities-into these interfaces are not understood. There are specific examples of designed CCs containing such aromatic residues, e.g., phenylalanine-rich sequences, and the use of polar aromatic residues to make buried hydrogen-bond networks. However, it is not known generally if sequences rich in tyrosine can form CCs, or what CC assemblies these would lead to. Here, we explore tyrosine-rich sequences in a general CC-forming background and resolve new CC structures. In one of these, an antiparallel tetramer, the tyrosine residues are solvent accessible and pack at the interface between the core and the surface. In another more complex structure, the residues are buried and form an extended hydrogen-bond network.

Triangular in Vivo Self-Assembling Coiled-Coil Protein Origami

Coiled-coil protein origami (CCPO) polyhedra are designed self-assembling nanostructures constructed from coiled coil (CC)-forming modules connected into a single chain. For testing new CCPO building modules, simpler polyhedra could be used that should maintain most features relevant to larger scaffolds. We show the design and characterization of nanoscale single-chain triangles, composed of six concatenated parallel CC dimer-forming segments connected by flexible linker peptides. The polypeptides self-assembled in bacteria in agreement with the design, and the shape of the polypeptides was confirmed with small-angle X-ray scattering. Fusion with split-fluorescent protein domains was used as a functional assay in bacteria, based on the discrimination between the correctly folded and misfolded nanoscale triangles comprising correct, mismatched, or truncated modules. This strategy was used to evaluate the optimal size of linkers between CC segments which comprised eight amino acid residues.