Ising Model Reprogramming of a Repeat Protein's Equilibrium Unfolding Pathway

On the origin of cooperativity effects in the formation of self-assembled molecular networks at the liquid/solid interface

In this work we investigate the behaviour of molecules at the nanoscale using scanning tunnelling microscopy in order to explore the origin of the cooperativity in the formation of self-assembled molecular networks (SAMNs) at the liquid/solid interface. By studying concentration dependence of alkoxylated dimethylbenzene, a molecular analogue to 5-alkoxylated isophthalic derivatives, but without hydrogen bonding moieties, we show that the cooperativity effect can be experimentally evaluated even for low-interacting systems and that the cooperativity in SAMN formation is its fundamental trait. We conclude that cooperativity must be a local effect and use the nearest-neighbor Ising model to reproduce the coverage vs. concentration curves. The Ising model offers a direct link between statistical thermodynamics and experimental parameters, making it a valuable tool for assessing the thermodynamics of SAMN formation.

Unraveling the Mechanics of a Repeat-Protein Nanospring: From Folding of Individual Repeats to Fluctuations of the Superhelix

Tandem-repeat proteins comprise small secondary structure motifs that stack to form one-dimensional arrays with distinctive mechanical properties that are proposed to direct their cellular functions. Here, we use single-molecule optical tweezers to study the folding of consensus-designed tetratricopeptide repeats (CTPRs), superhelical arrays of short helix-turn-helix motifs. We find that CTPRs display a spring-like mechanical response in which individual repeats undergo rapid equilibrium fluctuations between partially folded and unfolded conformations. We rationalize the force response using Ising models and dissect the folding pathway of CTPRs under mechanical load, revealing how the repeat arrays form from the center toward both termini simultaneously. Most strikingly, we also directly observe the protein's superhelical tertiary structure in the force signal. Using protein engineering, crystallography, and single-molecule experiments, we show that the superhelical geometry can be altered by carefully placed amino acid substitutions, and we examine how these sequence changes affect intrinsic repeat stability and inter-repeat coupling. Our findings provide the means to dissect and modulate repeat-protein stability and dynamics, which will be essential for researchers to understand the function of natural repeat proteins and to exploit artificial repeats proteins in nanotechnology and biomedical applications.

Unraveling the Mechanics of a Repeat-Protein Nanospring: From Folding of Individual Repeats to Fluctuations of the Superhelix

Tandem-repeat proteins comprise small secondary structure motifs that stack to form one-dimensional arrays with distinctive mechanical properties that are proposed to direct their cellular functions. Here, we use single-molecule optical tweezers to study the folding of consensus-designed tetratricopeptide repeats (CTPRs), superhelical arrays of short helix-turn-helix motifs. We find that CTPRs display a spring-like mechanical response in which individual repeats undergo rapid equilibrium fluctuations between partially folded and unfolded conformations. We rationalize the force response using Ising models and dissect the folding pathway of CTPRs under mechanical load, revealing how the repeat arrays form from the center toward both termini simultaneously. Most strikingly, we also directly observe the protein's superhelical tertiary structure in the force signal. Using protein engineering, crystallography, and single-molecule experiments, we show that the superhelical geometry can be altered by carefully placed amino acid substitutions, and we examine how these sequence changes affect intrinsic repeat stability and inter-repeat coupling. Our findings provide the means to dissect and modulate repeat-protein stability and dynamics, which will be essential for researchers to understand the function of natural repeat proteins and to exploit artificial repeats proteins in nanotechnology and biomedical applications.

Engineering and exploiting synthetic allostery of NanoLuc luciferase

Allostery enables proteins to interconvert different biochemical signals and form complex metabolic and signaling networks. We hypothesize that circular permutation of proteins increases the probability of functional coupling of new N- and C- termini with the protein's active center through increased local structural disorder. To test this we construct a synthetically allosteric version of circular permutated NanoLuc luciferase that can be activated through ligand-induced intramolecular non-covalent cyclisation. This switch module is tolerant of the structure of binding domains and their ligands, and can be used to create biosensors of proteins and small molecules. The developed biosensors covers a range of emission wavelengths and displays sensitivity as low as 50pM and dynamic range as high as 16-fold and could quantify their cognate ligand in human fluids. We apply hydrogen exchange kinetic mass spectroscopy to analyze time resolved structural changes in the developed biosensors and observe ligand-mediated folding of newly created termini.

Engineering mono- and multi-valent inhibitors on a modular scaffold

Here we exploit the simple, ultra-stable, modular architecture of consensus-designed tetratricopeptide repeat proteins (CTPRs) to create a platform capable of displaying both single as well as multiple functions and with diverse programmable geometrical arrangements by grafting non-helical short linear binding motifs (SLiMs) onto the loops between adjacent repeats. As proof of concept, we built synthetic CTPRs to bind and inhibit the human tankyrase proteins (hTNKS), which play a key role in Wnt signaling and are upregulated in cancer. A series of mono-valent and multi-valent hTNKS binders was assembled. To fully exploit the modular scaffold and to further diversify the multi-valent geometry, we engineered the binding modules with two different formats, one monomeric and the other trimeric. We show that the designed proteins are stable, correctly folded and capable of binding to and inhibiting the cellular activity of hTNKS leading to downregulation of the Wnt pathway. Multivalency in both the CTPR protein arrays and the hTNKS target results in the formation of large macromolecular assemblies, which can be visualized both in vitro and in the cell. When delivered into the cell by nanoparticle encapsulation, the multivalent CTPR proteins displayed exceptional activity. They are able to inhibit Wnt signaling where small molecule inhibitors have failed to date. Our results point to the tremendous potential of the CTPR platform to exploit a range of SLiMs and assemble synthetic binding molecules with built-in multivalent capabilities and precise, pre-programmed geometries.

Testing the length limit of loop grafting in a helical repeat protein

Alpha-helical repeat proteins such as consensus-designed tetratricopeptide repeats (CTPRs) are exceptionally stable molecules that are able to tolerate destabilizing sequence alterations and are therefore becoming increasingly valued as a modular platform for biotechnology and biotherapeutic applications. A simple approach to functionalize the CTPR scaffold that we are pioneering is the insertion of short linear motifs (SLiMs) into the loops between adjacent repeats. Here, we test the limits of the scaffold by inserting 17 highly diverse amino acid sequences of up to 58 amino acids in length into a two-repeat protein and examine the impact on protein folding, stability and solubility. The sequences include three SLiMs that bind oncoproteins and eleven naturally occurring linker sequences all predicted to be intrinsically disordered but with conformational preferences ranging from compact globules to expanded coils. We show that the loop-grafted proteins retain the native CTPR structure and are thermally stable with melting temperatures above 60 ​°C, despite the longest loop sequence being almost the same size as the CTPR scaffold itself (68 amino acids). Although the main determinant of the effect of stability was found to be loop length and was relatively insensitive to amino acid composition, the relationship between protein solubility and the loop sequences was more complex, with the presence of negatively charged amino acids enhancing the solubility. Our findings will help us to fully realize the potential of the repeat-protein scaffold, allowing a rational design approach to create artificial modular proteins with customized functional capabilities.

A modified Ising model of Barabási-Albert network with gene-type spins

The central question of systems biology is to understand how individual components of a biological system such as genes or proteins cooperate in emerging phenotypes resulting in the evolution of diseases. As living cells are open systems in quasi-steady state type equilibrium in continuous exchange with their environment, computational techniques that have been successfully applied in statistical thermodynamics to describe phase transitions may provide new insights to the emerging behavior of biological systems. Here we systematically evaluate the translation of computational techniques from solid-state physics to network models that closely resemble biological networks and develop specific translational rules to tackle problems unique to living systems. We focus on logic models exhibiting only two states in each network node. Motivated by the apparent asymmetry between biological states where an entity exhibits boolean states i.e. is active or inactive, we present an adaptation of symmetric Ising model towards an asymmetric one fitting to living systems here referred to as the modified Ising model with gene-type spins. We analyze phase transitions by Monte Carlo simulations and propose a mean-field solution of a modified Ising model of a network type that closely resembles a real-world network, the Barabási–Albert model of scale-free networks. We show that asymmetric Ising models show similarities to symmetric Ising models with the external field and undergoes a discontinuous phase transition of the first-order and exhibits hysteresis. The simulation setup presented herein can be directly used for any biological network connectivity dataset and is also applicable for other networks that exhibit similar states of activity. The method proposed here is a general statistical method to deal with non-linear large scale models arising in the context of biological systems and is scalable to any network size.

Decoupling a tandem-repeat protein: Impact of multiple loop insertions on a modular scaffold

The simple topology and modular architecture of tandem-repeat proteins such as tetratricopeptide repeats (TPRs) and ankyrin repeats makes them straightforward to dissect and redesign. Repeat-protein stability can be manipulated in a predictable way using site-specific mutations. Here we explore a different type of modification - loop insertion - that will enable a simple route to functionalisation of this versatile scaffold. We previously showed that a single loop insertion has a dramatically different effect on stability depending on its location in the repeat array. Here we dissect this effect by a combination of multiple and alternated loop insertions to understand the origins of the context-dependent loss in stability. We find that the scaffold is remarkably robust in that its overall structure is maintained. However, adjacent repeats are now only weakly coupled, and consequently the increase in solvent protection, and thus stability, with increasing repeat number that defines the tandem-repeat protein class is lost. Our results also provide us with a rulebook with which we can apply these principles to the design of artificial repeat proteins with precisely tuned folding landscapes and functional capabilities, thereby paving the way for their exploitation as a versatile and truly modular platform in synthetic biology.

Context-Dependent Energetics of Loop Extensions in a Family of Tandem-Repeat Proteins

Consensus-designed tetratricopeptide repeat proteins are highly stable, modular proteins that are strikingly amenable to rational engineering. They therefore have tremendous potential as building blocks for biomaterials and biomedicine. Here, we explore the possibility of extending the loops between repeats to enable further diversification, and we investigate how this modification affects stability and folding cooperativity. We find that extending a single loop by up to 25 residues does not disrupt the overall protein structure, but, strikingly, the effect on stability is highly context-dependent: in a two-repeat array, destabilization is relatively small and can be accounted for purely in entropic terms, whereas extending a loop in the middle of a large array is much more costly because of weakening of the interaction between the repeats. Our findings provide important and, to our knowledge, new insights that increase our understanding of the structure, folding, and function of natural repeat proteins and the design of artificial repeat proteins in biotechnology.

Folding cooperativity and allosteric function in the tandem-repeat protein class

The term allostery was originally developed to describe structural changes in one binding site induced by the interaction of a partner molecule with a distant binding site, and it has been studied in depth in the field of enzymology. Here, we discuss the concept of action at a distance in relation to the folding and function of the solenoid class of tandem-repeat proteins such as tetratricopeptide repeats (TPRs) and ankyrin repeats. Distantly located repeats fold cooperatively, even though only nearest-neighbour interactions exist in these proteins. A number of repeat-protein scaffolds have been reported to display allosteric effects, transferred through the repeat array, that enable them to direct the activity of the multi-subunit enzymes within which they reside. We also highlight a recently identified group of tandem-repeat proteins, the RRPNN subclass of TPRs, recent crystal structures of which indicate that they function as allosteric switches to modulate multiple bacterial quorum-sensing mechanisms. We believe that the folding cooperativity of tandem-repeat proteins and the biophysical mechanisms that transform them into allosteric switches are intimately intertwined. This opinion piece aims to combine our understanding of the two areas and develop ideas on their common underlying principles.This article is part of a discussion meeting issue 'Allostery and molecular machines'.

PyFolding: Open-Source Graphing, Simulation, and Analysis of the Biophysical Properties of Proteins

For many years, curve-fitting software has been heavily utilized to fit simple models to various types of biophysical data. Although such software packages are easy to use for simple functions, they are often expensive and present substantial impediments to applying more complex models or for the analysis of large data sets. One field that is reliant on such data analysis is the thermodynamics and kinetics of protein folding. Over the past decade, increasingly sophisticated analytical models have been generated, but without simple tools to enable routine analysis. Consequently, users have needed to generate their own tools or otherwise find willing collaborators. Here we present PyFolding, a free, open-source, and extensible Python framework for graphing, analysis, and simulation of the biophysical properties of proteins. To demonstrate the utility of PyFolding, we have used it to analyze and model experimental protein folding and thermodynamic data. Examples include: 1) multiphase kinetic folding fitted to linked equations, 2) global fitting of multiple data sets, and 3) analysis of repeat protein thermodynamics with Ising model variants. Moreover, we demonstrate how PyFolding is easily extensible to novel functionality beyond applications in protein folding via the addition of new models. Example scripts to perform these and other operations are supplied with the software, and we encourage users to contribute notebooks and models to create a community resource. Finally, we show that PyFolding can be used in conjunction with Jupyter notebooks as an easy way to share methods and analysis for publication and among research teams.

Programmed Protein Self-Assembly Driven by Genetically Encoded Intein-Mediated Native Chemical Ligation

Harnessing and controlling self-assembly is an important step in developing proteins as novel biomaterials. With this goal, here we report the design of a general genetically programmed system that covalently concatenates multiple distinct protein domains into specific assembled arrays. It is driven by iterative intein-mediated native chemical ligation (NCL) under mild native conditions. The system uses a series of initially inert recombinant protein fusions that sandwich the protein modules to be ligated between one of a number of different affinity tags and an intein protein domain. Orthogonal activation at opposite termini of compatible protein fusions, via protease and intein cleavage, coupled with sequential mixing directs an irreversible and traceless stepwise assembly process. This gives total control over the composition and arrangement of component proteins within the final product, enabled the limits of the system-reaction efficiency and yield-to be investigated, and led to the production of "functional" assemblies.

A method for rapid high-throughput biophysical analysis of proteins

Quantitative determination of protein thermodynamic stability is fundamental to many research areas, both basic and applied. Although chemical-induced denaturation is the gold-standard method, it has been replaced in many settings by semi-quantitative approaches such as thermal stability measurements. The reason for this shift is that chemical denaturation experiments are labour-intensive, sample-costly and time-consuming, and it has been assumed that miniaturisation to a high-throughput format would not be possible without concomitantly comprising data quality. Here we exploit current technologies to create a high-throughput label-free chemical denaturation method that is capable of generating replicate datasets on multiple proteins in parallel on a timescale that is at least ten times faster, much more economical on sample, and with the potential for superior data quality, than the conventional methods used in most research labs currently.

Advances in the design and engineering of peptide-binding repeat proteins

The specific recognition of peptides, which we define to include unstructured regions or denatured forms of proteins, is an intrinsic part of a multitude of biochemical assays and procedures. Many cellular interactions are also based on this principle as well. While it would be highly desirable to have a stockpile of sequence-specific binders for essentially any sequence, a de novo selection of individual binders against every possible target peptide sequence would be rather difficult to reduce to practice. Modular peptide binders could overcome this problem, as preselected and/or predesigned modules could be reused for the generation of new binders and thereby revolutionize the generation of binding proteins. This minireview summarizes advances in the development of peptide binders and possible scaffolds for their design.