Topological knots and links in proteins

Pretzelanes, [1]rotaxanes and molecular figures-of-eight - crossing the bridge from fundamentals to functional applications

There are myriad [2]catenanes and [2]rotaxanes that consist of two interlocked molecular components. On occasion, supramolecular chemists prepare interlocked molecules where there are covalent linkages between the interlocked molecular components. In this review, progress on pretzelanes ([1]catenanes), [1]rotaxanes and molecular figures-of-eight is surveyed. Particular attention is paid to the application of such molecules, especially where the interlocked structure and/or the covalent linkage(s) play a key functional role.

Deep Learning-Assisted Discovery of Protein Entangling Motifs

Natural topological proteins exhibit unique properties including enhanced stability, controlled quaternary structures, and dynamic switching properties, highlighting topology as a unique dimension in protein engineering. Although artificial design and synthesis of topological proteins have achieved certain success, their diversity and complexity remain rather limited due to the scarcity of available entangling motifs essential for the construction of nontrivial protein topologies. In this work, we developed a deep-learning model to predict the entanglement features of a homodimer based solely on its amino acid sequence via the Gauss linking number matrices. The model achieved a search speed that was dozens of times faster than AlphaFold-Multimer, while maintaining comparable mean squared error. It was used to screen for entangling motifs from the genome of a hyperthermophilic archaeon. We demonstrated the effectiveness of our model by successful wet-lab synthesis of protein catenanes using two candidate entangling motifs. These findings show the great potential of our model for advancing the design and synthesis of novel topological proteins.

Polymers in Physics, Chemistry and Biology: Behavior of Linear Polymers in Fractal Structures

We start presenting an overview on recent applications of linear polymers and networks in condensed matter physics, chemistry and biology by briefly discussing selected papers (published within 2022-2024) in some detail. They are organized into three main subsections: polymers in physics (further subdivided into simulations of coarse-grained models and structural properties of materials), chemistry (quantum mechanical calculations, environmental issues and rheological properties of viscoelastic composites) and biology (macromolecules, proteins and biomedical applications). The core of the work is devoted to a review of theoretical aspects of linear polymers, with emphasis on self-avoiding walk (SAW) chains, in regular lattices and in both deterministic and random fractal structures. Values of critical exponents describing the structure of SAWs in different environments are updated whenever available. The case of random fractal structures is modeled by percolation clusters at criticality, and the issue of multifractality, which is typical of these complex systems, is illustrated. Applications of these models are suggested, and references to known results in the literature are provided. A detailed discussion of the reptation method and its many interesting applications are provided. The problem of protein folding and protein evolution are also considered, and the key issues and open questions are highlighted. We include an experimental section on polymers which introduces the most relevant aspects of linear polymers relevant to this work. The last two sections are dedicated to applications, one in materials science, such as fractal features of plasma-treated polymeric materials surfaces and the growth of polymer thin films, and a second one in biology, by considering among others long linear polymers, such as DNA, confined within a finite domain.

Plant Cell Wall Loosening by Expansins

Expansins comprise an ancient group of cell wall proteins ubiquitous in land plants and their algal ancestors. During cell growth, they facilitate passive yielding of the wall's cellulose networks to turgor-generated tensile stresses, without evidence of enzymatic activity. Expansins are also implicated in fruit softening and other developmental processes and in adaptive responses to environmental stresses and pathogens. The major expansin families in plants include α-expansins (EXPAs), which act on cellulose-cellulose junctions, and β-expansins, which can act on xylans. EXPAs mediate acid growth, which contributes to wall enlargement by auxin and other growth agents. The genomes of diverse microbes, including many plant pathogens, also encode expansins designated expansin-like X. Expansins are proposed to disrupt noncovalent bonding between laterally aligned polysaccharides (notably cellulose), facilitating wall loosening for a variety of biological roles.

Everything AlphaFold tells us about protein knots

Recent advances in Machine Learning methods in structural biology opened up new perspectives for protein analysis. Utilizing these methods allows us to go beyond the limitations of empirical research, and take advantage of the vast amount of generated data. We use a complete set of potentially knotted protein models identified in all high-quality predictions from the AlphaFold Database to search for any common trends that describe them. We show that the vast majority of knotted proteins have 31 knot and that the presence of knots is preferred in neither Bacteria, Eukaryota, or Archaea domains. On the contrary, the percentage of knotted proteins in any given proteome is around 0.4%, regardless of the taxonomical group. We also verified that the organism's living conditions do not impact the number of knotted proteins in its proteome, as previously expected. We did not encounter an organism without a single knotted protein. What is more, we found four universally present families of knotted proteins in Bacteria, consisting of SAM synthase, and TrmD, TrmH, and RsmE methyltransferases.

Mechanical Regulation of Polymer Gels

The mechanical properties of polymer gels devote to emerging devices and machines in fields such as biomedical engineering, flexible bioelectronics, biomimetic actuators, and energy harvesters. Coupling network architectures and interactions has been explored to regulate supportive mechanical characteristics of polymer gels; however, systematic reviews correlating mechanics to interaction forces at the molecular and structural levels remain absent in the field. This review highlights the molecular engineering and structural engineering of polymer gel mechanics and a comprehensive mechanistic understanding of mechanical regulation. Molecular engineering alters molecular architecture and manipulates functional groups/moieties at the molecular level, introducing various interactions and permanent or reversible dynamic bonds as the dissipative energy. Molecular engineering usually uses monomers, cross-linkers, chains, and other additives. Structural engineering utilizes casting methods, solvent phase regulation, mechanochemistry, macromolecule chemical reactions, and biomanufacturing technology to construct and tailor the topological network structures, or heterogeneous modulus compositions. We envision that the perfect combination of molecular and structural engineering may provide a fresh view to extend exciting new perspectives of this burgeoning field. This review also summarizes recent representative applications of polymer gels with excellent mechanical properties. Conclusions and perspectives are also provided from five aspects of concise summary, mechanical mechanism, biofabrication methods, upgraded applications, and synergistic methodology.

Probing the Topological Effects on Stability Enhancement and Therapeutic Performance of Protein Bioconjugates: Tadpole, Macrocycle versus Figure-of-Eight

Chemical topology provides a unique dimension for making therapeutic protein bioconjugates with native structure and intact function, yet the effects of topology remain elusive. Herein, the design, synthesis, and characterization of therapeutic protein bioconjugates in three topologies (i.e., tadpole, macrocycle, and figure-of-eight), are reported. The interferon α2b (IFN) and albumin binding domain (ABD) are selected as the model proteins for bioconjugation and proof-of-concept. The biosynthesis of these topological isoforms is accomplished via direct expression in cells using SpyTag-SpyCatcher chemistry and/or split-intein-mediated ligation for topology diversification. The corresponding topologies are proven with combined techniques of LC-MS, SDS-PAGE, and controlled proteolytic digestion. While the properties of these topological isoforms are similar in most cases, the figure-of-eight-shaped bioconjugate, f8-IFN-ABD, exhibits the best thermal stability and anti-aggregation properties along with prolonged half-life and enhanced tumor retention relative to the tadpole-shaped control, tadp-IFN-ABD, and the macrocyclic control, c-IFN-ABD, showcasing considerable topological effects. The work expands the topological diversity of proteins and demonstrates the potential advantages of leveraging chemical topology for functional benefits beyond multi-function integration in protein therapeutics.

Knotted artifacts in predicted 3D RNA structures

Unlike proteins, RNAs deposited in the Protein Data Bank do not contain topological knots. Recently, admittedly, the first trefoil knot and some lasso-type conformations have been found in experimental RNA structures, but these are still exceptional cases. Meanwhile, algorithms predicting 3D RNA models have happened to form knotted structures not so rarely. Interestingly, machine learning-based predictors seem to be more prone to generate knotted RNA folds than traditional methods. A similar situation is observed for the entanglements of structural elements. In this paper, we analyze all models submitted to the CASP15 competition in the 3D RNA structure prediction category. We show what types of topological knots and structure element entanglements appear in the submitted models and highlight what methods are behind the generation of such conformations. We also study the structural aspect of susceptibility to entanglement. We suggest that predictors take care of an evaluation of RNA models to avoid publishing structures with artifacts, such as unusual entanglements, that result from hallucinations of predictive algorithms.

Geometric learning of knot topology

Knots are deeply entangled with every branch of science. One of the biggest open challenges in knot theory is to formalise a knot invariant that can unambiguously and efficiently distinguish any two knotted curves. Additionally, the conjecture that the geometrical embedding of a curve encodes information on its underlying topology is, albeit physically intuitive, far from proven. Here we attempt to tackle both these outstanding challenges by proposing a neural network (NN) approach that takes as input a geometric representation of a knotted curve and tries to make predictions of the curve's topology. Intriguingly, we discover that NNs trained with a so-called geometrical "local writhe" representation of a knot can distinguish curves that share one or many topological invariants and knot polynomials, such as mutant and composite knots, and can thus classify knotted curves more precisely than some knot polynomials. Additionally, we also show that our approach can be scaled up to classify all prime knots up to 10-crossings with more than 95% accuracy. Finally, we show that our NNs can also be trained to solve knot localisation problems on open and closed curves. Our main discovery is that the pattern of "local writhe" is a potentially unique geometric signature of the underlying topology of a curve. We hope that our results will suggest new methods for quantifying generic entanglements in soft matter and even inform new topological invariants.

Conservation of knotted and slipknotted topology in transmembrane transporters

The existence of nontrivial topology is well accepted in globular proteins but not in membrane proteins. Our comprehensive topological analysis of the Protein Data Bank structures reveals 18 families of transmembrane proteins with nontrivial topology, showing that they constitute a significant number of membrane proteins. Moreover, we found that they comprise one of the largest groups of secondary active transporters. We classified them based on their knotted fingerprint into four groups: three slipknotted and one knotted. Unexpectedly, we found that the same protein can possess two distinct slipknot motifs that correspond to its outward- and inward-open conformational state. Based on the analysis of structures and knotted fingerprints, we show that slipknot topology is directly involved in the conformational transition and substrate transfer. Therefore, entanglement can be used to classify proteins and to find their structure-function relationship. Furthermore, based on the topological analysis of the transmembrane protein structures predicted by AlphaFold, we identified new potentially slipknotted protein families.

The SKMT Algorithm: A method for assessing and comparing underlying protein entanglement

We present fast and simple-to-implement measures of the entanglement of protein tertiary structures which are appropriate for highly flexible structure comparison. These are performed using the SKMT algorithm, a novel method of smoothing the Cα backbone to achieve a minimal complexity curve representation of the manner in which the protein's secondary structure elements fold to form its tertiary structure. Its subsequent complexity is characterised using measures based on the writhe and crossing number quantities heavily utilised in DNA topology studies, and which have shown promising results when applied to proteins recently. The SKMT smoothing is used to derive empirical bounds on a protein's entanglement relative to its number of secondary structure elements. We show that large scale helical geometries dominantly account for the maximum growth in entanglement of protein monomers, and further that this large scale helical geometry is present in a large array of proteins, consistent across a number of different protein structure types and sequences. We also show how these bounds can be used to constrain the search space of protein structure prediction from small angle x-ray scattering experiments, a method highly suited to determining the likely structure of proteins in solution where crystal structure or machine learning based predictions often fail to match experimental data. Finally we develop a structural comparison metric based on the SKMT smoothing which is used in one specific case to demonstrate significant structural similarity between Rossmann fold and TIM Barrel proteins, a link which is potentially significant as attempts to engineer the latter have in the past produced the former. We provide the SWRITHE interactive python notebook to calculate these metrics.

Topological links in predicted protein complex structures reveal limitations of AlphaFold

AlphaFold is making great progress in protein structure prediction, not only for single-chain proteins but also for multi-chain protein complexes. When using AlphaFold-Multimer to predict protein‒protein complexes, we observed some unusual structures in which chains are looped around each other to form topologically intertwining links at the interface. Based on physical principles, such topological links should generally not exist in native protein complex structures unless covalent modifications of residues are involved. Although it is well known and has been well studied that protein structures may have topologically complex shapes such as knots and links, existing methods are hampered by the chain closure problem and show poor performance in identifying topologically linked structures in protein‒protein complexes. Therefore, we address the chain closure problem by using sliding windows from a local perspective and propose an algorithm to measure the topological-geometric features that can be used to identify topologically linked structures. An application of the method to AlphaFold-Multimer-predicted protein complex structures finds that approximately 1.72% of the predicted structures contain topological links. The method presented in this work will facilitate the computational study of protein‒protein interactions and help further improve the structural prediction of multi-chain protein complexes.

Knot Formation on DNA Pushed Inside Chiral Nanochannels

We performed coarse-grained molecular dynamics simulations of DNA polymers pushed inside infinite open chiral and achiral channels. We investigated the behavior of the polymer metrics in terms of span, monomer distributions and changes of topological state of the polymer in the channels. We also compared the regime of pushing a polymer inside the infinite channel to the case of polymer compression in finite channels of knot factories investigated in earlier works. We observed that the compression in the open channels affects the polymer metrics to different extents in chiral and achiral channels. We also observed that the chiral channels give rise to the formation of equichiral knots with the same handedness as the handedness of the chiral channels.

Polar Solomon rings in ferroelectric nanocrystals

Solomon rings, upholding the symbol of wisdom with profound historical roots, were widely used as decorations in ancient architecture and clothing. However, it was only recently discovered that such topological structures can be formed by self-organization in biological/chemical molecules, liquid crystals, etc. Here, we report the observation of polar Solomon rings in a ferroelectric nanocrystal, which consist of two intertwined vortices and are mathematically equivalent to a [Formula: see text] link in topology. By combining piezoresponse force microscopy observations and phase-field simulations, we demonstrate the reversible switching between polar Solomon rings and vertex textures by an electric field. The two types of topological polar textures exhibit distinct absorption of terahertz infrared waves, which can be exploited in infrared displays with a nanoscale resolution. Our study establishes, both experimentally and computationally, the existence and electrical manipulation of polar Solomon rings, a new form of topological polar structures that may provide a simple way for fast, robust, and high-resolution optoelectronic devices.

A single-domain green fluorescent protein catenane

Natural proteins exhibit rich structural diversity based on the folds of an invariably linear chain. Macromolecular catenanes that cooperatively fold into a single domain do not belong to the current protein universe, and their design and synthesis open new territories in chemistry. Here, we report the design, synthesis, and properties of a single-domain green fluorescent protein catenane via rewiring the connectivity of GFP's secondary motifs. The synthesis could be achieved in two steps via a pseudorotaxane intermediate or directly via expression in cellulo. Various proteins-of-interest may be inserted at the loop regions to give fusion protein catenanes where the two subunits exhibit enhanced thermal resilience, thermal stability, and mechanical stability due to strong conformational coupling. The strategy can be applied to other proteins with similar fold, giving rise to a family of single-domain fluorescent proteins. The results imply that there may be multiple protein topological variants with desirable functional traits beyond their corresponding linear protein counterparts, which are now made accessible and fully open for exploration.

A tile model of circuit topology for self-entangled biopolymers

Building on the theory of circuit topology for intra-chain contacts in entangled proteins, we introduce tiles as a way to rigorously model local entanglements which are held in place by molecular forces. We develop operations that combine tiles so that entangled chains can be represented by algebraic expressions. Then we use our model to show that the only knot types that such entangled chains can have are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and connected sums of these knots. This includes all proteins knots that have thus far been identified.

A catenane that is topologically achiral despite being composed of oriented rings

Catenanes-molecules comprising two interlocking rings held together like links in a chain-are topologically non-trivial: a catenane is a topological isomer of its separated rings, but the rings cannot be disconnected without bond scission. Catenanes can exist as topological enantiomers if both rings have directionality conferred by a defined atom sequence, but this has led to the assumption that the stereochemistry of chiral catenanes composed of oriented rings is inherently topological in nature. Here we show that this assumption is incorrect by synthesizing an example that contains the same fundamental stereogenic unit but whose stereochemistry is Euclidean. One ring in this chiral catenane is oriented by the geometry of an exocyclic double rather than determined by atom sequence within the ring. Isomerization of the exocyclic double bond results in racemization of the catenane, confirming that the stereochemistry is not topological in nature. Thus, we can unite the stereochemistry of catenanes with that of their topologically trivial cousins, the rotaxanes, enabling a more unified approach to their discussion.

Emergence of zero-field non-synthetic single and interchained antiferromagnetic skyrmions in thin films

Antiferromagnetic (AFM) skyrmions are envisioned as ideal localized topological magnetic bits in future information technologies. In contrast to ferromagnetic (FM) skyrmions, they are immune to the skyrmion Hall effect, might offer potential terahertz dynamics while being insensitive to external magnetic fields and dipolar interactions. Although observed in synthetic AFM structures and as complex meronic textures in intrinsic AFM bulk materials, their realization in non-synthetic AFM films, of crucial importance in racetrack concepts, has been elusive. Here, we unveil their presence in a row-wise AFM Cr film deposited on PdFe bilayer grown on fcc Ir(111) surface. Using first principles, we demonstrate the emergence of single and strikingly interpenetrating chains of AFM skyrmions, which can co-exist with the rich inhomogeneous exchange field, including that of FM skyrmions, hosted by PdFe. Besides the identification of an ideal platform of materials for intrinsic AFM skyrmions, we anticipate the uncovered knotted solitons to be promising building blocks in AFM spintronics.

The mechanical cell - the role of force dependencies in synchronising protein interaction networks

The role of mechanical signals in the proper functioning of organisms is increasingly recognised, and every cell senses physical forces and responds to them. These forces are generated both from outside the cell or via the sophisticated force-generation machinery of the cell, the cytoskeleton. All regions of the cell are connected via mechanical linkages, enabling the whole cell to function as a mechanical system. In this Review, we define some of the key concepts of how this machinery functions, highlighting the critical requirement for mechanosensory proteins, and conceptualise the coupling of mechanical linkages to mechanochemical switches that enables forces to be converted into biological signals. These mechanical couplings provide a mechanism for how mechanical crosstalk might coordinate the entire cell, its neighbours, extending into whole collections of cells, in tissues and in organs, and ultimately in the coordination and operation of entire organisms. Consequently, many diseases manifest through defects in this machinery, which we map onto schematics of the mechanical linkages within a cell. This mapping approach paves the way for the identification of additional linkages between mechanosignalling pathways and so might identify treatments for diseases, where mechanical connections are affected by mutations or where individual force-regulated components are defective.

Mechano-bioconjugation Strategy Empowering Fusion Protein Therapeutics with Aggregation Resistance, Prolonged Circulation, and Enhanced Antitumor Efficacy

Bioconjugation is a powerful protein modification strategy to improve protein properties. Herein, we report mechano-bioconjugation as a novel approach to empower fusion protein therapeutics and demonstrate its utility by a protein heterocatenane (cat-IFN-ABD) containing interferon-α2b (IFN) mechanically interlocked with a consensus albumin-binding domain (ABD). The conjugate was selectively synthesized in cellulo following a cascade of post-translational events using a pair of heterodimerizing p53dim variants and two orthogonal split-intein reactions. The catenane topology was proven by combined techniques of LC-MS, SDS-PAGE, SEC, and controlled proteolytic digestion. Not only did cat-IFN-ABD retain activities comparable to those of the wild-type IFN and ABD, the conjugate also exhibited enhanced aggregation resistance and prolonged circulation time over the simple linear and cyclic fusions. Consequently, cat-IFN-ABD potently inhibited tumor growth in the mouse xenograft model. Therefore, mechano-bioconjugation by catenation accomplishes function integration with additional benefits, providing an alternative pathway for developing advanced protein therapeutics.

Geometric Predictors of Knotted and Linked Arcs

Inspired by how certain proteins “sense” knots and entanglements in DNA molecules, here, we ask if local geometric features that may be used as a readout of the underlying topology of generic polymers exist. We perform molecular simulations of knotted and linked semiflexible polymers and study four geometric measures to predict topological entanglements: local curvature, local density, local 1D writhe, and nonlocal 3D writhe. We discover that local curvature is a poor predictor of entanglements. In contrast, segments with maximum local density or writhe correlate as much as 90% of the time with the shortest knotted and linked arcs. We find that this accuracy is preserved across different knot types and also under significant spherical confinement, which is known to delocalize essential crossings in knotted polymers. We further discover that nonlocal 3D writhe is the best geometric readout of the knot location. Finally, we discuss how these geometric features may be used to computationally analyze entanglements in generic polymer melts and gels.

Peptide/protein-based macrocycles: from biological synthesis to biomedical applications

Living organisms have evolved cyclic or multicyclic peptides and proteins with enhanced stability and high bioactivity superior to their linear counterparts for diverse purposes. Herein, we review recent progress in applying this concept to artificial peptides and proteins to exploit the functional benefits of these macrocycles. Not only have simple cyclic forms been prepared, numerous macrocycle variants, such as knots and links, have also been developed. The chemical tools and synthetic strategies are summarized for the biological synthesis of these macrocycles, demonstrating it as a powerful alternative to chemical synthesis. Its further application to therapeutic peptides/proteins has led to biomedicines with profoundly improved pharmaceutical performances. Finally, we present our perspectives on the field and its future developments.

The protein folding rate and the geometry and topology of the native state

Proteins fold in 3-dimensional conformations which are important for their function. Characterizing the global conformation of proteins rigorously and separating secondary structure effects from topological effects is a challenge. New developments in applied knot theory allow to characterize the topological characteristics of proteins (knotted or not). By analyzing a small set of two-state and multi-state proteins with no knots or slipknots, our results show that 95.4% of the analyzed proteins have non-trivial topological characteristics, as reflected by the second Vassiliev measure, and that the logarithm of the experimental protein folding rate depends on both the local geometry and the topology of the protein’s native state.

Investigation of the structural dynamics of a knotted protein and its unknotted analog using molecular dynamics

The role of knots in proteins remains elusive. Some studies suggest an impact on stability; the difficulty in comparing systems to assess this effect, however, has been a significant challenge. In this study, we produced and analyzed molecular dynamic trajectories considering three different temperatures of two variants of ornithine transcarbamylase (OTC), only one of which has a 3₁ knot, in order to evaluate the relative stability of the two molecules. RMSD showed equilibrated structures for the produced trajectories, and RMSF showed subtle differences in flexibility. In the knot moiety, the knotted protein did not show a great deal of fluctuation at any temperature. For the unknotted protein, the residue GLY243 showed a high fluctuation in the corresponding moiety. The fraction of native contacts (Q) showed a similar profile at all temperatures, with the greatest decrease by 436 K. The investigation of conformational behavior with principal component analysis (PCA) and dynamic cross-correlation map (DCCM) showed that knotted protein is less likely to undergo changes in its conformation under the conditions employed compared to unknotted. PCA data showed that the unknotted protein had greater dispersion in its conformations, which suggests that it has a greater capacity for conformation transitions in response to thermal changes. DCCM graphs comparing the 310 K and 436 K temperatures showed that the knotted protein had less change in its correlation and anti-correlation movements, indicating stability compared to the unknotted.

Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

To effectively archive configuration data during molecular dynamics (MD) simulations of polymer systems, we present an efficient compression method with good numerical accuracy that preserves the topology of ring-linear polymer blends. To compress the fraction of floating-point data, we used the Jointed Hierarchical Precision Compression Number - Data Format (JHPCN-DF) method to apply zero padding for the tailing fraction bits, which did not affect the numerical accuracy, then compressed the data with Huffman coding. We also provided a dataset of well-equilibrated configurations of MD simulations for ring-linear polymer blends with various lengths of linear and ring polymers, including ring complexes composed of multiple rings such as polycatenane. We executed 109 MD steps to obtain 150 equilibrated configurations. The combination of JHPCN-DF and SZ compression achieved the best compression ratio for all cases. Therefore, the proposed method enables efficient archiving of MD trajectories. Moreover, the publicly available dataset of ring-linear polymer blends can be employed for studies of mathematical methods, including topology analysis and data compression, as well as MD simulations.

Conformational Freedom and Topological Confinement of Proteins in Biomolecular Condensates

The emergence of biomolecular condensation and liquid-liquid phase separation (LLPS) introduces a new layer of complexity into our understanding of cell and molecular biology. Evidence steadily grows indicating that condensates are not only implicated in physiology but also human disease. Macro- and mesoscale characterization of condensates as a whole have been instrumental in understanding their biological functions and dysfunctions. By contrast, the molecular level characterization of condensates and how condensates modify the properties of the molecules that constitute them thus far remain comparably scarce. In this minireview we summarize and discuss the findings of several recent studies that have focused on structure, dynamics, and interactions of proteins undergoing condensation. The mechanistic insights they provide help us identify the relevant properties nature and scientists can leverage to modulate the behavior of condensate systems. We also discuss the unique environment of the droplet surface and speculate on effects of topological constraints and physical exclusion on condensate properties.

From 4-arm star proteins to diverse stimuli-responsive molecular networks enabled by orthogonal genetically encoded click chemistries

The integrated use of genetically encoded click chemistries and protein topology engineering enabled the creation of various smart protein hydrogels.

Lasso Proteins-Unifying Cysteine Knots and Miniproteins

Complex lasso proteins are a recently identified class of biological compounds that are present in considerable fraction of proteins with disulfide bridges. In this work, we look at complex lasso proteins as a generalization of well-known cysteine knots and miniproteins (lasso peptides). In particular, we show that complex lasso proteins with the same crucial topological features-cysteine knots and lasso peptides-are antimicrobial proteins, which suggests that they act as a molecular plug. Based on an analysis of the stability of the lasso piercing residue, we also introduce a method to determine which lasso motif is potentially functional. Using this method, we show that the lasso motif in antimicrobial proteins, as well in that in cytokines, is functionally relevant. We also study the evolution of lasso motifs, their conservation, and the usefulness of the lasso fingerprint, which extracts all topologically non-triviality concerning covalent loops. The work is completed by the presentation of extensive statistics on complex lasso proteins to analyze, in particular, the strange propensity for "negative" piercings. We also identify 21 previously unknown complex lasso proteins with an ester and a thioester bridge.

Higher Order Protein Catenation Leads to an Artificial Antibody with Enhanced Affinity and In Vivo Stability

The chemical topology is a unique dimension for protein engineering, yet the topological diversity and architectural complexity of proteins remain largely untapped. Herein, we report the biosynthesis of complex topological proteins using a rationally engineered, cross-entwining peptide heterodimer motif derived from p53dim (an entangled homodimeric mutant of the tetramerization domain of the tumor suppressor protein p53). The incorporation of an electrostatic interaction at specific sites converts the p53dim homodimer motif into a pair of heterodimer motifs with high specificity for directing chain entanglement upon folding. Its combination with split-intein-mediated ligation and/or SpyTag/SpyCatcher chemistry facilitates the programmed synthesis of protein heterocatenane or [n]catenanes in cells, leading to a general and modular approach to complex protein catenanes containing various proteins of interest. Concatenation enhances not only the target protein's affinity but also the in vivo stability as shown by its prolonged circulation time in blood. As a proof of concept, artificial antibodies have been developed by embedding a human epidermal growth factor receptor 2-specific affibody onto the [n]catenane scaffolds and shown to exhibit a higher affinity and a better pharmacokinetic profile than the wild-type affibody. These results suggest that topology engineering holds great promise in the development of therapeutic proteins.

Topological and physical links in soft matter systems

Linking, or multicomponent topological entanglement, is ubiquitous in soft matter systems, from mixtures of polymers and DNA filaments packedin vivoto interlocked line defects in liquid crystals and intertwined synthetic molecules. Yet, it is only relatively recently that theoretical and experimental advancements have made it possible to probe such entanglements and elucidate their impact on the physical properties of the systems. Here, we review the state-of-the-art of this rapidly expanding subject and organize it as follows. First, we present the main concepts and notions, from topological linking to physical linking and then consider the salient manifestations of molecular linking, from synthetic to biological ones. We next cover the main physical models addressing mutual entanglements in mixtures of polymers, both linear and circular. Finally, we consider liquid crystals, fluids and other non-filamentous systems where topological or physical entanglements are observed in defect or flux lines. We conclude with a perspective on open challenges.

Slipknotted and unknotted monovalent cation-proton antiporters evolved from a common ancestor

While the slipknot topology in proteins has been known for over a decade, its evolutionary origin is still a mystery. We have identified a previously overlooked slipknot motif in a family of two-domain membrane transporters. Moreover, we found that these proteins are homologous to several families of unknotted membrane proteins. This allows us to directly investigate the evolution of the slipknot motif. Based on our comprehensive analysis of 17 distantly related protein families, we have found that slipknotted and unknotted proteins share a common structural motif. Furthermore, this motif is conserved on the sequential level as well. Our results suggest that, regardless of topology, the proteins we studied evolved from a common unknotted ancestor single domain protein. Our phylogenetic analysis suggests the presence of at least seven parallel evolutionary scenarios that led to the current diversity of proteins in question. The tools we have developed in the process can now be used to investigate the evolution of other repeated-domain proteins.

In proteins with the slipknot topology, the polypeptide chain forms a slipknot—a structure that is not necessarily manifest to a naked eye, but it can be detected using mathematical methods. Slipknots are conserved motifs often found at catalytic sites and are directly involved in molecular transport. Although the first proteins with slipknots were found in 2007, many questions remain unanswered, e.g. how these proteins appeared, or whether the slipknotted proteins evolved from unknotted ones or vice versa. Here we provide the first analysis of homologous slipknotted and unknotted transmembrane proteins in order to elucidate their evolutionary relationship. We show that two-domain slipknotted and unknotted membrane transporters share the same one-domain unknotted protein as an ancestor. The ancestor gene duplicated and underwent various diversification and fusion events during the evolution, which have led to the appearance of a large superfamily of secondary active transporters. The slipknot motif seems to have been created by chance after a fusion of two single domain genes. Therefore, we show here that the slipknotted transporter evolved from an unknotted one-domain protein and that there are at least seven different evolutionary scenarios that gave rise to this large superfamily of transporters.

Protein self-entanglement modulates successful folding to the native state: A multi-scale modeling study

The computer-aided investigation of protein folding has greatly benefited from coarse-grained models, that is, simplified representations at a resolution level lower than atomistic, providing access to qualitative and quantitative details of the folding process that would be hardly attainable, via all-atom descriptions, for medium to long molecules. Nonetheless, the effectiveness of low-resolution models is itself hampered by the presence, in a small but significant number of proteins, of nontrivial topological self-entanglements. Features such as native state knots or slipknots introduce conformational bottlenecks, affecting the probability to fold into the correct conformation; this limitation is particularly severe in the context of coarse-grained models. In this work, we tackle the relationship between folding probability, protein folding pathway, and protein topology in a set of proteins with a nontrivial degree of topological complexity. To avoid or mitigate the risk of incurring in kinetic traps, we make use of the elastic folder model, a coarse-grained model based on angular potentials optimized toward successful folding via a genetic procedure. This light-weight representation allows us to estimate in silico folding probabilities, which we find to anti-correlate with a measure of topological complexity as well as to correlate remarkably well with experimental measurements of the folding rate. These results strengthen the hypothesis that the topological complexity of the native state decreases the folding probability and that the force-field optimization mimics the evolutionary process these proteins have undergone to avoid kinetic traps.

Dynamic covalent self-assembly of mechanically interlocked molecules solely made from peptides

Mechanically interlocked molecules (MIMs), such as rotaxanes and catenanes, have captured the attention of chemists both from a synthetic perspective and because of their role as simple prototypes of molecular machines. Although examples exist in nature, most synthetic MIMs are made from artificial building blocks and assembled in organic solvents. Synthesis of MIMs from natural biomolecules remains highly challenging. Here we report on a synthesis strategy for interlocked molecules solely made from peptides—mechanically interlocked peptides (MIPs). Fully peptidic, cysteine-decorated building blocks were self-assembled in water to generate disulfide-bonded dynamic combinatorial libraries consisting of multiple different rotaxanes, catenanes and daisy chains as well as more exotic structures. Detailed NMR spectroscopy and mass spectrometry characterization of a [2]catenane comprised of two peptide macrocycles revealed that this structure has rich conformational dynamics reminiscent of protein folding. Thus, MIPs can serve as a bridge between fully synthetic MIMs and those found in nature.

Topoly: Python package to analyze topology of polymers

The increasing role of topology in (bio)physical properties of matter creates a need for an efficient method of detecting the topology of a (bio)polymer. However, the existing tools allow one to classify only the simplest knots and cannot be used in automated sample analysis. To answer this need, we created the Topoly Python package. This package enables the distinguishing of knots, slipknots, links and spatial graphs through the calculation of different topological polynomial invariants. It also enables one to create the minimal spanning surface on a given loop, e.g. to detect a lasso motif or to generate random closed polymers. It is capable of reading various file formats, including PDB. The extensive documentation along with test cases and the simplicity of the Python programming language make it a very simple to use yet powerful tool, suitable even for inexperienced users. Topoly can be obtained from https://topoly.cent.uw.edu.pl.

Quantifying steric hindrance and topological obstruction to protein structure superposition

BACKGROUND

In computational structural biology, structure comparison is fundamental for our understanding of proteins. Structure comparison is, e.g., algorithmically the starting point for computational studies of structural evolution and it guides our efforts to predict protein structures from their amino acid sequences. Most methods for structural alignment of protein structures optimize the distances between aligned and superimposed residue pairs, i.e., the distances traveled by the aligned and superimposed residues during linear interpolation. Considering such a linear interpolation, these methods do not differentiate if there is room for the interpolation, if it causes steric clashes, or more severely, if it changes the topology of the compared protein backbone curves.

RESULTS

To distinguish such cases, we analyze the linear interpolation between two aligned and superimposed backbones. We quantify the amount of steric clashes and find all self-intersections in a linear backbone interpolation. To determine if the self-intersections alter the protein's backbone curve significantly or not, we present a path-finding algorithm that checks if there exists a self-avoiding path in a neighborhood of the linear interpolation. A new path is constructed by altering the linear interpolation using a novel interpretation of Reidemeister moves from knot theory working on three-dimensional curves rather than on knot diagrams. Either the algorithm finds a self-avoiding path or it returns a smallest set of essential self-intersections. Each of these indicates a significant difference between the folds of the aligned protein structures. As expected, we find at least one essential self-intersection separating most unknotted structures from a knotted structure, and we find even larger motions in proteins connected by obstruction free linear interpolations. We also find examples of homologous proteins that are differently threaded, and we find many distinct folds connected by longer but simple deformations. TM-align is one of the most restrictive alignment programs. With standard parameters, it only aligns residues superimposed within 5 Ångström distance. We find 42165 topological obstructions between aligned parts in 142068 TM-alignments. Thus, this restrictive alignment procedure still allows topological dissimilarity of the aligned parts.

CONCLUSIONS

Based on the data we conclude that our program ProteinAlignmentObstruction provides significant additional information to alignment scores based solely on distances between aligned and superimposed residue pairs.

Topological Twists in Nature

The first entangled protein was observed about 30 years ago, resulting in an increased interest for uncovering the biological functions and biophysical properties of these complex topologies. Recently, the Pierced Lasso Topology (PLT) was discovered in which a covalent bond forms an intramolecular loop, leaving one or both termini free to pierce the loop. This topology is related to knots and other entanglements. PLTs exist in many well-researched systems where the PLTs have previously been unnoticed. PLTs represents 18% of all disulfide containing proteins across all kingdoms of life. In this review, we investigate the biological implications of this specific topology in which the PLT-forming disulfide may act as a molecular switch for protein function and consequently human health.

DNA Mutations via Chern-Simons Currents

We test the validity of a possible schematization of DNA structure and dynamics based on the Chern-Simons theory, that is a topological field theory mostly considered in the context of effective gravity theories. By means of the expectation value of the Wilson Loop, derived from this analogue gravity approach, we find the point-like curvature of genomic strings in KRAS human gene and COVID-19 sequences, correlating this curvature with the genetic mutations. The point-like curvature profile, obtained by means of the Chern-Simons currents, can be used to infer the position of the given mutations within the genetic string. Generally, mutations take place in the highest Chern-Simons current gradient locations and subsequent mutated sequences appear to have a smoother curvature than the initial ones, in agreement with a free energy minimization argument.

Mechanically tightening, untying and retying a protein trefoil knot by single-molecule force spectroscopy

Knotted conformation is one of the most surprising topological features found in proteins, and understanding the folding mechanism of such knotted proteins remains a challenge. Here, we used optical tweezers (OT) to investigate the mechanical unfolding and folding behavior of a knotted protein Escherichia coli tRNA (guanosine-1) methyltransferase (TrmD). We found that when stretched from its N- and C-termini, TrmD can be mechanically unfolded and stretched into a tightened trefoil knot, which is composed of ca. 17 residues. Stretching of the unfolded TrmD involved a compaction process of the trefoil knot at low forces. The unfolding pathways of the TrmD were bifurcated, involving two-state and three-state pathways. Upon relaxation, the tightened trefoil knot loosened up first, leading to the expansion of the knot, and the unfolded TrmD can then fold back to its native state efficiently. By using an engineered truncation TrmD variant, we stretched TrmD along a pulling direction to allow us to mechanically unfold TrmD and untie the trefoil knot. We found that the folding of TrmD from its unfolded polypeptide without the knot is significantly slower. The knotting is the rate-limiting step of the folding of TrmD. Our results highlighted the critical importance of the knot conformation for the folding and stability of TrmD, offering a new perspective to understand the role of the trefoil knot in the biological function of TrmD.

Optical tweezers are used to stretch a knotted protein along different directions to probe its unfolding–folding behaviors, and the conformational change of its knot structure.

GLN: a method to reveal unique properties of lasso type topology in proteins

Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a matrix diagram-for a pair of a loop and a tail-to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a matrix diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.

Signaling Mechanism of Phytochromes in Solution

Phytochrome proteins guide the red/far-red photoresponse of plants, fungi, and bacteria. Crystal structures suggest that the mechanism of signal transduction from the chromophore to the output domains involves refolding of the so-called PHY tongue. It is currently not clear how the two other notable structural features of the phytochrome superfamily, the so-called helical spine and a knot in the peptide chain, are involved in photoconversion. Here, we present solution NMR data of the complete photosensory core module from Deinococcus radiodurans. Photoswitching between the resting and the active states induces changes in amide chemical shifts, residual dipolar couplings, and relaxation dynamics. All observables indicate a photoinduced structural change in the knot region and lower part of the helical spine. This implies that a conformational signal is transduced from the chromophore to the helical spine through the PAS and GAF domains. The discovered pathway underpins functional studies of plant phytochromes and may explain photosensing by phytochromes under biological conditions.

Cellular Synthesis and X-ray Crystal Structure of a Designed Protein Heterocatenane

Herein, we report the biosynthesis of protein heterocatenanes using a programmed sequence of multiple post-translational processing events including intramolecular chain entanglement, in situ backbone cleavage, and spontaneous cyclization. The approach is general, autonomous, and can obviate the need for any additional enzymes. The catenane topology was convincingly proven using a combination of SDS-PAGE, LC-MS, size exclusion chromatography, controlled proteolytic digestion, and protein crystallography. The X-ray crystal structure clearly shows two mechanically interlocked protein rings with intact folded domains. It opens new avenues in the nascent field of protein-topology engineering.

Lasso Proteins: Modular Design, Cellular Synthesis, and Topological Transformation

Entangled proteins have attracted significant research interest. Herein, we report the first rationally designed lasso proteins, or protein [1]rotaxanes, by using a p53dim-entwined dimer for intramolecular entanglement and a SpyTag-SpyCatcher reaction for side-chain ring closure. The lasso structures were confirmed by proteolytic digestion, mutation, NMR spectrometry, and controlled ligation. Their dynamic properties were probed by experiments such as end-capping, proteolytic digestion, and heating/cooling. As a versatile topological intermediate, a lasso protein could be converted to a rotaxane, a heterocatenane, and a "slide-ring" network. Being entirely genetically encoded, this robust and modular lasso-protein motif is a valuable addition to the topological protein repertoire and a promising candidate for protein-based biomaterials.

PyLink: a PyMOL plugin to identify links

SUMMARY

Links are generalization of knots, that consist of several components. They appear in proteins, peptides and other biopolymers with disulfide bonds or ions interactions giving rise to the exceptional stability. Moreover because of this stability such biopolymers are the target of commercial and medical use (including anti-bacterial and insecticidal activity). Therefore, topological characterization of such biopolymers, not only provides explanation of their thermodynamical or mechanical properties, but paves the way to design templates in pharmaceutical applications. However, distinction between links and trivial topology is not an easy task. Here, we present PyLink-a PyMOL plugin suited to identify three types of links and perform comprehensive topological analysis of proteins rich in disulfide or ion bonds. PyLink can scan for the links automatically, or the user may specify their own components, including closed loops with several bridges and ion interactions. This creates the possibility of designing new biopolymers with desired properties.

AVAILABILITY AND IMPLEMENTATION

The PyLink plugin, manual and tutorial videos are available at http://pylink.cent.uw.edu.pl.