Structural symmetry and protein function

Agglomeration: when folded proteins clump together

Protein self-association is a widespread phenomenon that results in the formation of multimeric protein structures with critical roles in cellular processes. Protein self-association can lead to finite protein complexes or open-ended, and potentially, infinite structures. This review explores the concept of protein agglomeration, a process that results from the infinite self-assembly of folded proteins. We highlight its differences from other better-described processes with similar macroscopic features, such as aggregation and liquid-liquid phase separation. We review the sequence, structural, and biophysical factors influencing protein agglomeration. Lastly, we briefly discuss the implications of agglomeration in evolution, disease, and aging. Overall, this review highlights the need to study protein agglomeration for a better understanding of cellular processes.

Mechanisms of Biomolecular Self-Assembly Investigated Through In Situ Observations of Structures and Dynamics

Biomolecular self-assembly of hierarchical materials is a precise and adaptable bottom-up approach to synthesizing across scales with considerable energy, health, environment, sustainability, and information technology applications. To achieve desired functions in biomaterials, it is essential to directly observe assembly dynamics and structural evolutions that reflect the underlying energy landscape and the assembly mechanism. This review will summarize the current understanding of biomolecular assembly mechanisms based on in situ characterization and discuss the broader significance and achievements of newly gained insights. In addition, we will also introduce how emerging deep learning/machine learning-based approaches, multiparametric characterization, and high-throughput methods can boost the development of biomolecular self-assembly. The objective of this review is to accelerate the development of in situ characterization approaches for biomolecular self-assembly and to inspire the next generation of biomimetic materials.

Computational Modeling of Stapled Coiled-Coil Inhibitors Against Bcr-Abl: Toward a Treatment Strategy for CML

The chimeric oncoprotein Bcr-Abl is the causative agent of virtually all chronic myeloid leukemias (CML) and a subset of acute lymphoblastic leukemias (ALL). As a result of the so-called Philadelphia Chromosome translocation t(9;22), Bcr-Abl manifests as a constitutively active tyrosine kinase which promotes leukemogenesis by activation of cell cycle signaling pathways. Constitutive and oncogenic activation is mediated by an N-terminal coiled-coil oligomerization domain in Bcr (Bcr-CC), presenting a therapeutic target for inhibition of Bcr-Abl activity toward the treatment of Bcr-Abl+ leukemias. Previously, we demonstrated that a rationally designed Bcr-CC mutant, CCmut3, exerts a dominant negative effect upon Bcr-Abl activity by preferential oligomerization with Bcr-CC. Moreover, we have shown conjugation to a leukemia-specific cell-penetrating peptide (CPP-CCmut3) improves intracellular delivery and activity. However, our full-length CPP-CCmut3 construct (81 aa) is encumbered by an intrinsically high degree of conformational variability and susceptibility to proteolytic degradation, relative to traditional small molecule therapeutics. Here, we iterate a new generation of our inhibitor against Bcr-CC mediated Bcr-Abl assembly that is designed to address these constraints through incorporation of all-hydrocarbon staples spanning i, i + 7 positions in helix α2 (CPP-CCmut3-st). We utilize computational modeling and biomolecular simulation to design and characterize single and double staple candidates in silico, evaluating binding energetics and building upon our seminal work modeling single hydrocarbon staples when applied to a truncated Bcr-CC sequence. This strategy enables us to efficiently build, characterize, and screen lead single/double stapled CPP-CCmut3-st candidates for experimental studies and validation in vitro and in vivo. In addition to full-length CPP-CCmut, we model a truncated system characterized by deletion of helix α1 and the flexible-loop linker, which are known to impart high conformational variability. To study the impact of the N-terminal cyclic CPP toward model stability and inhibitor activity, we also model the full-length and truncated systems without CPP, with cyclized CPP, and with linear CPP, for a total of six systems which comprise our library. From this library, we present lead stapled peptide candidates to be synthesized and evaluated experimentally as our next-generation inhibitors against Bcr-Abl.

Protein language models can capture protein quaternary state

BACKGROUND

Determining a protein's quaternary state, i.e. the number of monomers in a functional unit, is a critical step in protein characterization. Many proteins form multimers for their activity, and over 50% are estimated to naturally form homomultimers. Experimental quaternary state determination can be challenging and require extensive work. To complement these efforts, a number of computational tools have been developed for quaternary state prediction, often utilizing experimentally validated structural information. Recently, dramatic advances have been made in the field of deep learning for predicting protein structure and other characteristics. Protein language models, such as ESM-2, that apply computational natural-language models to proteins successfully capture secondary structure, protein cell localization and other characteristics, from a single sequence. Here we hypothesize that information about the protein quaternary state may be contained within protein sequences as well, allowing us to benefit from these novel approaches in the context of quaternary state prediction.

RESULTS

We generated ESM-2 embeddings for a large dataset of proteins with quaternary state labels from the curated QSbio dataset. We trained a model for quaternary state classification and assessed it on a non-overlapping set of distinct folds (ECOD family level). Our model, named QUEEN (QUaternary state prediction using dEEp learNing), performs worse than approaches that include information from solved crystal structures. However, it successfully learned to distinguish multimers from monomers, and predicts the specific quaternary state with moderate success, better than simple sequence similarity-based annotation transfer. Our results demonstrate that complex, quaternary state related information is included in such embeddings.

CONCLUSIONS

QUEEN is the first to investigate the power of embeddings for the prediction of the quaternary state of proteins. As such, it lays out strengths as well as limitations of a sequence-based protein language model approach, compared to structure-based approaches. Since it does not require any structural information and is fast, we anticipate that it will be of wide use both for in-depth investigation of specific systems, as well as for studies of large sets of protein sequences. A simple colab implementation is available at: https://colab.

RESEARCH

google.com/github/Furman-Lab/QUEEN/blob/main/QUEEN_prediction_notebook.ipynb .

Continuous symmetry and chirality measures: approximate algorithms for large molecular structures

Quantifying imperfect symmetry of molecules can help explore the sources, roles and extent of structural distortion. Based on the established methodology of continuous symmetry and chirality measures, we develop a set of three-dimensional molecular descriptors to estimate distortion of large structures. These three-dimensional geometrical descriptors quantify the gap between the desirable symmetry (or chirality) and the actual one. They are global parameters of the molecular geometry, intuitively defined, and have the ability to detect even minute structural changes of a given molecule across chemistry, including organic, inorganic, and biochemical systems. Application of these methods to large structures is challenging due to countless permutations that are involved in the symmetry operations and have to be accounted for. Our approach focuses on iteratively finding the approximate direction of the symmetry element in the three-dimensional space, and the relevant permutation. Major algorithmic improvements over previous versions are described, showing increased accuracy, reliability and structure preservation. The new algorithms are tested for three sets of molecular structures including pillar[5]arene complexes with Li+, C100 fullerenes, and large unit cells of metal organic frameworks. These developments complement our recent algorithms for calculating continuous symmetry and chirality measures for small molecules as well as protein homomers, and simplify the usage of the full set of measures for various research goals, in molecular modeling, QSAR and cheminformatics.

Co-evolution at protein-protein interfaces guides inference of stoichiometry of oligomeric protein complexes by de novo structure prediction

The quaternary structure with specific stoichiometry is pivotal to the specific function of protein complexes. However, determining the structure of many protein complexes experimentally remains a major bottleneck. Structural bioinformatics approaches, such as the deep learning algorithm Alphafold2-multimer (AF2-multimer), leverage the co-evolution of amino acids and sequence-structure relationships for accurate de novo structure and contact prediction. Pseudo-likelihood maximization direct coupling analysis (plmDCA) has been used to detect co-evolving residue pairs by statistical modeling. Here, we provide evidence that combining both methods can be used for de novo prediction of the quaternary structure and stoichiometry of a protein complex. We achieve this by augmenting the existing AF2-multimer confidence metrics with an interpretable score to identify the complex with an optimal fraction of native contacts of co-evolving residue pairs at intermolecular interfaces. We use this strategy to predict the quaternary structure and non-trivial stoichiometries of Bacillus subtilis spore germination protein complexes with unknown structures. Co-evolution at intermolecular interfaces may therefore synergize with AI-based de novo quaternary structure prediction of structurally uncharacterized bacterial protein complexes.

A morpheein equilibrium regulates catalysis in phosphoserine phosphatase SerB2 from Mycobacterium tuberculosis

Mycobacterium tuberculosis phosphoserine phosphatase MtSerB2 is of interest as a new antituberculosis target due to its essential metabolic role in L-serine biosynthesis and effector functions in infected cells. Previous works indicated that MtSerB2 is regulated through an oligomeric transition induced by L-Ser that could serve as a basis for the design of selective allosteric inhibitors. However, the mechanism underlying this transition remains highly elusive due to the lack of experimental structural data. Here we describe a structural, biophysical, and enzymological characterisation of MtSerB2 oligomerisation in the presence and absence of L-Ser. We show that MtSerB2 coexists in dimeric, trimeric, and tetrameric forms of different activity levels interconverting through a conformationally flexible monomeric state, which is not observed in two near-identical mycobacterial orthologs. This morpheein behaviour exhibited by MtSerB2 lays the foundation for future allosteric drug discovery and provides a starting point to the understanding of its peculiar multifunctional moonlighting properties.

Structural insights into hydrolytic defluorination of difluoroacetate by microbial fluoroacetate dehalogenases

Fluorine forms the strongest single bond to carbon with the highest bond dissociation energy among natural products. However, fluoroacetate dehalogenases (FADs) have been shown to hydrolyze this bond in fluoroacetate under mild reaction conditions. Furthermore, two recent studies demonstrated that the FAD RPA1163 from Rhodopseudomonas palustris can also accept bulkier substrates. In this study, we explored the substrate promiscuity of microbial FADs and their ability to defluorinate polyfluorinated organic acids. Enzymatic screening of eight purified dehalogenases with reported fluoroacetate defluorination activity revealed significant hydrolytic activity against difluoroacetate in three proteins. Product analysis using liquid chromatography-mass spectrometry identified glyoxylic acid as the final product of enzymatic DFA defluorination. The crystal structures of DAR3835 from Dechloromonas aromatica and NOS0089 from Nostoc sp. were determined in the apo-state along with the DAR3835 H274N glycolyl intermediate. Structure-based site-directed mutagenesis of DAR3835 demonstrated a key role for the catalytic triad and other active site residues in the defluorination of both fluoroacetate and difluoroacetate. Computational analysis of the dimer structures of DAR3835, NOS0089, and RPA1163 indicated the presence of one substrate access tunnel in each protomer. Moreover, protein-ligand docking simulations suggested similar catalytic mechanisms for the defluorination of both fluoroacetate and difluoroacetate, with difluoroacetate being defluorinated via two consecutive defluorination reactions producing glyoxylate as the final product. Thus, our findings provide molecular insights into substrate promiscuity and catalytic mechanism of FADs, which are promising biocatalysts for applications in synthetic chemistry and bioremediation of fluorochemicals.

Why does the first protein repeat often become the only one?

Proteins with two similar motifs in tandem are one of the most common cases of tandem repeat proteins. The question arises: why is the first emerged repeat frequently fixed in the process of evolution, despite the ample opportunities to continue its multiplication at the DNA level? To answer this question, we systematically analyzed the structure and function of these proteins. Our analysis showed that, in the vast majority of cases, the structural repetitive units have a two-fold (C2) internal symmetry. These closed structures provide an internal structural limitation for the subsequent growth of the repeat number. Frequently, the units "swap" their secondary structure elements with each other. Moreover, the duplicated domains, in contrast to other tandem repeat proteins, form binding sites for small molecules around the axis of C2 symmetry. Thus, the closure of the C2 structures and the emergence of new functional sites around the axis of C2 symmetry provide plausible explanations for why a repeat, once appeared, becomes fixed in the evolutionary process. We have placed these structures within the general structural classification of tandem repeat proteins, classifying them as either Class IV or V depending on the size of the repetitive unit.

De novo design of protein structure and function with RFdiffusion

There has been considerable recent progress in designing new proteins using deep-learning methods1-9. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Single-molecule visualization determines conformational substate ensembles in β-sheet-rich peptide fibrils

An understanding of protein conformational ensembles is essential for revealing the underlying mechanisms of interpeptide recognition and association. However, experimentally resolving multiple simultaneously existing conformational substates remains challenging. Here, we report the use of scanning tunneling microscopy (STM) to analyze the conformational substate ensembles of β sheet peptides with a submolecular resolution (in-plane <2.6 Å). We observed ensembles of more than 10 conformational substates (with free energy fluctuations between several k_BTs) in peptide homoassemblies of keratin (KRT) and amyloidal peptides (-5Aβ42 and TDP-43 341-357). Furthermore, STM reveals a change in the conformational ensemble of peptide mutants, which is correlated with the macroscopic properties of peptide assemblies. Our results demonstrate that the STM-based single-molecule imaging can capture a thorough picture of the conformational substates with which to build an energetic landscape of interconformational interactions and can rapidly screen conformational ensembles, which can complement conventional characterization techniques.

Hierarchical design of pseudosymmetric protein nanoparticles

Discrete protein assemblies ranging from hundreds of kilodaltons to hundreds of megadaltons in size are a ubiquitous feature of biological systems and perform highly specialized functions 1-3. Despite remarkable recent progress in accurately designing new self-assembling proteins, the size and complexity of these assemblies has been limited by a reliance on strict symmetry 4,5. Inspired by the pseudosymmetry observed in bacterial microcompartments and viral capsids, we developed a hierarchical computational method for designing large pseudosymmetric self-assembling protein nanomaterials. We computationally designed pseudosymmetric heterooligomeric components and used them to create discrete, cage-like protein assemblies with icosahedral symmetry containing 240, 540, and 960 subunits. At 49, 71, and 96 nm diameter, these nanoparticles are the largest bounded computationally designed protein assemblies generated to date. More broadly, by moving beyond strict symmetry, our work represents an important step towards the accurate design of arbitrary self-assembling nanoscale protein objects.

Buffering of genetic dominance by allele-specific protein complex assembly

Protein complex assembly often occurs while subunits are being translated, resulting in complexes whose subunits were translated from the same mRNA in an allele-specific manner. It has thus been hypothesized that such cotranslational assembly may counter the assembly-mediated dominant-negative effect, whereby co-assembly of mutant and wild-type subunits "poisons" complex activity. Here, we show that cotranslationally assembling subunits are much less likely to be associated with autosomal dominant relative to recessive disorders, and that subunits with dominant-negative disease mutations are significantly depleted in cotranslational assembly compared to those associated with loss-of-function mutations. We also find that complexes with known dominant-negative effects tend to expose their interfaces late during translation, lessening the likelihood of cotranslational assembly. Finally, by combining complex properties with other features, we trained a computational model for predicting proteins likely to be associated with non-loss-of-function disease mechanisms, which we believe will be of considerable utility for protein variant interpretation.

Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains

Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.

Asymmetric horseshoe-like assembly of peroxisomal yeast oxalyl-CoA synthetase

Oxalyl-CoA synthetase from Saccharomyces cerevisiae is one of the most abundant peroxisomal proteins in yeast and hence has become a model to study peroxisomal translocation. It contains a C-terminal Peroxisome Targeting Signal 1, which however is partly dispensable, suggesting additional receptor bindings sites. To unravel any additional features that may contribute to its capacity to be recognized as peroxisomal target, we determined its assembly and overall architecture by an integrated structural biology approach, including X-ray crystallography, single particle cryo-electron microscopy and small angle X-ray scattering. Surprisingly, it assembles into mixture of concentration-dependent dimers, tetramers and hexamers by dimer self-association. Hexameric particles form an unprecedented asymmetric horseshoe-like arrangement, which considerably differs from symmetric hexameric assembly found in many other protein structures. A single mutation within the self-association interface is sufficient to abolish any higher-level oligomerization, resulting in a homogenous dimeric assembly. The small C-terminal domain of yeast Oxalyl-CoA synthetase is connected by a partly flexible hinge with the large N-terminal domain, which provides the sole basis for oligomeric assembly. Our data provide a basis to mechanistically study peroxisomal translocation of this target.

Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution

Comprehensive sampling of natural genetic diversity with metagenomics enables highly resolved insights into the interplay between ecology and evolution. However, resolving adaptive, neutral, or purifying processes of evolution from intrapopulation genomic variation remains a challenge, partly due to the sole reliance on gene sequences to interpret variants. Here, we describe an approach to analyze genetic variation in the context of predicted protein structures and apply it to a marine microbial population within the SAR11 subclade 1a.3.V, which dominates low-latitude surface oceans. Our analyses reveal a tight association between genetic variation and protein structure. In a central gene in nitrogen metabolism, we observe decreased occurrence of nonsynonymous variants from ligand-binding sites as a function of nitrate concentrations, revealing genetic targets of distinct evolutionary pressures maintained by nutrient availability. Our work yields insights into the governing principles of evolution and enables structure-aware investigations of microbial population genetics.

DeepHomo2.0: improved protein-protein contact prediction of homodimers by transformer-enhanced deep learning

Protein-protein interactions play an important role in many biological processes. However, although structure prediction for monomer proteins has achieved great progress with the advent of advanced deep learning algorithms like AlphaFold, the structure prediction for protein-protein complexes remains an open question. Taking advantage of the Transformer model of ESM-MSA, we have developed a deep learning-based model, named DeepHomo2.0, to predict protein-protein interactions of homodimeric complexes by leveraging the direct-coupling analysis (DCA) and Transformer features of sequences and the structure features of monomers. DeepHomo2.0 was extensively evaluated on diverse test sets and compared with eight state-of-the-art methods including protein language model-based, DCA-based and machine learning-based methods. It was shown that DeepHomo2.0 achieved a high precision of >70% with experimental monomer structures and >60% with predicted monomer structures for the top 10 predicted contacts on the test sets and outperformed the other eight methods. Moreover, even the version without using structure information, named DeepHomoSeq, still achieved a good precision of >55% for the top 10 predicted contacts. Integrating the predicted contacts into protein docking significantly improved the structure prediction of realistic Critical Assessment of Protein Structure Prediction homodimeric complexes. DeepHomo2.0 and DeepHomoSeq are available at http://huanglab.phys.hust.edu.cn/DeepHomo2/.

Self-assembled nanoparticles: A new platform for revolutionizing therapeutic cancer vaccines

Cancer vaccines have had some success in the past decade. Based on in-depth analysis of tumor antigen genomics, many therapeutic vaccines have already entered clinical trials for multiple cancers, including melanoma, lung cancer, and head and neck squamous cell carcinoma, which have demonstrated impressive tumor immunogenicity and antitumor activity. Recently, vaccines based on self-assembled nanoparticles are being actively developed as cancer treatment, and their feasibility has been confirmed in both mice and humans. In this review, we summarize recent therapeutic cancer vaccines based on self-assembled nanoparticles. We describe the basic ingredients for self-assembled nanoparticles, and how they enhance vaccine immunogenicity. We also discuss the novel design method for self-assembled nanoparticles that pose as a promising delivery platform for cancer vaccines, and the potential in combination with multiple therapeutic approaches.

Head or tail? A molecular dynamics approach to the complex structure of TNF-associated factor TRAF2

Tumor necrosis factor receptor-associated factor proteins (TRAFs) are trimeric proteins that play a fundamental role in signaling, acting as intermediaries between the tumor necrosis factor (TNF) receptors and the proteins that transmit the downstream signal. The monomeric subunits of all the TRAF family members share a common tridimensional structure: a C-terminal globular domain and a long coiled-coil tail characterizing the N-terminal section. In this study, the dependence of the TRAF2 dynamics on the length of its tail was analyzed in silico. In particular, we used the available crystallographic structure of a C-terminal fragment of TRAF2 (168 out of 501 a.a.), TRAF2-C, and that of a longer construct, addressed as TRAF2-plus, that we have re-constructed using the AlphaFold2 code. The results indicate that the longer N-terminal tail of TRAF2-plus has a strong influence on the dynamics of the globular regions in the protein C-terminal head. In fact, the quaternary interactions among the TRAF2-C subunits change asymmetrically in time, while the movements of TRAF2-plus monomers are rather limited and more ordered than those of the shorter construct. Such findings shed a new light on the dynamics of TRAF subunits and on the protein mechanism in vivo, since TRAF monomer-trimer equilibrium is crucial for several reasons (receptor recognition, membrane binding, hetero-oligomerization).

A Guide to In Silico Drug Design

The drug discovery process is a rocky path that is full of challenges, with the result that very few candidates progress from hit compound to a commercially available product, often due to factors, such as poor binding affinity, off-target effects, or physicochemical properties, such as solubility or stability. This process is further complicated by high research and development costs and time requirements. It is thus important to optimise every step of the process in order to maximise the chances of success. As a result of the recent advancements in computer power and technology, computer-aided drug design (CADD) has become an integral part of modern drug discovery to guide and accelerate the process. In this review, we present an overview of the important CADD methods and applications, such as in silico structure prediction, refinement, modelling and target validation, that are commonly used in this area.

Oligomerization of peripheral membrane proteins provides tunable control of cell surface polarity

Asymmetric distributions of peripheral membrane proteins define cell polarity across all kingdoms of life. Non-linear positive feedback on membrane binding is essential to amplify and stabilize these asymmetries, but how specific molecular sources of non-linearity shape polarization dynamics remains poorly understood. Here we show that the ability to oligomerize, which is common to many peripheral membrane proteins, can play a profound role in shaping polarization dynamics in simple feedback circuits. We show that size-dependent binding avidity and mobility of membrane-bound oligomers endow polarity circuits with several key properties. Size-dependent membrane binding avidity confers a form of positive feedback on the accumulation of oligomer subunits. Although insufficient by itself, this sharply reduces the amount of additional feedback required for spontaneous emergence and stable maintenance of polarized states. Size-dependent oligomer mobility makes symmetry breaking and stable polarity more robust with respect to variation in subunit diffusivities and cell sizes, and slows the approach to a final stable spatial distribution, allowing cells to "remember" polarity boundaries imposed by transient external cues. Together, these findings reveal how oligomerization of peripheral membrane proteins can provide powerful and highly tunable sources of non-linear feedback in biochemical circuits that govern cell surface polarity. Given its prevalence and widespread involvement in cell polarity, we speculate that self-oligomerization may have provided an accessible path to evolving simple polarity circuits.

Catalytic RNA Oligomers Formed by Co-Oligomerization of a Pair of Bimolecular RNase P Ribozymes

Naturally occurring ribozymes with a modular architecture are promising platforms for construction of RNA nanostructures because modular redesign enables their oligomerization. The resulting RNA nanostructures can exhibit the catalytic function of the parent ribozyme in an assembly dependent manner. In this study, we designed and constructed open-form oligomers of a bimolecular form of an RNase P ribozyme. The ribozyme oligomers were analyzed biochemically and by atomic force microscopy (AFM).

Non-invasive chimeric HaloTag labeling to study clustering and diffusion of membrane proteins

As live imaging plays an increasingly critical role in cell biology research, the desire to label and track individual protein molecules in vivo has been growing. To address this, in this protocol we describe steps for sparse labeling using two different HaloTag ligand dyes in C. elegans. This labeling approach is simple, is non-invasive, and preserves the view of the bulk protein population. We further describe how to carry out single-particle tracking experiments and extract information about particle diffusion behavior. For complete details on the use and execution of this protocol, please refer to Chang and Dickinson (2022).¹.

Molecular physiology of Arc/Arg3.1: The oligomeric state hypothesis of synaptic plasticity

The immediate early gene, Arc, is a pivotal regulator of synaptic plasticity, memory, and cognitive flexibility. But what is Arc protein? How does it work? Inside the neuron, Arc is a protein interaction hub and dynamic regulator of intra-cellular signaling in synaptic plasticity. In remarkable contrast, Arc can also self-assemble into retrovirus-like capsids that are released in extracellular vesicles and capable of intercellular transfer of RNA. Elucidation of the molecular basis of Arc hub and capsid functions, and the relationship between them, is vital for progress. Here, we discuss recent findings on Arc structure-function and regulation of oligomerization that are giving insight into the molecular physiology of Arc. The unique features of mammalian Arc are emphasized, while drawing comparisons with Drosophila Arc and retroviral Gag. The Arc N-terminal domain, found only in mammals, is proposed to play a key role in regulating Arc hub signaling, oligomerization, and formation of capsids. Bringing together several lines of evidence, we hypothesize that Arc function in synaptic plasticity-long-term potentiation (LTP) and long-term depression (LTD)-are dictated by different oligomeric forms of Arc. Specifically, monomer/dimer function in LTP, tetramer function in basic LTD, and 32-unit oligomer function in enhanced LTD. The role of mammalian Arc capsids is unclear but likely depends on the cross-section of captured neuronal activity-induced RNAs. As the functional states of Arc are revealed, it may be possible to selectively manipulate specific forms of Arc-dependent plasticity and intercellular communication involved in brain function and dysfunction.

Simple mechanisms for the evolution of protein complexity

Proteins are tiny models of biological complexity: specific interactions among their many amino acids cause proteins to fold into elaborate structures, assemble with other proteins into higher-order complexes, and change their functions and structures upon binding other molecules. These complex features are classically thought to evolve via long and gradual trajectories driven by persistent natural selection. But a growing body of evidence from biochemistry, protein engineering, and molecular evolution shows that naturally occurring proteins often exist at or near the genetic edge of multimerization, allostery, and even new folds, so just one or a few mutations can trigger acquisition of these properties. These sudden transitions can occur because many of the physical properties that underlie these features are present in simpler proteins as fortuitous by-products of their architecture. Moreover, complex features of proteins can be encoded by huge arrays of sequences, so they are accessible from many different starting points via many possible paths. Because the bridges to these features are both short and numerous, random chance can join selection as a key factor in explaining the evolution of molecular complexity.

Helical ultrastructure of the metalloprotease meprin α in complex with a small molecule inhibitor

The zinc-dependent metalloprotease meprin α is predominantly expressed in the brush border membrane of proximal tubules in the kidney and enterocytes in the small intestine and colon. In normal tissue homeostasis meprin α performs key roles in inflammation, immunity, and extracellular matrix remodelling. Dysregulated meprin α is associated with acute kidney injury, sepsis, urinary tract infection, metastatic colorectal carcinoma, and inflammatory bowel disease. Accordingly, meprin α is the target of drug discovery programs. In contrast to meprin β, meprin α is secreted into the extracellular space, whereupon it oligomerises to form giant assemblies and is the largest extracellular protease identified to date (~6 MDa). Here, using cryo-electron microscopy, we determine the high-resolution structure of the zymogen and mature form of meprin α, as well as the structure of the active form in complex with a prototype small molecule inhibitor and human fetuin-B. Our data reveal that meprin α forms a giant, flexible, left-handed helical assembly of roughly 22 nm in diameter. We find that oligomerisation improves proteolytic and thermal stability but does not impact substrate specificity or enzymatic activity. Furthermore, structural comparison with meprin β reveal unique features of the active site of meprin α, and helical assembly more broadly.

Protein quaternary structures in solution are a mixture of multiple forms

Over half the proteins in the E. coli cytoplasm form homo or hetero-oligomeric structures. Experimentally determined structures are often considered in determining a protein's oligomeric state, but static structures miss the dynamic equilibrium between different quaternary forms. The problem is exacerbated in homo-oligomers, where the oligomeric states are challenging to characterize. Here, we re-evaluated the oligomeric state of 17 different bacterial proteins across a broad range of protein concentrations and solutions by native mass spectrometry (MS), mass photometry (MP), size exclusion chromatography (SEC), and small-angle X-ray scattering (SAXS), finding that most exhibit several oligomeric states. Surprisingly, some proteins did not show mass-action driven equilibrium between the oligomeric states. For approximately half the proteins, the predicted oligomeric forms described in publicly available databases underestimated the complexity of protein quaternary structures in solution. Conversely, AlphaFold multimer provided an accurate description of the potential multimeric states for most proteins, suggesting that it could help resolve uncertainties on the solution state of many proteins.

Hallucinating symmetric protein assemblies

Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of seven designs are very similar to the computational models (median root mean square deviation: 0.6 angstroms), as are three cryo-electron microscopy structures of giant 10-nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning and pave the way for the design of increasingly complex components for nanomachines and biomaterials.

Role of Half-of-Sites Reactivity and Inter-Subunit Communications in DAHP Synthase Catalysis and Regulation

α-Carboxyketose synthases, including 3-deoxy-d-arabinoheptulosonate 7-phosphate synthase (DAHPS), are long-standing targets for inhibition. They are challenging targets to create tight-binding inhibitors against, and inhibitors often display half-of-sites binding and partial inhibition. Half-of-sites inhibition demonstrates the existence of inter-subunit communication in DAHPS. We used X-ray crystallography and spatially resolved hydrogen-deuterium exchange (HDX) to reveal the structural and dynamic bases for inter-subunit communication in Escherichia coli DAHPS(Phe), the isozyme that is feedback-inhibited by phenylalanine. Crystal structures of this homotetrameric (dimer-of-dimers) enzyme are invariant over 91% of its sequence. Three variable loops make up 8% of the sequence and are all involved in inter-subunit contacts across the tight-dimer interface. The structures have pseudo-twofold symmetry indicative of inter-subunit communication across the loose-dimer interface, with the diagonal subunits B and C always having the same conformation as each other, while subunits A and D are variable. Spatially resolved HDX reveals contrasting responses to ligand binding, which, in turn, affect binding of the second substrate, erythrose-4-phosphate (E4P). The N-terminal peptide, M1-E12, and the active site loop that binds E4P, F95-K105, are key parts of the communication network. Inter-subunit communication appears to have a catalytic role in all α-carboxyketose synthase families and a regulatory role in some members.

Molecular asymmetry of a photosynthetic supercomplex from green sulfur bacteria

The photochemical reaction center (RC) features a dimeric architecture for charge separation across the membrane. In green sulfur bacteria (GSB), the trimeric Fenna-Matthews-Olson (FMO) complex mediates the transfer of light energy from the chlorosome antenna complex to the RC. Here we determine the structure of the photosynthetic supercomplex from the GSB Chlorobaculum tepidum using single-particle cryogenic electron microscopy (cryo-EM) and identify the cytochrome c subunit (PscC), two accessory protein subunits (PscE and PscF), a second FMO trimeric complex, and a linker pigment between FMO and the RC core. The protein subunits that are assembled with the symmetric RC core generate an asymmetric photosynthetic supercomplex. One linker bacteriochlorophyll (BChl) is located in one of the two FMO-PscA interfaces, leading to differential efficiencies of the two energy transfer branches. The two FMO trimeric complexes establish two different binding interfaces with the RC cytoplasmic surface, driven by the associated accessory subunits. This structure of the GSB photosynthetic supercomplex provides mechanistic insight into the light excitation energy transfer routes and a possible evolutionary transition intermediate of the bacterial photosynthetic supercomplex from the primitive homodimeric RC.

Thermodynamic coupling between neighboring binding sites in homo-oligomeric ligand sensing proteins from mass resolved ligand-dependent population distributions

Homo-oligomeric ligand-activated proteins are ubiquitous in biology. The functions of such molecules are commonly regulated by allosteric coupling between ligand-binding sites. Understanding the basis for this regulation requires both quantifying the free energy ΔG transduced between sites, and the structural basis by which it is transduced. We consider allostery in three variants of the model ring-shaped homo-oligomeric trp RNA-binding attenuation protein (TRAP). First, we developed a nearest-neighbor statistical thermodynamic binding model comprising microscopic free energies for ligand binding to isolated sites ΔG0 , and for coupling between adjacent sites, ΔGα . Using the resulting partition function (PF) we explored the effects of these parameters on simulated population distributions for the 2N possible liganded states. We then experimentally monitored ligand-dependent population shifts using conventional spectroscopic and calorimetric methods and using native mass spectrometry (MS). By resolving species with differing numbers of bound ligands by their mass, native MS revealed striking differences in their ligand-dependent population shifts. Fitting the populations to a binding polynomial derived from the PF yielded coupling free energy terms corresponding to orders of magnitude differences in cooperativity. Uniquely, this approach predicts which of the possible 2N liganded states are populated at different ligand concentrations, providing necessary insights into regulation. The combination of statistical thermodynamic modeling with native MS may provide the thermodynamic foundation for a meaningful understanding of the structure-thermodynamic linkage that drives cooperativity.

Understanding Supramolecular Assembly of Supercharged Proteins

Ordered supramolecular assemblies have recently been created using electrostatic interactions between oppositely charged proteins. Despite recent progress, the fundamental mechanisms governing the assembly of oppositely supercharged proteins are not fully understood. Here, we use a combination of experiments and computational modeling to systematically study the supramolecular assembly process for a series of oppositely supercharged green fluorescent protein variants. We show that net charge is a sufficient molecular descriptor to predict the interaction fate of oppositely charged proteins under a given set of solution conditions (e.g., ionic strength), but the assembled supramolecular structures critically depend on surface charge distributions. Interestingly, our results show that a large excess of charge is necessary to nucleate assembly and that charged residues not directly involved in interprotein interactions contribute to a substantial fraction (∼30%) of the interaction energy between oppositely charged proteins via long-range electrostatic interactions. Dynamic subunit exchange experiments further show that relatively small, 16-subunit assemblies of oppositely charged proteins have kinetic lifetimes on the order of ∼10-40 min, which is governed by protein composition and solution conditions. Broadly, our results inform how protein supercharging can be used to create different ordered supramolecular assemblies from a single parent protein building block.

Assembly of Two-Dimensional DNA Arrays Could Influence the Formation of Their Component Tiles

Tile-based DNA self-assembly is a powerful approach for nano-constructions. In this approach, individual DNA single strands first assemble into well-defined structural tiles, which, then, further associate with each other into final nanostructures. It is a general assumption that the lower-level structures (tiles) determine the higher-level, final structures. In this study, we present concrete experimental data to show that higher-level structures could, at least in the current example, also impact on the formation of lower-level structures. This study prompts questions such as: how general is this phenomenon in programmed DNA self-assembly and can we turn it into a useful tool for fine tuning DNA self-assembly?

Structural plasticity enables evolution and innovation of RuBisCO assemblies

Oligomerization is a core structural feature that defines the form and function of many proteins. Most proteins form molecular complexes; however, there remains a dearth of diversity-driven structural studies investigating the evolutionary trajectory of these assemblies. Ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO) is one such enzyme that adopts multiple assemblies, although the origins and distribution of its different oligomeric states remain cryptic. Here, we retrace the evolution of ancestral and extant form II RuBisCOs, revealing a complex and diverse history of oligomerization. We structurally characterize a newly discovered tetrameric RuBisCO, elucidating how solvent-exposed surfaces can readily adopt new interactions to interconvert or give rise to new oligomeric states. We further use these principles to engineer and demonstrate how changes in oligomerization can be mediated by relatively few mutations. Our findings yield insight into how structural plasticity may give rise to new oligomeric states.

Large protein complex interfaces have evolved to promote cotranslational assembly

Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

Oligomeric interactions maintain active-site structure in a noncooperative enzyme family

The evolutionary benefit accounting for widespread conservation of oligomeric structures in proteins lacking evidence of intersubunit cooperativity remains unclear. Here, crystal and cryo-EM structures, and enzymological data, demonstrate that a conserved tetramer interface maintains the active-site structure in one such class of proteins, the short-chain dehydrogenase/reductase (SDR) superfamily. Phylogenetic comparisons support a significantly longer polypeptide being required to maintain an equivalent active-site structure in the context of a single subunit. Oligomerization therefore enhances evolutionary fitness by reducing the metabolic cost of enzyme biosynthesis. The large surface area of the structure-stabilizing oligomeric interface yields a synergistic gain in fitness by increasing tolerance to activity-enhancing yet destabilizing mutations. We demonstrate that two paralogous SDR superfamily enzymes with different specificities can form mixed heterotetramers that combine their individual enzymological properties. This suggests that oligomerization can also diversify the functions generated by a given metabolic investment, enhancing the fitness advantage provided by this architectural strategy.

Exploring protein symmetry at the RCSB Protein Data Bank

The symmetry of biological molecules has fascinated structural biologists ever since the structure of hemoglobin was determined. The Protein Data Bank (PDB) archive is the central global archive of three-dimensional (3D), atomic-level structures of biomolecules, providing open access to the results of structural biology research with no limitations on usage. Roughly 40% of the structures in the archive exhibit some type of symmetry, including formal global symmetry, local symmetry, or pseudosymmetry. The Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (founding member of the Worldwide Protein Data Bank partnership that jointly manages, curates, and disseminates the archive) provides a variety of tools to assist users interested in exploring the symmetry of biological macromolecules. These tools include multiple modalities for searching and browsing the archive, turnkey methods for biomolecular visualization, documentation, and outreach materials for exploring functional biomolecular symmetry.

Box-shaped ribozyme octamer formed by face-to-face dimerization of a pair of square-shaped ribozyme tetramers

Naturally occurring ribozymes with defined three-dimensional (3D) structures serve as promising platforms for the design and construction of artificial RNA nanostructures. We constructed a hexameric ribozyme nanostructure by face-to-face dimerization of a pair of triangular ribozyme trimers, unit RNAs of which were derived from the Tetrahymena group I ribozyme. In this study, we have expanded the dimerization strategy to a square-shaped ribozyme tetramer by introducing four pillar units. The resulting box-shaped nanostructures, which contained eight ribozyme units, can be assembled from either four or two components of their unit RNAs.

Evolution of homo-oligomerization of methionine S-adenosyltransferases is replete with structure-function constrains

Homomers are prevalent in bacterial proteomes, particularly among core metabolic enzymes. Homomerization is often key to function and regulation, and interfaces that facilitate the formation of homomeric enzymes are subject to intense evolutionary change. However, our understanding of the molecular mechanisms that drive evolutionary variation in homomeric complexes is still lacking. How is the diversification of protein interfaces linked to variation in functional regulation and structural integrity of homomeric complexes? To address this question, we studied quaternary structure evolution of bacterial methionine S-adenosyltransferases (MATs)-dihedral homotetramers formed along a large and conserved dimeric interface harboring two active sites, and a small, recently evolved, interdimeric interface. Here, we show that diversity in the physicochemical properties of small interfaces is directly linked to variability in the kinetic stability of MAT quaternary complexes and in modes of their functional regulation. Specifically, hydrophobic interactions within the small interface of Escherichia coli MAT render the functional homotetramer kinetically stable yet impose severe aggregation constraints on complex assembly. These constraints are alleviated by electrostatic interactions that accelerate dimer-dimer assembly. In contrast, Neisseria gonorrhoeae MAT adopts a nonfunctional dimeric state due to the low hydrophobicity of its small interface and the high flexibility of its active site loops, which perturbs small interface integrity. Remarkably, in the presence of methionine and ATP, N. gonorrhoeae MAT undergoes substrate-induced assembly into a functional tetrameric state. We suggest that evolution acts on the interdimeric interfaces of MATs to tailor the regulation of their activity and stability to unique organismal needs.

A peptide interfering with the dimerization of oncogenic KITENIN protein and its stability suppresses colorectal tumour progression

The stability of a protein, as well as its function and versatility, can be enhanced through oligomerization. KITENIN (KAI1 C-terminal interacting tetraspanin) is known to promote the malignant progression of colorectal cancer (CRC). How KITENIN maintains its structural integrity and stability are largely unknown, however. Here we investigated the mechanisms regulating the stability of KITENIN with the aim of developing therapeutics blocking its oncogenic functions. We found that KITENIN formed a homo-oligomeric complex and that the intracellular C-terminal domain (KITENIN-CTD) was needed for this oligomerization. Expression of the KITENIN-CTD alone interfered with the formation of the KITENIN homodimer, and the amino acid sequence from 463 to 471 within the KITENIN-CTD was the most effective. This sequence coupled with a cell-penetrating peptide was named a KITENIN dimerization-interfering peptide (KDIP). We next studied the mechanisms by which KDIP affected the stability of KITENIN. The KITENIN-interacting protein myosin-X (Myo10), which has oncogenic activity in several cancers, functioned as an effector to stabilize the KITENIN homodimer in the cis formation. Treatment with KDIP resulted in the disintegration of the homodimer via downregulation of Myo10, which led to increased binding of RACK1 to the exposed RACK1-interacting motif (463-471 aa), and subsequent autophagy-dependent degradation of KITENIN and reduced CRC cell invasion. Intravenous injection of KDIP significantly reduced the tumour burden in a syngeneic mouse tumour model and colorectal liver metastasis in an intrasplenic hepatic metastasis model. Collectively, our present results provide a new cancer therapeutic peptide for blocking colorectal liver metastasis, which acts by inducing the downregulation of Myo10 and specifically targeting the stability of the oncogenic KITENIN protein.

Symmetry of 4-Oxalocrotonate Tautomerase Trimers Influences Unfolding and Fragmentation in the Gas Phase

The recent discovery of asymmetric arrangements of trimers in the tautomerase superfamily (TSF) adds structural diversity to this already mechanistically diverse superfamily. Classification of asymmetric trimers has previously been determined using X-ray crystallography. Here, native mass spectrometry (MS) and ultraviolet photodissociation (UVPD) are employed as an integrated strategy for more rapid and sensitive differentiation of symmetric and asymmetric trimers. Specifically, the unfolding of symmetric and asymmetric trimers initiated by collisional heating was probed using UVPD, which revealed unique gas-phase unfolding pathways. Variations in UVPD patterns from native-like, compact trimeric structures to unfolded, extended conformations indicate a rearrangement of higher-order structure in the asymmetric trimers that are believed to be stabilized by salt-bridge triads, which are absent from the symmetric trimers. Consequently, the symmetric trimers were found to be less stable in the gas phase, resulting in enhanced UVPD fragmentation overall and a notable difference in higher-order re-structuring based on the extent of hydrogen migration of protein fragments. The increased stability of the asymmetric trimers may justify their evolution and concomitant diversification of the TSF. Facilitating the classification of TSF members as symmetric or asymmetric trimers assists in delineating the evolutionary history of the TSF.

Sub-3-Å cryo-EM structure of RNA enabled by engineered homomeric self-assembly

High-resolution structural studies are essential for understanding the folding and function of diverse RNAs. Herein, we present a nanoarchitectural engineering strategy for efficient structural determination of RNA-only structures using single-particle cryogenic electron microscopy (cryo-EM). This strategy-ROCK (RNA oligomerization-enabled cryo-EM via installing kissing loops)-involves installing kissing-loop sequences onto the functionally nonessential stems of RNAs for homomeric self-assembly into closed rings with multiplied molecular weights and mitigated structural flexibility. ROCK enables cryo-EM reconstruction of the Tetrahymena group I intron at 2.98-Å resolution overall (2.85 Å for the core), allowing de novo model building of the complete RNA, including the previously unknown peripheral domains. ROCK is further applied to two smaller RNAs-the Azoarcus group I intron and the FMN riboswitch, revealing the conformational change of the former and the bound ligand in the latter. ROCK holds promise to greatly facilitate the use of cryo-EM in RNA structural studies.

Fluorescence lifetime imaging microscopy reveals sodium pump dimers in live cells

The sodium-potassium ATPase (Na/K-ATPase, NKA) establishes ion gradients that facilitate many physiological functions including action potentials and secondary transport processes. NKA comprises a catalytic subunit (alpha) that interacts closely with an essential subunit (beta) and regulatory transmembrane micropeptides called FXYD proteins. In the heart, a key modulatory partner is the FXYD protein phospholemman (PLM, FXYD1), but the stoichiometry of the alpha-beta-PLM regulatory complex is unknown. Here, we used fluorescence lifetime imaging and spectroscopy to investigate the structure, stoichiometry, and affinity of the NKA-regulatory complex. We observed a concentration-dependent binding of the subunits of NKA-PLM regulatory complex, with avid association of the alpha subunit with the essential beta subunit as well as lower affinity alpha-alpha and alpha-PLM interactions. These data provide the first evidence that, in intact live cells, the regulatory complex is composed of two alpha subunits associated with two beta subunits, decorated with two PLM regulatory subunits. Docking and molecular dynamics (MD) simulations generated a structural model of the complex that is consistent with our experimental observations. We propose that alpha-alpha subunit interactions support conformational coupling of the catalytic subunits, which may enhance NKA turnover rate. These observations provide insight into the pathophysiology of heart failure, wherein low NKA expression may be insufficient to support formation of the complete regulatory complex with the stoichiometry (alpha-beta-PLM)2.

Proteome-wide landscape of solubility limits in a bacterial cell

Proteins are prone to aggregate when expressed above their solubility limits. Aggregation may occur rapidly, potentially as early as proteins emerge from the ribosome, or slowly, following synthesis. However, in vivo data on aggregation rates are scarce. Here, we classified the Escherichia coli proteome into rapidly and slowly aggregating proteins using an in vivo image-based screen coupled with machine learning. We find that the majority (70%) of cytosolic proteins that become insoluble upon overexpression have relatively low rates of aggregation and are unlikely to aggregate co-translationally. Remarkably, such proteins exhibit higher folding rates compared to rapidly aggregating proteins, potentially implying that they aggregate after reaching their folded states. Furthermore, we find that a substantial fraction (~ 35%) of the proteome remain soluble at concentrations much higher than those found naturally, indicating a large margin of safety to tolerate gene expression changes. We show that high disorder content and low surface stickiness are major determinants of high solubility and are favored in abundant bacterial proteins. Overall, our study provides a global view of aggregation rates and hence solubility limits of proteins in a bacterial cell.

Deciphering Isoniazid Drug Resistance Mechanisms on Dimeric Mycobacterium tuberculosis KatG via Post-molecular Dynamics Analyses Including Combined Dynamic Residue Network Metrics

Resistance mutations in Mycobacterium tuberculosis (Mtb) catalase peroxidase protein (KatG), an essential enzyme in isoniazid (INH) activation, reduce the sensitivity of Mtb to first-line drugs, hence presenting challenges in tuberculosis (TB) management. Thus, understanding the mutational imposed resistance mechanisms remains of utmost importance in the quest to reduce the TB burden. Herein, effects of 11 high confidence mutations in the KatG structure and residue network communication patterns were determined using extensive computational approaches. Combined traditional post-molecular dynamics analysis and comparative essential dynamics revealed that the mutant proteins have significant loop flexibility around the heme binding pocket and enhanced asymmetric protomer behavior with respect to wild-type (WT) protein. Heme contact analysis between WT and mutant proteins identified a reduction to no contact between heme and residue His270, a covalent bond vital for the heme-enabled KatG catalytic activity. Betweenness centrality calculations showed large hub ensembles with new hubs especially around the binding cavity and expanded to the dimerization domain via interface in the mutant systems, providing possible compensatory allosteric communication paths for the active site as a result of the mutations which may destabilize the heme binding pocket and the loops in its vicinity. Additionally, an interesting observation came from Eigencentrality hubs, most of which are located in the C-terminal domain, indicating relevance of the domain in the protease functionality. Overall, our results provide insight toward the mechanisms involved in KatG-INH resistance in addition to identifying key regions in the enzyme functionality, which can be used for future drug design.

A particle size threshold governs diffusion and segregation of PAR-3 during cell polarization

The actomyosin cortex regulates the localization and function of proteins at the plasma membrane. Here, we study how membrane binding, cortical movements, and diffusion determine membrane protein distribution. In Caenorhabditis elegans zygotes, actomyosin flows transport PAR polarity proteins to establish the anterior-posterior axis. Oligomerization of a key scaffold protein, PAR-3, is required for polarization. PAR-3 oligomers are a heterogeneous population of many different sizes, and it remains unclear how oligomer size affects PAR-3 segregation. To address this question, we engineered PAR-3 to defined sizes. We report that PAR-3 trimers are necessary and sufficient for PAR-3 function during polarization and later embryo development. Quantitative analysis of PAR-3 diffusion shows that a threshold size of three subunits allows PAR-3 clusters to stably bind the membrane, where they are corralled and transported by the actomyosin cortex. Our study provides a quantitative model for size-dependent protein transportation of peripheral membrane proteins by cortical flow.

The actomyosin cytoskeleton is a major regulator of cellular organization. Chang and Dickinson develop protein-engineering and particle-tracking tools to study how clustered membrane-bound proteins are transported by actomyosin contractions in vivo. Data-driven modeling reveals how membrane binding, diffusion, and collisions with F-actin contribute to protein movement.

One for All, All for One: The Peculiar Dynamics of TNF-Receptor-Associated Factor (TRAF2) Subunits

TNF Receptor-Associated Factor 2 (TRAF2) is a homo-trimer belonging to the TNF-receptor-associated factor family (TRAFs). The TRAF2 oligomeric state is crucial for receptor binding, the interaction with other proteins (involved in the TNFR signaling), and the interaction with biological membranes. In this study, we present a computational analysis of the Molecular Dynamics of TRAF2-C (a truncated and soluble TRAF2 form) to identify patterns in the interactions between the three chains. We have performed a canonical analysis of the motion applied to molecular dynamics starting from the available crystal structure to identify correlated motions in TRAF2 dynamics. We have computed the displacement matrix, providing a frame-by-frame displacement for each residue in the dynamic. We provide the results in terms of the correlation matrix, which represents a detailed map of the correlated motions of residues. Eventually, we computed the so-called dynamical clusters, based on the Principal Component Analysis (PCA) of the motion (displacement) and the k means application on the first two principal components space. The results clearly indicate that, most of the time, two chains move in a strongly correlated motion, while the third chain follows a freer motion. A detailed analysis of the correlation matrix also shows that a few specific interface residues characterize the interaction of the more independent subunit with the other two. These findings suggest that the equilibrium between the trimer and the dissociated species (dimers and monomers) might be finely tuned by controlling a few critical residues in the protein quaternary structure, probably facilitating the regulation of oligomerization and dissociation in vivo.

A guide to designing photocontrol in proteins: methods, strategies and applications

Light is essential for various biochemical processes in all domains of life. In its presence certain proteins inside a cell are excited, which either stimulates or inhibits subsequent cellular processes. The artificial photocontrol of specifically proteins is of growing interest for the investigation of scientific questions on the organismal, cellular and molecular level as well as for the development of medicinal drugs or biocatalytic tools. For the targeted design of photocontrol in proteins, three major methods have been developed over the last decades, which employ either chemical engineering of small-molecule photosensitive effectors (photopharmacology), incorporation of photoactive non-canonical amino acids by genetic code expansion (photoxenoprotein engineering), or fusion with photoreactive biological modules (hybrid protein optogenetics). This review compares the different methods as well as their strategies and current applications for the light-regulation of proteins and provides background information useful for the implementation of each technique.