Simulated complexes formed from a set of postsynaptic proteins suggest a localised effect of a hypomorphic Shank mutation.

BACKGROUND: The postsynaptic density is an elaborate protein network beneath the postsynaptic membrane involved in the molecular processes underlying learning and memory. The postsynaptic density is built up from the same major proteins but its exact composition and organization differs between synapses. Mutations perturbing protein: protein interactions generally occurring in this network might lead to effects specific for cell types or processes, the understanding of which can be especially challenging. RESULTS: In this work we use systems biology-based modeling of protein complex distributions in a simplified set of major postsynaptic proteins to investigate the effect of a hypomorphic Shank mutation perturbing a single well-defined interaction. We use data sets with widely variable abundances of the constituent proteins. Our results suggest that the effect of the mutation is heavily dependent on the overall availability of all the protein components of the whole network and no trivial correspondence between the expression level of the directly affected proteins and overall complex distribution can be observed. CONCLUSIONS: Our results stress the importance of context-dependent interpretation of mutations. Even the weakening of a generally occurring protein: protein interaction might have well-defined effects, and these can not easily be predicted based only on the abundance of the proteins directly affected. Our results provide insight on how cell-specific effects can be exerted by a mutation perturbing a generally occurring interaction even when the wider interaction network is largely similar.

Diversity of synaptic protein complexes as a function of the abundance of their constituent proteins: A modeling approach.

The postsynaptic density (PSD) is a dense protein network playing a key role in information processing during learning and memory, and is also indicated in a number of neurological disorders. Efforts to characterize its detailed molecular organization are encumbered by the large variability of the abundance of its constituent proteins both spatially, in different brain areas, and temporally, during development, circadian rhythm, and also in response to various stimuli. In this study we ran large-scale stochastic simulations of protein binding events to predict the presence and distribution of PSD complexes. We simulated the interactions of seven major PSD proteins (NMDAR, AMPAR, PSD-95, SynGAP, GKAP, Shank3, Homer1) based on previously published, experimentally determined protein abundance data from 22 different brain areas and 42 patients (altogether 524 different simulations). Our results demonstrate that the relative ratio of the emerging protein complexes can be sensitive to even subtle changes in protein abundances and thus explicit simulations are invaluable to understand the relationships between protein availability and complex formation. Our observations are compatible with a scenario where larger supercomplexes are formed from available smaller binary and ternary associations of PSD proteins. Specifically, Homer1 and Shank3 self-association reactions substantially promote the emergence of very large protein complexes. The described simulations represent a first approximation to assess PSD complex abundance, and as such, use significant simplifications. Therefore, their direct biological relevance might be limited but we believe that the major qualitative findings can contribute to the understanding of the molecular features of the postsynapse.

Disentangling the complexity of low complexity proteins.

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs. SHORT ABSTRACT: There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.

Ensemble-Based Analysis of the Dynamic Allostery in the PSD-95 PDZ3 Domain in Relation to the General Variability of PDZ Structures.

PDZ domains are abundant interaction hubs found in a number of different proteins and they exhibit characteristic differences in their structure and ligand specificity. Their internal dynamics have been proposed to contribute to their biological activity via changes in conformational entropy upon ligand binding and allosteric modulation. Here we investigate dynamic structural ensembles of PDZ3 of the postsynaptic protein PSD-95, calculated based on previously published backbone and side-chain S2 order parameters. We show that there are distinct but interdependent structural rearrangements in PDZ3 upon ligand binding and the presence of the intramolecular allosteric modulator helix α3. We have also compared these rearrangements in PDZ1-2 of PSD-95 and the conformational diversity of an extended set of PDZ domains available in the PDB database. We conclude that although the opening-closing rearrangement, occurring upon ligand binding, is likely a general feature for all PDZ domains, the conformer redistribution upon ligand binding along this mode is domain-dependent. Our findings suggest that the structural and functional diversity of PDZ domains is accompanied by a diversity of internal motional modes and their interdependence.

Occurrence of Ordered and Disordered Structural Elements in Postsynaptic Proteins Supports Optimization for Interaction Diversity.

The human postsynaptic density is an elaborate network comprising thousands of proteins, playing a vital role in the molecular events of learning and the formation of memory. Despite our growing knowledge of specific proteins and their interactions, atomic-level details of their full three-dimensional structure and their rearrangements are mostly elusive. Advancements in structural bioinformatics enabled us to depict the characteristic features of proteins involved in different processes aiding neurotransmission. We show that postsynaptic protein-protein interactions are mediated through the delicate balance of intrinsically disordered regions and folded domains, and this duality is also imprinted in the amino acid sequence. We introduce Diversity of Potential Interactions (DPI), a structure and regulation based descriptor to assess the diversity of interactions. Our approach reveals that the postsynaptic proteome has its own characteristic features and these properties reliably discriminate them from other proteins of the human proteome. Our results suggest that postsynaptic proteins are especially susceptible to forming diverse interactions with each other, which might be key in the reorganization of the postsynaptic density (PSD) in molecular processes related to learning and memory.

Detection of single alpha-helices in large protein sequence sets using hardware acceleration.

Single alpha-helices (SAHs) are increasingly recognized as important structural and functional elements of proteins. Comprehensive identification of SAH segments in large protein datasets was largely hindered by the slow speed of the most restrictive prediction tool for their identification, FT_CHARGE on common hardware. We have previously implemented an FPGA-based version of this tool allowing fast analysis of a large number of sequences. Using this implementation, we have set up of a semi-automated pipeline capable of analyzing full UniProt releases in reasonable time and compiling monthly updates of a comprehensive database of SAH segments. Releases of this database, denoted CSAHDB, is available on the CSAHserver 2 website at csahserver.itk.ppke.hu. An overview of human SAH-containing sequences combined with a literature survey suggests specific roles of SAH segments in proteins involved in RNA-based regulation processes as well as cytoskeletal proteins, a number of which is also linked to the development and function of synapses.

A conserved charged single α-helix with a putative steric role in paraspeckle formation.

Paraspeckles are subnuclear particles involved in the regulation of mRNA expression. They are formed by the association of DBHS family proteins and the NEAT1 long noncoding RNA. Here, we show that a recently identified structural motif, the charged single α-helix, is largely conserved in the DBHS family. Based on the available structural data and a previously suggested multimerization scheme of DBHS proteins, we built a structural model of a (PSPC1/NONO)(n) multimer that might have relevance in paraspeckle formation. Our model contains an extended coiled-coil region that is followed by and partially overlaps with the predicted charged single α-helix. We suggest that the charged single α-helix can act as an elastic ruler governing the exact positioning of the dimeric core structures relative to each other during paraspeckle assembly along the NEAT1 noncoding RNA.

CoNSEnsX+ Webserver for the Analysis of Protein Structural Ensembles Reflecting Experimentally Determined Internal Dynamics.

Ensemble-based models of protein structure and dynamics reflecting experimental parameters are increasingly used to obtain deeper understanding of the role of dynamics in protein function. Such ensembles differ substantially from those routinely deposited in the PDB and, consequently, require specialized validation and analysis methodology. Here we describe our completely rewritten online validation tool, CoNSEnsX+, that offers a standardized way to assess the correspondence of such ensembles to experimental NMR parameters. The server provides a novel selection feature allowing a user-selectable set and weights of different parameters to be considered. This also offers an approximation of potential overfitting, namely, whether the number of conformers necessary to reflect experimental parameters can be reduced in the ensemble provided. The CoNSEnsX+ webserver is available at consensx.itk.ppke.hu . The corresponding Python source code is freely available on GitHub ( github.com/PPKE-Bioinf/consensx.itk.ppke.hu ).

"Invisible" conformers of an antifungal disulfide protein revealed by constrained cold and heat unfolding, CEST-NMR experiments, and molecular dynamics calculations.

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20-40 % at 298 K in a disulfide-rich protein. In addition, sensitive (15) N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR "dark matter". Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction.

Are proposed early genetic codes capable of encoding viable proteins?

Proteins are elaborate biopolymers balancing between contradicting intrinsic propensities to fold, aggregate, or remain disordered. Assessing their primary structural preferences observable without evolutionary optimization has been reinforced by the recent identification of de novo proteins that have emerged from previously non-coding sequences. In this paper we investigate structural preferences of hypothetical proteins translated from random DNA segments using the standard genetic code and three of its proposed evolutionarily predecessor models encoding 10, 6, and 4 amino acids, respectively. Our only main assumption is that the disorder, aggregation, and transmembrane helix predictions used are able to reflect the differences in the trends of the protein sets investigated. We found that the 10-residue code encodes proteins that resemble modern proteins in their predicted structural properties. All of the investigated early genetic codes give rise to proteins with enhanced disorder and diminished aggregation propensities. Our results suggest that an ancestral genetic code similar to the proposed 10-residue one is capable of encoding functionally diverse proteins but these might have existed under conditions different from today's common physiological ones. The existence of a protein functional repertoire for the investigated earlier stages which is quite distinct as it is today can be deduced from the presented results.

Charged single alpha-helices in proteomes revealed by a consensus prediction approach.

Charged single α-helices (CSAHs) constitute a recently recognized protein structural motif. Its presence and role is characterized in only a few proteins. To explore its general features, a comprehensive study is necessary. We have set up a consensus prediction method available as a web service (at http://csahserver.chem.elte.hu) and downloadable scripts capable of predicting CSAHs from protein sequences. Using our method, we have performed a comprehensive search on the UniProt database. We found that the motif is very rare but seems abundant in proteins involved in symbiosis and RNA binding/processing. Although there are related proteins with CSAH segments, the motif shows no deep conservation in protein families. We conclude that CSAH-containing proteins, although rare, are involved in many key biological processes. Their conservation pattern and prevalence in symbiosis-associated proteins suggest that they might be subjects of relatively rapid molecular evolution and thus can contribute to the emergence of novel functions.

Ensemble-based interpretations of NMR structural data to describe protein internal dynamics.

NMR spectroscopy is the leading technique to characterize protein internal dynamics at the atomic level and on multiple time scales. However, the structural interpretation of the observables obtained by various measurements is not always straightforward and in many cases dynamics-related parameters are only used to "decorate" static structural models without offering explicit description of conformational heterogeneity. To overcome such limitations, several computational techniques have been developed to generate ensemble-based representations of protein structure and dynamics with the use of NMR-derived data. An important common aspect of the methods is that NMR observables and derived parameters are interpreted as properties of the ensemble instead of individual conformers. The resulting ensembles reflect the experimentally determined internal mobility of proteins at a given time scale and can be used to understand the role of internal motions in biological processes at atomic detail. In this review we provide an overview of the calculation methods currently available and examples of biological insights obtained by the ensemble-based models of the proteins investigated.

Charged sequence motifs increase the propensity towards liquid-liquid phase separation.

Protein phase separation is a major governing factor in multiple cellular processes, such as RNA metabolism and those involving RNA-binding proteins. Despite many key observations, the exact structural characteristics of proteins involved in the phase separation process are still not fully deciphered. In this work, we show that proteins harbouring sequence regions with specific charged residue patterns are significantly associated with liquid-liquid phase separation. In particular, regions with repetitive arrays of alternating charges show the strongest association, whereas segments with generally high charge density and single α-helices also show detectable but weaker connections.

PSINDB: the postsynaptic protein-protein interaction database.

The postsynaptic region is the receiving part of the synapse comprising thousands of proteins forming an elaborate and dynamically changing network indispensable for the molecular mechanisms behind fundamental phenomena such as learning and memory. Despite the growing amount of information about individual protein-protein interactions (PPIs) in this network, these data are mostly scattered in the literature or stored in generic databases that are not designed to display aspects that are fundamental to the understanding of postsynaptic functions. To overcome these limitations, we collected postsynaptic PPIs complemented by a high amount of detailed structural and biological information and launched a freely available resource, the Postsynaptic Interaction Database (PSINDB), to make these data and annotations accessible. PSINDB includes tens of thousands of binding regions together with structural features, mediating and regulating the formation of PPIs, annotated with detailed experimental information about each interaction. PSINDB is expected to be useful for various aspects of molecular neurobiology research, from experimental design to network and systems biology-based modeling and analysis of changes in the protein network upon various stimuli. Database URL https://psindb.itk.ppke.hu/.

Resonance assignment of the Shank1 PDZ domain.

Shank proteins are among the most abundant and well-studied postsynaptic scaffold proteins. Their PDZ domain has unique characteristics as one of its loop regions flanking the ligand-binding site is uniquely long and has also been implicated in the formation of PDZ dimers. Here we report the initial characterization of the Shank1 PDZ domain by solution NMR spectroscopy. The assigned chemical shifts are largely consistent with the common features of PDZ domains in general and the available Shank PDZ crystal structures in particular. Our analysis suggests that under the conditions investigated, the domain is monomeric and the unique loop harbors a short helical segment, observed in only one of the known X-ray structures so far. Our work stresses the importance of solution-state investigations to fully decipher the functional relevance of the structural and dynamical features unique to Shank PDZ domains.

Directed Evolution-Driven Increase of Structural Plasticity Is a Prerequisite for Binding the Complement Lectin Pathway Blocking MASP-Inhibitor Peptides.

MASP-1 and MASP-2 are key activator proteases of the complement lectin pathway. The first specific mannose-binding lectin-associated serine protease (MASP) inhibitors had been developed from the 14-amino-acid sunflower trypsin inhibitor (SFTI) peptide by phage display, yielding SFTI-based MASP inhibitors, SFMIs. Here, we present the crystal structure of the MASP-1/SFMI1 complex that we analyzed in comparison to other existing MASP-1/2 structures. Rigidified backbone structure has long been accepted as a structural prerequisite for peptide inhibitors of proteases. We found that a hydrophobic cluster organized around the P2 Thr residue is essential for the structural stability of wild-type SFTI. We also found that the same P2 Thr prevents binding of the rigid SFTI-like peptides to the substrate-binding cleft of both MASPs as the cleft is partially blocked by large gatekeeper enzyme loops. Directed evolution removed this obstacle by replacing the P2 Thr with a Ser, providing the SFMIs with high-degree structural plasticity, which proved to be essential for MASP inhibition. To gain more insight into the structural criteria for SFMI-based MASP-2 inhibition, we systematically modified MASP-2-specific SFMI2 by capping its two termini and by replacing its disulfide bridge with varying length thioether linkers. By doing so, we also aimed to generate a versatile scaffold that is resistant to reducing environment and has increased stability in exopeptidase-containing biological environments. We found that the reduction-resistant disulfide-substituted l-2,3-diaminopropionic acid (Dap) variant possessed near-native potency. As MASP-2 is involved in the life-threatening thrombosis in COVID-19 patients, our synthetic, selective MASP-2 inhibitors could be relevant coronavirus drug candidates.

DIPEND: An Open-Source Pipeline to Generate Ensembles of Disordered Segments Using Neighbor-Dependent Backbone Preferences.

Ensemble-based structural modeling of flexible protein segments such as intrinsically disordered regions is a complex task often solved by selection of conformers from an initial pool based on their conformity to experimental data. However, the properties of the conformational pool are crucial, as the sampling of the conformational space should be sufficient and, in the optimal case, relatively uniform. In other words, the ideal sampling is both efficient and exhaustive. To achieve this, specialized tools are usually necessary, which might not be maintained in the long term, available on all platforms or flexible enough to be tweaked to individual needs. Here, we present an open-source and extendable pipeline to generate initial protein structure pools for use with selection-based tools to obtain ensemble models of flexible protein segments. Our method is implemented in Python and uses ChimeraX, Scwrl4, Gromacs and neighbor-dependent backbone distributions compiled and published previously by the Dunbrack lab. All these tools and data are publicly available and maintained. Our basic premise is that by using residue-specific, neighbor-dependent Ramachandran distributions, we can enhance the efficient exploration of the relevant region of the conformational space. We have also provided a straightforward way to bias the sampling towards specific conformations for selected residues by combining different conformational distributions. This allows the consideration of a priori known conformational preferences such as in the case of preformed structural elements. The open-source and modular nature of the pipeline allows easy adaptation for specific problems. We tested the pipeline on an intrinsically disordered segment of the protein Cd3ϵ and also a single-alpha helical (SAH) region by generating conformational pools and selecting ensembles matching experimental data using the CoNSEnsX+ server.

CoNSEnsX: an ensemble view of protein structures and NMR-derived experimental data.

BACKGROUND: In conjunction with the recognition of the functional role of internal dynamics of proteins at various timescales, there is an emerging use of dynamic structural ensembles instead of individual conformers. These ensembles are usually substantially more diverse than conventional NMR ensembles and eliminate the expectation that a single conformer should fulfill all NMR parameters originating from 10(16) - 10(17) molecules in the sample tube. Thus, the accuracy of dynamic conformational ensembles should be evaluated differently to that of single conformers. RESULTS: We constructed the web application CoNSEnsX (Consistency of NMR-derived Structural Ensembles with eXperimental data) allowing fast, simple and convenient assessment of the correspondence of the ensemble as a whole with diverse independent NMR parameters available. We have chosen different ensembles of three proteins, human ubiquitin, a small protease inhibitor and a disordered subunit of cGMP phosphodiesterase 5/6 for detailed evaluation and demonstration of the capabilities of the CoNSEnsX approach. CONCLUSIONS: Our results present a new conceptual method for the evaluation of dynamic conformational ensembles resulting from NMR structure determination. The designed CoNSEnsX approach gives a complete evaluation of these ensembles and is freely available as a web service at http://consensx.chem.elte.hu.

A redesigned genetic code for selective labeling in protein NMR.

The outline of a universal cell-free translation system capable of site-specific insertion of any types of labeled amino acids is presented. The system could be an invaluable tool for NMR spectroscopy by making the exclusive and exact labeling of the segments of interest possible. Although the development of such a system requires considerable efforts and can not be expected to be available in the next few years, we argue that recent findings concerning the translation apparatus provide clues for overcoming the major difficulties that might arise. We propose a genetic code and a reactor expected to fulfill the specific requirements. Importantly, incomplete systems could also be useful to study selected functional aspects of a number of proteins, examples of which are also given.

Structure and Oxidative Folding of AAI, the Major Alfa-Amylase Inhibitor From Amaranth Seeds.

AAI, the major alpha-amylase inhibitor (AAI) present in the seeds of the Mexican crop plant Amaranthus hypocondriacus is a 32-residue-long polypeptide with three disulfide bridges. Its structure is most closely related to the plant amylase inhibitor subfamily of knottins characterized by a topological knot formed by one disulfide bridge threading through a loop formed by the peptide chain as well as a short three-stranded beta sandwich core. AAI is specific against insect amylases and does not act on corresponding human or mammalian enzymes. It was found that the oxidative folding of AAI seems to follow a hirudine-like pathway with many non-native intermediates, but notably it proceeds through a major folding intermediate (MFI) that contains a vicinal disulfide bridge. Based on a review of the pertinent literature, the known vicinal disulfides in native proteins as well as well as the network of disulfide interchanges, we propose that MFI is a kinetic trap corresponding to a compact molten globule-like state which constrains the peptide chain to a smaller number of conformations that in turn can be rapidly funneled toward the native state.