Hubs and Bottlenecks in Protein-Protein Interaction Networks

Protein-protein interaction networks (PPINs) represent the physical interactions among proteins in a cell. These interactions are critical in all cellular processes, including signal transduction, metabolic regulation, and gene expression. In PPINs, centrality measures are widely used to identify the most critical nodes. The two most commonly used centrality measures in networks are degree and betweenness centralities. Degree centrality is the number of connections a node has in the network, and betweenness centrality is the measure of the extent to which a node lies on the shortest paths between pairs of other nodes in the network. In PPINs, proteins with high degree and betweenness centrality are referred to as hubs and bottlenecks respectively. Hubs and bottlenecks are topologically and functionally essential proteins that play crucial roles in maintaining the network's structure and function. This article comprehensively reviews essential literature on hubs and bottlenecks, including their properties and functions.

Free-Docking and Template-Based Docking: Physics Versus Knowledge-Based Docking

Docking methods can be used to predict the orientations of two or more molecules with respect of each other using a plethora of various algorithms, which can be based on the physics of interactions or can use information from databases and templates. The usability of these approaches depends on the type and size of the molecules, whose relative orientation will be estimated. The two most important limitations are (i) the computational cost of the prediction and (ii) the availability of the structural information for similar complexes. In general, if there is enough information about similar systems, knowledge-based and template-based methods can significantly reduce the computational cost while providing high accuracy of the prediction. However, if the information about the system topology and interactions between its partners is scarce, physics-based methods are more reliable or even the only choice. In this chapter, knowledge-, template-, and physics-based methods will be compared and briefly discussed providing examples of their usability with a special emphasis on physics-based protein-protein, protein-peptide, and protein-fullerene docking in the UNRES coarse-grained model.

Distinct or Overlapping Areas of Mitochondrial Thioredoxin 2 May Be Used for Its Covalent and Strong Non-Covalent Interactions with Protein Ligands

In silico approaches were employed to examine the characteristics of interactions between human mitochondrial thioredoxin 2 (HsTrx2) and its 38 previously identified mitochondrial protein ligands. All interactions appeared driven mainly by electrostatic forces. The statistically significant residues of HsTrx2 for interactions were characterized as "contact hot spots". Since these were identical/adjacent to putative thermodynamic hot spots, an energy network approach identified their neighbors to highlight possible contact interfaces. Three distinct areas for binding emerged: (i) one around the active site for covalent interactions, (ii) another antipodal to the active site for strong non-covalent interactions, and (iii) a third area involved in both kinds of interactions. The contact interfaces of HsTrx2 were projected as respective interfaces for Escherichia coli Trx1 (EcoTrx1), 2, and HsTrx1. Comparison of the interfaces and contact hot spots of HsTrx2 to the contact residues of EcoTx1 and HsTrx1 from existing crystal complexes with protein ligands supported the hypothesis, except for a part of the cleft/groove adjacent to Trp30 preceding the active site. The outcomes of this study raise the possibility for the rational design of selective inhibitors for the interactions of HsTrx2 with specific protein ligands without affecting the entirety of the functions of the Trx system.

Analysis of protein-protein interface with incorporating low-frequency molecular interactions in molecular dynamics simulation

Protein-protein interactions are vital for various biological processes such as immune reaction, signal transduction, and viral infection. Molecular Dynamics (MD) simulation is a powerful tool for analyzing non-covalent interactions between two protein molecules. In general, MD simulation studies on the protein-protein interface have focused on the analysis of major and frequent molecular interactions. In this study, we demonstrate that minor interactions with low-frequency need to be incorporated to analyze the molecular interactions in the protein-protein interface more efficiently using the complex of SARS-CoV2-RBD and ACE2 receptor as a model system. It was observed that the dominance of interactions in the MD-simulated structures didn't directly correlate with the interactions in the experimentally determined structure. The interactions from the experimentally determined structure could be reproduced better in the ensemble of MD simulated structures by including the less frequent interactions compared to the norm of choosing only highly frequent interactions. Residue Interaction Networks (RINs) analysis also showed that the critical residues in the protein-protein interface could be more efficiently identified by incorporating low-frequency interactions in MD simulation. It is expected that the approach proposed in this study can be a new way of studying protein-protein interaction through MD simulation.

Possibilities of Using De Novo Design for Generating Diverse Functional Food Enzymes

Food enzymes have an important role in the improvement of certain food characteristics, such as texture improvement, elimination of toxins and allergens, production of carbohydrates, enhancing flavor/appearance characteristics. Recently, along with the development of artificial meats, food enzymes have been employed to achieve more diverse functions, especially in converting non-edible biomass to delicious foods. Reported food enzyme modifications for specific applications have highlighted the significance of enzyme engineering. However, using direct evolution or rational design showed inherent limitations due to the mutation rates, which made it difficult to satisfy the stability or specific activity needs for certain applications. Generating functional enzymes using de novo design, which highly assembles naturally existing enzymes, provides potential solutions for screening desired enzymes. Here, we describe the functions and applications of food enzymes to introduce the need for food enzymes engineering. To illustrate the possibilities of using de novo design for generating diverse functional proteins, we reviewed protein modelling and de novo design methods and their implementations. The future directions for adding structural data for de novo design model training, acquiring diversified training data, and investigating the relationship between enzyme-substrate binding and activity were highlighted as challenges to overcome for the de novo design of food enzymes.

Exploiting Sequence-Dependent Rotamer Information in Global Optimization of Proteins

Rotamers, namely amino acid side chain conformations common to many different peptides, can be compiled into libraries. These rotamer libraries are used in protein modeling, where the limited conformational space occupied by amino acid side chains is exploited. Here, we construct a sequence-dependent rotamer library from simulations of all possible tripeptides, which provides rotameric states dependent on adjacent amino acids. We observe significant sensitivity of rotamer populations to sequence and find that the library is successful in locating side chain conformations present in crystal structures. The library is designed for applications with basin-hopping global optimization, where we use it to propose moves in conformational space. The addition of rotamer moves significantly increases the efficiency of protein structure prediction within this framework, and we determine parameters to optimize efficiency.

Integrated structure-based protein interface prediction

Background

Identifying protein interfaces can inform how proteins interact with their binding partners, uncover the regulatory mechanisms that control biological functions and guide the development of novel therapeutic agents. A variety of computational approaches have been developed for predicting a protein’s interfacial residues from its known sequence and structure. Methods using the known three-dimensional structures of proteins can be template-based or template-free. Template-based methods have limited success in predicting interfaces when homologues with known complex structures are not available to use as templates. The prediction performance of template-free methods that only rely only upon proteins’ intrinsic properties is limited by the amount of biologically relevant features that can be included in an interface prediction model.

Results

We describe the development of an integrated method for protein interface prediction (ISPIP) to explore the hypothesis that the efficacy of a computational prediction method of protein binding sites can be enhanced by using a combination of methods that rely on orthogonal structure-based properties of a query protein, combining and balancing both template-free and template-based features. ISPIP is a method that integrates these approaches through simple linear or logistic regression models and more complex decision tree models. On a diverse test set of 156 query proteins, ISPIP outperforms each of its individual classifiers in identifying protein binding interfaces.

Conclusions

The integrated method captures the best performance of individual classifiers and delivers an improved interface prediction. The method is robust and performs well even when one of the individual classifiers performs poorly on a particular query protein. This work demonstrates that integrating orthogonal methods that depend on different structural properties of proteins performs better at interface prediction than any individual classifier alone.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04852-2.

A recurring packing contact in crystals of InlB pinpoints functional binding sites in the internalin domain and the B repeat

InlB, a bacterial agonist of the human receptor tyrosine kinase MET, consists of an N-terminal internalin domain, a central B repeat and three C-terminal GW domains. In all previous structures of full-length InlB or an InlB construct lacking the GW domains (InlB392), there was no interpretable electron density for the B repeat. Here, three InlB392 crystal structures in which the B repeat is resolved are described. These are the first structures to reveal the relative orientation of the internalin domain and the B repeat. A wild-type structure and two structures of the T332E variant together contain five crystallographically independent molecules. Surprisingly, the threonine-to-glutamate substitution in the B repeat substantially improved the crystallization propensity and crystal quality of the T332E variant. The internalin domain and B repeat are quite rigid internally, but are flexibly linked to each other. The new structures show that inter-domain flexibility is the most likely cause of the missing electron density for the B repeat in previous InlB structures. A potential binding groove between B-repeat strand β2 and an adjacent loop forms an important crystal contact in all five crystallographically independent chains. This region may represent a hydrophobic `sticky patch' that supports protein–protein interactions. This assumption agrees with the previous finding that all known inactivating point mutations in the B repeat lie within strand β2. The groove formed by strand β2 and the adjacent loop may thus represent a functionally important protein–protein interaction site in the B repeat.

Residue-Residue Interaction Prediction via Stacked Meta-Learning

Protein-protein interactions (PPIs) are the basis of most biological functions determined by residue-residue interactions (RRIs). Predicting residue pairs responsible for the interaction is crucial for understanding the cause of a disease and drug design. Computational approaches that considered inexpensive and faster solutions for RRI prediction have been widely used to predict protein interfaces for further analysis. This study presents RRI-Meta, an ensemble meta-learning-based method for RRI prediction. Its hierarchical learning structure comprises four base classifiers and one meta-classifier to integrate predictive strengths from different classifiers. It considers multiple feature types, including sequence-, structure-, and neighbor-based features, for characterizing other properties of a residue interaction environment to better distinguish between noninteracting and interacting residues. We conducted the same experiments using the same data as previously reported in the literature to demonstrate RRI-Meta's performance. Experimental results show that RRI-Meta is superior to several current prediction tools. Additionally, to analyze the factors that affect the performance of RRI-Meta, we conducted a comparative case study using different protein complexes.

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MALTIR) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88TIR). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MALTIR. We demonstrate via mutagenesis that the MyD88TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88TIR. Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

Cryo-EM as a tool to study bacterial efflux systems and the membrane proteome

Antibiotic resistance is an emerging threat to global health. Current treatment regimens for these types of bacterial infections are becoming increasingly inadequate. Thus, new innovative technologies are needed to help identify and characterize novel drugs and drug targets which are critical in order to combat multidrug-resistant bacterial strains. Bacterial efflux systems have emerged as an attractive target for drug design, as blocking their export function significantly increases the potency of administered antibiotics. However, in order to develop potent and tolerable efflux pump inhibitors with high efficacy, detailed structural information is required for both the apo- and substrate-bound forms of these membrane proteins. The emergence of cryo-electron microscopy (cryo-EM) has greatly advanced the field of membrane protein structural biology. It has significantly enhanced the ability to solve large multi-protein complexes as well as extract meaningful data from a heterogeneous sample, such as identification of several assembly states of the bacterial ribosome, from a single data set. This technique can be expanded to solve the structures of substrate-bound efflux pumps and entire efflux systems from previously unusable membrane protein sample preparations. Subsequently, cryo-EM combined with other biophysical techniques has the potential to markedly advance the field of membrane protein structural biology. The ability to discern complete transport machineries, enzymatic signal transduction pathways, and other membrane-associated complexes will help us fully understand the complexities of the membrane proteome.

Exploring Manually Curated Annotations of Intrinsically Disordered Proteins with DisProt

DisProt is the major repository of manually curated data for intrinsically disordered proteins collected from the literature. Although lacking a stable tertiary structure under physiological conditions, intrinsically disordered proteins carry out a plethora of biological functions, some of them directly arising from their flexible nature. A growing number of scientific studies have been published during the last few decades in an effort to shed light on their unstructured state, their binding modes, and their functions. DisProt makes use of a team of expert biocurators to provide up-to-date annotations of intrinsically disordered proteins from the literature, making them available to the scientific community. Here we present a comprehensive description on how to use DisProt in different contexts and provide a detailed explanation of how to explore and interpret manually curated annotations of intrinsically disordered proteins. We describe how to search DisProt annotations, using both the web interface and the API for programmatic access. Finally, we explain how to visualize and interpret a DisProt entry, p53, a widely studied protein characterized by the presence of unstructured N-terminal and C-terminal regions. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Performing a search in DisProt Support Protocol 1: Downloading options Support Protocol 2: Programmatic access with DisProt REST API Basic Protocol 2: Visualizing and interpreting DisProt entries: the p53 use case Basic Protocol 3: Providing feedback and submitting new intrinsic disorder-related data.

Probing Specificity of Protein-Protein Interactions with Chiral Plasmonic Nanostructures

Protein-protein interactions (PPIs) play a pivotal role in many biological processes. Discriminating functionally important well-defined protein-protein complexes formed by specific interactions from random aggregates produced by nonspecific interactions is therefore a critical capability. While there are many techniques which enable rapid screening of binding affinities in PPIs, there is no generic spectroscopic phenomenon which provides rapid characterization of the structure of protein-protein complexes. In this study we show that chiral plasmonic fields probe the structural order and hence the level of PPI specificity in a model antibody-antigen system. Using surface-immobilized Fab' fragments of polyclonal rabbit IgG antibodies with high specificity for bovine serum albumin (BSA), we show that chiral plasmonic fields can discriminate between a structurally anisotropic ensemble of BSA-Fab' complexes and random ovalbumin (OVA)-Fab' aggregates, demonstrating their potential as the basis of a useful proteomic technology for the initial rapid high-throughput screening of PPIs.

In silico prediction of protein flexibility with local structure approach

Flexibility is an intrinsic essential feature of protein structures, directly linked to their functions. To this day, most of the prediction methods use the crystallographic data (namely B-factors) as the only indicator of protein's inner flexibility and predicts them as rigid or flexible. PredyFlexy stands differently from other approaches as it relies on the definition of protein flexibility (i) not only taken from crystallographic data, but also (ii) from Root Mean Square Fluctuation (RMSFs) observed in Molecular Dynamics simulations. It also uses a specific representation of protein structures, named Long Structural Prototypes (LSPs). From Position-Specific Scoring Matrix, the 120 LSPs are predicted with a good accuracy and directly used to predict (i) the protein flexibility in three categories (flexible, intermediate and rigid), (ii) the normalized B-factors, (iii) the normalized RMSFs, and (iv) a confidence index. Prediction accuracy among these three classes is equivalent to the best two class prediction methods, while the normalized B-factors and normalized RMSFs have a good correlation with experimental and in silico values. Thus, PredyFlexy is a unique approach, which is of major utility for the scientific community. It support parallelization features and can be run on a local cluster using multiple cores.

Protein painting, an optimized MS-based technique, reveals functionally relevant interfaces of the PD-1/PD-L1 complex and the YAP2/ZO-1 complex

Protein-protein interactions lie at the heart of many biological processes and therefore represent promising drug targets. Despite this opportunity, identification of protein-protein interfaces remains challenging. We have previously developed a method that relies on coating protein surfaces with small-molecule dyes to discriminate between solvent-accessible protein surfaces and hidden interface regions. Dye-bound, solvent-accessible protein regions resist trypsin digestion, whereas hidden interface regions are revealed by denaturation and sequenced by MS. The small-molecule dyes bind promiscuously and with high affinity, but their binding mechanism is unknown. Here, we report on the optimization of a novel dye probe used in protein painting, Fast Blue B + naphthionic acid, and show that its affinity for proteins strongly depends on hydrophobic moieties that we call here "hydrophobic clamps." We demonstrate the utility of this probe by sequencing the protein-protein interaction regions between the Hippo pathway protein Yes-associated protein 2 (YAP2) and tight junction protein 1 (TJP1 or ZO-1), uncovering interactions via the known binding domain as well as ZO-1's MAGUK domain and YAP's N-terminal proline-rich domain. Additionally, we demonstrate how residues predicted by protein painting are present exclusively in the complex interface and how these residues may guide the development of peptide inhibitors using a case study of programmed cell death protein 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1). Inhibitors designed around the PD-1/PD-L1 interface regions identified via protein painting effectively disrupted complex formation, with the most potent inhibitor having an IC₅₀ of 5 μm.

Rational modulator design by exploitation of protein-protein complex structures

The horizon of drug discovery is currently expanding to target and modulate protein-protein interactions (PPIs) in globular proteins and intrinsically disordered proteins that are involved in various diseases. To either interrupt or stabilize PPIs, the 3D structure of target protein-protein (or protein-peptide) complexes can be exploited to rationally design PPI modulators (inhibitors or stabilizers) through structure-based molecular design. In this review, we present an overview of experimental and computational methods that can be used to determine 3D structures of protein-protein complexes. Several approaches including rational and in silico methods that can be applied to design peptides, peptidomimetics and small compounds by utilization of determined 3D protein-protein/peptide complexes are summarized and illustrated.

Integrating co-evolutionary signals and other properties of residue pairs to distinguish biological interfaces from crystal contacts

It remains challenging to accurately discriminate between biological and crystal interfaces. Most existing analyses and algorithms focused on the features derived from a single side of the interface. However, less attention has been paid to the properties of residue pairs across protein interfaces. To address this problem, we defined a novel co-evolutionary feature for homodimers through integrating direct coupling analysis and image processing techniques. The residue pairs across biological homodimeric interfaces were significantly enriched in co-evolving residues compared to those across crystal contacts, resulting in a promising classification accuracy with area under the curves (AUCs) of >0.85. Considering the availability of co-evolutionary feature, we also designed other residue pair based features that were useful for both homodimers and heterodimers. The most informative residue pairs were identified to reflect the interaction preferences across protein interfaces. Regarding the other extant properties, we designed the new descriptors at the interface residue level as well as at the pairwise contact level. Extensive validation showed that these single properties can be used to identify biological interfaces with AUCs ranging from 0.60 to 0.88. By integrating co-evolutionary feature with other residue pair based properties, our final prediction model output excellent performance with AUCs of >0.91 on different datasets. Compared to existing methods, our algorithm not only yielded better or comparable results but also provided complementary information. An easy-to-use web server is freely accessible at http://liulab.hzau.edu.cn/RPAIAnalyst.

Computational Methods for Predicting Protein-Protein Interactions Using Various Protein Features

Understanding protein-protein interactions (PPIs) in a cell is essential for learning protein functions, pathways, and mechanism of diseases. PPIs are also important targets for developing drugs. Experimental methods, both small-scale and large-scale, have identified PPIs in several model organisms. However, results cover only a part of PPIs of organisms; moreover, there are many organisms whose PPIs have not yet been investigated. To complement experimental methods, many computational methods have been developed that predict PPIs from various characteristics of proteins. Here we provide an overview of literature reports to classify computational PPI prediction methods that consider different features of proteins, including protein sequence, genomes, protein structure, function, PPI network topology, and those which integrate multiple methods. © 2018 by John Wiley & Sons, Inc.

Alternative dimerization interfaces in the glucocorticoid receptor-α ligand binding domain

BACKGROUND

Nuclear hormone receptors (NRs) constitute a large family of multi-domain ligand-activated transcription factors. Dimerization is essential for their regulation, and both DNA binding domain (DBD) and ligand binding domain (LBD) are implicated in dimerization. Intriguingly, the glucocorticoid receptor-α (GRα) presents a DBD dimeric architecture similar to that of the homologous estrogen receptor-α (ERα), but an atypical dimeric architecture for the LBD. The physiological relevance of the proposed GRα LBD dimer is a subject of debate.

METHODS

We analyzed all GRα LBD homodimers observed in crystals using an energetic analysis based on the PISA and on the MM/PBSA methods and a sequence conservation analysis, using the ERα LBD dimer as a reference point.

RESULTS

Several dimeric assemblies were observed for GRα LBD. The assembly generally taken to be physiologically relevant showed weak binding free energy and no significant residue conservation at the contact interface, while an alternative homodimer mediated by both helix 9 and C-terminal residues showed significant binding free energy and residue conservation. However, none of the GRα LBD assemblies found in crystals are as stable or conserved as the canonical ERα LBD dimer. GRα C-terminal sequence (F-domain) forms a steric obstacle to the canonical dimer assembly in all available structures.

CONCLUSIONS

Our analysis calls for a re-examination of the currently accepted GRα homodimer structure and experimental investigations of the alternative architectures.

GENERAL SIGNIFICANCE

This work questions the validity of the currently accepted architecture. This has implications for interpreting physiological data and for therapeutic design pertaining to glucocorticoid research.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction

Background

The correct determination of protein–protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task.

Results

In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein–Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI).

Conclusions

The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2043-3) contains supplementary material, which is available to authorized users.

Engineered Cross-Linking to Study the Pore Architecture of the CRAC Channel

ORAI1 constitutes the pore-forming subunit of the calcium release-activated calcium (CRAC) channel, a prototypical store-operated channel that is essential for the activation of cells of the immune system. Here we describe a convenient yet powerful cross-linking approach to examine the pore architecture of CRAC channels using ORAI1 proteins engineered to contain one or two cysteine residues. The generalizable cross-linking in situ approach can also be readily extended to study other integral membrane proteins expressed in various types of cells.

Multiple functional self-association interfaces in plant TIR domains

The self-association of Toll/interleukin-1 receptor/resistance protein (TIR) domains has been implicated in signaling in plant and animal immunity receptors. Structure-based studies identified different TIR-domain dimerization interfaces required for signaling of the plant nucleotide-binding oligomerization domain-like receptors (NLRs) L6 from flax and disease resistance protein RPS4 from Arabidopsis Here we show that the crystal structure of the TIR domain from the Arabidopsis NLR suppressor of npr1-1, constitutive 1 (SNC1) contains both an L6-like interface involving helices αD and αE (DE interface) and an RPS4-like interface involving helices αA and αE (AE interface). Mutations in either the AE- or DE-interface region disrupt cell-death signaling activity of SNC1, L6, and RPS4 TIR domains and full-length L6 and RPS4. Self-association of L6 and RPS4 TIR domains is affected by mutations in either region, whereas only AE-interface mutations affect SNC1 TIR-domain self-association. We further show two similar interfaces in the crystal structure of the TIR domain from the Arabidopsis NLR recognition of Peronospora parasitica 1 (RPP1). These data demonstrate that both the AE and DE self-association interfaces are simultaneously required for self-association and cell-death signaling in diverse plant NLRs.

Identification and validation of small molecule modulators of the NusB-NusE interaction

Formation of highly possessive antitermination complexes is crucial for the efficient transcription of stable RNA in all bacteria. A key step in the formation of these complexes is the protein-protein interaction (PPI) between N-utilisation substances (Nus) B and E and thus this PPI offers a novel target for a new antibiotic class. A pharmacophore developed via a secondary structure epitope approach was utilised to perform an in silico screen of the mini-Maybridge library (56,000 compounds) which identified 25 hits of which five compounds were synthetically tractable leads. Here we report the synthesis of these five leads and their biological evaluation as potential inhibitors of the NusB-NusE PPI. Two chemically diverse scaffolds were identified to be low micro molar potent PPI inhibitors, with compound (4,6-bis(2',4',3.4 tetramethoxyphenyl))pyrimidine-2-sulphonamido-N-4-acetamide 1 and N,N'-[1,4-butanediylbis(oxy-4,1-phenylene)]bis(N-ethyl)urea 3 exhibiting IC₅₀ values of 6.1μM and 19.8μM, respectively. These inhibitors were also shown to be moderate inhibitors of Gram-positive Bacillus subtilis and Gram-negative Escherichia coli growth.

Towards the structure of the TIR-domain signalosome

TIR (Toll/interleukin-1 receptor/resistance protein) domains feature in animal, plant and bacterial proteins involved in innate immunity pathways and associated processes. They function through protein:protein interactions, in particular self-association and homotypic association with other TIR domains. Structures of TIR domains from all phyla have been determined, but common association modes have only emerged for plant and bacterial TIR domains, and not for mammalian TIR domains. Numerous attempts involving hybrid approaches, which have combined structural, computational, mutagenesis and biophysical data, have failed to converge onto common models of how these domains associate and function. We propose that the available data can be reconciled in the context of higher-order assembly formation, and that TIR domains function through signaling by cooperative assembly formation (SCAF).

New Dynamic Rotamer Libraries: Data-Driven Analysis of Side-Chain Conformational Propensities

Most rotamer libraries are generated from subsets of the PDB and do not fully represent the conformational scope of protein side chains. Previous attempts to rectify this sparse coverage of conformational space have involved application of weighting and smoothing functions. We resolve these limitations by using physics-based molecular dynamics simulations to determine more accurate frequencies of rotameric states. This work forms part of our Dynameomics initiative and uses a set of 807 proteins selected to represent 97% of known autonomous protein folds, thereby eliminating the bias toward common topologies found within the PDB. Our Dynameomics derived rotamer libraries encompass 4.8 × 10(9) rotamers, sampled from at least 51,000 occurrences of each of 93,642 residues. Here, we provide a backbone-dependent rotamer library, based on secondary structure ϕ/ψ regions, and an update to our 2011 backbone-independent library that addresses the doubling of our dataset since its original publication.

Structure and Function of the TIR Domain from the Grape NLR Protein RPV1

The N-terminal Toll/interleukin-1 receptor/resistance protein (TIR) domain has been shown to be both necessary and sufficient for defense signaling in the model plants flax and Arabidopsis. In examples from these organisms, TIR domain self-association is required for signaling function, albeit through distinct interfaces. Here, we investigate these properties in the TIR domain containing resistance protein RPV1 from the wild grapevine Muscadinia rotundifolia. The RPV1 TIR domain, without additional flanking sequence present, is autoactive when transiently expressed in tobacco, demonstrating that the TIR domain alone is capable of cell-death signaling. We determined the crystal structure of the RPV1 TIR domain at 2.3 Å resolution. In the crystals, the RPV1 TIR domain forms a dimer, mediated predominantly through residues in the αA and αE helices ("AE" interface). This interface is shared with the interface discovered in the dimeric complex of the TIR domains from the Arabidopsis RPS4/RRS1 resistance protein pair. We show that surface-exposed residues in the AE interface that mediate the dimer interaction in the crystals are highly conserved among plant TIR domain-containing proteins. While we were unable to demonstrate self-association of the RPV1 TIR domain in solution or using yeast 2-hybrid, mutations of surface-exposed residues in the AE interface prevent the cell-death autoactive phenotype. In addition, mutation of residues known to be important in the cell-death signaling function of the flax L6 TIR domain were also shown to be required for RPV1 TIR domain mediated cell-death. Our data demonstrate that multiple TIR domain surfaces control the cell-death function of the RPV1 TIR domain and we suggest that the conserved AE interface may have a general function in TIR-NLR signaling.

Understanding the fabric of protein crystals: computational classification of biological interfaces and crystal contacts

Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein–protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein–protein docking.

Supplementary information: Supplementary data are available at Bioinformatics online.

Contact:guido.capitani@psi.ch

SdsA polymorph isolation and improvement of their crystal quality using nonconventional crystallization techniques

SdsA, a sodium dodecyl sulfate hydrolase, fromPseudomonas aeruginosawas crystallized in three different crystal polymorphs and their three-dimensional structure was determined. The different polymorphs present different crystal packing habits. One of the polymorphs suggests the existence of a tetramer, an oligomeric state not observed previously, while the crystal packing of the remaining two polymorphs obstructs the active site entrance but stabilizes flexible regions of the protein. Nonconventional crystallization methods that minimize convection, such as counterdiffusion in polyvinyl alcohol gel coupled with the influence of a 500 MHz (10.2 T) magnetic field, were necessary to isolate the poorest diffracting polymorph and increase its internal order to determine its structure by X-ray diffraction. The results obtained show the effectiveness of nonconventional crystallographic methods to isolate different crystal polymorphs.

A structural dissection of large protein-protein crystal packing contacts

With the rapid increase in crystal structures of protein-protein complexes deposited in the Protein Data Bank (PDB), more and more crystal contacts have been shown to have similar or even larger interface areas than biological interfaces. However, little attention has been paid to these large crystal packing contacts and their structural principles remain unknown. To address this issue, we used a comparative feature analysis to analyze the geometric and physicochemical properties of large crystal packing contacts by comparing two types of specific protein-protein interactions (PPIs), weak transient complexes and permanent homodimers. Our results show that although large crystal packing contacts have a similar interface area and contact size as permanent homodimers, they tend to be more planar, loosely packed and less hydrophobic than permanent homodimers and cannot form a central core region that is fully buried during interaction. However, the properties of large crystal packing contacts, except for the interface area and contact size, more closely resemble those of weak transient complexes. The large overlap between biological and large crystal packing contacts indicates that interface properties are not efficient indicators for classification of biological interfaces from large crystal packing contacts and finding other specific features urgently needed.

A linker strategy for the production and crystallization of Toll/interleukin-1 receptor/resistance protein domain complexes

Structural characterization of protein-protein complexes is required to fully understand biological processes. However, such studies can be difficult, particularly when the interactions are transient. In some cases, the covalent linking of weakly interacting binding partners has been shown to facilitate structural studies. Here, we used this approach to investigate, by X-ray crystallography, the interactions between TIR (Toll/interleukin-1 receptor/resistance protein) domains from proteins involved in plant and animal innate immunity. Combinations of TIR domains known to interact were covalently attached using short glycine- and serine-rich linkers. This approach enabled the production of a number of TIR-TIR domain complexes in soluble form, facilitating crystallization studies. Crystallization of two of the tested combinations was achieved. Furthermore, production in soluble form was achieved for another two combinations, where this was not possible for individual proteins. Our results demonstrate that the linker strategy can aid in the structural studies of TIR domains. Similarly, this approach has potential for improving protein production and facilitating structural studies of other protein-protein interaction domains.

Structural insight into proteorhodopsin oligomers

Oligomerization has important functional implications for many membrane proteins. However, obtaining structural insight into oligomeric assemblies is challenging, as they are large and resist crystallization. We focus on proteorhodopsin (PR), a protein with seven transmembrane α-helices that was found to assemble to hexamers in densely packed lipid membrane, or detergent-solubilized environments. Yet, the structural organization and the subunit interface of these PR oligomers were unknown. We used site-directed spin-labeling together with electron spin-resonance lineshape and Overhauser dynamic nuclear polarization analysis to construct a model for the specific orientation of PR subunits within the hexameric complex. We found intersubunit distances to average 16 Å between neighboring 55 residues and that residues 177 are >20 Å apart from each other. These distance constraints show that PR has a defined and radial orientation within a hexamer, with the 55-site of the A-B loop facing the hexamer core and the 177-site of the E-F loop facing the hexamer exterior. Dynamic nuclear polarization measurements of the local solvent dynamics complement the electron spin-resonance-based distance analysis, by resolving whether protein surfaces at positions 55, 58, and 177 are exposed to solvent, or covered by protein-protein or protein-detergent contacts.

Roles for focal adhesion kinase (FAK) in blastomere abscission and vesicle trafficking during cleavage in the sea urchin embryo

Is focal adhesion kinase (FAK) needed for embryonic cleavage? We find that FAK is expressed during early cleavage divisions of sea urchin embryos as determined by polyclonal antibodies to the Lytechinus variegatus protein. FAK is absent in eggs and zygotes and then cycles in abundance during the first cleavages after fertilization. It is maximal at anaphase, similar to the destruction and synthesis of cyclin proteins. To investigate whether FAK is needed during early cleavage, we interfered with its function by microinjecting eggs with anti-FAK antibodies or with FAK antisense morpholino oligonucleotides. Both treatments led to regression of the cleavage furrow. FAK knockdown with antibodies or morpholino oligonucleotides also resulted in an over-accumulation of endocytic vesicles. Thus, FAK could be restricting endocytosis or increasing exocytosis in localized areas important for abscission. FAK appears to be necessary for successful cleavage. These results are the first to document a functional role for FAK during embryonic cleavage.

Tools used to study how protein complexes are assembled in signaling cascades

Most proteins do not function on their own but as part of large signaling complexes that are arranged in every living cell in response to specific environmental cues. Proteins interact with each other either constitutively or transiently and do so with different affinity. When identifying the role played by a protein inside a cell, it is essential to define its particular cohort of binding partners so that the researcher can predict what signaling pathways the protein is engaged in. Once identified and confirmed, the information might allow the interaction to be manipulated by pharmacological inhibitors to help fight disease. In this review, we discuss protein-protein interactions and how they are essential to propagate signals in signaling pathways. We examine some of the high-throughput screening methods and focus on the methods used to confirm specific protein-protein interactions including; affinity tagging, co-immunoprecipitation, peptide array technology and fluorescence microscopy.

A lattice model of the nuclear pore complex

The nuclear pore complex (NPC) is one of the largest protein machines in the cell and forms the sole conduit for nucleocytoplasmic transport in eukaryotes. The NPC is composed of an eightfold radially symmetric scaffold of architectural proteins that anchor a set of phenylalanine-glycine (FG) repeat proteins that form the transport barrier. As a step toward elucidating the molecular architecture of the NPC, we solved the structure of nucleoporin 85 (Nup85) in complex with Seh1, a module in the heptameric Nup84 subcomplex. We define a new tripartite protein element, the ancestral coatomer element ACE1, which Nup85 specifically shares with several other nucleoporins and vesicle coat proteins. We predicted and verified functional sites on nucleoporin ACE1 members based on analogy to ACE1 interactions that propagate the COPII vesicle coat. Thus, we provide the first experimental evidence for evolution of the NPC and vesicle coats from a common ancestor. We propose that the NPC structural scaffold, like vesicle coats, is a polygonal network composed of vertex and edge elements that forms a molecular lattice upon which additional nucleoporins assemble. Here we further discuss our findings and elaborate on our lattice model of the nuclear pore complex.

Structural and functional analysis of a plant resistance protein TIR domain reveals interfaces for self-association, signaling, and autoregulation

The Toll/interleukin-1 receptor (TIR) domain occurs in animal and plant immune receptors. In the animal Toll-like receptors, homodimerization of the intracellular TIR domain is required for initiation of signaling cascades leading to innate immunity. By contrast, the role of the TIR domain in cytoplasmic nucleotide-binding/leucine-rich repeat (NB-LRR) plant immune resistance proteins is poorly understood. L6 is a TIR-NB-LRR resistance protein from flax (Linum usitatissimum) that confers resistance to the flax rust phytopathogenic fungus (Melampsora lini). We determine the crystal structure of the L6 TIR domain and show that, although dispensable for pathogenic effector protein recognition, the TIR domain alone is both necessary and sufficient for L6 immune signaling. We demonstrate that the L6 TIR domain self-associates, most likely forming a homodimer. Analysis of the structure combined with site-directed mutagenesis suggests that self-association is a requirement for immune signaling and reveals distinct surface regions involved in self-association, signaling, and autoregulation.

Progress in the structural understanding of voltage-gated calcium channel (CaV) function and modulation

Voltage-gated calcium channels (CaVs) are large, transmembrane multiprotein complexes that couple membrane depolarization to cellular calcium entry. These channels are central to cardiac action potential propagation, neurotransmitter and hormone release, muscle contraction, and calcium-dependent gene transcription. Over the past six years, the advent of high-resolution structural studies of CaV components from different isoforms and CaV modulators has begun to reveal the architecture that underlies the exceptionally rich feedback modulation that controls CaV action. These descriptions of CaV molecular anatomy have provided new, structure-based insights into the mechanisms by which particular channel elements affect voltage-dependent inactivation (VDI), calcium‑dependent inactivation (CDI), and calcium‑dependent facilitation (CDF). The initial successes have been achieved through structural studies of soluble channel domains and modulator proteins and have proven most powerful when paired with biochemical and functional studies that validate ideas inspired by the structures. Here, we review the progress in this growing area and highlight some key open challenges for future efforts.

Multiple C-terminal tail Ca(2+)/CaMs regulate Ca(V)1.2 function but do not mediate channel dimerization

Interactions between voltage-gated calcium channels (Ca(V)s) and calmodulin (CaM) modulate Ca(V) function. In this study, we report the structure of a Ca(2+)/CaM Ca(V)1.2 C-terminal tail complex that contains two PreIQ helices bridged by two Ca(2+)/CaMs and two Ca(2+)/CaM-IQ domain complexes. Sedimentation equilibrium experiments establish that the complex has a 2:1 Ca(2+)/CaM:C-terminal tail stoichiometry and does not form higher order assemblies. Moreover, subunit-counting experiments demonstrate that in live cell membranes Ca(V)1.2s are monomers. Thus, contrary to previous proposals, the crystallographic dimer lacks physiological relevance. Isothermal titration calorimetry and biochemical experiments show that the two Ca(2+)/CaMs in the complex have different properties. Ca(2+)/CaM bound to the PreIQ C-region is labile, whereas Ca(2+)/CaM bound to the IQ domain is not. Furthermore, neither of lobes of apo-CaM interacts strongly with the PreIQ domain. Electrophysiological studies indicate that the PreIQ C-region has a role in calcium-dependent facilitation. Together, the data show that two Ca(2+)/CaMs can bind the Ca(V)1.2 tail simultaneously and indicate a functional role for Ca(2+)/CaM at the C-region site.

The 1.4 A crystal structure of the ArsD arsenic metallochaperone provides insights into its interaction with the ArsA ATPase

Arsenic is a carcinogen that tops the Superfund list of hazardous chemicals. Bacterial resistance to arsenic is facilitated by ArsD, which delivers As(III) to the ArsA ATPase, the catalytic subunit of the ArsAB pump. Here we report the structure of the arsenic metallochaperone ArsD at 1.4 A and a model for its binding of metalloid. There are two ArsD molecules in the asymmetric unit. The overall structure of the ArsD monomer has a thioredoxin fold, with a core of four beta-strands flanked by four alpha-helices. Based on data from structural homologues, ArsD was modeled with and without bound As(III). ArsD binds one arsenic per monomer coordinated with the three sulfur atoms of Cys12, Cys13, and Cys18. Using this structural model, an algorithm was used to dock ArsD and ArsA. The resulting docking model provides testable predictions of the contact points of the two proteins and forms the basis for future experiments.

Amino acid substitutions at protein-protein interfaces that modulate the oligomeric state

Despite similarities in their sequence and structure, there are a number of homologous proteins that adopt various oligomeric states. Comparisons of these homologous protein pairs, in terms of residue substitutions at the protein-protein interfaces, have provided fundamental characteristics that describe how proteins interact with each other. We have prepared a dataset composed of pairs of related proteins with different homo-oligomeric states. Using the protein complexes, the interface residues were identified, and using structural alignments, the shadow-interface residues have been defined as the surface residues that align with the interface residues. Subsequently, we investigated residue substitutions between the interfaces and the shadow interfaces. Based on the degree of the contributions to the interactions, the aligned sites of the interfaces and shadow interfaces were divided into primary and secondary sites; the primary sites are the focus of this work. The primary sites were further classified into two groups (i.e. exposed and buried) based on the degree to which the residue is buried within the shadow interfaces. Using these classifications, two simple mechanisms that mediate the oligomeric states were identified. In the primary-exposed sites, the residues on the shadow interfaces are replaced by more hydrophobic or aromatic residues, which are physicochemically favored at protein-protein interfaces. In the primary-buried sites, the residues on the shadow interfaces are replaced by larger residues that protrude into other proteins. These simple rules are satisfied in 23 out of 25 Structural Classification of Proteins (SCOP) families with a different-oligomeric-state pair, and thus represent a basic strategy for modulating protein associations and dissociations.

Understanding protein non-folding

This review describes the family of intrinsically disordered proteins, members of which fail to form rigid 3-D structures under physiological conditions, either along their entire lengths or only in localized regions. Instead, these intriguing proteins/regions exist as dynamic ensembles within which atom positions and backbone Ramachandran angles exhibit extreme temporal fluctuations without specific equilibrium values. Many of these intrinsically disordered proteins are known to carry out important biological functions which, in fact, depend on the absence of a specific 3-D structure. The existence of such proteins does not fit the prevailing structure-function paradigm, which states that a unique 3-D structure is a prerequisite to function. Thus, the protein structure-function paradigm has to be expanded to include intrinsically disordered proteins and alternative relationships among protein sequence, structure, and function. This shift in the paradigm represents a major breakthrough for biochemistry, biophysics and molecular biology, as it opens new levels of understanding with regard to the complex life of proteins. This review will try to answer the following questions: how were intrinsically disordered proteins discovered? Why don't these proteins fold? What is so special about intrinsic disorder? What are the functional advantages of disordered proteins/regions? What is the functional repertoire of these proteins? What are the relationships between intrinsically disordered proteins and human diseases?

Functional and structural properties of mammalian acyl-coenzyme A thioesterases

Acyl-coenzyme A thioesterases (Acots) play important cellular roles in mammalian fatty acid metabolism through modulation of cellular concentrations of activated fatty acyl-CoAs. Acots catalyse the hydrolysis of the thioester bond present within acyl-CoA ester molecules to yield coenzyme A (CoASH) and the corresponding non-esterified fatty acid. Acyl-CoA thioesterases are expressed ubiquitously in both prokaryotes and eukaryotes and, in higher order organisms, the enzymes are expressed and localised in a tissue-dependent manner within the cytosol, mitochondria, peroxisomes and endoplasmic reticulum. Recent studies have led to advances in the functional and structural characterization of many mammalian Acot family members. These include the structure determination of both type-I and type-II Acot family members, structural elucidation of the START domain of ACOT11, identification of roles in arachidonic acid and inflammatory prostaglandin production by Acot7, and inclusion of a 13th Acot family member. Here, we review and analyse the current literature on mammalian Acots with respect to their characterization and summarize the current knowledge on the structure, function and regulation of this enzyme family.

Structural determinants of cadherin-23 function in hearing and deafness

The hair-cell tip link, a fine filament directly conveying force to mechanosensitive transduction channels, is composed of two proteins, protocadherin-15 and cadherin-23, whose mutation causes deafness. However, their molecular structure, elasticity, and deafness-related structural defects are unknown. We present crystal structures of the first and second extracellular cadherin repeats of cadherin-23. Overall, structures show typical cadherin folds, but reveal an elongated N terminus that precludes classical cadherin interactions and contributes to an N-terminal Ca(2+)-binding site. The deafness mutation D101G, in the linker region between the repeats, causes a slight bend between repeats and decreases Ca(2+) affinity. Molecular dynamics simulations suggest that cadherin-23 repeats are stiff and that either removing Ca(2+) or mutating Ca(2+)-binding residues reduces rigidity and unfolding strength. The structures define an uncharacterized cadherin family and, with simulations, suggest mechanisms underlying inherited deafness and how cadherin-23 may bind with itself and with protocadherin-15 to form the tip link.