Motif mediated protein-protein interactions as drug targets

Microcapsules based on biological macromolecules for intestinal health: A review

Intestinal dysfunction is becoming increasingly associated with neurological and endocrine issues, raising concerns about its impact on world health. With the introduction of several breakthrough technologies for detecting and treating intestinal illnesses, significant progress has been made in the previous few years. On the other hand, traditional intrusive diagnostic techniques are expensive and time-consuming. Furthermore, the efficacy of conventional drugs (not capsules) is reduced since they are more likely to degrade before reaching their target. In this context, microcapsules based on different types of biological macromolecules have been used to encapsulate active drugs and sensors to track intestinal ailments and address these issues. Several biomacromolecules/biomaterials (natural protein, alginate, chitosan, cellulose and RNA etc.) are widely used for make microcapsules for intestinal diseases, and can significantly improve the therapeutic effect and reduce adverse reactions. This article systematically summarizes microencapsulated based on biomacromolecules material for intestinal health control and efficacy enhancement. It also discusses the application and mechanism research of microencapsulated biomacromolecules drugs in reducing intestinal inflammation, in addition to covering the preparation techniques of microencapsulated drug delivery systems used for intestinal health. Microcapsule delivery systems' limits and potential applications for intestinal disease diagnosis, treatment, and surveillance were highlighted.

Analysis of protein-protein and protein-membrane interactions by isotope-edited infrared spectroscopy

The objective of this work is to highlight the power of isotope-edited Fourier transform infrared (FTIR) spectroscopy in resolving important problems encountered in biochemistry, biophysics, and biomedical research, focusing on protein-protein and protein membrane interactions that play key roles in practically all life processes. An overview of the effects of isotope substitutions in (bio)molecules on spectral frequencies and intensities is given. Data are presented demonstrating how isotope-labeled proteins and/or lipids can be used to elucidate enzymatic mechanisms, the mode of membrane binding of peripheral proteins, regulation of membrane protein function, protein aggregation, and local and global structural changes in proteins during functional transitions. The use of polarized attenuated total reflection FTIR spectroscopy to identify the spatial orientation and the secondary structure of a membrane-bound interfacial enzyme and the mode of lipid hydrolysis is described. Methods of production of site-directed, segmental, and domain-specific labeling of proteins by the synthetic, semisynthetic, and recombinant strategies, including advanced protein engineering technologies such as nonsense suppression and frameshift quadruplet codons are overviewed.

De Novo Rational Design of Peptide-Based Protein-Protein Inhibitors (Pep-PPIs) Approach by Mapping the Interaction Motifs of the PP Interface and Physicochemical Filtration: A Case on p25-Cdk5-Mediated Neurodegenerative Diseases

Protein-protein interactions, or PPIs, are a part of every biological activity and have been linked to a number of diseases, including cancer, infectious diseases, and neurological disorders. As such, targeting PPIs is considered a strategic and vital approach in the development of new medications. Nonetheless, the wide and flat contact interface makes it difficult to find small-molecule PP inhibitors. An alternative strategy would be to use the PPI interaction motifs as building blocks for the design of peptide-based inhibitors. Herein, we designed 12-mer peptide inhibitors to target p25-inducing-cyclin-dependent kinase (Cdk5) hyperregulation, a PPI that has been shown to perpetuate neuroinflammation, which is one of the major causal implications of neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, and frontotemporal dementia. We generated a library of 5 062 500 peptide combination sequences (PCS) derived from the interaction motif of Cdk5/p25 PP interface. The 20 amino acids were differentiated into six groups, namely, hydrophobic (aliphatic), aromatic, basic, acidic, unique, and polar uncharged, on the basis of their physiochemical properties. To preserve the interaction motif necessary for ideal binding, de novo modeling of all possible peptide sequence substitutions was considered. A set of filters, backed by the Support Vector Machine (SVM) algorithm, was then used to create a shortlisted custom peptide library that met specific bioavailability, toxicity, and therapeutic relevance, leading to a refined library of 15 PCS. A greedy algorithm and coarse-grained force field were used to predict peptide structure and folding before subsequent modeling studies. Molecular docking was performed to estimate the relative binding affinities, and out of the top hits, Pep15 was subjected to molecular dynamics simulations and binding free-energy calculations in comparison to a known peptide inhibitor with experimental data (template peptide). Interestingly, the identified peptide through our protocol, Pep15, was found to show a significantly higher binding affinity than the reference template peptide (-48.10 ± 0.23 kcal/mol and -17.53 ± 0.27 kcal/mol, respectively). In comparison to the template peptide, Pep15 was found to possess a more compact and buried surface area, tighter binding landscape, and reduced conformational variability, leading to enhanced structural and kinetic stability of the Cdk5/p25 complex. Notably, both peptide inhibitors were found to have a minimal impact on the architectural integrity of the Cdk5/p25 secondary structure. Herein, we propose Pep15 as a novel and potentially disruptive peptide drug for Cdk5/p25-mediated neurodegenerative phenotypes that require further clinical investigation. The systematic protocol and findings of this report would serve as a valuable tool in the identification of critical PPI interface reactive residues, designing of analogs, and identification of more potent peptide-based PPI inhibitors.

MotifQuest: An Automated Pipeline for Motif Database Creation to Improve Peptidomics Database Searching Programs

Endogenous peptides are an abundant and versatile class of biomolecules with vital roles pertinent to the functionality of the nervous, endocrine, and immune systems and others. Mass spectrometry stands as a premier technique for identifying endogenous peptides, yet the field still faces challenges due to the lack of optimized computational resources for reliable raw mass spectra analysis and interpretation. Current database searching programs can exhibit discrepancies due to the unique properties of endogenous peptides, which typically require specialized search considerations. Herein, we present a high throughput, novel scoring algorithm for the extraction and ranking of conserved amino acid sequence motifs within any endogenous peptide database. Motifs are conserved patterns across organisms, representing sequence moieties crucial for biological functions, including maintenance of homeostasis. MotifQuest, our novel motif database generation algorithm, is designed to work in partnership with EndoGenius, a program optimized for database searching of endogenous peptides and that is powered by a motif database to capitalize on biological context to produce identifications. MotifQuest aims to quickly develop motif databases without any prior knowledge, a laborious task not possible with traditional sequence alignment resources. In this work we illustrate the utility of MotifQuest to expand EndoGenius' identification utility to other endogenous peptides by showcasing its ability to identify antimicrobial peptides. Additionally, we discuss the potential utility of MotifQuest to parse out motifs from a FASTA database file that can be further validated as new peptide drug candidates.

Molecular Mechanism of pH-Induced Protrusion Configuration Switching in Piscine Betanodavirus Implies a Novel Antiviral Strategy

Many viruses contain surface spikes or protrusions that are essential for virus entry. These surface structures can thereby be targeted by antiviral drugs to treat viral infections. Nervous necrosis virus (NNV), a simple nonenveloped virus in the genus of betanodavirus, infects fish and damages aquaculture worldwide. NNV has 60 conspicuous surface protrusions, each comprising three protrusion domains (P-domain) of its capsid protein. NNV uses protrusions to bind to common receptors of sialic acids on the host cell surface to initiate its entry via the endocytic pathway. However, structural alterations of NNV in response to acidic conditions encountered during this pathway remain unknown, while detailed interactions of protrusions with receptors are unclear. Here, we used cryo-EM to discover that Grouper NNV protrusions undergo low-pH-induced compaction and resting. NMR and molecular dynamics (MD) simulations were employed to probe the atomic details. A solution structure of the P-domain at pH 7.0 revealed a long flexible loop (amino acids 311-330) and a pocket outlined by this loop. Molecular docking analysis showed that the N-terminal moiety of sialic acid inserted into this pocket to interact with conserved residues inside. MD simulations demonstrated that part of this loop converted to a β-strand under acidic conditions, allowing for P-domain trimerization and compaction. Additionally, a low-pH-favored conformation is attained for the linker connecting the P-domain to the NNV shell, conferring resting protrusions. Our findings uncover novel pH-dependent conformational switching mechanisms underlying NNV protrusion dynamics potentially utilized for facilitating NNV entry, providing new structural insights into complex NNV-host interactions with the identification of putative druggable hotspots on the protrusion.

Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions

One of the mechanisms viruses use in hijacking host cellular machinery is mimicking Short Linear Motifs (SLiMs) in host proteins to maintain their life cycle inside host cells. In the face of the escalating volume of virus-host protein-protein interactions (vhPPIs) documented in databases; the accurate prediction of molecular mimicry remains a formidable challenge due to the inherent degeneracy of SLiMs. Consequently, there is a pressing need for computational methodologies to predict new instances of viral mimicry. Our present study introduces a DMI-de-novo pipeline, revealing that vhPPIs catalogued in the VirHostNet3.0 database effectively capture domain-motif interactions (DMIs). Notably, both affinity purification coupled mass spectrometry and yeast two-hybrid assays emerged as good approaches for delineating DMIs. Furthermore, we have identified new vhPPIs mediated by SLiMs across different viruses. Importantly, the de-novo prediction strategy facilitated the recognition of several potential mimicry candidates implicated in the subversion of host cellular proteins. The insights gleaned from this research not only enhance our comprehension of the mechanisms by which viruses co-opt host cellular machinery but also pave the way for the development of novel therapeutic interventions.

Delivery of external proteins into the cytoplasm using protein capsules modified with IgG on the surface, created from the amphiphilic two helix-bundle protein OLE-ZIP

This study explores a new method for delivering therapeutic proteins into specific cells using OLE-ZIP capsules that present IgG. OLE-ZIP capsules is a spherical caspules prepared from amphihilic dimetic coiled-coil peptide, OLE-ZIP. Upon presenting cetuximab, these capsules showed preferential uptake in A431 cells and increased cytotoxicity when loaded with RNase A.

Discovery and Characterization of Linear Motif Mediated Protein-Protein Complexes

There are myriads of protein-protein complexes that form within the cell. In addition to classical binding events between globular domains, many protein-protein interactions involve short disordered protein regions. The latter contain so-called linear motifs binding specifically to ordered protein domain surfaces. Linear binding motifs are classified based on their consensus sequence, where only a few amino acids are conserved. In this chapter we will review experimental and in silico techniques that can be used for the discovery and characterization of linear motif mediated protein-protein complexes involved in cellular signaling, protein level and gene expression regulation.

Targeting the SOX2/CDP protein complex with a peptide suppresses the malignant progression of esophageal squamous cell carcinoma

Emerging evidence indicates that SOX2 is an oncogene for esophageal squamous cell carcinoma (ESCC). However, direct targeting of SOX2 is not feasible given that this transcription factor plays important roles in the maintenance of tissues such as the brain. Here, we identified CDP (Homeobox protein cut-like 1 or CASP) as a unique SOX2 binding partner enriched in ESCC with Duolink proximity ligation assay, bimolecular fluorescence complementation (BiFc) and immunoprecipitation. We then screened a peptide aptamer library using BiFc and immunoprecipitation and identified several peptide aptamers, including P58, that blocked the CDP/SOX2 interaction, leading to the inhibition of ESCC progress in vitro and in vivo. Upon administration, synthetic peptide P58, containing the YGRKKRRQRRR cell-penetrating peptide and the fluorophore TAMRA, also blocked the growth and metastasis of ESCC in both mice and zebrafish. Therefore, targeting the SOX2 binding partner CDP with peptide P58 offers an alternative avenue to treat ESCC with increased SOX2 levels.

How different viruses perturb host cellular machinery via short linear motifs

The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.

Genome-wide identification of GH9 gene family and the assessment of its role during fruit abscission zone formation in Vaccinium ashei

KEY MESSAGE

The genomic location and stage-specific expression pattern of GH9 genes reveal their critical roles during fruit abscission zone formation in Vaccinium ashei. Glycosyl hydrolase family 9 (GH9) cellulases play a crucial role in both cellulose synthesis and hydrolysis during plant growth and development. Despite this importance, there is currently no study on the involvement of GH9-encoding genes, specifically VaGH9s, in abscission zone formation of rabbiteye blueberries (Vaccinium ashei). In this study, we identified a total of 61 VaGH9s in the genome, which can be classified into 3 subclasses based on conserved motifs and domains, gene structures, and phylogenetic analyses. Our synteny analysis revealed that VaGH9s are more closely related to the GH9s of Populus L. than to those of Arabidopsis, Vitis vinifera, and Citrus sinensis. In silico structural analysis predicted that most of VaGH9s are hydrophilic, and localized in cell membrane and/or cell wall, and the variable sets of cis-acting regulatory elements and functional diversity with four categories of stress response, hormone regulation, growth and development, and transcription factor-related elements are present in the promoter sequence of VaGH9s genes. Transcriptomic analysis showed that there were 22 differentially expressed VaGH9s in fruit abscission zone tissue at the veraison stage, and the expression of VaGH9B2 and VaGH9C10 was continuously increased during fruit maturation, which were in parallel with the increasing levels of cellulase activity and oxidative stress indicators, suggesting that they are involved in the separation stage of fruit abscission in Vaccinium ashei. Our work identified 22 VaGH9s potentially involved in different stages of fruit abscission and would aid further investigation into the molecular regulation of abscission in rabbiteye blueberries fruit.

SLiM-binding pockets: an attractive target for broad-spectrum antivirals

Short linear motif (SLiM)-mediated interactions offer a unique strategy for viral intervention due to their compact interfaces, ease of convergent evolution, and key functional roles. Consequently, many viruses extensively mimic host SLiMs to hijack or deregulate cellular pathways and the same motif-binding pocket is often targeted by numerous unrelated viruses. A toolkit of therapeutics targeting commonly mimicked SLiMs could provide prophylactic and therapeutic broad-spectrum antivirals and vastly improve our ability to treat ongoing and future viral outbreaks. In this opinion article, we discuss the therapeutic relevance of SLiMs, advocating their suitability as targets for broad-spectrum antiviral inhibitors.

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysiological pathways and are important targets for the design of compounds of therapeutic interest. However, the identification of binding sites on protein surfaces and the development of modulators of protein-protein interactions still represent a major challenge due to their highly dynamic and extensive interfacial areas. Over the years, multiple strategies including structural, computational, and combinatorial approaches have been developed to characterize PPI and to date, several successful examples of small molecules, antibodies, peptides, and aptamers able to modulate these interfaces have been determined. Notably, peptides are a particularly useful tool for inhibiting PPIs due to their exquisite potency, specificity, and selectivity. Here, after an overview of PPIs and of the commonly used approaches to identify and characterize them, we describe and evaluate the impact of chemical peptide libraries in medicinal chemistry with a special focus on the results achieved through recent applications of this methodology. Finally, we also discuss the role that this methodology can have in the framework of the opportunities, and challenges that the application of new predictive approaches based on artificial intelligence is generating in structural biology.

Disrupting the α-synuclein-ESCRT interaction with a peptide inhibitor mitigates neurodegeneration in preclinical models of Parkinson's disease

Accumulation of α-synuclein into toxic oligomers or fibrils is implicated in dopaminergic neurodegeneration in Parkinson's disease. Here we performed a high-throughput, proteome-wide peptide screen to identify protein-protein interaction inhibitors that reduce α-synuclein oligomer levels and their associated cytotoxicity. We find that the most potent peptide inhibitor disrupts the direct interaction between the C-terminal region of α-synuclein and CHarged Multivesicular body Protein 2B (CHMP2B), a component of the Endosomal Sorting Complex Required for Transport-III (ESCRT-III). We show that α-synuclein impedes endolysosomal activity via this interaction, thereby inhibiting its own degradation. Conversely, the peptide inhibitor restores endolysosomal function and thereby decreases α-synuclein levels in multiple models, including female and male human cells harboring disease-causing α-synuclein mutations. Furthermore, the peptide inhibitor protects dopaminergic neurons from α-synuclein-mediated degeneration in hermaphroditic C. elegans and preclinical Parkinson's disease models using female rats. Thus, the α-synuclein-CHMP2B interaction is a potential therapeutic target for neurodegenerative disorders.

Molecular mimicry of host short linear motif-mediated interactions utilised by viruses for entry

Viruses are obligate intracellular parasites that depend on host cellular machinery for performing even basic biological functions. One of the many ways they achieve this is through molecular mimicry, wherein the virus mimics a host sequence or structure, thereby being able to hijack the host's physiological interactions for its pathogenesis. Such adaptations are specific recognitions that often confer tissue and species-specific tropisms to the virus, and enable the virus to utilise previously existing host signalling networks, which ultimately aid in further steps of viral infection, such as entry, immune evasion and spread. A common form of sequence mimicry utilises short linear motifs (SLiMs). SLiMs are short-peptide sequences that mediate transient interactions and are major elements in host protein interaction networks. This work is aimed at providing a comprehensive review of current literature of some well-characterised SLiMs that play a role in the attachment and entry of viruses into host cells, which mimic physiological receptor-ligand interactions already present in the host. Considering recent trends in emerging diseases, further research on such motifs involved in viral entry can help in the discovery of previously unknown cellular receptors utilised by viruses, as well as help in the designing of targeted therapeutics such as vaccines or inhibitors directed towards these interactions.

Targeting peptide-mediated interactions in omics

Peptide-mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein-protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome-wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self-inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI-targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

Lipid Binding of SH2 Domains

The Src homology 2 (SH2) domain is a modular protein interaction domain that specifically recognizes the phosphotyrosine (pY) motif of a target molecule. We recently reported that a large majority of human SH2 domains tightly bind membrane lipids, and many show high lipid specificity. Most of them can bind a lipid and the pY motif coincidently because their lipid-binding sites are topologically distinct from pY-binding pockets. Lipid binding of SH2 domain-containing kinases and phosphatases is functionally important because it exerts exquisite spatiotemporal control on protein-protein interaction and cell signaling activities mediated by these proteins. Here, we describe two assays, surface plasmon resonance analysis and fluorescence quenching analysis, which allow quantitative determination of the affinity and specificity of SH2-lipid interaction and high-throughput screening for SH2 domain-lipid-binding inhibitors.

Structural modeling, energetic analysis and molecular design of a π-stacking system at the complex interface of pediatric respiratory syncytial virus nucleocapsid with the C-terminal peptide of phosphoprotein

Human respiratory syncytial virus (RSV) is a primary cause of lower respiratory tract infections and hospital visits during infancy and childhood. The RSV phosphoprotein (P) is a major polymerase cofactor that interacts with nucleoprotein (N) to promote the recognition of ribonucleoprotein complex (RNP) by viral RNA polymerase. The binding pocket of N protein is chemically diverse, in or around which a number of aromatic and charged amino acid residues are observed. Previously, a nonapeptide segment (P peptide, ²³³DNDLSLEDF²⁴¹) representing the C-terminal tail of P protein was identified to mediate the N-P interaction with a moderate affinity, in which the Phe241 at the end of P's C-terminus plays a critical role in the binding of P peptide to N protein. Here, we found that the side-chain aromatic phenyl moiety of P Phe241 residue can form short- and long-range cation-π interactions with N Arg132 and Arg150 residues, respectively, as well as T-shaped and parallel-displaced π-π stackings with N Tyr135 and His151 residues, respectively, which co-define a geometrically satisfactory π-stacking system at the complex interface of N protein with P peptide, thus largely stabilizing the complex architecture. The stacking effect was further optimized by systematically mutating the P Phe241 residue to other natural and non-natural aromatic amino acids with diverse chemical substitutions at the phenyl moiety to examine their structural and energetic effects on π-stacking system and on protein-peptide binding. The electron-donating mutations at the phenyl moiety of P Phe241 residue can effectively enhance the π-stacking system and then promote peptide binding, whereas the bulky and positively charged mutations would considerably impair the peptide potency by introducing steric hindrance and electrostatic repulsion. The [Tyr]P, [Thp]P and [Fph]P mutants were determined to have an increased affinity relative to wild-type P peptide, which could be used as self-inhibitory peptides to competitively disrupt the native interaction between N and P proteins.

AP-2δ Is the Most Relevant Target of AP-2 Family-Focused Cancer Therapy and Affects Genome Organization

Formerly hailed as "undruggable" proteins, transcription factors (TFs) are now under investigation for targeted therapy. In cancer, this may alter, inter alia, immune evasion or replicative immortality, which are implicated in genome organization, a process that accompanies multi-step tumorigenesis and which frequently develops in a non-random manner. Still, targeting-related research on some TFs is scarce, e.g., among AP-2 proteins, which are known for their altered functionality in cancer and prognostic importance. Using public repositories, bioinformatics tools, and RNA-seq data, the present study examined the ligandability of all AP-2 members, selecting the best one, which was investigated in terms of mutations, targets, co-activators, correlated genes, and impact on genome organization. AP-2 proteins were found to have the conserved "TF_AP-2" domain, but manifested different binding characteristics and evolution. Among them, AP-2δ has not only the highest number of post-translational modifications and extended strands but also contains a specific histidine-rich region and cleft that can receive a ligand. Uterine, colon, lung, and stomach tumors are most susceptible to AP-2δ mutations, which also co-depend with cancer hallmark genes and drug targets. Considering AP-2δ targets, some of them were located proximally in the spatial genome or served as co-factors of the genes regulated by AP-2δ. Correlation and functional analyses suggested that AP-2δ affects various processes, including genome organization, via its targets; this has been eventually verified in lung adenocarcinoma using expression and immunohistochemistry data of chromosomal conformation-related genes. In conclusion, AP-2δ affects chromosomal conformation and is the most appropriate target for cancer therapy focused on the AP-2 family.

Large-Scale Crystallographic Fragment Screening Expedites Compound Optimization and Identifies Putative Protein-Protein Interaction Sites

The identification of starting points for compound development is one of the key steps in early-stage drug discovery. Information-rich techniques such as crystallographic fragment screening can potentially increase the efficiency of this step by providing the structural information of the binding mode of the ligands in addition to the mere binding information. Here, we present the crystallographic screening of our 1000-plus-compound F2X-Universal Library against the complex of the yeast spliceosomal Prp8 RNaseH-like domain and the snRNP assembly factor Aar2. The observed 269 hits are distributed over 10 distinct binding sites on the surface of the protein-protein complex. Our work shows that hit clusters from large-scale crystallographic fragment screening campaigns identify known interaction sites with other proteins and suggest putative additional interaction sites. Furthermore, the inherent binding pose validation within the hit clusters may accelerate downstream compound optimization.

TRPM8-Rap1A Interaction Sites as Critical Determinants for Adhesion and Migration of Prostate and Other Epithelial Cancer Cells

Emerging evidence indicates that the TRPM8 channel plays an important role in prostate cancer (PCa) progression, by impairing the motility of these cancer cells. Here, we reveal a novel facet of PCa motility control via direct protein-protein interaction (PPI) of the channel with the small GTPase Rap1A. The functional interaction of the two proteins was assessed by active Rap1 pull-down assays and live-cell imaging experiments. Molecular modeling analysis allowed the identification of four putative residues involved in TRPM8-Rap1A interaction. Point mutations of these sites impaired PPI as shown by GST-pull-down, co-immunoprecipitation, and PLA experiments and revealed their key functional role in the adhesion and migration of PC3 prostate cancer cells. More precisely, TRPM8 inhibits cell migration and adhesion by trapping Rap1A in its GDP-bound inactive form, thus preventing its activation at the plasma membrane. In particular, residues E207 and Y240 in the sequence of TRPM8 and Y32 in that of Rap1A are critical for the interaction between the two proteins not only in PC3 cells but also in cervical (HeLa) and breast (MCF-7) cancer cells. This study deepens our knowledge of the mechanism through which TRPM8 would exert a protective role in cancer progression and provides new insights into the possible use of TRPM8 as a new therapeutic target in cancer treatment.

Integrated unsupervised-supervised modeling and prediction of protein-peptide affinities at structural level

Cell signal networks are orchestrated directly or indirectly by various peptide-mediated protein-protein interactions, which are normally weak and transient and thus ideal for biological regulation and medicinal intervention. Here, we develop a general-purpose method for modeling and predicting the binding affinities of protein-peptide interactions (PpIs) at the structural level. The method is a hybrid strategy that employs an unsupervised approach to derive a layered PpI atom-residue interaction (ulPpI[a-r]) potential between different protein atom types and peptide residue types from thousands of solved PpI complex structures and then statistically correlates the potential descriptors with experimental affinities (KD values) over hundreds of known PpI samples in a supervised manner to create an integrated unsupervised-supervised PpI affinity (usPpIA) predictor. Although both the ulPpI[a-r] potential and usPpIA predictor can be used to calculate PpI affinities from their complex structures, the latter seems to perform much better than the former, suggesting that the unsupervised potential can be improved substantially with a further correction by supervised statistical learning. We examine the robustness and fault-tolerance of usPpIA predictor when applied to treat the coarse-grained PpI complex structures modeled computationally by sophisticated peptide docking and dynamics simulation. It is revealed that, despite developed solely based on solved structures, the integrated unsupervised-supervised method is also applicable for locally docked structures to reach a quantitative prediction but can only give a qualitative prediction on globally docked structures. The dynamics refinement seems not to change (or improve) the predictive results essentially, although it is computationally expensive and time-consuming relative to peptide docking. We also perform extrapolation of usPpIA predictor to the indirect affinity quantities of HLA-A*0201 binding epitope peptides and NHERF PDZ binding scaffold peptides, consequently resulting in a good and moderate correlation of the predicted KD with experimental IC50 and BLU on the two peptide sets, with Pearson's correlation coefficients Rp = 0.635 and 0.406, respectively.

The PentUnFOLD algorithm as a tool to distinguish the dark and the light sides of the structural instability of proteins

Intrinsically disordered proteins are frequently involved in important regulatory processes in the cell thanks to their ability to bind several different targets performing sometimes even opposite functions. The PentUnFOLD algorithm is a physicochemical method that is based on new propensity scales for disordered, nonstable and stable elements of secondary structure and on the counting of stabilizing and destabilizing intraprotein contacts. Unlike other methods, it works with a PDB file, and it can determine not only those fragments of alpha helices, beta strands, and random coils that can turn into disordered state (the “dark” side of the disorder), but also nonstable regions of alpha helices and beta strands which are able to turn into random coils (the “light” side), and vice versa (H ↔ C, E ↔ C). The scales have been obtained from structural data on disordered regions from the middle parts of amino acid sequences only, and not on their expectedly disordered N- and C-termini. Among other tendencies we have found that regions of both alpha helices and beta strands that can turn into the disordered state are relatively enriched in residues of Ala, Met, Asp, and Lys, while regions of both alpha helices and beta strands that can turn into random coil are relatively enriched in hydrophilic residues, and Cys, Pro, and Gly. Moreover, PentUnFOLD has the option to determine the effect of secondary structure transitions on the stability of a given region of a protein. The PentUnFOLD algorithm is freely available at http://3.17.12.213/pent-un-fold and http://chemres.bsmu.by/PentUnFOLD.htm.

Physical ARTEMIS:DNA-PKcs interaction is necessary for V(D)J recombination

The nuclease ARTEMIS and the DNA-dependent protein kinase catalytic subunit (DNA-PKcs) are involved in the repair of physiological and pathogenic DNA double strand breaks. Both proteins are indispensable for the hairpin-opening activity in V(D)J recombination and therefore essential for the adaptive immune response. ARTEMIS and DNA-PKcs interact, however experimental evidence for in vivo significance is missing. We demonstrate that mutations abolishing this protein-protein interaction affect nuclease function. In DNA-PKcs, mutation L3062R impairs the physical interaction with ARTEMIS and was previously identified as pathogenic variant, resulting in radiosensitive severe combined immunodeficiency. In ARTEMIS, specific mutations in two conserved regions affect interaction with DNA-PKcs. In combination they impair V(D)J recombination activity, independent of ARTEMIS autoinhibitory self-interaction between the ARTEMIS C-terminus and the N-terminal nuclease domain. We describe small fragments from both proteins, capable of interaction with the corresponding full-length partner proteins: In DNA-PKcs 42 amino acids out of FAT region 2 (PKcs3041-3082) can mediate interaction with ARTEMIS. In the nuclease we have defined 26 amino acids (ARM378-403) as minimal DNA-PKcs interacting fragment. The exact mapping of the ARTEMIS:DNA-PKcs interaction may pave the way for the design of specific inhibitors targeting the repair of DNA double strand breaks.

Understanding binding affinity and specificity of modular protein domains: A focus in ligand design for the polyproline-binding families

Within the modular protein domains there are five families that recognize proline-rich sequences: SH3, WW, EVH1, GYF and UEV domains. This chapter reviews the main strategies developed for the design of ligands for these families, including peptides, peptidomimetics and drugs. We also describe some studies aimed to understand the molecular reasons responsible for the intrinsic affinity and specificity of these domains.

Rapid Rational Design of Cyclic Peptides Mimicking Protein-Protein Interfaces

The cPEPmatch approach is a rapid computational methodology for the rational design of cyclic peptides to target desired regions of protein-protein interfaces. The method selects cyclic peptides that structurally match backbone structures of short segments at a protein-protein interface. In a second step, the cyclic peptides act as templates for designed binders by adapting the amino acid side chains to the side chains found in the target complex. A link to access the different tools that comprise the cPEPmatch method and a detailed step-by-step guide is provided. We outline the protocol by following the application to a trypsin protease in complex with the bovine inhibitor protein (BPTI). An extension of our original approach is also presented, where we give a detailed description of the usage of the cPEPmatch methodology focusing on identifying hot regions of protein-protein interfaces prior to the matching. This extension allows one to reduce the amount of evaluated putative cyclic peptides and to specifically design only those that compete with the strongest protein-protein binding regions. It is illustrated by an application to an MHC class I protein complex.

Mapping, Structure and Modulation of PPI

Because of the key relevance of protein–protein interactions (PPI) in diseases, the modulation of protein-protein complexes is of relevant clinical significance. The successful design of binding compounds modulating PPI requires a detailed knowledge of the involved protein-protein system at molecular level, and investigation of the structural motifs that drive the association of the proteins at the recognition interface. These elements represent hot spots of the protein binding free energy, define the complex lifetime and possible modulation strategies. Here, we review the advanced technologies used to map the PPI involved in human diseases, to investigate the structure-function features of protein complexes, and to discover effective ligands that modulate the PPI for therapeutic intervention.

Comparative analysis of Rosetta stone events in Klebsiella pneumoniae and Streptococcus pneumoniae for drug target identification

Background

Drug target identification is a fast-growing field of research in many human diseases. Many strategies have been devised in the post-genomic era to identify new drug targets for infectious diseases. Analysis of protein sequences from different organisms often reveals cases of exon/ORF shuffling in a genome. This results in the fusion of proteins/domains, either in the same genome or that of some other organism, and is termed Rosetta stone sequences. They help link disparate proteins together describing local and global relationships among proteomes. The functional role of proteins is determined mainly by domain-domain interactions and leading to the corresponding signaling mechanism. Putative proteins can be identified as drug targets by re-annotating their functional role through domain-based strategies.

Results

This study has utilized a bioinformatics approach to identify the putative proteins that are ideal drug targets for pneumonia infection by re-annotating the proteins through position-specific iterations. The putative proteome of two pneumonia-causing pathogens was analyzed to identify protein domain abundance and versatility among them. Common domains found in both pathogens were identified, and putative proteins containing these domains were re-annotated. Among many druggable protein targets, the re-annotation of EJJ83173 (which contains the GFO_IDH_MocA domain) showed that its probable function is glucose-fructose oxidoreduction. This protein was found to have sufficient interactor proteins and homolog in both pathogens but no homolog in the host (human), indicating it as an ideal drug target. 3D modeling of the protein showed promising model parameters. The model was utilized for virtual screening which revealed several ligands with inhibitory activity. These ligands included molecules documented in traditional Chinese medicine and currently marketed drugs.

Conclusions

This novel strategy of drug target identification through domain-based putative protein re-annotation presents a prospect to validate the proposed drug target to confer its utility as a typical protein targeting both pneumonia-causing species studied herewith.

TRP Channels Interactome as a Novel Therapeutic Target in Breast Cancer

Breast cancer is one of the most frequent cancer types worldwide and the first cause of cancer-related deaths in women. Although significant therapeutic advances have been achieved with drugs such as tamoxifen and trastuzumab, breast cancer still caused 627,000 deaths in 2018. Since cancer is a multifactorial disease, it has become necessary to develop new molecular therapies that can target several relevant cellular processes at once. Ion channels are versatile regulators of several physiological- and pathophysiological-related mechanisms, including cancer-relevant processes such as tumor progression, apoptosis inhibition, proliferation, migration, invasion, and chemoresistance. Ion channels are the main regulators of cellular functions, conducting ions selectively through a pore-forming structure located in the plasma membrane, protein–protein interactions one of their main regulatory mechanisms. Among the different ion channel families, the Transient Receptor Potential (TRP) family stands out in the context of breast cancer since several members have been proposed as prognostic markers in this pathology. However, only a few approaches exist to block their specific activity during tumoral progress. In this article, we describe several TRP channels that have been involved in breast cancer progress with a particular focus on their binding partners that have also been described as drivers of breast cancer progression. Here, we propose disrupting these interactions as attractive and potential new therapeutic targets for treating this neoplastic disease.

Sub-structure-based screening and molecular docking studies of potential enteroviruses inhibitors

Rhinoviruses (RV), especially Human rhinovirus (HRVs) have been accepted as the most common cause for upper respiratory tract infections (URTIs). Pleconaril, a broad spectrum anti-rhinoviral compound, has been used as a drug of choice for URTIs for over a decade. Unfortunately, for various complications associated with this drug, it was rejected, and a replacement is highly desirable. In silico screening and prediction methods such as sub-structure search and molecular docking have been widely used to identify alternative compounds. In our study, we have utilised sub-structure search to narrow down our quest in finding relevant chemical compounds. Molecular docking studies were then used to study their binding interaction at the molecular level. Interestingly, we have identified 3 residues that is worth further investigation in upcoming molecular dynamics simulation systems of their contribution in stable interaction.

Release of adenosine-induced immunosuppression: Comprehensive characterization of dual A2A/A2B receptor antagonist

Immunosuppression is one of the main mechanisms facilitating tumor expansion. It may be driven by immune checkpoint protein expression, anti-inflammatory cytokine secretion or enhanced metabolic enzyme production, leading to the subsequent build-up of metabolites such as adenosine. Under physiological conditions, adenosine prevents the development of tissue damage resulting from a prolonged immune response; the same mechanism might be employed by tumor tissue to promote immunosuppression. Immune cells expressing A_2A and A_2B adenosine receptors present in an adenosine-rich environment have suppressed effector functions, such as cytotoxicity, proinflammatory cytokine release, antigen presentation and others, making them inert to cancer cells. This study was designed to investigate the dual antagonist potential of SEL330-639 to abolish adenosine-driven immunosuppression. SEL330-639 has slow dissociation kinetics. It inhibits cAMP production in human CD4⁺ cells, CD8⁺ cells and moDCs, which leads to diminished CREB phosphorylation and restoration of antitumor cytokine production (IL-2, TNFα, IL-12) in multiple primary human immune cells. The aforementioned results were additionally validated by gene expression analysis and functional assays in which NK cell line cytotoxicity was recovered by SEL330-639. Adenosine-driven immunosuppression is believed to preclude the effectiveness of immune checkpoint inhibitor therapies. Hence, there is an urgent need to develop new immuno-oncological strategies. Here, we comprehensively characterize SEL330-639, a novel dual A_2A/A_2B receptor antagonist effective in both lymphoid and myeloid cell populations with nanomolar potency. Due to its tight binding to the A_2A and A_2B receptors, this binding is sustained even at high adenosine concentrations mimicking the upper limit of the range of adenosine levels observed in the tumor microenvironment.

Structure-based peptide design targeting intrinsically disordered proteins: Novel histone H4 and H2A peptidic inhibitors

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Intrinsically disordered proteins/protein regions (IDPs/IDPRs) are emerging drug targets.

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Lack of fast methods hinders the discovery of inhibitors for IDPs/ IDPRs.

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Fast and inexpensive structure-based approaches have been developed.

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The developed methods were applied to succesfully design inhibitors targeting the disordered tail of histone H4 and H2A.

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The presented methods can be widely used to identify inhibitors for other IDPs/IDPRs.

A growing body of research has demonstrated that targeting intrinsically disordered proteins (IDPs) and intrinsically disordered protein regions (IDPRs) is feasible and represents a new trending strategy in drug discovery. However, the number of inhibitors targeting IDPs/IDPRs is increasing slowly due to limitations of the methods that can be used to accelerate the discovery process. We have applied structure-based methods to successfully develop the first peptidic inhibitor (HIPe - Histone Inhibitory Peptide) that targets histone H4 that are released from NETs (Neutrophil Extracellular Traps). HIPe binds stably to the disordered N-terminal tail of histone H4, thereby preventing histone H4-induced cell death. Recently, by utilisation of the same state-of-the-art approaches, we have developed a novel peptidic inhibitor (CHIP - Cyclical Histone H2A Interference Peptide) that binds to NET-resident histone H2A, which results in a blockade of monocyte adhesion and consequently reduction in atheroprogression. Here, we present comprehensive details on the computational methods utilised to design and develop HIPe and CHIP. We have exploited protein–protein complexes as starting structures for rational peptide design and then applied binding free energy methods to predict and prioritise binding strength of the designed peptides with histone H4 and H2A. By doing this way, we have modelled only around 20 peptides and from these were able to select 4–5 peptides, from a total of more than a trillion candidate peptides, for functional characterisation in different experiments. The developed computational protocols are generic and can be widely used to design and develop novel inhibitors for other disordered proteins.

Motifs and interface amino acid-mediated regulation of amyloid biogenesis in microbes to humans: potential targets for intervention

Amyloids are linked to many debilitating diseases in mammals. Some organisms produce amyloids that have a functional role in the maintenance of their biological processes. Microbes utilize functional bacterial amyloids (FuBA) for pathogenicity and infections. Amyloid biogenesis is regulated differentially in various systems to avoid its toxic accumulation. A familiar feature in the process of amyloid biogenesis from humans to microbes is its regulation by protein-protein interactions (PPI). The spatial arrangement of amino acid residues in proteins generates topologies like flat interface and linear motif, which participate in protein interactions. Motifs and interface residue-mediated interactions have a direct or an indirect impact on amyloid secretion and assembly. Some motifs undergo post-translational modifications (PTM), which effects interactions and dynamics of the amyloid biogenesis cascade. Interaction-induced local changes stimulate global conformational transitions in the PPI complex, which indirectly affects amyloid formation. Perturbation of such motifs and interface residues results in amyloid abolishment. Interface residues, motifs and their respective interactive protein partners could serve as potential targets for intervention to inhibit amyloid biogenesis.

Exploring Proteomic Drug Targets, Therapeutic Strategies and Protein - Protein Interactions in Cancer: Mechanistic View

Protein-Protein Interactions (PPIs) drive major signalling cascades and play critical role in cell proliferation, apoptosis, angiogenesis and trafficking. Deregulated PPIs are implicated in multiple malignancies and represent the critical targets for treating cancer. Herein, we discuss the key protein-protein interacting domains implicated in cancer notably PDZ, SH2, SH3, LIM, PTB, SAM and PH. These domains are present in numerous enzymes/kinases, growth factors, transcription factors, adaptor proteins, receptors and scaffolding proteins and thus represent essential sites for targeting cancer. This review explores the candidature of various proteins involved in cellular trafficking (small GTPases, molecular motors, matrix-degrading enzymes, integrin), transcription (p53, cMyc), signalling (membrane receptor proteins), angiogenesis (VEGFs) and apoptosis (BCL-2family), which could possibly serve as targets for developing effective anti-cancer regimen. Interactions between Ras/Raf; X-linked inhibitor of apoptosis protein (XIAP)/second mitochondria-derived activator of caspases (Smac/DIABLO); Frizzled (FRZ)/Dishevelled (DVL) protein; beta-catenin/T Cell Factor (TCF) have also been studied as prospective anticancer targets. Efficacy of diverse molecules/ drugs targeting such PPIs although evaluated in various animal models/cell lines, there is an essential need for human-based clinical trials. Therapeutic strategies like the use of biologicals, high throughput screening (HTS) and fragment-based technology could play an imperative role in designing cancer therapeutics. Moreover, bioinformatic/computational strategies based on genome sequence, protein sequence/structure and domain data could serve as competent tools for predicting PPIs. Exploring hot spots in proteomic networks represents another approach for developing targetspecific therapeutics. Overall, this review lays emphasis on a productive amalgamation of proteomics, genomics, biochemistry, and molecular dynamics for successful treatment of cancer.

Mending Fences: Na,K-ATPase signaling via Ca2+ in the maintenance of epithelium integrity

Na,K-ATPase is a ubiquitous multifunctional protein that acts both as an ion pump and as a signal transducer. The signaling function is activated by ouabain in non-toxic concentrations. In epithelial cells the ouabain-bound Na,K-ATPase connects with the inositol 1,4,5-trisphosphate receptor via a short linear motif to activate low frequency Ca2+ oscillations. Within a couple of minutes this ouabain mediated signal has resulted in phosphorylation or dephosphorylation of 2580 phospho-sites. Proteins that control cell proliferation and cell adhesion and calmodulin regulated proteins are enriched among the ouabain phosphor-regulated proteins. The inositol 1,4,5-trisphosphate receptor and the stromal interaction molecule, which are both essential for the initiation of Ca2+ oscillations, belong to the ouabain phosphor-regulated proteins. Downstream effects of the ouabain-evoked Ca2+ signal in epithelial cells include interference with the intrinsic mitochondrial apoptotic process and stimulation of embryonic growth processes. The dual function of Na,K-ATPase as an ion pump and a signal transducer is now well established and evaluation of the physiological and pathophysiological consequences of this universal signal emerges as an urgent topic for future studies.

Protein Domain Level Cancer Drug Targets in the Network of MAPK Pathways

Proteins in the MAPK pathways considered as potential drug targets for cancer treatment. Pathways along with the cross-talks increase their scope to view them as a network of MAPK pathways. Side effect causing targeted domains act as a proxy for drug targets due to its structural similarity and frequent reuse of their variants. We proposed to identify non-repeatable protein domains as the drug targets to disrupt the signal transduction than targeting the whole protein. Network based approach is used to understand the contribution of 52 domains in non-hub, non-essential, and intra-pathway cancerous nodes and to identify potential drug target domains. 34 distinct domains in the cancerous proteins are playing vital roles in making cancer as a complex disease and pose challenges to identify potential drug targets. Distribution of domain families follows the power law in the network. Single promiscuous domains are contributing to the formation of hubs like Pkinease, Pkinease Tyr, and Ras. Hub nodes are positively correlated with the domain coverage and targeting them would disrupt functional properties of the proteins. EIF 4EBP, alpha Kinase, Sel1, ROKNT, and KH 1 are the domains identified as potential domain targets for the disruption of the signaling mechanism involved in cancer.

Understanding protein multifunctionality: from short linear motifs to cellular functions

Moonlighting proteins perform multiple unrelated functions without any change in polypeptide sequence. They can coordinate cellular activities, serving as switches between pathways and helping to respond to changes in the cellular environment. Therefore, regulation of the multiple protein activities, in space and time, is likely to be important for the homeostasis of biological systems. Some moonlighting proteins may perform their multiple functions simultaneously while others alternate between functions due to certain triggers. The switch of the moonlighting protein's functions can be regulated by several distinct factors, including the binding of other molecules such as proteins. We here review the approaches used to identify moonlighting proteins and existing repositories. We particularly emphasise the role played by short linear motifs and PTMs as regulatory switches of moonlighting functions.

MotifAnalyzer-PDZ: A computational program to investigate the evolution of PDZ-binding target specificity

Recognition of short linear motifs (SLiMs) or peptides by proteins is an important component of many cellular processes. However, due to limited and degenerate binding motifs, prediction of cellular targets is challenging. In addition, many of these interactions are transient and of relatively low affinity. Here, we focus on one of the largest families of SLiM-binding domains in the human proteome, the PDZ domain. These domains bind the extreme C-terminus of target proteins, and are involved in many signaling and trafficking pathways. To predict endogenous targets of PDZ domains, we developed MotifAnalyzer-PDZ, a program that filters and compares all motif-satisfying sequences in any publicly available proteome. This approach enables us to determine possible PDZ binding targets in humans and other organisms. Using this program, we predicted and biochemically tested novel human PDZ targets by looking for strong sequence conservation in evolution. We also identified three C-terminal sequences in choanoflagellates that bind a choanoflagellate PDZ domain, the Monsiga brevicollis SHANK1 PDZ domain (mbSHANK1), with endogenously-relevant affinities, despite a lack of conservation with the targets of a homologous human PDZ domain, SHANK1. All three are predicted to be signaling proteins, with strong sequence homology to cytosolic and receptor tyrosine kinases. Finally, we analyzed and compared the positional amino acid enrichments in PDZ motif-satisfying sequences from over a dozen organisms. Overall, MotifAnalyzer-PDZ is a versatile program to investigate potential PDZ interactions. This proof-of-concept work is poised to enable similar types of analyses for other SLiM-binding domains (e.g., MotifAnalyzer-Kinase). MotifAnalyzer-PDZ is available at http://motifAnalyzerPDZ.cs.wwu.edu.

An intrinsically disordered proteins community for ELIXIR

Intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) are now recognised as major determinants in cellular regulation. This white paper presents a roadmap for future e-infrastructure developments in the field of IDP research within the ELIXIR framework. The goal of these developments is to drive the creation of high-quality tools and resources to support the identification, analysis and functional characterisation of IDPs. The roadmap is the result of a workshop titled “An intrinsically disordered protein user community proposal for ELIXIR” held at the University of Padua. The workshop, and further consultation with the members of the wider IDP community, identified the key priority areas for the roadmap including the development of standards for data annotation, storage and dissemination; integration of IDP data into the ELIXIR Core Data Resources; and the creation of benchmarking criteria for IDP-related software. Here, we discuss these areas of priority, how they can be implemented in cooperation with the ELIXIR platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for an IDP Community in ELIXIR and is an appeal to identify and involve new stakeholders.

Engineering selective competitors for the discrimination of highly conserved protein-protein interaction modules

Designing highly specific modulators of protein-protein interactions (PPIs) is especially challenging in the context of multiple paralogs and conserved interaction surfaces. In this case, direct generation of selective and competitive inhibitors is hindered by high similarity within the evolutionary-related protein interfaces. We report here a strategy that uses a semi-rational approach to separate the modulator design into two functional parts. We first achieve specificity toward a region outside of the interface by using phage display selection coupled with molecular and cellular validation. Highly selective competition is then generated by appending the more degenerate interaction peptide to contact the target interface. We apply this approach to specifically bind a single PDZ domain within the postsynaptic protein PSD-95 over highly similar PDZ domains in PSD-93, SAP-97 and SAP-102. Our work provides a paralog-selective and domain specific inhibitor of PSD-95, and describes a method to efficiently target other conserved PPI modules.

Developing inhibitors that target specific protein-protein interactions (PPIs) is challenging. Here, the authors show that target selectivity and PPI blocking can be achieved simultaneously with PPI inhibitors that contain two functional modules, and create a paralog-selective PSD-95 inhibitor as proof-of-concept.

Smad7 Binds Differently to Individual and Tandem WW3 and WW4 Domains of WWP2 Ubiquitin Ligase Isoforms

WWP2 is an E3 ubiquitin ligase that differentially regulates the contextual tumour suppressor/progressor TGFβ signalling pathway by alternate isoform expression. WWP2 isoforms select signal transducer Smad2/3 or inhibitor Smad7 substrates for degradation through different compositions of protein–protein interaction WW domains. The WW4 domain-containing WWP2-C induces Smad7 turnover in vivo and positively regulates the metastatic epithelial–mesenchymal transition programme. This activity and the overexpression of these isoforms in human cancers make them candidates for therapeutic intervention. Here, we use NMR spectroscopy to solve the solution structure of the WWP2 WW4 domain and observe the binding characteristics of Smad7 substrate peptide. We also reveal that WW4 has an enhanced affinity for a Smad7 peptide phosphorylated at serine 206 adjacent to the PPxY motif. Using the same approach, we show that the WW3 domain also binds Smad7 and has significantly enhanced Smad7 binding affinity when expressed in tandem with the WW4 domain. Furthermore, and relevant to these biophysical findings, we present evidence for a novel WWP2 isoform (WWP2C-ΔHECT) comprising WW3–WW4 tandem domains and a truncated HECT domain that can inhibit TGFβ signalling pathway activity, providing a further layer of complexity and feedback to the WWP2 regulatory apparatus. Collectively, our data reveal a structural platform for Smad substrate selection by WWP2 isoform WW domains that may be significant in the context of WWP2 isoform switching linked to tumorigenesis.

Next Generation Techniques for Determination of Protein-Protein Interactions: Beyond the Crystal Structure

PURPOSE OF REVIEW

We discuss recent advancements in structural biology methods for investigating sites of protein-protein interactions. We will inform readers outside the field of structural biology about techniques beyond crystallography, and how these different technologies can be utilized for drug development.

RECENT FINDINGS

Advancements in cryo-electron microscopy (cryoEM) and micro-electron diffraction (microED) may change how we view atomic resolution structural biology, such that well-ordered macrocrystals of protein complexes are not required for interface identification. However, some drug discovery applications, such as lead peptide compound generation, may not require atomic resolution; mass spectrometry techniques can provide an expedited path to generation of lead compounds. New crosslinking compounds, more user-friendly data analysis, and novel protocols such as protein painting can advance drug discovery programs, even in the absence of atomic resolution structural data. Finally, artificial intelligence and machine learning methods, while never truly replacing experimental methods, may provide rational ways to stratify potential druggable regions identified with mass spectrometry into higher and lower priority candidates.

SUMMARY

Electron diffraction of nanocrystals combines the benefits of both x-ray diffraction and cryoEM, and may prove to be the next generation of atomic resolution protein-protein interface identification. However, in situations such as peptide drug discovery, mass spectrometry techniques supported by advancements in computational methods will likely prove sufficient to support drug discovery efforts. In addition, these methods can be significantly faster than any crystallographic or cryoEM methods for identification of interacting regions.

A Coordinated Response at The Transcriptome and Interactome Level is Required to Ensure Uropathogenic Escherichia coli Survival during Bacteremia

Localized infections or disruption of the skin barrier can enable the entry of bacteria into the bloodstream, possibly leading to acute inflammation and sepsis. There is currently no holistic view on how bacteria can survive and spread in the bloodstream. In this context, we combined transposon mutagenesis, gene-expression profiling and a protein interaction network analysis to examine how uropathogenic Escherichia coli can proliferate in blood. Our results indicate that, upon migration from the urea to serum, E. coli reacts to the osmolarity difference, triggering a transcriptomic response in order to express survival genes. The proteins codified by these genes are precisely organized at the interactome level and specifically target short linear motifs located in disordered regions of host proteins. Such a coordinated response helps to explain how bacteria can adapt to and survive environmental changes within the host. Overall, our results provide a general framework for the study of bacteremia and reveal new targets for potential study as novel antimicrobials.

Machine Learning in Quantitative Protein–peptide Affinity Prediction: Implications for Therapeutic Peptide Design

Background:

Protein–peptide recognition plays an essential role in the orchestration and regulation of cell signaling networks, which is estimated to be responsible for up to 40% of biological interaction events in the human interactome and has recently been recognized as a new and attractive druggable target for drug development and disease intervention.

Methods:

We present a systematic review on the application of machine learning techniques in the quantitative modeling and prediction of protein–peptide binding affinity, particularly focusing on its implications for therapeutic peptide design. We also briefly introduce the physical quantities used to characterize protein–peptide affinity and attempt to extend the content of generalized machine learning methods.

Results:

Existing issues and future perspective on the statistical modeling and regression prediction of protein– peptide binding affinity are discussed.

Conclusion:

There is still a long way to go before establishment of general, reliable and efficient machine leaningbased protein–peptide affinity predictors.

Protein-Catalyzed Capture Agents

Protein-catalyzed capture agents (PCCs) are synthetic and modular peptide-based affinity agents that are developed through the use of single-generation in situ click chemistry screens against large peptide libraries. In such screens, the target protein, or a synthetic epitope fragment of that protein, provides a template for selectively promoting the noncopper catalyzed azide-alkyne dipolar cycloaddition click reaction between either a library peptide and a known ligand or a library peptide and the synthetic epitope. The development of epitope-targeted PCCs was motivated by the desire to fully generalize pioneering work from the Sharpless and Finn groups in which in situ click screens were used to develop potent, divalent enzymatic inhibitors. In fact, a large degree of generality has now been achieved. Various PCCs have demonstrated utility for selective protein detection, as allosteric or direct inhibitors, as modulators of protein folding, and as tools for in vivo tumor imaging. We provide a historical context for PCCs and place them within the broader scope of biological and synthetic aptamers. The development of PCCs is presented as (i) Generation I PCCs, which are branched ligands engineered through an iterative, nonepitope-targeted process, and (ii) Generation II PCCs, which are typically developed from macrocyclic peptide libraries and are precisely epitope-targeted. We provide statistical comparisons of Generation II PCCs relative to monoclonal antibodies in which the protein target is the same. Finally, we discuss current challenges and future opportunities of PCCs.

Modeling ErbB2-p130Cas interaction to design new potential anticancer agents

The ErbB2 receptor tyrosine kinase is overexpressed in approximately 15–20% of breast tumors and associated with aggressive disease and poor clinical outcome. p130Cas represents a nodal scaffold protein regulating cell survival, migration and proliferation in normal and pathological contexts. p130Cas overexpression in ErbB2 human breast cancer correlates with poor prognosis and metastasis formation. Recent data indicate that p130Cas association to ErbB2 protects ErbB2 from degradation, thus enhancing tumorigenesis. Therefore, inhibiting p130Cas/ErbB2 interaction might represent a new therapeutic strategy to target breast cancer. Here we demonstrate by performing Molecular Modeling, Molecular Dynamics, dot blot, ELISA and fluorescence quenching experiments, that p130Cas binds directly to ErbB2. Then, by structure-based virtual screening, we identified two potential inhibitors of p130Cas/ErbB2 interaction. Their experimental validation was performed in vitro and in ErbB2-positive breast cancer cellular models. The results highlight that both compounds interfere with p130Cas/ErbB2 binding and significantly affect cell proliferation and sensitivity to Trastuzumab. Overall, this study identifies p130Cas/ErbB2 complex as a potential breast cancer target revealing new therapeutic perspectives for protein-protein interaction (PPI).

Reciprocal regulation of integrin β4 and KLF4 promotes gliomagenesis through maintaining cancer stem cell traits

BACKGROUND

The dismal prognosis of patients with glioma is largely attributed to cancer stem cells that display pivotal roles in tumour initiation, progression, metastasis, resistance to therapy, and relapse. Therefore, understanding how these populations of cells maintain their stem-like properties is critical in developing effective glioma therapeutics.

METHODS

RNA sequencing analysis was used to identify genes potentially involved in regulating glioma stem cells (GSCs). Integrin β4 (ITGB4) expression was validated by quantitative real-time PCR (qRT-PCR) and immunohistochemical (IHC) staining. The role of ITGB4 was investigated by flow cytometry, mammosphere formation, transwell, colony formation, and in vivo tumorigenesis assays. The reciprocal regulation between Integrin β4 and KLF4 was investigated by chromatin immunoprecipitation (ChIP), dual-luciferase reporter assay, immunoprecipitation, and in vivo ubiquitylation assays.

RESULTS

In this study, we found that ITGB4 expression was increased in GSCs and human glioma tissues. Upregulation of ITGB4 was correlated with glioma grades. Inhibition of ITGB4 in glioma cells decreased the self-renewal abilities of GSCs and suppressed the malignant behaviours of glioma cells in vitro and in vivo. Further mechanistic studies revealed that KLF4, an important transcription factor, directly binds to the promoter of ITGB4, facilitating its transcription and contributing to increased ITGB4 expression in glioma. Interestingly, this increased expression enabled ITGB4 to bind KLF4, thus attenuating its interaction with its E3 ligase, the von Hippel-Lindau (VHL) protein, which subsequently decreases KLF4 ubiquitination and leads to its accumulation.

CONCLUSIONS

Collectively, our data indicate the existence of a positive feedback loop between KLF4 and ITGB4 that promotes GSC self-renewal and gliomagenesis, suggesting that ITGB4 may be a valuable therapeutic target for glioma.

DIBS: a repository of disordered binding sites mediating interactions with ordered proteins

Motivation

Intrinsically Disordered Proteins (IDPs) mediate crucial protein–protein interactions, most notably in signaling and regulation. As their importance is increasingly recognized, the detailed analyses of specific IDP interactions opened up new opportunities for therapeutic targeting. Yet, large scale information about IDP-mediated interactions in structural and functional details are lacking, hindering the understanding of the mechanisms underlying this distinct binding mode.

Results

Here, we present DIBS, the first comprehensive, curated collection of complexes between IDPs and ordered proteins. DIBS not only describes by far the highest number of cases, it also provides the dissociation constants of their interactions, as well as the description of potential post-translational modifications modulating the binding strength and linear motifs involved in the binding. Together with the wide range of structural and functional annotations, DIBS will provide the cornerstone for structural and functional studies of IDP complexes.

Availability and implementation

DIBS is freely accessible at http://dibs.enzim.ttk.mta.hu/. The DIBS application is hosted by Apache web server and was implemented in PHP. To enrich querying features and to enhance backend performance a MySQL database was also created.

Supplementary information

Supplementary data are available at Bioinformatics online.