Large-scale survey and database of high affinity ligands for peptide recognition modules

Cell-Penetrating Milk-Derived Peptides with a Non-Inflammatory Profile

Milk-derived peptides are known to confer anti-inflammatory effects. We hypothesised that milk-derived cell-penetrating peptides might modulate inflammation in useful ways. Using computational techniques, we identified and synthesised peptides from the milk protein Alpha-S1-casein that were predicted to be cell-penetrating using a machine learning predictor. We modified the interpretation of the prediction results to consider the effects of histidine. Peptides were then selected for testing to determine their cell penetrability and anti-inflammatory effects using HeLa cells and J774.2 mouse macrophage cell lines. The selected peptides all showed cell penetrating behaviour, as judged using confocal microscopy of fluorescently labelled peptides. None of the peptides had an effect on either the NF-κB transcription factor or TNFα and IL-1β secretion. Thus, the identified milk-derived sequences have the ability to be internalised into the cell without affecting cell homeostatic mechanisms such as NF-κB activation. These peptides are worthy of further investigation for other potential bioactivities or as a naturally derived carrier to promote the cellular internalisation of other active peptides.

Large-scale phosphomimetic screening identifies phospho-modulated motif-based protein interactions

Phosphorylation is a ubiquitous post-translation modification that regulates protein function by promoting, inhibiting or modulating protein-protein interactions. Hundreds of thousands of phosphosites have been identified but the vast majority have not been functionally characterised and it remains a challenge to decipher phosphorylation events modulating interactions. We generated a phosphomimetic proteomic peptide-phage display library to screen for phosphosites that modulate short linear motif-based interactions. The peptidome covers ~13,500 phospho-serine/threonine sites found in the intrinsically disordered regions of the human proteome. Each phosphosite is represented as wild-type and phosphomimetic variant. We screened 71 protein domains to identify 248 phosphosites that modulate motif-mediated interactions. Affinity measurements confirmed the phospho-modulation of 14 out of 18 tested interactions. We performed a detailed follow-up on a phospho-dependent interaction between clathrin and the mitotic spindle protein hepatoma-upregulated protein (HURP), demonstrating the essentiality of the phospho-dependency to the mitotic function of HURP. Structural characterisation of the clathrin-HURP complex elucidated the molecular basis for the phospho-dependency. Our work showcases the power of phosphomimetic ProP-PD to discover novel phospho-modulated interactions required for cellular function.

Large-scale phage-based screening reveals extensive pan-viral mimicry of host short linear motifs

Viruses mimic host short linear motifs (SLiMs) to hijack and deregulate cellular functions. Studies of motif-mediated interactions therefore provide insight into virus-host dependencies, and reveal targets for therapeutic intervention. Here, we describe the pan-viral discovery of 1712 SLiM-based virus-host interactions using a phage peptidome tiling the intrinsically disordered protein regions of 229 RNA viruses. We find mimicry of host SLiMs to be a ubiquitous viral strategy, reveal novel host proteins hijacked by viruses, and identify cellular pathways frequently deregulated by viral motif mimicry. Using structural and biophysical analyses, we show that viral mimicry-based interactions have similar binding strength and bound conformations as endogenous interactions. Finally, we establish polyadenylate-binding protein 1 as a potential target for broad-spectrum antiviral agent development. Our platform enables rapid discovery of mechanisms of viral interference and the identification of potential therapeutic targets which can aid in combating future epidemics and pandemics.

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.

Peptide-binding specificity prediction using fine-tuned protein structure prediction networks

Peptide-binding proteins play key roles in biology, and predicting their binding specificity is a long-standing challenge. While considerable protein structural information is available, the most successful current methods use sequence information alone, in part because it has been a challenge to model the subtle structural changes accompanying sequence substitutions. Protein structure prediction networks such as AlphaFold model sequence-structure relationships very accurately, and we reasoned that if it were possible to specifically train such networks on binding data, more generalizable models could be created. We show that placing a classifier on top of the AlphaFold network and fine-tuning the combined network parameters for both classification and structure prediction accuracy leads to a model with strong generalizable performance on a wide range of Class I and Class II peptide-MHC interactions that approaches the overall performance of the state-of-the-art NetMHCpan sequence-based method. The peptide-MHC optimized model shows excellent performance in distinguishing binding and non-binding peptides to SH3 and PDZ domains. This ability to generalize well beyond the training set far exceeds that of sequence-only models and should be particularly powerful for systems where less experimental data are available.

Plasma proteome profiling identifies changes associated to AD but not to FTD

BACKGROUND

Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process.

METHODS

Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis.

RESULTS

Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified.

CONCLUSIONS

We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

SRC homology 3 domains: multifaceted binding modules

The assembly of complexes following the detection of extracellular signals is often controlled by signaling proteins comprising multiple peptide binding modules. The SRC homology (SH)3 family represents the archetypical modular protein interaction module, with ~300 annotated SH3 domains in humans that regulate an impressive array of signaling processes. We review recent findings regarding the allosteric contributions of SH3 domains host protein context, their phosphoregulation, and their roles in phase separation that challenge the simple model in which SH3s are considered to be portable domains binding to specific proline-rich peptide motifs.

Use of viral motif mimicry improves the proteome-wide discovery of human linear motifs

Linear motifs have an integral role in dynamic cell functions, including cell signaling. However, due to their small size, low complexity, and frequent mutations, identifying novel functional motifs poses a challenge. Viruses rely extensively on the molecular mimicry of cellular linear motifs. In this study, we apply systematic motif prediction combined with functional filters to identify human linear motifs convergently evolved also in viral proteins. We observe an increase in the sensitivity of motif prediction and improved enrichment in known instances. We identify >7,300 non-redundant motif instances at various confidence levels, 99 of which are supported by all functional and structural filters. Overall, we provide a pipeline to improve the identification of functional linear motifs from interactomics datasets and a comprehensive catalog of putative human motifs that can contribute to our understanding of the human domain-linear motif code and the associated mechanisms of viral interference.

Orchestrating serine/threonine phosphorylation and elucidating downstream effects by short linear motifs

Cellular function is based on protein-protein interactions. A large proportion of these interactions involves the binding of short linear motifs (SLiMs) by folded globular domains. These interactions are regulated by post-translational modifications, such as phosphorylation, that create and break motif binding sites or tune the affinity of the interactions. In addition, motif-based interactions are involved in targeting serine/threonine kinases and phosphatases to their substrate and contribute to the specificity of the enzymatic actions regulating which sites are phosphorylated. Here, we review how SLiM-based interactions assist in determining the specificity of serine/threonine kinases and phosphatases, and how phosphorylation, in turn, affects motif-based interactions. We provide examples of SLiM-based interactions that are turned on/off, or are tuned by serine/threonine phosphorylation and exemplify how this affects SLiM-based protein complex formation.

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.

Proteome-scale mapping of binding sites in the unstructured regions of the human proteome

Specific protein-protein interactions are central to all processes that underlie cell physiology. Numerous studies have together identified hundreds of thousands of human protein-protein interactions. However, many interactions remain to be discovered, and low affinity, conditional, and cell type-specific interactions are likely to be disproportionately underrepresented. Here, we describe an optimized proteomic peptide-phage display library that tiles all disordered regions of the human proteome and allows the screening of ~ 1,000,000 overlapping peptides in a single binding assay. We define guidelines for processing, filtering, and ranking the results and provide PepTools, a toolkit to annotate the identified hits. We uncovered >2,000 interaction pairs for 35 known short linear motif (SLiM)-binding domains and confirmed the quality of the produced data by complementary biophysical or cell-based assays. Finally, we show how the amino acid resolution-binding site information can be used to pinpoint functionally important disease mutations and phosphorylation events in intrinsically disordered regions of the proteome. The optimized human disorderome library paired with PepTools represents a powerful pipeline for unbiased proteome-wide discovery of SLiM-based interactions.

Discovery of an exosite on the SOCS2-SH2 domain that enhances SH2 binding to phosphorylated ligands

Suppressor of cytokine signaling (SOCS)2 protein is a key negative regulator of the growth hormone (GH) and Janus kinase (JAK)-Signal Transducers and Activators of Transcription (STAT) signaling cascade. The central SOCS2-Src homology 2 (SH2) domain is characteristic of the SOCS family proteins and is an important module that facilitates recognition of targets bearing phosphorylated tyrosine (pTyr) residues. Here we identify an exosite on the SOCS2-SH2 domain which, when bound to a non-phosphorylated peptide (F3), enhances SH2 affinity for canonical phosphorylated ligands. Solution of the SOCS2/F3 crystal structure reveals F3 as an α-helix which binds on the opposite side of the SH2 domain to the phosphopeptide binding site. F3:exosite binding appears to stabilise the SOCS2-SH2 domain, resulting in slower dissociation of phosphorylated ligands and consequently, enhances binding affinity. This biophysical enhancement of SH2:pTyr binding affinity translates to increase SOCS2 inhibition of GH signaling.

Large scale discovery of coronavirus-host factor protein interaction motifs reveals SARS-CoV-2 specific mechanisms and vulnerabilities

Viral proteins make extensive use of short peptide interaction motifs to hijack cellular host factors. However, most current large-scale methods do not identify this important class of protein-protein interactions. Uncovering peptide mediated interactions provides both a molecular understanding of viral interactions with their host and the foundation for developing novel antiviral reagents. Here we describe a viral peptide discovery approach covering 23 coronavirus strains that provides high resolution information on direct virus-host interactions. We identify 269 peptide-based interactions for 18 coronaviruses including a specific interaction between the human G3BP1/2 proteins and an ΦxFG peptide motif in the SARS-CoV-2 nucleocapsid (N) protein. This interaction supports viral replication and through its ΦxFG motif N rewires the G3BP1/2 interactome to disrupt stress granules. A peptide-based inhibitor disrupting the G3BP1/2-N interaction dampened SARS-CoV-2 infection showing that our results can be directly translated into novel specific antiviral reagents.

Systems Biology to Understand and Regulate Human Retroviral Proinflammatory Response

The majority of human genome are non-coding genes. Recent research have revealed that about half of these genome sequences make up of transposable elements (TEs). A branch of these belong to the endogenous retroviruses (ERVs), which are germline viral infection that occurred over millions of years ago. They are generally harmless as evolutionary mutations have made them unable to produce viral agents and are mostly epigenetically silenced. Nevertheless, ERVs are able to express by still unknown mechanisms and recent evidences have shown links between ERVs and major proinflammatory diseases and cancers. The major challenge is to elucidate a detailed mechanistic understanding between them, so that novel therapeutic approaches can be explored. Here, we provide a brief overview of TEs, human ERVs and their links to microbiome, innate immune response, proinflammatory diseases and cancer. Finally, we recommend the employment of systems biology approaches for future HERV research.

Comprehensive Assessment of the Relationship Between Site-2 Specificity and Helix α2 in the Erbin PDZ Domain

PDZ domains are key players in signalling pathways. These modular domains generally recognize short linear C-terminal stretches of sequences in proteins that organize the formation of complex multi-component assemblies. The development of new methodologies for the characterization of the molecular principles governing these interactions is critical to fully understand the functional diversity of the family and to elucidate biological functions for family members. Here, we applied an in vitro evolution strategy to explore comprehensively the capacity of PDZ domains for specific recognition of different amino acids at a key position in C-terminal peptide ligands. We constructed a phage-displayed library of the Erbin PDZ domain by randomizing the binding site^-2 and adjacent residues, which are all contained in helix α2, and we selected for variants binding to a panel of peptides representing all possible position^-2 residues. This approach generated insights into the basis for the common natural class I and II specificities, demonstrated an alternative basis for a rare natural class III specificity for Asp^-2, and revealed a novel specificity for Arg^-2 that has not been reported in natural PDZ domains. A structure of a PDZ-peptide complex explained the minimum requirement for switching specificity from class I ligands containing Thr/Ser^-2 to class II ligands containing hydrophobic residues at position^-2. A second structure explained the molecular basis for the specificity for ligands containing Arg^-2. Overall, the evolved PDZ variants greatly expand our understanding of site^-2 specificities and the variants themselves may prove useful as building blocks for synthetic biology.