Screening Intrinsically Disordered Regions for Short Linear Binding Motifs

ASXLs binding to the PHD2/3 fingers of MLL4 provides a mechanism for the recruitment of BAP1 to active enhancers

The human methyltransferase and transcriptional coactivator MLL4 and its paralog MLL3 are frequently mutated in cancer. MLL4 and MLL3 monomethylate histone H3K4 and contain a set of uncharacterized PHD fingers. Here, we report a novel function of the PHD2 and PHD3 (PHD2/3) fingers of MLL4 and MLL3 that bind to ASXL2, a component of the Polycomb repressive H2AK119 deubiquitinase (PR-DUB) complex. The structure of MLL4 PHD2/3 in complex with the MLL-binding helix (MBH) of ASXL2 and mutational analyses reveal the molecular mechanism which is conserved in homologous ASXL1 and ASXL3. The native interaction of the Trithorax MLL3/4 complexes with the PR-DUB complex in vivo depends solely on MBH of ASXL1/2, coupling the two histone modifying activities. ChIP-seq analysis in embryonic stem cells demonstrates that MBH of ASXL1/2 is required for the deubiquitinase BAP1 recruitment to MLL4-bound active enhancers. Our findings suggest an ASXL1/2-dependent functional link between the MLL3/4 and PR-DUB complexes.

MLL4 binds TET3

Human mixed lineage leukemia 4 (MLL4), also known as KMT2D, regulates cell type specific transcriptional programs through enhancer activation. Along with the catalytic methyltransferase domain, MLL4 contains seven less characterized plant homeodomain (PHD) fingers. Here, we report that the sixth PHD finger of MLL4 (MLL4PHD6) binds to the hydrophobic motif of ten-eleven translocation 3 (TET3), a dioxygenase that converts methylated cytosine into oxidized derivatives. The solution NMR structure of the TET3-MLL4PHD6 complex and binding assays show that, like histone H4 tail, TET3 occupies the hydrophobic site of MLL4PHD6, and that this interaction is conserved in the seventh PHD finger of homologous MLL3 (MLL3PHD7). Analysis of genomic localization of endogenous MLL4 and ectopically expressed TET3 in mouse embryonic stem cells reveals a high degree overlap on active enhancers and suggests a potential functional relationship of MLL4 and TET3.

ELM-the Eukaryotic Linear Motif resource-2024 update

Short Linear Motifs (SLiMs) are the smallest structural and functional components of modular eukaryotic proteins. They are also the most abundant, especially when considering post-translational modifications. As well as being found throughout the cell as part of regulatory processes, SLiMs are extensively mimicked by intracellular pathogens. At the heart of the Eukaryotic Linear Motif (ELM) Resource is a representative (not comprehensive) database. The ELM entries are created by a growing community of skilled annotators and provide an introduction to linear motif functionality for biomedical researchers. The 2024 ELM update includes 346 novel motif instances in areas ranging from innate immunity to both protein and RNA degradation systems. In total, 39 classes of newly annotated motifs have been added, and another 17 existing entries have been updated in the database. The 2024 ELM release now includes 356 motif classes incorporating 4283 individual motif instances manually curated from 4274 scientific publications and including >700 links to experimentally determined 3D structures. In a recent development, the InterPro protein module resource now also includes ELM data. ELM is available at: http://elm.eu.org.

Identification of motif-based interactions between SARS-CoV-2 protein domains and human peptide ligands pinpoint antiviral targets

The virus life cycle depends on host-virus protein-protein interactions, which often involve a disordered protein region binding to a folded protein domain. Here, we used proteomic peptide phage display (ProP-PD) to identify peptides from the intrinsically disordered regions of the human proteome that bind to folded protein domains encoded by the SARS-CoV-2 genome. Eleven folded domains of SARS-CoV-2 proteins were found to bind 281 peptides from human proteins, and affinities of 31 interactions involving eight SARS-CoV-2 protein domains were determined (KD ∼ 7-300 μM). Key specificity residues of the peptides were established for six of the interactions. Two of the peptides, binding Nsp9 and Nsp16, respectively, inhibited viral replication. Our findings demonstrate how high-throughput peptide binding screens simultaneously identify potential host-virus interactions and peptides with antiviral properties. Furthermore, the high number of low-affinity interactions suggest that overexpression of viral proteins during infection may perturb multiple cellular pathways.

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.

Assessing structure and disorder prediction tools for de novo emerged proteins in the age of machine learning

Background: De novo protein coding genes emerge from scratch in the non-coding regions of the genome and have, per definition, no homology to other genes. Therefore, their encoded de novo proteins belong to the so-called "dark protein space". So far, only four de novo protein structures have been experimentally approximated. Low homology, presumed high disorder and limited structures result in low confidence structural predictions for de novo proteins in most cases. Here, we look at the most widely used structure and disorder predictors and assess their applicability for de novo emerged proteins. Since AlphaFold2 is based on the generation of multiple sequence alignments and was trained on solved structures of largely conserved and globular proteins, its performance on de novo proteins remains unknown. More recently, natural language models of proteins have been used for alignment-free structure predictions, potentially making them more suitable for de novo proteins than AlphaFold2. Methods: We applied different disorder predictors (IUPred3 short/long, flDPnn) and structure predictors, AlphaFold2 on the one hand and language-based models (Omegafold, ESMfold, RGN2) on the other hand, to four de novo proteins with experimental evidence on structure. We compared the resulting predictions between the different predictors as well as to the existing experimental evidence. Results: Results from IUPred, the most widely used disorder predictor, depend heavily on the choice of parameters and differ significantly from flDPnn which has been found to outperform most other predictors in a comparative assessment study recently. Similarly, different structure predictors yielded varying results and confidence scores for de novo proteins. Conclusions: We suggest that, while in some cases protein language model based approaches might be more accurate than AlphaFold2, the structure prediction of de novo emerged proteins remains a difficult task for any predictor, be it disorder or structure.

Reciprocal regulatory balance within the CLEC16A-RNF41 mitophagy complex depends on an intrinsically disordered protein region

CLEC16A is an E3 ubiquitin ligase that regulates mitochondrial quality control through mitophagy and is associated with over 20 human diseases. CLEC16A forms a complex with another E3 ligase, RNF41, and a ubiquitin-specific peptidase, USP8; however, regions that regulate CLEC16A activity or the assembly of the tripartite mitophagy regulatory complex are unknown. Here, we report that CLEC16A contains an internal intrinsically disordered protein region (IDPR) that is crucial for CLEC16A function and turnover. IDPRs lack a fixed secondary structure and possess emerging, yet still equivocal roles in protein stability, interactions, and enzymatic activity. We find that the internal IDPR of CLEC16A is crucial for its degradation. CLEC16A turnover was promoted by RNF41, which binds and acts upon the internal IDPR to destabilize CLEC16A. Loss of this internal IDPR also destabilized the ubiquitin-dependent tripartite CLEC16A-RNF41-USP8 complex. Finally, the presence of an internal IDPR within CLEC16A was confirmed using NMR and circular dichroism spectroscopy. Together, our studies reveal that an IDPR is essential to control the reciprocal regulatory balance between CLEC16A and RNF41, which could be targeted to improve mitochondrial health in disease.

Heterologous expression of naturally evolved putative de novo proteins with chaperones

Over the past decade, evidence has accumulated that new protein‐coding genes can emerge de novo from previously non‐coding DNA. Most studies have focused on large scale computational predictions of de novo protein‐coding genes across a wide range of organisms. In contrast, experimental data concerning the folding and function of de novo proteins are scarce. This might be due to difficulties in handling de novo proteins in vitro, as most are short and predicted to be disordered. Here, we propose a guideline for the effective expression of eukaryotic de novo proteins in Escherichia coli. We used 11 sequences from Drosophila melanogaster and 10 from Homo sapiens, that are predicted de novo proteins from former studies, for heterologous expression. The candidate de novo proteins have varying secondary structure and disorder content. Using multiple combinations of purification tags, E. coli expression strains, and chaperone systems, we were able to increase the number of solubly expressed putative de novo proteins from 30% to 62%. Our findings indicate that the best combination for expressing putative de novo proteins in E. coli is a GST‐tag with T7 Express cells and co‐expressed chaperones. We found that, overall, proteins with higher predicted disorder were easier to express.

The Eukaryotic Linear Motif resource: 2022 release

Almost twenty years after its initial release, the Eukaryotic Linear Motif (ELM) resource remains an invaluable source of information for the study of motif-mediated protein-protein interactions. ELM provides a comprehensive, regularly updated and well-organised repository of manually curated, experimentally validated short linear motifs (SLiMs). An increasing number of SLiM-mediated interactions are discovered each year and keeping the resource up-to-date continues to be a great challenge. In the current update, 30 novel motif classes have been added and five existing classes have undergone major revisions. The update includes 411 new motif instances mostly focused on cell-cycle regulation, control of the actin cytoskeleton, membrane remodelling and vesicle trafficking pathways, liquid-liquid phase separation and integrin signalling. Many of the newly annotated motif-mediated interactions are targets of pathogenic motif mimicry by viral, bacterial or eukaryotic pathogens, providing invaluable insights into the molecular mechanisms underlying infectious diseases. The current ELM release includes 317 motif classes incorporating 3934 individual motif instances manually curated from 3867 scientific publications. ELM is available at: http://elm.eu.org.

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.

Structural Insights into Protein Regulation by Phosphorylation and Substrate Recognition of Protein Kinases/Phosphatases

Protein phosphorylation is one of the most widely observed and important post-translational modification (PTM) processes. Protein phosphorylation is regulated by protein kinases, each of which covalently attaches a phosphate group to an amino acid side chain on a serine (Ser), threonine (Thr), or tyrosine (Tyr) residue of a protein, and by protein phosphatases, each of which, conversely, removes a phosphate group from a phosphoprotein. These reversible enzyme activities provide a regulatory mechanism by activating or deactivating many diverse functions of proteins in various cellular processes. In this review, their structures and substrate recognition are described and summarized, focusing on Ser/Thr protein kinases and protein Ser/Thr phosphatases, and the regulation of protein structures by phosphorylation. The studies reviewed here and the resulting information could contribute to further structural, biochemical, and combined studies on the mechanisms of protein phosphorylation and to drug discovery approaches targeting protein kinases or protein phosphatases.

Tandem domain structure determination based on a systematic enumeration of conformations

Protein structure determination is undergoing a change of perspective due to the larger importance taken in biology by the disordered regions of biomolecules. In such cases, the convergence criterion is more difficult to set up and the size of the conformational space is a obstacle to exhaustive exploration. A pipeline is proposed here to exhaustively sample protein conformations using backbone angle limits obtained by nuclear magnetic resonance (NMR), and then to determine the populations of conformations. The pipeline is applied to a tandem domain of the protein whirlin. An original approach, derived from a reformulation of the Distance Geometry Problem is used to enumerate the conformations of the linker connecting the two domains. Specifically designed procedure then permit to assemble the domains to the linker conformations and to optimize the tandem domain conformations with respect to two sets of NMR measurements: residual dipolar couplings and paramagnetic resonance enhancements. The relative populations of optimized conformations are finally determined by fitting small angle X-ray scattering (SAXS) data. The most populated conformation of the tandem domain is a semi-closed one, fully closed and more extended conformations being in minority, in agreement with previous observations. The SAXS and NMR data show different influences on the determination of populations.

Identification of PDZ Interactions by Proteomic Peptide Phage Display

PSD95-Disc large-Zonula occludens (PDZ) domains are among the most abundant modular domains in the human proteome. They typically bind short carboxy-terminal sequence motifs of their ligand proteins, which may be transmembrane proteins such as ion channels and GPCRs, as well as soluble proteins. The identity of the endogenous ligands of many PDZ domains remains unclear despite more than two decades of PDZ research. Combinatorial peptide phage display and bioinformatics predictions have contributed to shed light on PDZ-mediated interactions. However, the efficiency of these methods for the identification of interactions of potential biological relevance is hampered by different biases. Proteomic peptide-phage display (ProP-PD) was developed to overcome these limitations. Here we describe a ProP-PD protocol for the identification of C-terminal PDZ domain ligands. The method efficiently identifies peptide ligands within a proteome of interest, and pinpoint targets of potential biological relevance.