The human methyltransferases mixed lineage leukemia 4 and 3 (MLL4 and MLL3) play pivotal roles in the regulation of epigenetic and transcriptional programs. Here, we report the identification and characterization of a tryptophan-phenylalanine binding motif recognized by MLL4 and MLL3. Binding of the sixth PHD finger of MLL4 and the seventh PHD finger of MLL3 to the tryptophan-phenylalanine motif derived from a set of human proteins was detected in a proteomic peptide-phage screening of intrinsically disordered regions of the human proteome and confirmed in NMR and MST assays. Mutational, genetic and binding interface analyses reveal the molecular mechanism underlying the direct interaction of MLL4 and MLL3 with the motif. A high correlation of expression of MLL4/MLL3 and the motif containing proteins in several tumor types suggests shared roles in oncogenic transcriptional programs. In conclusion, our findings highlight a potential relationship between the MLL4/MLL3 methyltransferases and diverse motif-containing epigenetic coregulators.

Short linear motifs (SLiMs) within intrinsically disordered protein regions mediate transient interactions crucial for cell physiology1. However, the global interaction landscape of human SLiMs remains largely uncharted. Here we present the Atlas of SLiM-mediated Human protein-protein Interactions (ASHI), which maps more than 20,000 interactions by screening over 800 human protein domains against a library of one million peptides tiling the human disordered proteome. ASHI expands the SLiM interactome, uncovers novel binding modes for known peptide-binding domains, and reveals unexpected peptide-binding activities in enzymes, chaperones, RNA-binding proteins, and modification-reader domains. Furthermore, intrinsically disordered regions emerge as densely encoded interaction platforms where interaction specificity is governed by diverse mechanisms, including key motif determinants, flanking residues, competition, and multivalency. These data provide an unprecedented foundation for modeling dynamic interaction networks, interpreting disease-associated variants, and decoding the dark proteome.

The ubiquitin-specific proteases (USPs) family is the largest family of human deubiquitinating enzymes (DUBs). While most USPs are agnostic to polyubiquitin linkage-type, their substrate specificity is thought to be mediated by the recognition of the ubiquitnated protein itself. In addition to their catalytic domain, USPs have one or more auxiliary domains (ADs) with key functions in regulating DUB activity and localization. We hypothesize that some ADs bind short linear motifs (SLiMs) typically found in intrinsically disordered regions of proteins to achieve targeting to substrates and multiprotein complexes. To test this, we systematically assess the potential of 29 USP-ADs and two full-length USPs for SLiM binding using a combination of proteomic-peptide phage display, peptide SPOT arrays and affinity measurements. We discover SLiM-based interactions for 14 ADs from 9 USP-DUBs, including CYLD, USP11, USP19, USP20, USP22 and USP33, and define the consensus motif and properties of the SLiM-AD binding. Interestingly, we establish that the zf-UBP and DUSP2 domains of USP20 and USP33 are SLiM binding ADs with similar binding profiles, explaining the functional redundancy between the two DUBs. Our work reveals unique motifs recognized by the auxiliary domains CAP-Gly, UBL, zf-UBP and DUSP, with potential functional implications for substrate recognition and complex assemblies.

Deep mutational scanning (DMS) has emerged as a powerful approach for evaluating the effects of mutations on binding or function. Here, we developed a DMS by phage display protocol to define the specificity determinants of short linear motifs (SLiMs) binding to peptide-binding domains. We first designed a benchmarking DMS library to evaluate the performance of the approach on well-known ligands for 11 different peptide-binding domains, including the talin-1 PTB domain, the G3BP1 NTF2 domain, and the MDM2 SWIB domain. Comparison with a set of reference motifs from the eukaryotic linear motif (ELM) database confirmed that the DMS by phage display analysis correctly identifies known motif binding determinants and provides novel insights into specificity determinants, including defining a non-canonical talin-1 PTB binding motif with a putative extended conformation. A second DMS library was designed, aiming to provide information on the binding determinants for 19 SLiM-based interactions between human and SARS-CoV-2 proteins. The analysis confirmed the affinity determining residues of viral peptides binding to host proteins and refined the consensus motifs in human peptides binding to five domains from SARS-CoV-2 proteins, including the non-structural protein (NSP) 9. The DMS analysis further pinpointed mutations that increased the affinity of ligands for NSP3 and NSP9. An affinity-improved cell-permeable NSP9-binding peptide was found to exert stronger antiviral effects than the wild-type peptide. Our study demonstrates that DMS by phage display can efficiently be multiplexed and applied to refine binding determinants and shows how the results can guide peptide-engineering efforts.

Prokaryotic and eukaryotic ribosomes accumulate differences throughout their evolution, including structural variations, which have been targeted to produce drugs with differential action. Following this initial significant divergence, within the eukaryotic lineage, a group of organisms has emerged that possess ribosomes with distinctive characteristics. Trypanosomatids diverged early from the rest of the eukaryotes, and several components of their protein synthesis machinery have developed differences that gave rise to unique domains. Upon studying these differences, we observed that Trypanosoma brucei ribosomal protein L19 (TbL19) possesses distinctive domains at its C-Terminal end, establishing novel interactions between the large and the small subunits of ribosomes. Furthermore, through RNAi downregulation, we demonstrate that TbL19 is essential for the survival of this parasite. Additionally, TbL19 failed to complement conditional-mutant yeasts, highlighting this evolutionary divergence. We propose that this distinct structural feature could serve as a target for new antiparasitic drugs, given its specificity to T. brucei and its close relative, Trypanosoma cruzi.

PDZ domains play key roles in mediating protein-protein interactions by recognizing short PDZ-binding motifs, typically at the C-termini of target proteins. Zonula occludens 1 (ZO-1) is a scaffolding protein that links tight junction proteins to the actin cytoskeleton, and contains three PDZ domains. Here, we focus on its third PDZ (PDZ3_ZO-1) domain, which interacts with the C-terminus of junctional adhesion protein A as well as connexin 45. To investigate how the domain context of the PDZ3_ZO-1 domain affects its folding and function, we previously established two distinct fusions of PDZ3_ZO-1 and a Trp-cage mini-protein. These fusions with swapped domain order result in FD3A with Trp-cage fused C-terminally and FD4A with Trp-cage fused N-terminally. This study aims to explore the extent to which the distinct Trp-cage fusions affect the function of PDZ3_ZO-1 domain in peptide binding. We find that PDZ3_ZO-1 retains its function, interaction with the connexin 45 peptide, also as part of the fusion proteins. Furthermore, using a phage display approach, we identified a new PDZ3_ZO-1 binding peptide derived from the C-terminal region of methylcytosine dioxygenase TET3. Subsequent validation revealed a significantly higher affinity of PDZ3_ZO-1 for the TET3 peptide as compared to the connexin 45 peptide. Thermodynamic analyses revealed that the swapped domain order conferred distinct effects on the thermodynamic parameters. These results provide insights into the structural and functional adaptability of PDZ domains in engineered proteins, and offer useful principles for the rational design of functional fusion proteins.

Ubiquitin-specific protease 8 (USP8) is a deubiquitinating enzyme with essential functions in protein trafficking and stability. It is a multidomain protein, with an N-terminal MIT (microtubule interacting and trafficking) domain, followed by a non-catalytic rhodanese (Rhod) domain, a long intrinsically disordered region, and a C-terminal catalytic domain. The N-terminal MIT domain of USP8 is known to mediate protein-protein interactions through binding to short linear motifs. The non-catalytic Rhod domain is also involved in protein-protein interactions, however detailed insights into these interactions remain limited. In this study we explore the short linear motif-based interactions of the MIT and Rhod domains of USP8 using a combination of proteomic peptide-phage display, peptide arrays and deep mutational scanning. We show that the MIT domain can bind ligands with a general [DE][LIF]x2,3R[FYIL]xxL[LV] consensus motif. We uncover that the rhodanese domain of USP8 is a peptide-binding domain, and define two distinct binding motifs (Rx[LI]xGxxxPxxL and G[LV][DE][IM]WExKxxxLxE) for this domain by deep mutational scanning of two different peptide ligands. Using the motif information, we predict binding sites within known USP8 interactors and substrates and validate interactions through peptide array analysis. Our findings demonstrate that both the USP8 MIT and rhodanese domains are peptide-binding domains that can be bound by degenerate and distinct binding motifs. The detailed information on the peptide binding preference of the two N-terminal domains of USP8 provide novel insights into the molecular recognition events that underlie the function of this essential deubiquitinating enzyme.

Deep mutational scanning (DMS) has emerged as a powerful approach for evaluating the effects of mutations on binding or function. Here, we developed a multiplexed DMS by phage display protocol to define the binding determinants of short linear motifs (SLiMs) binding to peptide binding domains. We first designed a benchmarking DMS library to evaluate the performance of the approach on well-known ligands for eleven different peptide binding domains, including the talin-1 PTB domain. Systematic benchmarking against a gold-standard set of motifs from the eukaryotic linear motif (ELM) database confirmed that the DMS by phage analysis correctly identifies known motif binding determinants. The DMS analysis further defined a non-canonical PTB binding motif, with a putative extended conformation. A second DMS library was designed aiming to provide information on the binding determinants for 19 SLiM-based interactions between human and SARS-CoV-2 proteins. The analysis confirmed the affinity determining residues of viral peptides binding to host proteins, and refined the consensus motifs in human peptides binding to five domains from SARS-CoV-2 proteins, including the non-structural protein (NSP) 9. The DMS analysis further pinpointed mutations that increased the affinity of ligands for NSP3 and NSP9. An affinity improved cell-permeable NSP9-binding peptide was found to exert stronger antiviral effects as compared to the initial wild-type peptide. Our study demonstrates that DMS by phage display can efficiently be multiplexed and applied to refine binding determinants, and shows how DMS by phage display can guide peptide-engineering efforts. ### Competing Interest Statement The authors have declared no competing interest.

AbstractWhole genome and exome sequencing are reporting on hundreds of thousands of missense mutations. Taking a pan-disease approach, we explored how mutations in intrinsically disordered regions (IDRs) break or generate protein interactions mediated by short linear motifs. We created a peptide-phage display library tiling ~57,000 peptides from the IDRs of the human proteome overlapping 12,301 single nucleotide variants associated with diverse phenotypes including cancer, metabolic diseases and neurological diseases. By screening 80 human proteins, we identified 366 mutation-modulated interactions, with half of the mutations diminishing binding, and half enhancing binding or creating novel interaction interfaces. The effects of the mutations were confirmed by affinity measurements. In cellular assays, the effects of motif-disruptive mutations were validated, including loss of a nuclear localisation signal in the cell division control protein CDC45 by a mutation associated with Meier-Gorlin syndrome. The study provides insights into how disease-associated mutations may perturb and rewire the motif-based interactome.

Background Over the past twenty years, numerous motif discovery bioinformatic tools have been developed for discovering short linear motifs (SLiMs) from high-throughput experimental data on domain-peptide interactions. However, these tools are generally evaluated individually and mostly using synthetic data that do not accurately capture the motif context observed within proteomic data. Consequently, it is unclear how these tools perform in real-world use cases and how they perform compared to each other.Results Here, we benchmarked five motif discovery tools and seven general sequence alignment tools on their capacity to find SLiMs. For this purpose we have built MEP-Bench, a benchmarking dataset of peptides of varying complexity from curated SLiM instances from the Eukaryotic Linear Motif database. MEP-Bench allows tools to be tested for the effect of dataset size, peptide length, background noise level and motif complexity on motif discovery. The main metric used to compare all tools was the percentage of correctly aligned SLiM containing peptides. Two motif discovery tools (DEME and SLiMFinder) and a sequence alignment tool (Opal) outperformed the rest of the tools when benchmarked with this metric, averaging over 70% correctly aligned motif-containing peptides. The performance of the motif discovery tools and Opal were not affected by the sizes of the datasets. However, increasing peptide lengths and noise levels decreased all tools’ performances. While all tools performed well for N-/C-terminal motifs, for low-complexity motifs only DEME and SLiMFinder returned correctly aligned motifs for 50% or more of the datasets.Conclusions This study highlights DEME, SLiMFinder and Opal as the best performing tools for finding motifs in short peptides, and it indicates experimental parameters that should be considered given the limitations of the available tools. However, there is room for improvement, as no tool was able to identify all motif types. We propose that MEP-Bench can serve as a valuable resource for the SLiM community to compare new motif discovery methods with those benchmarked here.### Competing Interest StatementThe authors have declared no competing interest.* AT : Alignment Tool ELM : Eukaryotic Linear Motif (database) MDT : Motif Discovery Tool MEP-Bench : Motif Extraction from Peptides Benchmarking (datasets) PSS : Positive Set Size PSSM : Position-Specific Scoring Matrix SLiM : Short Linear Motif

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. Human methyltransferase MLL4 mediates embryonic development and is dysregulated in diseases. Zhang et al. found that binding of PHD fingers of MLL4 to ASXL1/2 is required for recruitment of the deubiquitinase BAP1 to MLL4-bound active enhancers in vitro.

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 ( K D ∼ 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.

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.

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.

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.

Short linear motifs (SLiMs) are a unique and ubiquitous class of protein interaction modules that perform key regulatory functions and drive dynamic complex formation. For decades, interactions mediated by SLiMs have accumulated through detailed low-throughput experiments. Recent methodological advances have opened this previously underexplored area of the human interactome to high-throughput protein-protein interaction discovery. In this article, we discuss that SLiM-based interactions represent a significant blind spot in the current interactomics data, introduce the key methods that are illuminating the elusive SLiM-mediated interactome of the human cell on a large scale, and discuss the implications for the field.

To complement descriptions of scientific methodologies, it is often incredibly valuable to have accompanying figures. In this seventh installment of the Special series: Scientific figure development, recent TIBS authors consider the following questions about how they present technological workflows in a visual manner: what aspects do you consider when generating such a figure? How do you decide how to represent the workflow being described (i.e., organization, background colors, arrows, legends, etc.)? What program(s) do you prefer for generating such figures and why? Contributing to this article are M. Florencia Sánchez, first author of 'Ligand-independent receptor clustering modulates transmembrane signaling: a new paradigm' ([1.Sánchez M.F. Tampé R. Ligand-independent receptor clustering modulates transmembrane signaling: a new paradigm.Trends Biochem. Sci. 2022; 48: 156-171Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar] see Figure 3); Louisa Iselin, first author of 'Uncovering viral RNA–host cell interactions on a proteome-wide scale' ([2.Iselin L. et al.Uncovering viral RNA–host cell interactions on a proteome-wide scale.Trends Biochem. Sci. 2022; 47: 23-38Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar] see Figure 1); and Leandro Simonetti, coauthor of 'ProP-PD for proteome-wide motif-mediated interaction discovery' [3.Davey N.E. et al.ProP-PD for proteome-wide motif-mediated interaction discovery.Trends Biochem. Sci. 2022; 47: 547-548Abstract Full Text Full Text PDF PubMed Scopus (6) Google Scholar] (see both figures). M. Florencia Sánchez The ability of cells to sense changes in their environment and to transmit signals to each other is an essential aspect of multicellular life. Cell–cell communication and signal transduction rely on the assembly of receptor–ligand complexes at the plasma membrane. Unraveling of cellular signaling requires a broad variety of techniques in the fields of molecular and structural biology, biophysics, and cell biology, ranging from the development of complex cloning strategies to the establishment of sensors to detect molecular interactions inside living cells. It is fundamental that all these discoveries are translated into compressive publications to have an impact on the scientific community and society. When generating a figure for an article, I first ask myself what is the message that I want to transmit, and which would be the easiest way to do this. Cartoons instead of text are highly desirable. Further, it is crucial to summarize the most important aspects you would like to present. In Figure 3 of our review: 'Ligand-independent receptor clustering modulates transmembrane signaling: a new paradigm' [1.Sánchez M.F. Tampé R. Ligand-independent receptor clustering modulates transmembrane signaling: a new paradigm.Trends Biochem. Sci. 2022; 48: 156-171Abstract Full Text Full Text PDF PubMed Scopus (4) Google Scholar], I focused on showing the main advantages of the systems I wished to present (optochemistry, optogenetics, and DNA technology) and their main working principles with cartoons. For the cartoons, it is important to use complementary colors and, for the background, I frequently use transparency since it enables differentiation of the figure from the rest of the text, but does not disturb its interpretation. Arrows should not dominate the figure, and I generally choose gray colors instead of black. Adobe Illustrator is a very complete program which I use on a daily basis. As a complement, Biorender is another software which I consider of high interest for scientists. Overall, I have acquired experience by practicing, which I think is the principal way of learning. Louisa Iselin For our review 'Uncovering viral RNA–host cell interactions on a proteome-wide scale' [2.Iselin L. et al.Uncovering viral RNA–host cell interactions on a proteome-wide scale.Trends Biochem. Sci. 2022; 47: 23-38Abstract Full Text Full Text PDF PubMed Scopus (10) Google Scholar], we wanted to make a figure summarizing seven different methods that were discussed in the paper. These methods shared a common workflow but differed in the ways that they approached each step in the protocol. We initially considered describing each method separately; however, we realized that it was critical to both show their shared underlying principles and highlight their key differences. The main challenge of this approach was preserving the important details of each method while avoiding the figure becoming incoherent and overcrowded. We employed a few different strategies to help achieve this. First, we used simple and consistent icons, instead of attempting to make them look 'realistic'. For example, by using the same single hexagon to represent an exemplar RNA-binding protein throughout the workflow, we not only decluttered the figure but also made comparisons across different methods simpler. We combined these icons with changes in color to highlight variations, such as 4SU labeled and unlabeled RNA, or different wavelengths of UV radiation. Second, the use of consistent icons allowed us to add an explanatory legend, instead including labels within the figure. This made the schematic more visually coherent, simple, and conceptual without losing important details that could be needed to understand the methods. Third, we removed unnecessary and repeated details that felt important to us as biologists in highlighting the complexity of the system but were not necessarily relevant to understand the principles underpinning the method. Removing duplicated information, such as multiple biotin molecules or antisense probes, gave us more space to clarify the important aspects of the visual and reduced clutter. Leandro Simonetti When building a complex figure, I start by planning it together with my coworkers. We brainstorm to define the main idea to convey and the pieces needed to showcase it. Before jumping into figure-making, we iteratively hand-draw sketches of the figure, trying to nail the necessary text and graphics and their general layout. The main goal at this stage is to remove unnecessary parts while keeping all key elements. Finding this balance is usually the hardest part and the general rule is always 'simpler is better'. Once the basic idea is set, I move into making the figure. I find it's good practice to first define some parameters: font sizes (complying to journal requirements), border and arrow thicknesses, boxes' round corner's size, and so on. For the color palette I tend to google color-blind friendly palettes and work from there. Ideally, I use colors to either highlight parts of the figure or to establish a language along the figure (like 'proteins are green, DNA is blue', etc.). Then, I build all assets trying to make them clearly distinguishable: each asset type should have a unique and readable silhouette. I use open source software(s) to make the figure. Inkscape (https://inkscape.org/) is my preferred vector-based graphic tool. If 3D assets are needed, I use Blender 3D (https://www.blender.org/) to set their shapes and viewing angle. Blender's particle system is also a very good tool to randomly distribute objects. Finally, when laying-out all the components, I try to place them on an uninterrupted path with consistent spacing and with the arrows aligned to said path. Once the figure feels complete, I share it with someone unrelated to its planning and ask what they understand from it. This usually provides valuable feedback on what sections are obscure and can be improved.

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.