Biology subjects

Schueler-Furman, O.

Publications and source records attributed to Schueler-Furman, O..

At least 19 recordsLinked to original sources

bioRxiv2026

An Atlas of Short Linear Motif-Mediated Human Protein-Protein Interactions

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.

biochemistry↗

bioRxiv2026

Dihydropyrimidines sustain aggressive cancer states by stabilizing DPYSL2

Cancer cell states are governed by coordinated signaling and metabolic networks, yet the mechanisms coupling metabolic activity to oncogenic signaling remain poorly understood. Here, we identify dihydropyrimidines (DHPs), metabolites generated during pyrimidine catabolism, as "signaling metabolites" that sustain aggressive cancer cell states. Depletion of DHPs, either by knockout of the pyrimidine catabolic enzyme DPYD or by expression of the DHP-degrading enzyme DPYS, suppressed STAT3 signaling and attenuated mesenchymal and inflammatory transcriptional programs. Mechanistically, DHPs stabilized DPYSL2, a JAK1-interacting adaptor protein required for efficient STAT3 activation. Structural modeling and thermal stability analyses further support a direct interaction between DHPs and DPYSL2. Accordingly, high DPYD expression was associated with EMT, inflammatory signaling, and poor-prognosis breast cancer subtypes across patient cohorts. Ultimately, our findings establish pyrimidine catabolism as a direct regulator of signaling competence and identify DHPs as signaling-active metabolites that couple cellular metabolic state to oncogenic transcriptional programs and mesenchymal identity.

cancer biology↗

bioRxiv2026

Molecular basis for C-degron recognition by the SCFDas1 ubiquitin ligase

Selective protein degradation by the ubiquitin-proteasome system frequently involves substrate recognition via short linear motifs known as degradation signals or degrons. Whereas degrons located at protein N-termini (N-degrons) have been extensively studied, our understanding of C-terminal degrons (C-degrons) is comparatively limited. Previously, we showed that the yeast SCF ubiquitin ligase and one of its substrate receptor subunits, the F-box protein Das1, target a broad range of C-degrons and implicated SCFDas1 in orphan quality control. Here, we sought to determine how Das1 recognizes its substrates. By combining in vivo competition assays with structural modeling and mutational analysis, we demonstrate that distinct C-degrons compete for a common site on Das1, indicating a shared mode of recognition. We identify a positively charged pocket within the Das1 leucine-rich repeat domain as the C-degron binding site. Three basic residues at the base of this pocket are essential for Das1 function, likely mediating electrostatic interactions with the C-terminal carboxyl group of the degron, while additional residues contribute to substrate specificity. Comparative analysis reveals that this pocket and its function are conserved across the Saccharomycetaceae family, supporting a conserved role for Das1 in protein quality control.

biochemistry↗

bioRxiv2026

Strategic template filtering accelerates fragment-based peptide docking

Peptide-protein interactions are often transient and structurally elusive, necessitating computational approaches to identify both binding sites and peptide conformations. PatchMAN, one of the leading but computationally expensive biophysic-based global peptide-docking protocols, addresses this challenge by treating peptide docking as a protein-folding problem, using structural motifs from solved structures as templates that are subsequently refined using Rosetta FlexPepDock. Here we present PatchMAN2, which introduces 1) strategic fragment filtering and 2) local docking modes that focus sampling on relevant surfaces or known binding regions, thereby reducing the high computational cost of the original implementation due to extensive refinement of many non-productive low-quality fragments. Benchmarking shows that PatchMAN2 removes [~]30-70% of unnecessary fragments while preserving accuracy, substantially reducing runtime and improving the practical efficiency of peptide-protein docking.

bioinformatics↗

bioRxiv2026

CliPepPI: Scalable prediction of domain-peptide specificityusing contrastive learning

Domain-peptide interactions mediate a significant fraction of cellular protein networks, yet accurately predicting their specificity remains challenging. Peptide motifs typically have short, fuzzy sequence profiles, and their interactions are often weak and transient, limiting the size, coverage, and quality of experimentally validated domain-peptide datasets. Since true non-binders are rarely known, constructing negative examples often introduces bias. While structure-based prediction methods can achieve high accuracy, they are computationally demanding and difficult to scale to the proteome level. We introduce CLIPepPI, a dual-encoder model that leverages contrastive learning to embed domains and peptides into a shared space directly from sequence. Both encoders are initialized from a protein language model (ESM-C) and fine-tuned using lightweight LoRA adapters, enabling parameter-efficient training on positive pairs alone. To overcome data scarcity, we augment [~]3K protein-peptide complexes from PPI3D with [~]150K domain-peptide pairs derived from protein-protein interfaces. CLIPepPI further injects structural information by marking interface residues in the domain sequence, thus guiding the encoders toward binding regions and linking sequence-level learning with structural context. Competitive performance is achieved across three independent benchmarks: domain-peptide complexes from PPI3D, large-scale phage-library data from ProP-PD, and a curated dataset of nuclear export signal (NES) sequences. We demonstrate scalability and generalization through two applications: (i) proteome-wide NES scanning, and (ii) variant-effect prediction, where score changes in domain-peptide interactions between wild-type and mutant sequences discriminate pathogenic from benign variants. Together, CLIPepPI offers a scalable, structure-informed model for predicting domain-peptide specificity and generating meaningful embeddings suited for large-scale proteomic analyses. CLIPepPI is available at: https://bio3d.cs.huji.ac.il/webserver/clipeppi/.

bioinformatics↗

bioRxiv2025

Systematic Discovery of Motif-based Interactions of the Auxiliary Domains of USP Family Deubiquitinases

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 ubiquitylated protein itself. In addition to their catalytic domain, USPs have one or more auxiliary domains (ADs) with key functions in regulating DUB activity and subcellular 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 hypothesis, we systematically assessed the potential of 29 USP-ADs and two full-length USPs for SLiM binding using a combination of proteomic-peptide phage display, peptide arrays and affinity measurements. We discovered 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 established 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.

biochemistry↗

bioRxiv2025

Bidirectional control of a metabolic transition by the GID ubiquitin ligase

The GID/CTLH ubiquitin ligase is a multisubunit E3 conserved across eukaryotes. GID/CTLH has been implicated in a variety of processes, including metabolic regulation, cell proliferation, embryonic development and cell differentiation. However, our understanding of substrate recognition by GID/CTLH remains incomplete. Here, we characterize the regulation, specificity and functions of the putative substrate receptor Gid11 in budding yeast. We find that upon its expression during the switch of carbon source from glucose to ethanol, Gid11 associates with the core GID complex, likely forming a large ring assembly. Through systematic mutagenesis, we identify a negatively charged pocket on Gid11 that binds substrates carrying N-terminal degrons starting with threonine and define the Thr/N-degron motif. Such Thr/N-degrons are exposed upon co-translational removal of the initiator methionine, while escaping N-terminal acetylation. Finally, we show that during the switch to ethanol, GIDGid11 targets for degradation factors linked to glycolysis, opposing the established role of GID in the degradation of gluconeogenic enzymes during the reverse switch from ethanol to glucose. Taken together, our results establish Gid11 as a bona fide GID substrate receptor and highlight GID as a regulator of metabolic transitions.

molecular biology↗

bioRxiv2025

Signal peptides as potential structural modulators of human splice isoforms

Signal peptides (SPs) are short protein segments responsible for protein localization, typically cleaved from mature proteins and rapidly degraded after fulfilling their targeting function. Beyond localization however, these sequentially and structurally diverse elements may play additional roles. We explore how alternative splicing potentially creates structural contexts where SPs become integral components of folded domains. Employing AlphaFold and additional computational approaches, we examined a known functional immune protein splice isoform of human SLAMF6 that retains biological activity, despite forming a truncated domain that lacks the central elements of the canonical interaction interface. We revealed striking characteristic similarities between the SLAMF6 SP and the absent segment, indicating its ability to complement and stabilize the isoform domain. An in silico screen of 235,000 reported expressed human isoforms identified several dozen additional candidates with potential SP complementation, previously dismissed as modeling artifacts. Notably, immunoglobulin and carbonic anhydrase domains show particular enrichment among these candidates. SPs are commonly regarded as dispensable elements that can be altered or eliminated when investigating proteins and their structures. Our research proposes an alternative perspective wherein SPs might perform integral roles in stabilizing their source proteins, or others. These findings extend the growing body of evidence for moonlighting SPs, suggesting that we have only begun to uncover their true functional scope. Specifically, SPs emerge as unique modulatory elements essential for understanding the structural and functional behavior of protein splice isoforms.

bioinformatics↗

bioRxiv2024

A Chaperonin Complex Regulates Organelle Proteostasis in Malaria Parasites

The apicoplast of Plasmodium parasites serves as a metabolic hub that synthesize essential biomolecules. Like other endosymbiotic organelles, 90% of the apicoplast proteome is encoded by the cell nucleus and transported to the organelle. Evidence suggests that the apicoplast has minimal control over the synthesis of its proteome and therefore it is unclear how organelle proteostasis is regulated. Here, we identified and investigated a large and conserved chaperonin (CPN) complex with a previously unknown function. Using genetic tools, we demonstrated that ablation of the apicoplast CPN60 subunit leads to parasite death due to organellar damage, immediately within its first replication cycle, deviating from the delayed death phenotype commonly observed for apicoplast translation inhibitors. Unlike its close orthologues in other prokaryotic and eukaryotic cells, CPN60 is not upregulated during heat shock (HS) and does not affect HS response in the parasite. Instead, we found that it is directly involved in proteostasis through interaction with the Clp (caseinolytic protease) proteolytic complex. We showed that CPN60 physically binds both the active and inactive forms of the Clp complex, and manipulates its stability. A computational structural model of a possible interaction between these two large complexes suggests a stable interface. Finally, we screened a panel of inhibitors for the bacterial CPN60 orthologue GroEL, to test the potential of chaperonin inhibition as antimalarial. These inhibitors demonstrated an anti-Plasmodium activity that was not restricted to apicoplast function, with additional targets outsides of this organelle. Taken together, this work reveals how balanced activities of proteolysis and refolding safeguard the apicoplast proteome, and is essential for organelle biogenesis. Author SummaryThe cell of the human malaria parasite Plasmodium falciparum has a unique organelle called the apicoplast that produces essential metabolites, but it is unclear how it maintains a stable proteome. Here, we address the question of organelle proteostasis by investigating the function of a large chaperonin complex and its main subunit CPN60. We show that CPN60 mutants die due to organellar damage immediately within the first replication cycle, avoiding the typical apicoplast-delayed cell death. We demonstrate that it binds and stabilizes another large proteolytic complex and use computational predicting tools to demonstrate how a stable interface is attained. We use bacterial inhibitors to explore their potential as an antimalarial drug target. This study reveals how balanced refolding and proteolysis safeguard the apicoplast proteome and opens a new avenue for antimalarial drug discovery.

microbiology↗

bioRxiv2024

Peptide therapeutic leads for multi-target inhibition of inflammatory cytokines in Inflammatory Bowel Disease - computational design and in-vitro validation

Inflammatory Bowel Disease (IBD) are chronic and recurrent inflammatory disorders affecting the gastrointestinal tract, characterized by the involvement of numerous pro-inflammatory cytokines. These conditions profoundly impact both immune system dynamics and intestinal tissue integrity. Current therapeutic approaches predominantly rely on monoclonal antibodies, and frequently encounter limitations such as non-responsiveness, loss of efficacy over time, immunogenicity, adverse effects, and substantial cost. Consequently, there is a critical need for novel, targeted anti-inflammatory strategies. We present the computational structure guided design of peptidic inhibitors aimed at attenuating the activity of pivotal pro-inflammatory cytokines implicated in IBD pathogenesis, namely TNF, IL-1{beta}, and IL-6. These peptides were engineered to disrupt specific cytokine - receptor interactions, to block the release of pro-inflammatory cytokines. We structurally characterized key features in the studied interactions and used these to guide two computational design strategies, one based on the identification of dominant segments using our PeptiDerive approach, and one based on complementing fragments detected using our PatchMAN protocol. The designed peptides were synthesized and their efficacy was validated on Caco-2 intestinal epithelial cells and THP-1 macrophages, representative of the epithelial and immunological alterations typical of active IBD. The majority of the novel peptides effectively suppressed release of pro-inflammatory cytokines by both macrophages and intestinal epithelial cells, thereby reducing the risk of inflammation. This study underscores the efficacy of a rational design approach rooted in structural insights into inflammatory signaling complexes. Our findings demonstrate the potential of targeting key cytokines and receptor interaction with designed peptides as a promising therapeutic avenue for managing IBD and other inflammatory disorders.

bioinformatics↗

bioRxiv2024

Binding of SARS-CoV-2 nucleocapsid protein to uninfected epithelial cells induces antibody-mediated complement deposition

SARS-CoV-2 infection triggers strong antibody response toward Nucleocapsid-Protein (NP), suggesting extracellular presence beyond its intra-virion RNA binding. Interestingly, NP was found to decorate infected and proximal uninfected cell-surfaces. Here, we propose a new mechanism through which extracellular NP on uninfected cells contributes to COVID-19 pathogenicity. We show that NP binds to cell-surface sulfated linear-glycosaminoglycans by spatial rearrangement of its RNA-binding sites facilitated by the flexible, positively charged, linker. Coating of uninfected lung-derived cells with purified NP attracted anti-NP-IgG from lung fluids and sera collected from COVID-19 patients. The magnitude of this immune recognition was significantly elevated in moderate compared to mild COVID-19 cases. Importantly, binding of anti-NP-IgG present in sera generated clusters that triggered C3b deposition by the classical complement pathway. Heparin analog enoxaparin outcompeted NP-binding, rescuing cells from anti-NP IgG-mediated complement deposition. Our findings unveil how extracellular NP may exacerbate COVID-19 tissue damage, and suggest leads for preventative therapy. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/585388v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1084e20org.highwire.dtl.DTLVardef@4126caorg.highwire.dtl.DTLVardef@159c610org.highwire.dtl.DTLVardef@da7b7f_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIIgG from patients sera target NP-bound cells resulting in complement activation C_LIO_LIThe flexible linker allows NP to both bind linear sulfated GAGs and wrap around RNA C_LIO_LIHeparin analogs prevent NP surface binding and alleviate complement activation C_LIO_LICell-ELISA anti-NP IgG levels differ between mild and moderate COVID-19 C_LI

immunology↗

bioRxiv2024

Substrate recognition principles for PP2A-B55

The PP2A-B55 phosphatase regulates a plethora of signaling pathways throughout eukaryotes. How PP2A-B55 selects its substrates presents a severe knowledge gap. By integrating AlphaFold modelling with comprehensive high resolution mutational scanning, we show that -helices in substrates bind B55 through an evolutionary conserved mechanism. Despite a large diversity in sequence and composition, these -helices share key amino acid determinants that engage discrete hydrophobic and electrostatic patches. Using deep learning protein design, we generate a specific and potent competitive peptide inhibitor of PP2A-B55 substrate interactions. With this inhibitor, we uncover that PP2A-B55 regulates the nuclear exosome targeting complex by binding to an -helical recruitment module in RBM7. Collectively, our findings provide a framework for the understanding and interrogation of PP2A-B55 in health and disease. One sentence summary-helices in PP2A-B55 substrates bind a conserved pocket on B55 through a common mechanism that is conserved in eukaryotes.

cell biology↗

bioRxiv2023

Systematic discovery of protein interaction interfaces using AlphaFold and experimental validation

Structural resolution of protein interactions enables mechanistic and functional studies as well as interpretation of disease variants. However, structural data is still missing for most protein interactions because we lack computational and experimental tools at scale. We thoroughly assessed AlphaFold-Multimer accuracy for structure prediction of interactions involving folded domains binding to short linear motifs from the ELM database. The structure predictions were highly sensitive but not very specific when using small protein fragments. Sensitivity decreased substantially when using long protein fragments or full length proteins with intrinsically disordered regions. We delineated a fragmentation strategy to optimize sensitivity and applied it to interactions between proteins associated with neurodevelopmental disorders. This enabled prediction of highly confident and likely disease-related novel interfaces, but also resulted in many high scoring false positive predictions. Experiments supported predicted interfaces between CREBZF-HCFC1, FBXO23-STX1B, STX1B-VAMP2, ESRRG-PSMC5, PEX3-PEX19, PEX3-PEX16, and SNRPB-GIGYF1 providing novel molecular insights for diverse biological processes. Our work highlights exciting perspectives, but also reveals clear limitations and the need for future developments to maximize the power of Alphafold-Multimer for interface predictions.

systems biology↗

bioRxiv2023

Protein language models can capture protein quaternary state

BackgroundDetermining a proteins quaternary state, i.e. how many monomers assemble together to form the functioning unit, is a critical step in protein characterization, and deducing it is not trivial. Many proteins form multimers for their activity, and over 50% are estimated to naturally form homomultimers. Experimental quaternary state determination can be challenging and require extensive work. To complement these efforts, a number of computational tools have been developed for quaternary state prediction, often utilizing experimentally validated structural information. Recently, dramatic advances have been made in the field of deep learning for predicting protein structure and other characteristics. Protein language models that apply computational natural-language models to proteins successfully capture secondary structure, protein cell localization and other characteristics, from a single sequence. Here we hypothesize that information about the protein quaternary state may be contained within protein sequences as well, allowing us to benefit from these novel approaches in the context of quaternary state prediction. ResultsWe generated embeddings for a large dataset of quaternary state labels, extracted from the curated QSbio dataset. We then trained a model for quaternary state classification and assessed it on a non-overlapping set of distinct folds (ECOD family level). Our model, named QUEEN (QUaternary state prediction using dEEp learNing), performs worse than approaches that include information from solved crystal structures. However, we show that it successfully learned to distinguish multimers from monomers, and that the specific quaternary state is predicted with moderate success, better than a simple model that transfers annotation based on sequence similarity. Our results demonstrate that complex, quaternary state related information is included in these embeddings. ConclusionsQUEEN is the first to investigate the power of embeddings for the prediction of the quaternary state of proteins. As such, it lays out the strength as well as limitations of a sequence-based protein language model approach compared to structure-based approaches. Since it does not require any structural information and is fast, we anticipate that it will be of wide use both for in-depth investigation of specific systems, as well as for studies of large sets of protein sequences. A simple colab implementation is available at: https://colab.research.google.com/github/Orly-A/QUEEN_prediction/blob/main/QUEEN_prediction_notebook.ipynb.

bioinformatics↗

bioRxiv2022

AlphaFold2-based fusion design deciphers crucial role of the E3 UFL1 N-terminal helix in E2 UFC1 binding and ufmylation

Ufmylation, a protein modification by Ubiquitin-like (UBL) protein UFM1, plays a crucial role in several cellular processes including DNA damage response, protein translation and ER homeostasis. To date, little is known how the enzymes responsible for this modification coordinate their action. Here we have studied the details of UFL1 (E3) activity, its binding to UFC1 (E2), and its relation to UBA5 (E1), using a combination of structural modeling with Alphafold2, X-ray crystallography, NMR, and in vitro biochemical activity assays. Guided by an Alphafold2 model, we generated an active UFL1 fusion construct that includes its cofactor DDRGK1, and solved the first crystal structure of this critical interaction. This fusion construct also unveiled the importance of the N-terminal helix of UFL1 for its binding to UFC1, which was validated by ITC and NMR experiments. Importantly, the binding site suggested by our structural model of the UFL1-UFC1 interaction reveals a conserved interface, and suggests a competition for binding to UFC1 between UFL1 and UBA5, which we reconfirmed by NMR. Altogether, our study reveals a novel, terminal helix-mediated regulatory mechanism which coordinates the cascade of E1-E2-E3 mediated transfer of UFM1 to its substrate, and provides new leads to target this important modification. Significance statementUfmylation is an important post-translational modification, but little is known about the mechanistic details of its machinery, and in particular how the UFM1 E3 ligase (UFL1) binds and functions together with the E2 conjugating enzyme (UFC1). We combined AlphaFold2 modeling, X-ray crystallography, NMR and biochemical experiments to reveal crucial elements that govern UFL1 activity and ufmylation. We discover a crucial role for the UFL1 N-terminal helix in binding to UFC1 and productive ufmylation. This helix competes with the E1 (UBA5) C-terminal helix for binding to UFC1. Altogether, our findings uncover a new, helix-mediated regulatory mechanism in ufmylation.

biochemistry↗

bioRxiv2021

Tandem WW/PPxY motif interactions in WWOX: the multifaceted role of the second WW domain

Class I WW domains mediate protein interactions by binding short linear PPxY motifs. They occur predominantly as tandem repeats, and their target proteins often contain multiple PPxY motifs, but the interplay of WW/peptide interactions is not always intuitive. WW domain-containing oxidoreductase (WWOX) protein harbors two WW domains: unstable WW1 capable of PPxY binding, and well-folded but mutated WW2 that cannot bind such motifs. WW2 is considered to act as a WW1 chaperone, but the underlying mechanism remains to be revealed. Here we combine NMR, ITC and structural modeling to elucidate the role of both WW domains in WWOX binding to single and double motif peptides derived from its substrate ErbB4. Using NMR we identified an interaction surface between the two domains that supports a WWOX conformation that is compatible with peptide substrate binding. ITC and NMR measurements reveal that while binding affinity to a single motif is marginally increased in the presence of WW2, affinity to a dual motif peptide increases tenfold, and that WW2 can directly bind double motif-peptides using its canonical binding site. Finally, differential binding of peptides in a mutagenesis study is consistent with a parallel orientation binding to the WW1-WW2 tandem domain, agreeing with structural models of the interaction. Our results reveal the complex nature of tandem WW domain organization and substrate binding, highlighting the contribution of WWOX WW2 to both stability and binding. This opens the way to assess how evolution can utilize the multivariate nature of binding to fine-tune interactions for specific biological functions.

biophysics↗

bioRxiv2021

PatchMAN docking: Modeling peptide-protein interactions in the context of the receptor surface

Peptide docking can be perceived as a subproblem of protein-protein docking. However, due to the short length and flexible nature of peptides, many do not adopt one defined conformation prior to binding. Therefore, to tackle a peptide docking problem, not only the relative orientation between the two partners, but also the bound conformation of the peptide needs to be modeled. Traditional peptide-centered approaches use information about the peptide sequence to generate a representative conformer ensemble, which can then be rigid body docked to the receptor. Alternatively, one may look at this problem from the viewpoint of the receptor, namely that the protein surface defines the peptide bound conformation.We present PatchMAN (Patch-Motif AligNments), a novel peptide docking approach which uses structural motifs to map the receptor surface with backbone scaffolds extracted from protein structures. On a non-redundant set of protein-peptide complexes, starting from free receptor structures, PatchMAN successfully models and identifies near-native peptide-protein complexes in 62% / 81% within 2.5[A] / 5[A] RMSD, with corresponding sampling in 81% / 100% of the cases, outperforming other approaches. PatchMAN leverages the observation that structural units of peptides with their binding pocket can be found not only within interfaces, but also within monomers. We show that the conformation of the bound peptide is sampled based on the structural context of the receptor only, without taking into account any sequence information. Beyond peptide docking, this approach opens exciting new avenues to study principles of peptide-protein association, and to the design of new peptide binders.

bioinformatics↗

bioRxiv2021

Harnessing protein folding neural networks for peptide-protein docking

Highly accurate protein structure predictions by the recently published deep neural networks such as AlphaFold2 and RoseTTAFold are truly impressive achievements, and will have a tremendous impact far beyond structural biology. If peptide-protein binding can be seen as a final complementing step in the folding of a protein monomer, we reasoned that these approaches might be applicable to the modeling of such interactions. We present a simple implementation of AlphaFold2 to model the structure of peptide-protein interactions, enabled by linking the peptide sequence to the protein c-terminus via a poly glycine linker. We show on a large non-redundant set of 162 peptide-protein complexes that peptide-protein interactions can indeed be modeled accurately. Importantly, prediction is fast and works without multiple sequence alignment information for the peptide partner. We compare performance on a smaller, representative set to the state-of-the-art peptide docking protocol PIPER-FlexPepDock, and describe in detail specific examples that highlight advantages of the two approaches, pointing to possible further improvements and insights in the modeling of peptide-protein interactions. Peptide-mediated interactions play important regulatory roles in functional cells. Thus the present advance holds much promise for significant impact, by bringing into reach a wide range of peptide-protein complexes, and providing important starting points for detailed study and manipulation of many specific interactions.

bioinformatics↗