The PNUTS-PAD domain recruits MYC to the PNUTS:PP1 phosphatase complex via the oncogenic MYC-MB0 region

Despite MYC dysregulation in most human cancers, strategies to target this potent oncogenic driver remains an urgent unmet need. Recent evidence shows the PP1 phosphatase and its regulatory subunit PNUTS control MYC phosphorylation and stability, however the molecular basis remains unclear. Here we demonstrate that MYC interacts directly with PNUTS through the MYC homology Box 0 (MB0), a highly conserved region recently shown to be important for MYC oncogenic activity. MB0 interacts with PNUTS residues 1-148, a functional unit here termed, PNUTS amino-terminal domain (PAD). Using NMR spectroscopy we determined the solution structure of PAD, and characterised its interaction with MYC. Point mutations of residues at the MYC-PNUTS interface significantly weaken their interaction both in vitro and in vivo. These data demonstrate the MB0 binding pocket of the PAD represents an attractive site for pharmacological disruption of the MYC-PNUTS interaction. In Brief Solving the structure of MYC-PNUTS direct interaction reveals how the intrinsically disordered MYC-Box0 (MB0) region anchors into a binding pocket in the N-terminal PAD domain of PNUTS. These data provide insight into the molecular mechanism of how the PNUTS:PP1 phosphatase complex regulates MYC phosphorylation. Highlights A region critical for MYC oncogenesis, MYC-Box0 (MB0), directly interacts with PNUTS PNUTS amino-terminal domain (PAD) is a structural domain that interacts with MYC MB0 Mutation of single residues at the interaction interface disrupts MYC-PNUTS binding in cells MYC-PNUTS binding releases MYC intramolecular interactions to enable PP1substrate access


Introduction
Dysregulated MYC activity is a hallmark of >50% of human cancers and is often linked to aggressive disease and poor prognosis (Kalkat et al., 2017;Meyer and Penn, 2008). MYC controls the transcription of ~15% of genes, thereby regulating numerous biological processes including cell growth, metabolism and immune response (Casey et al., 2017;Lorenzin et al., 2016;Luscher and Vervoorts, 2012;Meyer and Penn, 2008;Poole and van Riggelen, 2017). In non-transformed cells, the expression of this master-regulator is tightly controlled. By contrast, in cancer MYC activity is dysregulated by a plethora of mechanisms, resulting in constitutive activity that drives oncogenic growth. The MYC family of proteins also includes N-MYC and L-MYC, whose expression is normally restricted to fetal development, but can be reactivated and dysregulated in cancer. (Meyer and Penn, 2008) Thus, dysregulated MYC activity is a potent oncogenic driver of most human cancers.
Evidence from mouse models of cancer strongly suggest that inhibiting MYC oncogenic activity will dramatically improve cancer outcome (Ponzielli et al., 2005;Prochownik and Vogt, 2010;Whitfield et al., 2017), as treatment with cycles of systemic genetic suppression of MYC leads to tumour eradication, without adverse side-effects to normal cells (Bellovin et al., 2013;Felsher and Bishop, 1999;Li et al., 2014;Soucek et al., 2013). Despite these promising results, targeting MYC using traditional drug development approaches has failed (Chen et al., 2018;Dang et al., 2017;McKeown and Bradner, 2014), largely because MYC is intrinsically disordered in the absence of a binding partner . MYC contains a basic helix-loophelix leucine zipper domain (bHLHLZ), common to many transcription factors, and six regions termed MYC boxes that are unique and highly conserved amongst the MYC family of proteins.
MYC Box II (MBII), and more recently MYC Box 0 (MB0), have been shown to be functionally required for the full oncogenic activity of MYC, suggesting these MYC boxes are key regulatory regions . A promising strategy to develop MYC inhibitors is to identify MYC protein interactors that are essential for MYC oncogenic activity, and then disrupt these MYCprotein interactions by targeting the structured region of the partner proteins (Bugge et al., 2020;Lu et al., 2020). The identification of structurally and dynamically unique binding modes of MYC to different protein interactors will then lead to the development of an arsenal of inhibitors targeting MYC activity with high specificity. However, few direct protein interactors of MYC have been validated. As a first step to filling this gap, we identified hundreds of novel MYC binding proteins using the BioID in-cell, proximity labelling technique followed by mass spectrometry, which includes both direct and indirect protein interactors (Dingar et al., 2015;Kalkat et al., 2018). We then further characterized one of the hits, protein phosphatase 1 (PP1), a serine threonine phosphatase and its regulatory substrate-specifying subunit, PP1 nuclear targeting subunit (PNUTS), as we and others have shown that phosphorylation regulates MYC stability and/or activity (Huang et al., 2004;Wasylishen et al., 2013)(20-23) (Chakraborty et al., 2015;Hemann et al., 2005). Indeed, inhibiting PP1 using RNAi or pharmacological inhibitors triggers MYC hyperphosphorylation, leading to chromatin eviction and MYC protein degradation (Dingar et al., 2018). Exploiting this PP1:PNUTS-MYC regulatory axis to target MYC destruction has promise; however, inhibiting PP1 catalytic activity is not a viable approach as PP1 has several protein substrates (Bollen et al., 2010;Casamayor and Arino, 2020;Cohen, 2002). Thus, to advance our understanding of how MYC is regulated by this phosphatase complex and to evaluate the potential for pharmacological disruption of MYC interaction with PP1:PNUTS to promote MYC degradation, we sought to delineate the molecular basis of this interaction.
Here, we report that MYC interacts directly with PNUTS. Using biolayer interferometry (BLI) analysis the interaction has been mapped to conserved residues 16-33 of MYC, recently termed MB0 , and a functional unit of PNUTS consisting of the N-terminal 148 residues, which we have termed the PNUTS amino-terminal domain (PAD). Using nuclear magnetic resonance (NMR) spectroscopy, we first determined the structure of PAD alone (apo).
Building on these results, the molecular interaction of PAD and MB0 was then resolved by analyzing each protein in the presence of the partner protein, and by analyzing a PAD-MB0 fusion protein, in conjunction with molecular modeling. Together, this revealed the critical residues and structural details essential for the PNUTS-MYC interaction. Validation of key residues important for the interaction within both proteins was achieved by demonstrating that point mutants of these residues disrupted the PNUTS-MYC interaction in vitro and in vivo.
Taken together, these results not only provide new insights into the molecular basis of MYC interaction with PNUTS, but also provide foundational data for the potential development of drugs targeting PNUTS to disrupt the PNUTS-MYC interaction and inhibit MYC oncogenic activity.

MB0 interacts directly with PAD
Our previous work identified MYC as a substrate of the PP1:PNUTS phosphatase complex, however the molecular basis of the interaction and whether it is direct remained unclear (Dingar et al., 2018). As MYC does not contain a canonical PP1 recognition motif (RVxF), we hypothesized that MYC may interact with the non-catalytic, substrate-specifying subunit PNUTS. PNUTS contains two previously annotated domains: a TFIIS helical bundle-like domain (residues 73-147) of the Med26 Pfam family (PF08711) with no functional annotation (Zacharchenko et al., 2016); and a zinc finger domain at the C-terminus (Allen et al., 1998;Kim et al., 2003) (Fig. 1a). Since the former is a putative protein-protein interaction domain, we first interrogated the interaction potential of the N-terminal region by designing and testing several expression constructs of proteins within the first 186 amino acids of PNUTS. The shortest of these that was successfully expressed and purified as a stable protein encompassed residues 1-148 (PNUTS(1-148)), suggesting this region represents an independently folded functional domain. This N-terminal region of PNUTS(1-148) was then further evaluated in binding assays with MYC peptides and protein.

Specific residues within MB0 interact with PAD
To identify MB0 residues critically involved in binding to PAD, we used NMR spectroscopy. We have previously shown that MB0 and MBI are transiently ordered regions, in an otherwise disordered 6His-MYC(1-88) fragment, which was refolded from inclusion bodies (Andresen et al., 2012). For this study, we expressed and purified MYC(1-88) under native conditions from a cleavable TRX-tagged construct, and found the NMR chemical shifts of 13 C-15 N-MYC(1-88) near-identical to those of 6His-MYC(1-88). NMR titrations were then performed with unlabeled PAD at 15°C. As MYC(1-88) is predominantly intrinsically disordered, most of its amide resonances in the ( 1 H-15 N) HSQC spectra overlap heavily and are clustered between 7.7 and 8.6 ppm (Andresen et al., 2012;Fladvad et al., 2005). Nevertheless, an ( 1 H-15 N) HSQC overlay at increasing PAD:MYC(1-88) ratios shows clear shifting and/or broadening of V19, Q20 and F23 peaks (Fig. 2a).
To more accurately determine chemical shift perturbations (CSPs) and broadening of MYC amide resonance due to PAD binding, it was necessary to acquire conventional 3D backbone spectra (HNCO and HNCA) to resolve the amide signals based on their coupling to neighbouring carbonyl groups or Cα carbons. When MYC(1-88) was titrated with PAD , substantial CSPs and broadening of MYC resonances were observed (Fig. 2b, c). A six-residue stretch of MB0 (V19 to Y24) exhibited the most substantial CSPs and broadening effects ( Fig.   2b), which is in agreement with MB0 being critical for PAD binding by BLI (Fig. 1b). All assigned MYC residues between D13 and Q33 lose at least 75% of their peak intensity at a 1.9:1 PAD to MYC ratio with no signs of signal recovery in the bound state (Fig. 2c, Supplementary   Fig. 2). This indicates continued chemical exchange between multiple bound states (Bozoky et al., 2013;Helander et al., 2015), which is characteristic for intrinsically disordered proteins (Forman-Kay and Mittag, 2013;Fuxreiter, 2018). Consistent with our BLI data, other parts of MYC(1-88) also show resonance shifts and broadening, including a sequence in MBI (residues W50-L55) with smaller CSP and intensity changes compared to those of MB0.
Interestingly, a region within and adjacent to MBI (L61 to V75) showed sharper amide signals in response to PAD binding, with S64, R65 and S67 amide intensity increased up to 6-fold (Fig.   2c). This suggests that PAD interaction with MB0 leads to greater conformational mobility of this segment and more rapid interconversion between states than in free . This would be in agreement with PAD-induced release of previously identified transient interactions between MB0 and MBI regions (Andresen, 2012) (Fig. 2c, inset).

MB0 interacts with the C-terminal facing surface of PAD ARM2 motif
To map the region of interaction between MB0 with PAD, we performed NMR binding studies at 30°C using 13 C, 15 N-labeled PAD titrated with biotinyl-MB0 peptide and MYC(1-88) ( Supplementary Fig. 4a, b). At a MB0 to PAD molar ratio of 2 to 1, there was a significant movement of PAD amide resonances in ( 1 H-15 N) HSQC spectra with an average CSP of 0.012 ppm and a STDEV of 0.018. A similar perturbation pattern was observed, when MYC(1-88) was added to PAD ( Supplementary Fig. 4b). We then analyzed normalized combined CSPs for these experiments (Fig. 3c, see Methods for CSP calculations). Eight residues (K109, Q110, N111, A114, K115, Q119, M141, and Q147) had composite amide CSPs ≥ 3 standard deviations from 0, and an additional 13 had values ≥ 2 standard deviations from 0, of which 6 are solventexposed according to the NMR-derived solution structure (V45, R58, T104, K118, W140, and S146) (Fig. 3c). These data further confirm that the MB0 residues are the dominant drivers of the PNUTS-MYC interaction, consistent with our BLI data ( Fig. 1b and 1c) and NMR titrations of ( 13 C, 15 N) MYC(1-88) (Fig. 2). A map of CSPs on the PAD surface in response to MB0 interaction indicates that the highly perturbed residues (with a combined CSP greater than 1 standard deviation) form part of, or are close to the C-terminal facing surface of the ARM2 motif ( Fig. 3d). This C-terminal facing surface is mainly composed of hydrophobic residues in the center, and surrounded by several charged residues, including three Lysines (K109, K115, and K118) ( Fig. 3e; Supplementary Fig. 4c). We next used ( 1 H-13 C) HSQC spectra of the PAD, to detect perturbations to the resonances of amino acid side chains. The methyl groups of A114 (γ), I144 (δ1 and γ2), T113 (γ2), and M141 (ε) -all in or near the C-terminal facing surface -were noticeably perturbed upon MB0 peptide binding ( Supplementary Fig. 4d). Importantly, a ConSurf analysis (Ashkenazy et al., 2016;Landau et al., 2005) indicates that the C-terminal facing surface of the ARM2 motif is conserved across species (Fig. 3f), suggesting a potential conserved interaction surface.

NMR guided model of PAD and MB0 interaction
To analyze structural features of the PAD-MB0 interaction, a computational modelling approach was taken to identify possible interaction modes of MYC with PNUTS. Guided by the intensity changes and CSPs of MB0, and the CSPs of PAD as described above (see methods), we generated 50,000 models of the PAD-MB0 complex using the Rosetta FlexPepDock ab-initio protocol (Raveh et al., 2011), with NMR-derived constraints accounting for circa 50% of the inter-chain interaction energy. These models were clustered with respect to the position of MB0 residues 19-26 and, using a LASSO algorithm (Tibshirani, 1996)  PAD-MB0-fusion, the CSP patterns for PAD amides are similar to those observed when apo PAD is titrated with MB0 peptide (Supplementary Fig. 6b,c). For instance, several resonances in the ARM2 hydrophobic pocket that shift upon PAD binding to MB0 (e.g. M141, V117 and A114) follow a similar trajectory to their position in the spectrum of PAD-MB0-fusion; however these associated CSP amplitudes are significantly higher ( Supplementary Fig. 6b). Differences in the perturbation patterns seen with PAD-MB0-fusion compared to those in the MB0 peptide binding assay are mainly localized to the PAD C-terminus close to the (GGGS)2 linker (Fig. 3c;Supplementary Fig. 6c,d ). Taken together, these data suggest that the fusion construct favours MB0-bound states that are highly populated in the non-fused system, likely by increasing the local concentration of MB0 at the MYC-binding site of PNUTS.
Having validated the relevance of the PNUTS-MYC interaction within the fusion protein, we next performed a full, NOE-driven structure determination, including 43 experimental NOE restraints between the PAD and MB0 residues 13-30 (PDB ID: 7LQT, Fig. 4b, 5a, 5b; Table 1).
As expected, MB0 binds on the conserved surface of ARM2 comprising helixes α7, α8, and α9, in good agreement with the NMR titration data (Fig. 3d,4b). There are small differences between the structure of apo and PAD-MB0-fusion which superimpose with a backbone RMSD of 1.9±0.2Å ( Supplementary Fig. 6d). The most important difference is confined to a small repositioning of the C-terminal helix (α9) in the ARM2 motif, which we discuss in detail below.
There is excellent agreement between the solution structure of the PAD-MB0-fusion and the NMR-guided computational modeling of the interaction (  Fig. 5a, d). Indeed, the inter-chain contact frequency of residues over the total number of computational models are also similar to the fusion protein, especially the largest cluster of docked models with a correlation R of 0.82 ( Supplementary Fig. 5c).
The N-and C-termini of MB0 show no NOEs with any PAD residues, and are more disordered than the bound MYC-V19QPYFY24 in all 20 structures of the ensemble ( Supplementary Fig. 6e).
Comparison of the MB0 interaction site of PAD in the absence (apo) and presence of MB0 reveals a subtle conformational adjustment of the three helices in the ARM2 motif upon MB0 binding in the fusion protein. Notably, this helix movement was also required in the NMRguided computational models for MB0 binding to PAD, further supporting this observation ( Supplementary Fig. 6g). In the MB0-bound state, helix α9 is slightly tilted away from helices α7 and α8 ( Fig. 5e) translocating its C-terminus approximately 8 Å in the presence of MB0 compared to the apo form of PAD. As a result, key residues in 9, including binding pocket residues I144, V137, M141, are slightly distanced from helices α7 and α8 in the presence of MB0 ( Supplementary Fig. 6f). Thus, PAD appears to accommodate MB0 binding by opening a binding pocket between helices 7-9 in ARM2.

Mutation of key residues diminish PNUTS-MYC interaction in vitro and in human cells.
To further validate the mode of interaction, we generated point mutations of residues in To assess whether these residues also contribute to the interaction of MYC and PNUTS in a cellular context, we evaluated the interaction using a proximity ligation assay (PLA). First, V5-tagged MYC and MYC point mutants were generated and stably expressed in the MCF10A breast epithelial cell line, which was one of many cell lines used to show functional relevance of the PP1:PNUTS-MYC axis (Dingar et al., 2018) and were chosen as they image well for PLA.
Using V5 antibody, which was common to all constructs, we demonstrated similar levels of expression and nuclear localization of all mutants as well as wildtype MYC by immunoblot and immunofluorescence, respectively (Supplementary Fig. 8a, b). We then performed PLA to measure the interaction of MYC(WT), MYC(P21A), MYC(Y22A), MYC(F23A) and MYC(Y24A) with endogenous PNUTS (Fig. 6b). With this assay co-localization of two proteins of interest within approximately 40 nm is scored as a fluorescent focus. Several fields of view were assayed and the foci enumerated on a per nucleus basis. Indeed, each of the four MYC point mutants significantly reduced the number of fluorescent foci formed as compared to wildtype MYC (Fig. 6c). Overall, our mutational analysis confirmed that the residues on MYC, that we identified as key determinants of PNUTS-MYC interaction in vitro, are functionally important for this protein-protein interaction within cells.
We also evaluated the impact of single amino acid substitutions of PAD for their binding to MYC. Using FoldX (foldx.crg.es), amino acid substitutions were chosen to preferentially alter PNUTS-MYC interaction without disrupting protein structure. All six of the PAD point mutants (K109A, A114K, K118A, K122A, M141F and M141W) displayed weaker interaction with the MB0 peptide; in five of these, the binding affinity was reduced by more than 2-fold ( Fig. 6d; We similarly evaluated the degree to which the PAD can interact with MYC in human cell lines. To this end, we expressed a doxycycline-inducible, in-frame, fusion protein consisting of a Flag-tag, PNUTS amino acids 1 to 160 (PNUTS(1-160)) and three tandem SV40 nuclear localization signal (NLS) motifs. PNUTS(1-160) was used to achieve sufficient expression of the PAD in mammalian cells and the NLS ensured nuclear localization. Upon addition of doxycycline to the media, we observed the expected induction of PNUTS(1-160) as confirmed by immunoblot (Supplementary Fig. 9a) and nuclear localization determined by immunofluorescence ( Supplementary Fig. 9b). To evaluate binding of PNUTS(1-160) to fulllength MYC in human cells, we next performed PLA. Induction of PNUTS(1-160) dramatically increased the number of foci formed per nucleus compared to the EV control, giving us confidence that the PAD is also responsible for the interaction of MYC and PNUTS in human cells (Fig 6e). Evaluation of point mutants of key PAD residues important for MYC interaction, A114K and M141W, by PLA showed a significant reduction in foci formation as compared to wild-type PNUTS(1-160) (Fig. 6f). Taken together, these findings demonstrate that the interaction domains of MYC and PNUTS we mapped in vitro are also responsible for MYC:PNUTS interaction in human cells.

Discussion
Distinguishing direct protein interactors of the MYC oncoprotein is essential not only to understand the mechanism of MYC function, but also to potentially unveil novel strategies to inhibit MYC binding to key protein partners and thus disable MYC as a potent cancer driver. We have previously shown the PP1:PNUTS phosphatase complex regulates MYC phosphorylation and degradation (Dingar et al., 2018), however the molecular basis of the interaction remained unclear. Here we show that PNUTS and MYC interact directly through the PAD and MB0 regions, respectively. Using NMR, the key residues of PAD-MB0 interaction were identified.
The apo structure of the PAD was determined (PDB ID: 6VTI) and shown to consist of nine helices arranged as three helical bundles, with the two C-terminal bundles consisting of two ARM repeats; ARM1 and ARM2. Using NMR and computational modeling, we determined the molecular basis of the interaction not only by analyzing PAD and MB0 as well as PAD and MYC(1-88), but also a PAD-MB0-fusion protein (PDB ID: 7LQT). Our data support a model in which a core hydrophobic stretch in MB0 anchors onto the C-terminal facing surface of the PAD ARM2 motif primarily through hydrophobic interactions. Moreover, we show this interaction ensemble is highly dynamic but comprises a narrow range of specific, bound conformations.
Validation of the interaction was achieved by demonstrating that point mutants of key interacting residues in either MYC or PNUTS disrupted the interaction both in vitro and in vivo.
The dynamic alterations in MYC in response to PAD binding, together with structural specifics of the bound state and in vivo effects of its inhibition, suggest a model in which MB0 binding to PAD could facilitate PP1:PNUTS access to phosphorylation sites within and adjacent to MBI for subsequent dephosphorylation (see Graphical Abstract). Our NMR analyses of  showed that MB0 residues V19-Y24 comprise the primary anchor site of the PAD-MYC(1-88) interaction, with a weaker second touch-point within MBI (residues W50-L55). In contrast, MBI-neighbouring residues (P61 to V75) show dramatically sharper amide signals on PAD binding to MB0, suggesting a more rapidly interconverting ensemble state in this region compared to MYC(1-88) alone and a possible release of internal MYC interactions upon PAD binding, as we previously observed for tumour suppressor Bin1 binding to MBI (Andresen et al., 2012). In the context of the MYC-PNUTS interaction, the region of MYC that appears to be released upon PAD binding comprises critical serine/threonine residues essential for functional phosphorylation. This agrees with the role of the PP1:PNUTS-MYC axis in the regulation of MYC phosphorylation, activity and stability (Dingar et al., 2018). Such an anchor-release mechanism of PAD-MB0 binding in the PNUTS-MYC complex resembles that of Pin1 binding to MYC, where its anchoring to MB0 enhances cis-trans isomerisation c-terminal of MBI, thereby enhancing phosphorylation of S62 . However, while Pin1 is a general cis-trans isomerase acting on many targets, PNUTS binding to MYC holds a specific key regulatory role of MYC function and degradation. In agreement, the specificity of the binding motif identified here is verified by single structure-based point-mutations that entirely abort the

MYC-PNUTS interaction in vitro and in vivo.
Our analyses revealed that the structure of the PAD is also affected by the PAD-MB0 interaction. Specifically, in the MB0-bound state, the α9 helix of PNUTS ARM2 is tilted away from α8 compared to apo PAD. Both in-silico modeling and direct NMR studies suggest that this conformational change supports the formation of the PAD binding pocket required to Targeting MYC activity by disrupting MYC-protein interactions is an area of intense interest as inhibiting MYC directly has not been fruitful to date. As the bHLHLZ interaction with MAX was the first binding partner of MYC (Blackwood and Eisenman, 1991), several groups endeavour to exploit this partnership for the development of inhibitors (Carabet et al., 2018;Castell et al., 2018;Dang et al., 2017;Han et al., 2019;Lu et al., 2020). More recently, the focus has been on targeting interactors of the unique MYC Box regions. The interaction of MBIV with WDR5 induces a specific subset of genes whose products regulate protein synthesis, and inhibitors to block this interaction are under development (Chacon Simon et al., 2020;Thomas et al., 2019). Moreover, recent insight into the structural basis of MBII-TRRAP interaction has unveiled potential strategies to target this key interaction (Feris et al., 2019). Despite decades of MYC research, MB0 has only recently been recognized as a highly conserved MYC box that is functionally important for MYC oncogenic activity Kalkat et al., 2018).
Our finding here that PNUTS directly interacts with MB0 further reinforces the functional importance of this PP1:PNUTS-MYC regulatory axis, which we had previously shown controls MYC activity and stability (Dingar et al., 2018). Indeed, PNUTS was recently shown by an independent group to regulate N-MYC stability (Tee et al., 2020), further emphasizing the critical nature of the PNUTS-MYC interaction to MYC family activity. This is consistent with MB0 being conserved amongst MYC family members, thereby enabling PP1:PNUTS to regulate the rapid turnover of these oncoproteins. Importantly, MYC and PP1:PNUTS are often overexpressed in human cancers (Dingar et al., 2018;Marx et al., 2020) further supporting the concept that disrupting PNUTS-MYC by developing inhibitors targeting the PNUTS pocket in which MYC binds, may be possible, and have therapeutic utility. Such an inhibitor would not be generally cytotoxic as it would not target PNUTS per se, but would disrupt the PAD-MB0 interaction leading to MYC hyperphosphorylation and degradation. MYC-driven and/ordependent cancers would be particularly vulnerable to the loss of MYC and undergo cell death.
Given that MYC is dysregulated in the majority of human cancers, this strategy to decrease MYC activity makes the MB0-binding pocket of PNUTS an attractive drug target.

DECLARATION OF INTERESTS
The authors declare no competing interests.   (a) Backbone trace of the NMR ensemble of PAD (20 structures), as seen from the 'front' view.
Helices are numbered with respect to their order from the N-to C-terminus colored from blue to red. (b) Cartoon representation of the lowest energy PAD structure, which comprises an Nterminal terminal domain (NTD) consisting of a 3-helix bundle (helices 1 to 3), followed by two Armadillo (ARM) repeats (ARM1 and ARM2, helices 4 to 6 and 7 to 9, respectively). (c) differing by more than 1 standard deviation from 0, are colored blue, with a more saturated hue for greater δi. Residues with a δi lower than 1 standard deviation from 0 are colored grey. Bars of buried residues are colored white with grey borders. A residue is defined as buried if less than 5% of its relative area normalized as a Gly-X-Gly chain is exposed. (d) Surface representation of apo-state PAD as seen from the view of a 70 degree rotation of panel (a) on the Y axis, with residues colored by the scheme used in Figure 3c. (e) Representation of the PAD electrostatic surface potential using a color gradient spanning red (kT/e =-8) to blue (kT/e =8), in the same view as (d). (f) Analysis of PAD sequence conservation between species (using ConSurf server) with a structure color-coding bar spanning turquoise (for residues that are not conserved) to maroon (highly conserved residues), in the same view as (d). See also Figure S3 and S4.

Contact for Reagents and Resource Sharing
Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Linda Z. Penn (Linda.Penn@uhnresearch.ca).

Protein expression and purification
Several  (Savitsky et al., 2010) and a TEV cleavage site. Thioredoxin was cleaved using TEV protease in dialysis buffer (1X PBS, 5% glycerol, 2mM β-ME) at 4°C overnight, after which the fusion protein was purified as described above.
Transformed BL21(DE3) cells (ROS-2, pRAR3 plasmid) were grown in LB medium and induced by 0.5 mM IPTG at 37° for 3 h. When OD600 was reached a level of 0.6, the cells were harvested by centrifugation, resuspended in lysis buffer (50 mM NaH2PO4, 10 mM Tris-HCl,
Assignments were performed with aid of the software FMCGUI (Lemak et al., 2011).
Assignments were 98.5% and 90.4% complete for backbone and sidechain resonances, respectively for PAD, and 96.4% and 90.2% complete for backbone and sidechain resonances, respectively for PAD-MB0-fusion. ϕ and ψ torsion angle restraints were derived from backbone chemical shifts using TALOS (Shen et al., 2009). Distance restraints were derived from cross peaks in NOESY spectra, and H-bond restraints, when applied, were for residues unambiguously determined to be in secondary structural elements based on NOE patterns, chemical shift assignments and backbone torsion angles. Automated NOE assignments and structure calculations were performed using CYANA 2.1 (Guntert, 2004). The final 20 lowest energy structures were refined with CNSSOLVE by performing a short restrained molecular dynamics simulation in explicit solvent (Bollen et al., 2010); the resulting 20 structures comprise the NMR ensemble.

Molecular Docking of MB0 to the PAD
A model of the PAD-MB0 complex was constructed by docking the MB0 peptide guided by experimentally derived constraints using Rosetta FlexPepDock protocol (Raveh et al., 2011). The constraints were derived from chemical shift perturbations (CSP) and intensity differences from titration experiments, similarly to previous work modelling MB0 interacting with Pin1 . For PAD, 1 H-15 N HSQC CSP were used from titration experiments with MYC(1-88) and biotinylated MB0, and additionally 1 H-13 C HSQC CSP was also used for MYC  titration. For MB0, 1 H-15 N HNCO CSP and intensity changes were used from titrating in PAD to . The CSPs for the same nucleus and molecule were averaged, followed by the combination of all different CSPs to a single combined chemical shift perturbation, δi for each residue i, using a weighted average of the individual shifts with the weights based on the magnetogyric ratio of the nucleus; 1.000, 0.102, and 0.251 for 1 H, 15 N, and 13 C (Schumann et al., 2007).
All combined chemical shift perturbations δi of residues differing by more than 2σ from 0 were included as constraints for the residues involved in binding. σ was calculated in an iterative manner as outlined in Schumann et al. (Schumann et al., 2007), by omitting combined shift perturbations, δi,outside 3σ and recalculating until σ converged. The resulting shifts were normalized to a maximum signal of 1.0. For MB0, the HSQC intensity followed a similar process, but using σ from 1 instead. Relative intensities larger than 1.0 were set to 1.0. Resulting signals were reversely scaled from 1.0 to the lowest observed value. The actual significant combined shifts for MB0 were averaged with the significant signals from the peak intensity to form the final significant shifts for MB0. In preparation for usage as constraints, combined chemical shifts δi were reduced to a representative set of significant shifts by the iterative process as described above, and reweighted so the different chemical shift perturbation and intensity difference experiments contributed equally to the final constraints.
Pairwise ambiguous constraints were constructed between every exposed PAD residue (> 5% relative surface exposure) with significant combined shift to every MB0 residue with significant shift by pairwise addition of the signals. The constraints were imposed during the docking using a square well scoring function that positively favour the atom pair when within 5.0 Å, and linearly decreasing the constraint influence in the distance range 5 Å to 10 Å, while not penalizing distances further than 10 Å. This corresponds to the FADE constraint function type in Rosetta with a lower bound -5.0, upper bound 10.0, and cubic splines of width 5.0. The overall constraint weight was set to contribute as much to the final scoring of the complex as all the unconstrained energy functions.
The PAD structure was energy-minimized using the Rosetta relax protocol. 50,000 decoys of PAD:MB0 interactions were generated using Rosetta Flex-PepDock ab-initio protocol guided by the constraints. Each decoy was generated starting from an extended MB0 peptide superpositioned on one of the constraint-pairs in a random orientation on the receptor surface.
Rosetta FlexPepDock utilizes Monte-Carlo sampling to minimize the 'REF2015' energy function (Raveh et al., 2010), while sampling the translational, rotational, and torsional degrees of freedom of both MB0 and PAD. The translational and rotational degrees of freedom are sampled by randomly moving and rotating MB0 with respect to PAD. The backbone torsions of MB0 are sampled using fragment insertions, where the fragments are 3-, 5-, or 9-residue backbone dihedrals with local sequence similarity to the MB0. After each structural change, the side chains are rebuilt using Dunbrack's backbone-dependent rotamer library (Shapovalov and Dunbrack, 2011) followed by energy minimization before the trial energy is calculated. Following the standard Metropolis acceptance criterion, the structural change is accepted with a probability related to the difference in energy before and after the change.
To properly represent the plausible conformations of the MB0 peptide, a subset of representative decoys which best describe the observed CSP were selected. First, the 25,000 models (median filter) with best resulting energy scores were clustered by backbone position, with cluster radii ranging from 1.0 to 4.0 Å in increments of 0.25, ignoring the flexible loops on the receptor when superpositioning and calculating RMSD. Then, each model in a cluster was described as a binary vector denoting for each residue the involvement in inter-chain interaction, defined as an inter-chain distance between any pair of non-hydrogen atoms ≤ 4.5 Å. Each cluster was represented by the sum of all member vectors. The Lasso algorithm as implemented in scikit-learn (Pedregosa, 2011), a linear model with L1 regularizer, was used to find the combination of clusters that had the best square-sum fit to the experimentally derived constraints.
This was repeated for all cluster radii from above and the cluster radius 1.75 Å obtained the best fit to the constraints, with 9 clusters together describing the constraints with R 2 0.71 (correlation R of 0.84).
Detection was performed using fluorescently labeled secondary antibodies against rabbit and mouse (LI-COR) on the LI-COR Odyssey imaging system.

Proximity Ligation Assay
The expression of the PNUTS constructs was induced through the addition of 0  The PLA was performed as previously described (Dingar et al., 2015).