Stability and deformation of biomolecular condensates under the action of shear flow.

Biomolecular condensates play a key role in cytoplasmic compartmentalization and cell functioning. Despite extensive research on the physico-chemical, thermodynamic, or crowding aspects of the formation and stabilization of the condensates, one less studied feature is the role of external perturbative fluid flow. In fact, in living cells, shear stress may arise from streaming or active transport processes. Here, we investigate how biomolecular condensates are deformed under different types of shear flows. We first model Couette flow perturbations via two-way coupling between the condensate dynamics and fluid flow by deploying Lattice Boltzmann Molecular Dynamics. We then show that a simplified approach where the shear flow acts as a static perturbation (one-way coupling) reproduces the main features of the condensate deformation and dynamics as a function of the shear rate. With this approach, which can be easily implemented in molecular dynamics simulations, we analyze the behavior of biomolecular condensates described through residue-based coarse-grained models, including intrinsically disordered proteins and protein/RNA mixtures. At lower shear rates, the fluid triggers the deformation of the condensate (spherical to oblated object), while at higher shear rates, it becomes extremely deformed (oblated or elongated object). At very high shear rates, the condensates are fragmented. We also compare how condensates of different sizes and composition respond to shear perturbation, and how their internal structure is altered by external flow. Finally, we consider the Poiseuille flow that realistically models the behavior in microfluidic devices in order to suggest potential experimental designs for investigating fluid perturbations in vitro.

Charge block-driven liquid-liquid phase separation - mechanism and biological roles.

Liquid-liquid phase separation (LLPS) has increasingly been found to play pivotal roles in a number of intracellular events and reactions, and has introduced a new paradigm in cell biology to explain protein-protein and enzyme-ligand interactions beyond conventional molecular and biochemical theories. LLPS is driven by the cumulative effects of weak and promiscuous interactions, including electrostatic, hydrophobic and cation-π interactions, among polypeptides containing intrinsically disordered regions (IDRs) and describes the macroscopic behaviours of IDR-containing proteins in an intracellular milieu. Recent studies have revealed that interactions between 'charge blocks' - clusters of like charges along the polypeptide chain - strongly induce LLPS and play fundamental roles in its spatiotemporal regulation. Introducing a new parameter, termed 'charge blockiness', into physicochemical models of disordered polypeptides has yielded a better understanding of how the intrinsic amino acid sequence of a polypeptide determines the spatiotemporal occurrence of LLPS within a cell. Charge blockiness might also explain why some post-translational modifications segregate within IDRs and how they regulate LLPS. In this Review, we summarise recent progress towards understanding the mechanism and biological roles of charge block-driven LLPS and discuss how this new characteristic parameter of polypeptides offers new possibilities in the fields of structural biology and cell biology.

High-throughput structure determination of an intrinsically disordered protein using cell-free protein crystallization.

Intrinsically disordered proteins (IDPs) play a crucial role in various biological phenomena, dynamically changing their conformations in response to external environmental cues. To gain a deeper understanding of these proteins, it is essential to identify the determinants that fix their structures at the atomic level. Here, we developed a pipeline for rapid crystal structure analysis of IDP using a cell-free protein crystallization (CFPC) method. Through this approach, we successfully demonstrated the determination of the structure of an IDP to uncover the key determinants that stabilize its conformation. Specifically, we focused on the 11-residue fragment of c-Myc, which forms an α-helix through dimerization with a binding partner protein. This fragment was strategically recombined with an in-cell crystallizing protein and was expressed in a cell-free system. The resulting crystal structures of the c-Myc fragment were successfully determined at a resolution of 1.92 Å and we confirmed that they are identical to the structures of the complex with the native binding partner protein. This indicates that the environment of the scaffold crystal can fix the structure of c-Myc. Significantly, these crystals were obtained directly from a small reaction mixture (30 µL) incubated for only 72 h. Analysis of eight crystal structures derived from 22 mutants revealed two hydrophobic residues as the key determinants responsible for stabilizing the α-helical structure. These findings underscore the power of our CFPC screening method as a valuable tool for determining the structures of challenging target proteins and elucidating the essential molecular interactions that govern their stability.

Linear and Nonlinear Dielectric Response of Intrinsically Disordered Proteins.

Linear and nonlinear dielectric responses of solutions of intrinsically disordered proteins (IDPs) were analyzed by combining molecular dynamics simulations with formal theories. A large increment of the linear dielectric function over that of the solvent is found and related to large dipole moments of IDPs. The nonlinear dielectric effect (NDE) of the IDP far exceeds that of the bulk electrolyte, offering a route to interrogate protein conformational and rotational statistics and dynamics. Conformational flexibility of the IDP makes the dipole moment statistics consistent with the gamma/log-normal distributions and contributes to the NDE through the dipole moment's non-Gaussian parameter. The intrinsic non-Gaussian parameter of the dipole moment combines with the protein osmotic compressibility in the nonlinear dielectric susceptibility when dipolar correlations are screened by the electrolyte. The NDE is dominated by dipolar correlations when electrolyte screening is reduced.

Isolation of nucleic acids using liquid-liquid phase separation of pH-sensitive elastin-like polypeptides.

Extraction of nucleic acids (NAs) is critical for many methods in molecular biology and bioanalytical chemistry. NA extraction has been extensively studied and optimized for a wide range of applications and its importance to society has significantly increased. The COVID-19 pandemic highlighted the importance of early and efficient NA testing, for which NA extraction is a critical analytical step prior to the detection by methods like polymerase chain reaction. This study explores simple, new approaches to extraction using engineered smart nanomaterials, namely NA-binding, intrinsically disordered proteins (IDPs), that undergo triggered liquid-liquid phase separation (LLPS). Two types of NA-binding IDPs are studied, both based on genetically engineered elastin-like polypeptides (ELPs), model IDPs that exhibit a lower critical solution temperature in water and can be designed to exhibit LLPS at desired temperatures in a variety of biological solutions. We show that ELP fusion proteins with natural NA-binding domains can be used to extract DNA and RNA from physiologically relevant solutions. We further show that LLPS of pH responsive ELPs that incorporate histidine in their sequences can be used for both binding, extraction and release of NAs from biological solutions, and can be used to detect SARS-CoV-2 RNA in samples from COVID-positive patients.

Structural studies of intrinsically disordered MLL-fusion protein AF9 in complex with peptidomimetic inhibitors.

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL-rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP-AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1-2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the ß-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein-inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

Synthetic intrinsically disordered protein fusion tags that enhance protein solubility.

We report the de novo design of small (<20 kDa) and highly soluble synthetic intrinsically disordered proteins (SynIDPs) that confer solubility to a fusion partner with minimal effect on the activity of the fused protein. To identify highly soluble SynIDPs, we create a pooled gene-library utilizing a one-pot gene synthesis technology to create a large library of repetitive genes that encode SynIDPs. We identify three small (<20 kDa) and highly soluble SynIDPs from this gene library that lack secondary structure and have high solvation. Recombinant fusion of these SynIDPs to three known inclusion body forming proteins rescue their soluble expression and do not impede the activity of the fusion partner, thereby eliminating the need for removal of the SynIDP tag. These findings highlight the utility of SynIDPs as solubility tags, as they promote the soluble expression of proteins in E. coli and are small, unstructured proteins that minimally interfere with the biological activity of the fused protein.

Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation.

The diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichocki et al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove to be valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.

The temperature sensor TWA1 is required for thermotolerance in Arabidopsis.

Plants exposed to incidences of excessive temperatures activate heat-stress responses to cope with the physiological challenge and stimulate long-term acclimation1,2. The mechanism that senses cellular temperature for inducing thermotolerance is still unclear3. Here we show that TWA1 is a temperature-sensing transcriptional co-regulator that is needed for basal and acquired thermotolerance in Arabidopsis thaliana. At elevated temperatures, TWA1 changes its conformation and allows physical interaction with JASMONATE-ASSOCIATED MYC-LIKE (JAM) transcription factors and TOPLESS (TPL) and TOPLESS-RELATED (TPR) proteins for repressor complex assembly. TWA1 is a predicted intrinsically disordered protein that has a key thermosensory role functioning through an amino-terminal highly variable region. At elevated temperatures, TWA1 accumulates in nuclear subdomains, and physical interactions with JAM2 and TPL appear to be restricted to these nuclear subdomains. The transcriptional upregulation of the heat shock transcription factor A2 (HSFA2) and heat shock proteins depended on TWA1, and TWA1 orthologues provided different temperature thresholds, consistent with the sensor function in early signalling of heat stress. The identification of the plant thermosensors offers a molecular tool for adjusting thermal acclimation responses of crops by breeding and biotechnology, and a sensitive temperature switch for thermogenetics.

Nascent chains derived from a foldable protein sequence interact with specific ribosomal surface sites near the exit tunnel.

In order to become bioactive, proteins must be translated and protected from aggregation during biosynthesis. The ribosome and molecular chaperones play a key role in this process. Ribosome-bound nascent chains (RNCs) of intrinsically disordered proteins and RNCs bearing a signal/arrest sequence are known to interact with ribosomal proteins. However, in the case of RNCs bearing foldable protein sequences, not much information is available on these interactions. Here, via a combination of chemical crosslinking and time-resolved fluorescence-anisotropy, we find that nascent chains of the foldable globin apoHmp1-140 interact with ribosomal protein L23 and have a freely-tumbling non-interacting N-terminal compact region comprising 63-94 residues. Longer RNCs (apoHmp1-189) also interact with an additional yet unidentified ribosomal protein, as well as with chaperones. Surprisingly, the apparent strength of RNC/r-protein interactions does not depend on nascent-chain sequence. Overall, foldable nascent chains establish and expand interactions with selected ribosomal proteins and chaperones, as they get longer. These data are significant because they reveal the interplay between independent conformational sampling and nascent-protein interactions with the ribosomal surface.

Tardigrade secretory proteins protect biological structures from desiccation.

Tardigrades, microscopic animals that survive a broad range of environmental stresses, express a unique set of proteins termed tardigrade-specific intrinsically disordered proteins (TDPs). TDPs are often expressed at high levels in tardigrades upon desiccation, and appear to mediate stress adaptation. Here, we focus on the proteins belonging to the secreted family of tardigrade proteins termed secretory-abundant heat soluble ("SAHS") proteins, and investigate their ability to protect diverse biological structures. Recombinantly expressed SAHS proteins prevent desiccated liposomes from fusion, and enhance desiccation tolerance of E. coli and Rhizobium tropici upon extracellular application. Molecular dynamics simulation and comparative structural analysis suggest a model by which SAHS proteins may undergo a structural transition upon desiccation, in which removal of water and solutes from a large internal cavity in SAHS proteins destabilizes the beta-sheet structure. These results highlight the potential application of SAHS proteins as stabilizing molecules for preservation of cells.

Copper(II) coordination to the intrinsically disordered region of SARS-CoV-2 Nsp1.

The intrinsically disordered C-terminal peptide region of severe acute respiratory syndrome coronavirus 2 nonstructural protein-1 (Nsp1-CT) inhibits host protein synthesis by blocking messenger RNA (mRNA) access to the 40S ribosome entrance tunnel. Aqueous copper(II) ions bind to the disordered peptide with micromolar affinity, creating a possible strategy to restore protein synthesis during host infection. Electron paramagnetic resonance (EPR) and tryptophan fluorescence measurements on a 10-residue model of the disordered protein region (Nsp1-CT10), combined with advanced quantum mechanics calculations, suggest that the peptide binds to copper(II) as a multidentate ligand. Two optimized computational models of the copper(II)-peptide complexes were derived: One corresponding to pH 6.5 and the other describing the complex at pH 7.5 to 8.5. Simulated EPR spectra based on the calculated model structures are in good agreement with experimental spectra.

Unveiling the Binding between the Armadillo-Repeat Domain of Plakophilin 1 and the Intrinsically Disordered Transcriptional Repressor RYBP.

Plakophilin 1 (PKP1), a member of the p120ctn subfamily of the armadillo (ARM)-repeat-containing proteins, is an important structural component of cell-cell adhesion scaffolds although it can also be ubiquitously found in the cytoplasm and the nucleus. RYBP (RING 1A and YY1 binding protein) is a multifunctional intrinsically disordered protein (IDP) best described as a transcriptional regulator. Both proteins are involved in the development and metastasis of several types of tumors. We studied the binding of the armadillo domain of PKP1 (ARM-PKP1) with RYBP by using in cellulo methods, namely immunofluorescence (IF) and proximity ligation assay (PLA), and in vitro biophysical techniques, namely fluorescence, far-ultraviolet (far-UV) circular dichroism (CD), and isothermal titration calorimetry (ITC). We also characterized the binding of the two proteins by using in silico experiments. Our results showed that there was binding in tumor and non-tumoral cell lines. Binding in vitro between the two proteins was also monitored and found to occur with a dissociation constant in the low micromolar range (~10 µM). Finally, in silico experiments provided additional information on the possible structure of the binding complex, especially on the binding ARM-PKP1 hot-spot. Our findings suggest that RYBP might be a rescuer of the high expression of PKP1 in tumors, where it could decrease the epithelial-mesenchymal transition in some cancer cells.

Understanding the Energy Landscape of Intrinsically Disordered Protein Ensembles.

A substantial portion of various organisms' proteomes comprises intrinsically disordered proteins (IDPs) that lack a defined three-dimensional structure. These IDPs exhibit a diverse array of conformations, displaying remarkable spatiotemporal heterogeneity and exceptional conformational flexibility. Characterizing the structure or structural ensemble of IDPs presents significant conceptual and methodological challenges owing to the absence of a well-defined native structure. While databases such as the Protein Ensemble Database (PED) provide IDP ensembles obtained through a combination of experimental data and molecular modeling, the absence of reaction coordinates poses challenges in comprehensively understanding pertinent aspects of the system. In this study, we leverage the energy landscape visualization method (JCTC, 6482, 2019) to scrutinize four IDP ensembles sourced from PED. ELViM, a methodology that circumvents the need for a priori reaction coordinates, aids in analyzing the ensembles. The specific IDP ensembles investigated are as follows: two fragments of nucleoporin (NUL: 884-993 and NUS: 1313-1390), yeast sic 1 N-terminal (1-90), and the N-terminal SH3 domain of Drk (1-59). Utilizing ELViM enables the comprehensive validation of ensembles, facilitating the detection of potential inconsistencies in the sampling process. Additionally, it allows for identifying and characterizing the most prevalent conformations within an ensemble. Moreover, ELViM facilitates the comparative analysis of ensembles obtained under diverse conditions, thereby providing a powerful tool for investigating the functional mechanisms of IDPs.

MoRF_ESM: Prediction of MoRFs in disordered proteins based on a deep transformer protein language model.

Molecular recognition features (MoRFs) are particular functional segments of disordered proteins, which play crucial roles in regulating the phase transition of membrane-less organelles and frequently serve as central sites in cellular interaction networks. As the association between disordered proteins and severe diseases continues to be discovered, identifying MoRFs has gained growing significance. Due to the limited number of experimentally validated MoRFs, the performance of existing MoRF's prediction algorithms is not good enough and still needs to be improved. In this research, we present a model named MoRF_ESM, which utilizes deep-learning protein representations to predict MoRFs in disordered proteins. This approach employs a pretrained ESM-2 protein language model to generate embedding representations of residues in the form of attention map matrices. These representations are combined with a self-learned TextCNN model for feature extraction and prediction. In addition, an averaging step was incorporated at the end of the MoRF_ESM model to refine the output and generate final prediction results. In comparison to other impressive methods on benchmark datasets, the MoRF_ESM approach demonstrates state-of-the-art performance, achieving [Formula: see text] higher AUC than other methods when tested on TEST1 and achieving [Formula: see text] higher AUC than other methods when tested on TEST2. These results imply that the combination of ESM-2 and TextCNN can effectively extract deep evolutionary features related to protein structure and function, along with capturing shallow pattern features located in protein sequences, and is well qualified for the prediction task of MoRFs. Given that ESM-2 is a highly versatile protein language model, the methodology proposed in this study can be readily applied to other tasks involving the classification of protein sequences.

The Streptococcus phage protein paratox is an intrinsically disordered protein.

The bacteriophage protein paratox (Prx) blocks quorum sensing in its streptococcal host by directly binding the signal receptor and transcription factor ComR. This reduces the ability of Streptococcus to uptake environmental DNA and protects phage DNA from damage by recombination. Past work characterizing the Prx:ComR molecular interaction revealed that paratox adopts a well-ordered globular fold when bound to ComR. However, solution-state biophysical measurements suggested that Prx may be conformationally dynamic. To address this discrepancy, we investigated the stability and dynamic properties of Prx in solution using circular dichroism, nuclear magnetic resonance, and several fluorescence-based protein folding assays. Our work shows that under dilute buffer conditions Prx is intrinsically disordered. We also show that the addition of kosmotropic salts or protein stabilizing osmolytes induces Prx folding. However, the solute stabilized fold is different from the conformation Prx adopts when it is bound to ComR. Furthermore, we have characterized Prx folding thermodynamics and folding kinetics through steady-state fluorescence and stopped flow kinetic measurements. Our results show that Prx is a highly dynamic protein in dilute solution, folding and refolding within the 10 ms timescale. Overall, our results demonstrate that the streptococcal phage protein Prx is an intrinsically disordered protein in a two-state equilibrium with a solute-stabilized folded form. Furthermore, the solute-stabilized fold is likely the predominant form of Prx in a solute-crowded bacterial cell. Finally, our work suggests that Prx binds and inhibits ComR, and thus quorum sensing in Streptococcus, by a combination of conformational selection and induced-fit binding mechanisms.

Influence of an Intrinsically Disordered Region on Protein Domains Revealed by NMR-Based Electrostatic Potential Measurements.

Many human proteins possess intrinsically disordered regions containing consecutive aspartate or glutamate residues ("D/E repeats"). Approximately half of them are DNA/RNA-binding proteins. In this study, using nuclear magnetic resonance (NMR) spectroscopy, we investigated the electrostatic properties of D/E repeats and their influence on folded domains within the same protein. Local electrostatic potentials were directly measured for the HMGB1 protein, its isolated D/E repeats, and DNA-binding domains by NMR. The data provide quantitative information about the electrostatic interactions between distinct segments of HMGB1. Due to the interactions between the D/E repeats and the DNA-binding domains, local electrostatic potentials of the DNA-binding domains within the full-length HMGB1 protein were largely negative despite the presence of many positively charged residues. Our NMR data on counterions and electrostatic potentials show that the D/E repeats and DNA have similar electrostatic properties and compete for the DNA-binding domains. The competition promotes dissociation of the protein-DNA complex and influences the molecular behavior of the HMGB1 protein. These effects may be general among the DNA/RNA-binding proteins with D/E repeats.

Transferable deep generative modeling of intrinsically disordered protein conformations.

Intrinsically disordered proteins have dynamic structures through which they play key biological roles. The elucidation of their conformational ensembles is a challenging problem requiring an integrated use of computational and experimental methods. Molecular simulations are a valuable computational strategy for constructing structural ensembles of disordered proteins but are highly resource-intensive. Recently, machine learning approaches based on deep generative models that learn from simulation data have emerged as an efficient alternative for generating structural ensembles. However, such methods currently suffer from limited transferability when modeling sequences and conformations absent in the training data. Here, we develop a novel generative model that achieves high levels of transferability for intrinsically disordered protein ensembles. The approach, named idpSAM, is a latent diffusion model based on transformer neural networks. It combines an autoencoder to learn a representation of protein geometry and a diffusion model to sample novel conformations in the encoded space. IdpSAM was trained on a large dataset of simulations of disordered protein regions performed with the ABSINTH implicit solvent model. Thanks to the expressiveness of its neural networks and its training stability, idpSAM faithfully captures 3D structural ensembles of test sequences with no similarity in the training set. Our study also demonstrates the potential for generating full conformational ensembles from datasets with limited sampling and underscores the importance of training set size for generalization. We believe that idpSAM represents a significant progress in transferable protein ensemble modeling through machine learning.

AlphaFold2 modeling and molecular dynamics simulations of an intrinsically disordered protein.

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations.

TurboID mapping reveals the exportome of secreted intrinsically disordered proteins in the transforming parasite Theileria annulata.

Theileria annulata is a tick-transmitted apicomplexan parasite that gained the unique ability among parasitic eukaryotes to transform its host cell, inducing a fatal cancer-like disease in cattle. Understanding the mechanistic interplay between the host cell and malignant Theileria species that drives this transformation requires the identification of responsible parasite effector proteins. In this study, we used TurboID-based proximity labeling, which unbiasedly identified secreted parasite proteins within host cell compartments. By fusing TurboID to nuclear export or localization signals, we biotinylated proteins in the vicinity of the ligase enzyme in the nucleus or cytoplasm of infected macrophages, followed by mass spectrometry analysis. Our approach revealed with high confidence nine nuclear and four cytosolic candidate parasite proteins within the host cell compartments, eight of which had no orthologs in non-transforming T. orientalis. Strikingly, all eight of these proteins are predicted to be highly intrinsically disordered proteins. We discovered a novel tandem arrayed protein family, nuclear intrinsically disordered proteins (NIDP) 1-4, featuring diverse functions predicted by conserved protein domains. Particularly, NIDP2 exhibited a biphasic host cell-cycle-dependent localization, interacting with the EB1/CD2AP/CLASP1 parasite membrane complex at the schizont surface and the tumor suppressor stromal antigen 2 (STAG2), a cohesion complex subunit, in the host nucleus. In addition to STAG2, numerous NIDP2-associated host nuclear proteins implicated in various cancers were identified, shedding light on the potential role of the T. annulata exported protein family NIDP in host cell transformation and cancer-related pathways.IMPORTANCETurboID proximity labeling was used to identify secreted proteins of Theileria annulata, an apicomplexan parasite responsible for a fatal, proliferative disorder in cattle that represents a significant socio-economic burden in North Africa, central Asia, and India. Our investigation has provided important insights into the unique host-parasite interaction, revealing secreted parasite proteins characterized by intrinsically disordered protein structures. Remarkably, these proteins are conspicuously absent in non-transforming Theileria species, strongly suggesting their central role in the transformative processes within host cells. Our study identified a novel tandem arrayed protein family, with nuclear intrinsically disordered protein 2 emerging as a central player interacting with established tumor genes. Significantly, this work represents the first unbiased screening for exported proteins in Theileria and contributes essential insights into the molecular intricacies behind the malignant transformation of immune cells.