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The study of protein-drug interaction plays a crucial role in understanding drug mechanisms, identifying new drug targets and biomarkers, and facilitating drug development and disease treatment. In recent years, significant progress has been made in various protein-drug interaction research methods due to the rapid development and in-depth application of mass spectrometry, nuclear magnetic resonance, Raman spectroscopy, and other technologies. The progress has enhanced the sensitivity, precision, accuracy, and applicability of analytical methods, enabling the establishment of drug-protein interaction networks. This review discusses various emerging research methods, such as native mass spectrometry, infrared spectroscopy, nuclear magnetic resonance and spectrum, biosensor technologies employing surface enhanced Raman, electrochemistry, and magneto resistive signals, as well as affinity magnetic levitation and affinity chromatography. The article also delves into the principles, applications, advantages, and limitations of these technologies.

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Protein mechanical stability determines the function of a myriad of proteins, especially proteins from the extracellular matrix. Failure to maintain protein mechanical stability may result in diseases and disorders such as cancer, cardiomyopathies, or muscular dystrophy. Thus, developing mutation-free approaches to enhance and control the mechanical stability of proteins using pharmacology-based methods may have important implications in drug development and discovery. Here, we present the first approach that employs computational high-throughput virtual screening and molecular docking to search for small molecules in chemical libraries that function as mechano-regulators of the stability of human cluster of differentiation 4, receptor of HIV-1. Using single-molecule force spectroscopy, we prove that these small molecules can increase the mechanical stability of CD4D1D2 domains over 4-fold in addition to modifying the mechanical unfolding pathways. Our experiments demonstrate that chemical libraries are a source of mechanoactive molecules and that drug discovery approaches provide the foundation of a new type of molecular function, that is, mechano-regulation, paving the way toward mechanopharmacology.

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Previous work showed that matrix metalloproteinase-7 (MMP-7) regulates colon cancer activities through an interaction with syndecan-2 (SDC-2) and SDC-2-derived peptide that disrupts this interaction and exhibits anticancer activity in colon cancer. Here, to identify potential anticancer agents, a library of 1,379 Food and Drug Administration (FDA)-approved drugs that interact with the MMP-7 prodomain were virtually screened by protein-ligand docking score analysis using the GalaxyDock3 program. Among five candidates selected based on their structures and total energy values for interacting with the MMP-7 prodomain, the known mechanistic target of rapamycin kinase (mTOR) inhibitor, everolimus, showed the highest binding affinity and the strongest ability to disrupt the interaction of the MMP-7 prodomain with the SDC-2 extracellular domain in vitro. Everolimus treatment of the HCT116 human colon cancer cell line did not affect the mRNA expression levels of MMP-7 and SDC-2 but reduced the adhesion of cells to MMP-7 prodomain-coated plates and the cell-surface localization of MMP-7. Thus, everolimus appears to inhibit the interaction between MMP-7 and SDC-2. Everolimus treatment of HCT116 cells also reduced their gelatin-degradation activity and anticancer activities, including colony formation. Interestingly, cells treated with sirolimus, another mTOR inhibitor, triggered less gelatin-degradation activity, suggesting that this inhibitory effect of everolimus was not due to inhibition of the mTOR pathway. Consistently, everolimus inhibited the colony-forming ability of mTOR-resistant HT29 cells. Together, these data suggest that, in addition to inhibiting mTOR signaling, everolimus exerts anticancer activity by interfering with the interaction of MMP-7 and SDC-2, and could be a useful therapeutic anticancer drug for colon cancer.NEW & NOTEWORTHY The utility of cancer therapeutics targeting the proteolytic activities of MMPs is limited because MMPs are widely distributed throughout the body and involved in many different aspects of cell functions. This work specifically targets the activation of MMP-7 through its interaction with syndecan-2. Notably, everolimus, a known mTOR inhibitor, blocked this interaction, demonstrating a novel role for everolimus in inhibiting mTOR signaling and impairing the interaction of MMP-7 with syndecan-2 in colon cancer.

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Striatal-enriched protein tyrosine phosphatase (STEP) is a brain-specific enzyme that regulates the signaling molecules that control synaptic plasticity and neuronal function. Dysregulation of STEP is linked to the pathophysiology of Alzheimer's disease and other neuropsychiatric disorders. Experimental results from neurological deficit disease models suggest that the modulation of STEP could be beneficial in a number of these disorders. This prompted our work to identify small-molecule modulators of STEP to provide the foundation of a drug discovery program. As a component of our testing funnel to identify small-molecule STEP inhibitors, we have developed a cellular target engagement assay that can identify compounds that interact with STEP46. We provide a comprehensive protocol to enable the use of this miniaturized assay, and we demonstrate its utility to benchmark the binding of newly discovered compounds.

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Human nucleolin (hNcl) is a multifunctional protein involved in the progression of various cancers and plays a key role in other pathologies. Therefore, there is still unsatisfied demand for hNcl modulators. Recently, we demonstrated that the plant ent-kaurane diterpene oridonin inhibits hNcl but, unfortunately, this compound is quite toxic for healthy cells. Trachylobane diterpene 6,19-dihydroxy-ent-trachiloban-17-oic acid (compound 12) extracted from Psiadia punctulata (DC.) Vatke (Asteraceae) emerged as a ligand of hNcl from a cellular thermal shift assay (CETSA)-based screening of a small library of diterpenes. Effective interaction between this compound and the protein was demonstrated to occur both in vitro and inside two different types of cancer cells. Based on the experimental and computational data, a model of the hNcl/compound 12 complex was built. Because of this binding, hNcl mRNA chaperone activity was significantly reduced, and the level of phosphorylation of the protein was affected. At the biological level, cancer cell incubation with compound 12 produced a cell cycle block in the subG0/G1 phase and induced early apoptosis, whereas no cytotoxicity towards healthy cells was observed. Overall, these results suggested that 6,19-dihydroxy-ent-trachiloban-17-oic could represent a selective antitumoral agent and a promising lead for designing innovative hNcl inhibitors also usable for therapeutic purposes.

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The coronavirus disease 2019 pandemic accelerated drug/vaccine development processes, integrating scientists all over the globe to create therapeutic alternatives against this virus. In this work, we have collected information regarding proteins from SARS-CoV-2 and humans and how these proteins interact. We have also collected information from public databases on protein-drug interactions. We represent this data as networks that allow us to gain insights into protein-protein interactions between both organisms. With the collected data, we have obtained statistical metrics of the networks. This data analysis has allowed us to find relevant information on which proteins and drugs are the most relevant from the network pharmacology perspective. This method not only allows us to focus on viral proteins as the main targets for COVID-19 but also reveals that some human proteins could be also important in drug repurposing campaigns. As a result of the analysis of the SARS-CoV-2-human interactome, we have identified some old drugs, such as disulfiram, auranofin, gefitinib, suloctidil, and bromhexine as potential therapies for the treatment of COVID-19 deciphering their potential complex mechanism of action.

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The mutant p53Y220C (mutp53Y220C) is frequently observed in numerous tumors, including pancreatic cancer. The mutation creates a crevice in the DNA binding core domain and makes p53 a thermally unstable non-functional protein that assists tumor progression and confers resistance to chemotherapeutic drugs. Restoring mutp53 function to its wild type by selectively targeting this crevice with small molecules is a pivotal strategy to promote apoptosis. In this study, we have shown through different biophysical and cell-based studies that curcumin binds and rescues mutp53Y220C to an active wild-type conformation and restores its apoptotic transcription function in BxPC-3-pancreatic cancer cells. In addition, the curcumin-rescued-p53Y220C (CRp53) showed significant hyperphosphorylation at Ser15, Ser20, and acetylation at Lys382 with an 8-fold increase in transcription activity in the BxPC-3 cell lines. We also observed that the active CRp53 escapes Mdm2-mediated proteasomal degradation and the majority of the proteins were localized inside the nucleus with an increased half-life and transcription restoration compared to untreated BxPC-3 cells. By label-free proteomics analysis, we observed that upon curcumin treatment almost 227 proteins were dysregulated with the majority of them being transcriptional targets of p53. Based on our studies, it reflects that apoptosis in pancreatic cancer cells is mediated by curcumin-rescued mutant p53Y220C.

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The majority of drug screening approaches are performed using recombinant proteins, however, drug binding to its target(s) in cells should be also assessed, especially for drugs aimed at modulating intracellular signaling pathways. As a result, the development of a cellular thermal shift assay (CETSA) has become an important tool for determining the binding affinity of drugs to their intracellular targets. Cell lines, such as Ba/F3, are an excellent model system to stably express and study a target protein when this protein is not endogenously expressed or only present at low levels. Together with CETSA, Ba/F3 clones allow study of the transforming properties of the protein in question, its downstream intracellular signaling activation pathways, as well as its drug binding kinetics. This chapter describes in detail the establishment of Ba/F3 clones stably expressing receptor pseudokinases, such as receptor tyrosine kinase-like orphan receptors (ROR1, ROR2) and protein tyrosine kinase 7 (PTK7), and the use thereof to evaluate binding of small molecule inhibitors to their intracellular (pseudo)kinase domain by CETSA.

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INTRODUCTION: Selonsertib, the most recently developed selective inhibitor of apoptosis signal-regulating kinase 1. We elucidated the binding characteristics, mechanism of interaction, and dynamic behaviors of selonsertib with human serum albumin (HSA), a major circulatory transport protein. METHODS: Different biophysical approaches (fluorescence quenching and isothermal titration calorimetry (ITC) were combined with various in silico techniques to examine the binding of selonsertib to HSA. Molecular docking results, analysis of molecular dynamics trajectories, and essential dynamics investigations indicated the stable binding of selonsertib to HSA. Further in vitro studies were performed to validate the observed interaction. RESULTS: ITC results confirmed the robust binding and high affinity of selonsertib and HSA. Likewise, the fluorescence quenching results highlighted the binding affinity of selonsertib and HSA. Collectively, our findings offer deeper insight into the binding mechanism of selonsertib and HSA, emphasizing the selonsertib-mediated structural changes within HSA, along with a comprehensive rationale for the biological transport and accumulation of selonsertib in the blood plasma. CONCLUSION: Therefore, considering the bioavailability and effectiveness of selonsertib, assessing the interactions of this inhibitor with carrier proteins is crucial to elucidate its biological processes at the molecular level. This evidence carries the considerable scientific potential for future drug design.

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Parkinson's disease (PD) is a neurodegenerative disorder responsible for shaking, rigidity, and trouble in walking and patients' coordination ability and physical stability deteriorate day by day. Bipolar disorder (BD) is a psychiatric disorder which is the reason behind extreme shiftiness in mood, and frequent mood inversion may reach too high called mania. People with BD have a greater chance of developing PD during the follow-up period. A lot of work has been done to understand the key factors for developing these 2 diseases. But the molecular functionalities that trigger the development of PD in people with BD are not clear yet. In our study, we are intended to identify the molecular biomarkers and pathways shared between BD and PD. We have investigated the RNA-Seq gene expression data sets of PD and BD. A total of 45 common unique genes (32 up-regulated and 13 down-regulated) abnormally expressed in both PD and BD were identified by applying statistical methods on the GEO data sets. Gene ontology (GO) and BioCarta, KEGG, and Reactome pathways analysis of these 45 common dysregulated genes identified numerous altered molecular pathways such as mineral absorption, Epstein-Barr virus infection, HTLV-I infection, antigen processing, and presentation. Analysis of protein-protein interactions revealed 9 significant hub-proteins, namely RPL21, RPL34, CKS2, B2M, TNFRSF10A, DTX2, HLA-B, ATP2A3, and TAPBP. Significant transcription factors (IRF8, SPI1, RUNX1, and FOXA1) and posttranscriptional regulator microRNAs (hsa-miR-491-3p and hsa-miR-1246) are also found by analyzing gene-transcription factors and gene-miRNAs interactions, respectively. Protein-drug interaction analysis revealed hub-protein B2M's interaction with molecular drug candidates like N-formylmethionine, 3-indolebutyric acid, and doxycycline. Finally, a link between pathological processes of PD and BD is identified at transcriptional level. This study may help us to predict the development of PD among the people suffering from BD and gives some clue to understand significant pathological mechanisms.

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Alzheimer's disease (AD) and type 2 diabetes (T2D) are common in the general elderly population, conferring heavy individual, social, and economic stresses on families and society. Accumulating evidence indicates T2D to be a risk factor for AD. However, the underlying mechanisms for this association are largely unknown. This study aimed to identify the shared molecular signatures between AD and T2D through integrated analysis of temporal cortex gene expression data. Gene Ontology (GO) and pathway enrichment analysis, protein over-representation analysis, protein-protein interaction, DEG-transcription factor interactions, DEG-microRNA interactions, protein-drug interactions, gene-disease association analysis, and protein subcellular localization analysis of the common DEGs were performed. We identified 16 common DEGs between the two datasets, which were mainly enriched in the biological processes of apoptosis, autophagy, inflammation, and hemostasis. We also identified five hub proteins encoded by the DEGs, five central regulatory transcription factors, and six microRNAs. Protein-drug interaction analysis showed C1QB to be associated with different drugs. Gene-disease association analysis revealed that hub genes, SFN and ITGB2, were actively engaged in other diseases. Collectively, these findings provide new insights into shared molecular mechanisms between AD and T2D and provide novel candidate targets for therapeutic intervention.

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Mycobacterium leprae, the causative organism of leprosy, harbors many antigenic proteins, and one such protein is the 18-kDa antigen. This protein belongs to the small heat shock protein family and is commonly known as HSP18. Its chaperone function plays an important role in the growth and survival of M. leprae inside infected hosts. HSP18/18-kDa antigen is often used as a diagnostic marker for determining the efficacy of multidrug therapy (MDT) in leprosy. However, whether MDT drugs (dapsone, clofazimine, and rifampicin) do interact with HSP18 and how these interactions affect its structure and chaperone function is still unclear. Here, we report evidence of HSP18-dapsone/clofazimine/rifampicin interaction and its impact on the structure and chaperone function of HSP18. These three drugs interact efficiently with HSP18 (having submicromolar binding affinity) with 1 : 1 stoichiometry. Binding of these MDT drugs to the 'α-crystallin domain' of HSP18 alters its secondary structure and tryptophan micro-environment. Furthermore, surface hydrophobicity, oligomeric size, and thermostability of the protein are reduced upon interaction with these three drugs. Eventually, all these structural alterations synergistically decrease the chaperone function of HSP18. Interestingly, the effect of rifampicin on the structure, stability, and chaperone function of this mycobacterial small heat shock protein is more pronounced than the other two MDT drugs. This reduction in the chaperone function of HSP18 may additionally abate M. leprae survivability during multidrug treatment. Altogether, this study provides a possible foundation for rational designing and development of suitable HSP18 inhibitors in the context of effective treatment of leprosy.

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Understanding the core replication complex of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential to the development of novel coronavirus-specific antiviral therapeutics. Among the proteins required for faithful replication of the SARS-CoV-2 genome are nonstructural protein 14 (NSP14), a bifunctional enzyme with an N-terminal 3'-to-5' exoribonuclease (ExoN) and a C-terminal N7-methyltransferase, and its accessory protein, NSP10. The difficulty in producing pure and high quantities of the NSP10/14 complex has hampered the biochemical and structural study of these important proteins. We developed a straightforward protocol for the expression and purification of both NSP10 and NSP14 from Escherichia coli and for the in vitro assembly and purification of a stoichiometric NSP10/14 complex with high yields. Using these methods, we observe that NSP10 provides a 260-fold increase in kcat/Km in the exoribonucleolytic activity of NSP14 and enhances protein stability. We also probed the effect of two small molecules on NSP10/14 activity, remdesivir monophosphate and the methyltransferase inhibitor S-adenosylhomocysteine. Our analysis highlights two important factors for drug development: first, unlike other exonucleases, the monophosphate nucleoside analog intermediate of remdesivir does not inhibit NSP14 activity; and second, S-adenosylhomocysteine modestly activates NSP14 exonuclease activity. In total, our analysis provides insights for future structure-function studies of SARS-CoV-2 replication fidelity for the treatment of coronavirus disease 2019.

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Background: Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there are limited studies reflecting the available biomarkers from separate gene expression profiles in PAH. This study explored two microarray datasets by an integrative analysis to estimate the molecular signatures in PAH. Methods: Two microarray datasets (GSE53408 and GSE113439) were exploited to compare lung tissue transcriptomes of patients and controls with PAH and to estimate differentially expressed genes (DEGs). According to common DEGs of datasets, gene and protein overrepresentation analyses, protein-protein interactions (PPIs), DEG-transcription factor (TF) interactions, DEG-microRNA (miRNA) interactions, drug-target protein interactions, and protein subcellular localizations were conducted in this study. Results: We obtained 38 common DEGs for these two datasets. Integration of the genome transcriptome datasets with biomolecular interactions revealed hub genes (HSP90AA1, ANGPT2, HSPD1, HSPH1, TTN, SPP1, SMC4, EEA1, and DKC1), TFs (FOXC1, FOXL1, GATA2, YY1, and SRF), and miRNAs (hsa-mir-17-5p, hsa-mir-26b-5p, hsa-mir-122-5p, hsa-mir-20a-5p, and hsa-mir-106b-5p). Protein-drug interactions indicated that two compounds, namely, nedocromil and SNX-5422, affect the identification of PAH candidate biomolecules. Moreover, the molecular signatures were mostly localized in the extracellular and nuclear areas. Conclusions: In conclusion, several lung tissue-derived molecular signatures, highlighted in this study, might serve as novel evidence for elucidating the essential mechanisms of PAH. The potential drugs associated with these molecules could thus contribute to the development of diagnostic and therapeutic strategies to ameliorate PAH.

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Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. Here, we develop iDTPnd (integrated Drug Target Predictor with negative dataset), a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding sites. To facilitate assessment of unintended targets, iDTPnd also provides a docking-based interaction score and its statistical significance. We confirm the interactions of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity of 52% and a specificity of 55%. We also validate 10 predicted novel targets by using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450, and MHC class I molecules, can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein-small molecule interactions, when sufficient drug-target 3D data are available. The code for constructing the structural signatures is available at https://sfb.kaust.edu.sa/Documents/iDTP.zip.

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The interactions of proteins with drugs are very important from a pharmacological point of view. Holo-transferrin is a blood-plasma glycoprotein whose main function is iron-binding and the transport of other ligands. Additionally, the protein is only transferrin-form recognized by TfR1 and TfR2 receptors at the surface of rapidly proliferating malignant cells. Imatinib mesylate is a tyrosine-kinase inhibitor mainly used in the treatment of blood cancers, frequently in multidrug therapy with cyclophosphamide. In this study the effect of cyclophosphamide on the interaction of imatinib mesylate with human holo-transferrin has been investigated. Using spectroscopic techniques such as fluorescence, circular dichroism, ultraviolet-visible and electrophoretic light scattering additive parameters, system stability and the effect of the ligands on the protein conformation at varying pH values have been defined. Calculated quenching constants are in the order of 2 × 104 M-1 and the type of interaction depends on the reaction medium. Under physiological conditions binding constant is 1.329 × 106 M-1 whereas in an environment similar to that of cancer cells the constant is significantly lower, Ka = 6.060 × 104 M-1. N values are approximate to 1 in all cases. Moreover, some changes are observed in the α-helical structure of the protein after interaction with the drugs and the presence of cyclophosphamide slightly stabilizes the protein secondary structure. All collected data proves the effect of cyclophosphamide on the interaction between imatinib mesylate and human holo-transferrin. It is of great clinical interest due to anticancer, multidrug therapies including both imatinib mesylate and cyclophosphamide.

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The well-defined and characterized 3D crystal structure of a protein is important to explore the topological and physiological features of the protein. The distinguished topography of a protein helps medical chemists design drugs on the basis of the pharmacophoric features of the protein. Structure-based drug discovery, specifically for pathological proteins that cause a higher risk of disease, takes advantage of this fact. Current tools for studying drug-protein interactions include physical, chromatographic, and electrophoretic methods. These techniques can be separated into either non-spectroscopic (equilibrium dialysis, ultrafiltration, ultracentrifugation, etc.) or spectroscopic (Fluorescence spectroscopy, NMR, X-ray diffraction, etc.) methods. These methods, however, can be time-consuming and expensive. On the other hand, in silico methods of analyzing protein-drug interactions, such as docking, molecular simulations, and High-Throughput Virtual Screenings (HTVS), are heavily underutilized by core drug discovery laboratories. These kinds of approaches have a great potential for the mass screening of potential small drugs molecules. Studying protein-drug interactions is of particular importance for understanding how the structural conformation of protein elements affect overall ligand binding affinity. By taking a bioinformatics approach to analyzing drug-protein interactions, the speed with which we identify potential drugs for genetic targets can be greatly increased.

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Centrioles are key eukaryotic organelles that are responsible for the formation of cilia and flagella, and for organizing the microtubule network and the mitotic spindle in animals. Centriole assembly requires oligomerization of the essential protein spindle assembly abnormal 6 (SAS-6), which forms a structural scaffold templating the organization of further organelle components. A dimerization interaction between SAS-6 N-terminal "head" domains was previously shown to be essential for protein oligomerization in vitro and for function in centriole assembly. Here, we developed a pharmacophore model allowing us to assemble a library of low-molecular-weight ligands predicted to bind the SAS-6 head domain and inhibit protein oligomerization. We demonstrate using NMR spectroscopy that a ligand from this family binds at the head domain dimerization site of algae, nematode, and human SAS-6 variants, but also that another ligand specifically recognizes human SAS-6. Atomistic molecular dynamics simulations starting from SAS-6 head domain crystallographic structures, including that of the human head domain which we now resolve, suggest that ligand specificity derives from favorable Van der Waals interactions with a hydrophobic cavity at the dimerization site.

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Emerging evidence indicates IBD is a risk factor for the increasing incidence of colorectal cancer (CRC) development. We used a system biology approach to identify common molecular signatures and pathways that interact between IBD and CRC and the indispensable pathological mechanisms. First, we identified 177 common differentially expressed genes (DEGs) between IBD and CRC. Gene set enrichment, protein-protein, DEGs-transcription factors, DEGs-microRNAs, protein-drug interaction, gene-disease association, Gene Ontology, pathway enrichment analyses were conducted to these common genes. The inclusion of common DEGs with bimolecular networks disclosed hub proteins (LYN, PLCB1, NPSR1, WNT5A, CDC25B, CD44, RIPK2, ASAP1), transcription factors (SCD, SLC7A5, IKZF3, SLC16A1, SLC7A11) and miRNAs (mir-335-5p, mir-26b-5p, mir-124-3p, mir-16-5p, mir-192-5p, mir-548c-3p, mir-29b-3p, mir-155-5p, mir-21-5p, mir-15a-5p). Analysis of the interaction between protein and drug discovered ASAP1 interacts with cysteine sulfonic acid and double oxidized cysteine drug compounds. Gene-disease association analysis retrieved ASAP1 also associated with pulmonary and bladder neoplasm diseases.

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Modification-dependent and -independent biomolecular interactions, including protein-protein, protein-DNA/RNA, protein-sugar, and protein-lipid interactions, play crucial roles in all cellular processes. Dysregulation of these biomolecular interactions or malfunction of the associated enzymes results in various diseases; therefore, these interactions and enzymes are attractive targets for therapies. High-throughput screening can greatly facilitate the discovery of drugs for these targets. Here, we describe a biomolecular interaction detection method, called phase-separated condensate-aided enrichment of biomolecular interactions in test tubes (CEBIT). The readout of CEBIT is the selective recruitment of biomolecules into phase-separated condensates harboring their cognate binding partners. We tailored CEBIT to detect various biomolecular interactions and activities of biomolecule-modifying enzymes. Using CEBIT-based high-throughput screening assays, we identified known inhibitors of the p53/MDM2 (MDM2) interaction and of the histone methyltransferase, suppressor of variegation 3-9 homolog 1 (SUV39H1), from a compound library. CEBIT is simple and versatile, and is likely to become a powerful tool for drug discovery and basic biomedical research.

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