Phosphorylated protein chip combined with artificial intelligence tools for precise drug screening.

We have developed a protein array system, named "Phospho-Totum", which reproduces the phosphorylation state of a sample on the array. The protein array contains 1471 proteins from 273 known signaling pathways. According to the activation degrees of tyrosine kinases in the sample, the corresponding groups of substrate proteins on the array are phosphorylated under the same conditions. In addition to measuring the phosphorylation levels of the 1471 substrates, we have developed and performed the artificial intelligence-assisted tools to further characterize the phosphorylation state and estimate pathway activation, tyrosine kinase activation, and a list of kinase inhibitors that produce phosphorylation states similar to that of the sample. The Phospho-Totum system, which seamlessly links and interrogates the measurements and analyses, has the potential to not only elucidate pathophysiological mechanisms in diseases by reproducing the phosphorylation state of samples, but also be useful for drug discovery, particularly for screening targeted kinases for potential drug kinase inhibitors.

RNAapt3D: RNA aptamer 3D-structural modeling database.

RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.

Phosprof: pathway analysis database of drug response based on phosphorylation activity measurements.

Protein phosphorylation plays a fundamental role in many cellular processes. Proteins are phosphorylated by kinases, which have been studied as drug targets for the treatment of various diseases, particularly cancer. Because kinases have multiple roles in interconnected molecular pathways, their specific regulation is required to enhance beneficial and reduce adversarial effects of drugs. Using our previously developed platform, we measured phosphorylation profiles of MCF7 and K562 cells treated with 94 clinical drugs. These phosphorylation profiles can provide insights into pathway activities and biological functions. Here, we introduce Phosprof, a novel database of drug response based on phosphorylation activity. Phosprof is able to present up- or downregulated phosphorylated signature proteins on pathway maps, significant pathways on the hierarchal tree in signal transduction and commonly perturbed pathways affected by the selected drugs. It also serves as a useful web interface for new or known drug profile search based on their molecular similarity with the 94 drugs. Phosprof can be helpful for further investigation of drug responses in terms of phosphorylation by utilizing the various approved drugs whose target phenotypes are known. DATABASE URL: https://phosprof.medals.jp/.

Assessing the activation/inhibition of tyrosine kinase-related pathways with a newly developed platform.

The phosphorylation of cellular proteins plays a crucial role in the transduction of various signals from outside the cell into the nucleus. The signals are transduced by phosphorylation chain reactions within multiple pathways; however, determining which pathways are responsible for each defined signal has proven challenging. To estimate the activity of each pathway, we developed a phosphorylation array platform comprising a protein array with 1200 proteins belonging to 376 signalling pathways and an analytical method to estimate pathway activity based on the phosphorylation levels of proteins. The performance of our system was assessed by reconstructing kinase-substrate relationships, as well as by estimating pathway activity upon epidermal growth factor (EGF) stimulation and the pharmacological inhibition of epidermal growth factor receptor (EGFR). As a result, kinase-substrate relationships were reliably reconstructed based on the precise measurement of phosphorylation levels of constituent proteins on the array. Furthermore, the pathway activities associated with EGF stimulation and EGFR inhibition were successfully traced through the related pathways from the outer membrane to the nucleus along a time course. Thus, our phosphorylation array system can effectively assess the activity of specific signalling pathways that are perturbed by extracellular stimuli, such as various drugs.

Application of multiple omics and network projection analyses to drug repositioning for pathogenic mosquito-borne viruses.

Pathogenic mosquito-borne viruses are a serious public health issue in tropical and subtropical regions and are increasingly becoming a problem in other climate zones. Drug repositioning is a rapid, pharmaco-economic approach that can be used to identify compounds that target these neglected tropical diseases. We have applied a computational drug repositioning method to five mosquito-borne viral infections: dengue virus (DENV), zika virus (ZIKV), West Nile virus (WNV), Japanese encephalitis virus (JEV) and Chikungunya virus (CHIV). We identified signature molecules and pathways for each virus infection based on omics analyses, and determined 77 drug candidates and 146 proteins for those diseases by using a filtering method. Based on the omics analyses, we analyzed the relationship among drugs, target proteins and the five viruses by projecting the signature molecules onto a human protein-protein interaction network. We have classified the drug candidates according to the degree of target proteins in the protein-protein interaction network for the five infectious diseases.

Potential use of lenvatinib for patients with unresectable hepatocellular carcinoma including after treatment with sorafenib: Real-world evidence and in vitro assessment via protein phosphorylation array.

The efficacy and safety of lenvatinib (LEN) as a second/third-line treatment for unresectable hepatocellular carcinoma (HCC) after sorafenib (SOR) therapy remains unknown. We evaluated the outcomes of second/third-line LEN treatment, investigated the sensitivity of a SOR-resistant HCC cell line (PLC/PRF5-R2) to LEN, and assessed their signal transduction pathways by protein array analysis. We retrospectively enrolled 57 patients with unresectable HCC. Fifty-three radiologically evaluated patients comprised 34 molecular-targeted agent (MTA)-naive (first-line), nine intolerant to SOR (second-line), and 10 resistant to regorafenib (third-line). The objective response rates (ORRs) were 61.8% in first-line, 33.3% in second-line, and 20.0% in third-line groups. The overall survival (OS) in the first-line was significantly longer than that in the third-line group (p < 0.05). Patients with better liver functional reserves (child score, ALBI grade) exhibited higher ORR and longer OS. The IC50 of LEN against PLC/PRF5-R2 was significantly higher than that against PLC/PRF5. LEN significantly inhibited more LEN-related signal transduction pathways in PLC/PRF5 than in PLC/PRF5-R2 cells. This suggests that LEN is active and safe as a second/third-line treatment for unresectable HCC. LEN seems more effective for patients with HCC with better hepatic reserve functions or before MTA-resistance is acquired because of the partial cross-resistance to SOR.

IGF2 Autocrine-Mediated IGF1R Activation Is a Clinically Relevant Mechanism of Osimertinib Resistance in Lung Cancer.

EGFR-mutated lung cancer accounts for a significant proportion of lung cancer cases worldwide. For these cases, osimertinib, a third-generation EGFR tyrosine kinase inhibitor, is extensively used as a first-line or second-line treatment. However, lung cancer cells acquire resistance to osimertinib in 1 to 2 years. Thus, a thorough clarification of resistance mechanisms to osimertinib is highly anticipated. Recent next-generation sequencing (NGS) of lung cancer samples identified several genetically defined resistance mechanisms to osimertinib, such as EGFR C797S or MET amplification. However, nongenetically defined mechanisms are not well evaluated. For a thorough clarification of osimertinib resistance, both genetic and nongenetic mechanisms are essential. By using our comprehensive protein phosphorylation array, we detected IGF1R bypass pathway activation after EGFR abolishment. Both of our established lung cancer cells and patient-derived lung cancer cells demonstrated IGF2 autocrine-mediated IGF1R pathway activation as a mechanism of osimertinib resistance. Notably, this resistance mechanism was not detected by a previously performed NGS, highlighting the essential roles of living cancer cells for a thorough clarification of resistance mechanisms. Interestingly, the immunohistochemical analysis confirmed the increased IGF2 expression in lung cancer patients who were treated with osimertinib and met the established clinical definition of acquired resistance. The findings highlight the crucial roles of cell-autonomous ligand expression in osimertinib resistance. Here, we report for the first time the IGF2 autocrine-mediated IGF1R activation as a nongenetic mechanism of osimertinib resistance in lung cancer at a clinically relevant level. IMPLICATIONS: Using comprehensive protein phosphorylation array and patient-derived lung cancer cells, we found that IGF2 autocrine-mediated IGF1R pathway activation is a clinically relevant and common mechanism of acquired resistance to osimertinib.

Promotion of the Warburg effect is associated with poor benefit from adjuvant chemotherapy in colorectal cancer.

Metabolic reprogramming, including the Warburg effect, is a hallmark of cancer. Indeed, the diversity of cancer metabolism leads to cancer heterogeneity, but accurate assessment of metabolic properties in tumors has not yet been undertaken. Here, we performed absolute quantification of the expression levels of 113 proteins related to carbohydrate metabolism and antioxidant pathways, in stage III colorectal cancer surgical specimens from 70 patients. The Warburg effect appeared in absolute protein levels between tumor and normal mucosa specimens demonstrated. Notably, the levels of proteins associated with the tricarboxylic citric acid cycle were remarkably reduced in the malignant tumors which had relapsed after surgery and treatment with 5-fluorouracil-based adjuvant therapy. In addition, the efficacy of 5-fluorouracil also decreased in the cultured cancer cell lines with promotion of the Warburg effect. We further identified nine and eight important proteins, which are closely related to the Warburg effect, for relapse risk and 5-fluorouracil benefit, respectively, using a biomarker exploration procedure. These results provide us a clue for bridging between metabolic protein expression profiles and benefit from 5-fluorouracil adjuvant chemotherapy.

CD4+ T-cell Immunity in the Peripheral Blood Correlates with Response to Anti-PD-1 Therapy.

Accumulating evidence indicates that CD8+ T cells in the tumor microenvironment and systemic CD4+ T-cell immunity play an important role in mediating durable antitumor responses. We longitudinally examined T-cell immunity in the peripheral blood of patients with non-small lung cancer and found that responders had significantly (P < 0.0001) higher percentages of effector, CD62Llow CD4+ T cells prior to PD-1 blockade. Conversely, the percentage of CD25+FOXP3+ CD4+ T cells was significantly (P = 0.034) higher in nonresponders. We developed a formula, which demonstrated 85.7% sensitivity and 100% specificity, based on the percentages of CD62Llow CD4+ T cells and CD25+FOXP3+ cells to predict nonresponders. Mass cytometry analysis revealed that the CD62Llow CD4+ T-cell subset expressed T-bet+, CD27-, FOXP3-, and CXCR3+, indicative of a Th1 subpopulation. CD62Llow CD4+ T cells significantly correlated with effector CD8+ T cells (P = 0.0091) and with PD-1 expression on effector CD8+ T cells (P = 0.0015). Gene expression analysis revealed that CCL19, CLEC-2A, IFNA, IL7, TGFBR3, CXCR3, and HDAC9 were preferentially expressed in CD62Llow CD4+ T cells derived from responders. Notably, long-term responders, who had >500-day progression-free survival, showed significantly higher numbers of CD62Llow CD4+ T cells prior to PD-1 blockade therapy. Decreased CD62Llow CD4+ T-cell percentages after therapy resulted in acquired resistance, with long-term survivors maintaining high CD62Llow CD4+ T-cell percentages. These results pave the way for new treatment strategies for patients by monitoring CD4+ T-cell immune statuses in their peripheral blood.

ToGo-WF: prediction of RNA tertiary structures and RNA-RNA/protein interactions using the KNIME workflow.

Recent progress in molecular biology has revealed that many non-coding RNAs regulate gene expression or catalyze biochemical reactions in tumors, viruses and several other diseases. The tertiary structure of RNA molecules and RNA-RNA/protein interaction sites are of increasing importance as potential targets for new medicines that treat a broad array of human diseases. Current RNA drugs are split into two groups: antisense RNA molecules and aptamers. In this report, we present a novel workflow to predict RNA tertiary structures and RNA-RNA/protein interactions using the KNIME environment, which enabled us to assemble a combination of RNA-related analytical tools and databases. In this study, three analytical workflows for comprehensive structural analysis of RNA are introduced: (1) prediction of the tertiary structure of RNA; (2) prediction of the structure of RNA-RNA complexes and analysis of their interactions; and (3) prediction of the structure of RNA-protein complexes and analysis of their interactions. In an RNA-protein case study, we modeled the tertiary structure of pegaptanib, an aptamer drug, and performed docking calculations of the pegaptanib-vascular endothelial growth factor complex using a fragment of the interaction site of the aptamer. We also present molecular dynamics simulations of the RNA-protein complex to evaluate the affinity of the complex by mutating bases at the interaction interface. The results provide valuable information for designing novel features of aptamer-protein complexes.

Drug repositioning for dengue haemorrhagic fever by integrating multiple omics analyses.

To detect drug candidates for dengue haemorrhagic fever (DHF), we employed a computational drug repositioning method to perform an integrated multiple omics analysis based on transcriptomic, proteomic, and interactomic data. We identified 3,892 significant genes, 389 proteins, and 221 human proteins by transcriptomic analysis, proteomic analysis, and human-dengue virus protein-protein interactions, respectively. The drug candidates were selected using gene expression profiles for inverse drug-disease relationships compared with DHF patients and healthy controls as well as interactomic relationships between the signature proteins and chemical compounds. Integrating the results of the multiple omics analysis, we identified eight candidates for drug repositioning to treat DHF that targeted five proteins (ACTG1, CALR, ERC1, HSPA5, SYNE2) involved in human-dengue virus protein-protein interactions, and the signature proteins in the proteomic analysis mapped to significant pathways. Interestingly, five of these drug candidates, valparoic acid, sirolimus, resveratrol, vorinostat, and Y-27632, have been reported previously as effective treatments for flavivirus-induced diseases. The computational approach using multiple omics data for drug repositioning described in this study can be used effectively to identify novel drug candidates.

A large-scale targeted proteomics assay resource based on an in vitro human proteome.

Targeted proteomics approaches are of value for deep and accurate quantification of protein abundance. Extending such methods to quantify large numbers of proteins requires the construction of predefined targeted assays. We developed a targeted proteomics platform-in vitro proteome-assisted multiple reaction monitoring (MRM) for protein absolute quantification (iMPAQT)-by using >18,000 human recombinant proteins, thus enabling protein absolute quantification on a genome-wide scale. Our platform comprises experimentally confirmed MRM assays of mass tag (mTRAQ)-labeled peptides to allow for rapid and straightforward measurement of the absolute abundance of predefined sets of proteins by mass spectrometry. We applied iMPAQT to delineate the quantitative metabolic landscape of normal and transformed human fibroblasts. Oncogenic transformation gave rise to relatively small but global changes in metabolic pathways resulting in aerobic glycolysis (Warburg effect) and increased rates of macromolecule synthesis. iMPAQT should facilitate quantitative biology studies based on protein abundance measurements.

A crosslinker-based identification of redox relay targets.

Thiol-based redox control is among the most important mechanisms for maintaining cellular redox homeostasis, with essential participation of cysteine thiols of oxidoreductases. To explore cellular redox regulatory networks, direct interactions among active cysteine thiols of oxidoreductases and their targets must be clarified. We applied a recently described thiol-ene crosslinking-based strategy, named divinyl sulfone (DVSF) method, enabling identification of new potential redox relay partners of the cytosolic oxidoreductases thioredoxin (TXN) and thioredoxin domain containing 17 (TXNDC17). Applying multiple methods, including classical substrate-trapping techniques, will increase understanding of redox regulatory mechanisms in cells.

Identification of novel natural inhibitor for NorM - a multidrug and toxic compound extrusion transporter - an insilico molecular modeling and simulation studies.

The emergence of bacterial multidrug resistance is an increasing problem in treatment of infectious diseases. An important cause for the multidrug resistance of bacteria is the expression of multidrug efflux transporters. The multidrug and toxic compound extrusion (MATE) transporters are most recently recognized as unique efflux system for extrusion of antimicrobials and therapeutic drugs due to energy stored in either Na+ or H+ electrochemical gradient. In the present study, high throughput virtual screening of natural compound collections against NorM - a MATE transporter from Neisseria gonorrhea (NorM-NG) has been carried out followed by flexible docking. The molecular simulation in membrane environment has been performed for understanding the stability and binding energetic of top lead compounds. Results identified a compound from the Indian medicinal plant "Terminalia chebula" which has good binding free energy compared to substrates (rhodamine 6 g, ethidium) and more favorable interactions with the central cavity forming active site residues. The compound has restricted movement in TM7, TM8, and TM1, thus blocking the disruption of Na+ - coordination along with equilibrium state bias towards occlude state of NorM transporter. Thus, this compound blocks the effluxing pathway of antimicrobial drugs and provides as a natural bioactive lead inhibitor against NorM transporter in drug-resistant gonorrhea.

Functional profiling of asymmetrically-organized human CCT/TRiC chaperonin.

Molecular organization of the eukaryote chaperonin known as CCT/TRiC complex was recently clarified. Eight distinct subunits are uniquely organized, providing a favorable folding cavity for specific client proteins such as tubulin and actin. Because of its heterogeneous subunit composition, CCT complex has polarized inner faces, which may underlie an essential part of its chaperonin function. In this study, we structurally characterized the closed and open states of CCT complex, using molecular dynamics analyses. Our results showed that the inter-subunit interaction energies were asymmetrically distributed and were remodeled during conformational changes of CCT complex. In addition, exploration of redox related characteristics indicated changes in inner surface properties, including electrostatic potential, pKa and exposure of inner cysteine thiol groups, between the closed and open states. Cysteine activation events were experimentally verified by interaction analyses, using tubulin as a model substrate. Our data highlighted the importance of dynamics-based structural profiling of asymmetrically oriented chaperonin function.

Redox Sensitivities of Global Cellular Cysteine Residues under Reductive and Oxidative Stress.

The protein cysteine residue is one of the amino acids most susceptible to oxidative modifications, frequently caused by oxidative stress. Several applications have enabled cysteine-targeted proteomics analysis with simultaneous detection and quantitation. In this study, we employed a quantitative approach using a set of iodoacetyl-based cysteine reactive isobaric tags (iodoTMT) and evaluated the transient cellular oxidation ratio of free and reversibly modified cysteine thiols under DTT and hydrogen peroxide (H2O2) treatments. DTT treatment (1 mM for 5 min) reduced most cysteine thiols, irrespective of their cellular localizations. It also caused some unique oxidative shifts, including for peroxiredoxin 2 (PRDX2), uroporphyrinogen decarboxylase (UROD), and thioredoxin (TXN), proteins reportedly affected by cellular reactive oxygen species production. Modest H2O2 treatment (50 µM for 5 min) did not cause global oxidations but instead had apparently reductive effects. Moreover, with H2O2, significant oxidative shifts were observed only in redox active proteins, like PRDX2, peroxiredoxin 1 (PRDX1), TXN, and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Overall, our quantitative data illustrated both H2O2- and reduction-mediated cellular responses, whereby while redox homeostasis is maintained, highly reactive thiols can potentiate the specific, rapid cellular signaling to counteract acute redox stress.

Theoretical investigation on the glycan-binding specificity of Agrocybe cylindracea galectin using molecular modeling and molecular dynamics simulation studies.

Galectins are ß-galactoside binding proteins which have the ability to serve as potent antitumor, cancer biomarker, and induce tumor cell apoptosis. Agrocybe cylindracea galectin (ACG) is a fungal galectin which specifically recognizes α(2,3)-linked sialyllactose at the cell surface that plays extensive roles in the biological recognition processes. To investigate the change in glycan-binding specificity upon mutations, single point and double point site-directed in silico mutations are performed at the binding pocket of ACG. Molecular dynamics (MD) simulation studies are carried out for the wild-type (ACG) and single point (ACG1) and double point (ACG2) mutated ACGs to investigate the dynamics of substituted mutants and their interactions with the receptor sialyllactose. Plausible binding modes are proposed for galectin-sialylglycan complexes based on the analysis of hydrogen bonding interactions, total pair-wise interaction energy between the interacting binding site residues and sialyllactose and binding free energy of the complexes using molecular mechanics-Poisson-Boltzmann surface area. Our result shows that high contribution to the binding in different modes is due to the direct and water-mediated hydrogen bonds. The binding specificity of double point mutant Y59R/N140Q of ACG2 is found to be high, and it has 26 direct and water-mediated hydrogen bonds with a relatively low-binding free energy of -47.52 ± 5.2 kcal/mol. We also observe that the substituted mutant Arg59 is crucial for glycan-binding and for the preference of α(2,3)-linked sialyllactose at the binding pocket of ACG2 galectin. When compared with the wild-type and single point mutant, the double point mutant exhibits enhanced affinity towards α(2,3)-linked sialyllactose, which can be effectively used as a model for biological cell marker in cancer therapeutics.

Mutational studies to understand the structure-function relationship in multidrug efflux transporters: applications for distinguishing mutants with high specificity.

Multidrug transporters play key roles for drug resistance, mediating the transport of organic compounds and substrate recognition. The specificity of substrates and functions of multidrug transporters are affected with amino acid substitutions. Hence, it is important to understand the effect of mutations in multidrug resistance proteins on transport function and substrate specificity. In this work, we have analyzed the relationship between amino acid properties and activity of multidrug resistance proteins upon mutations and substrates. We found that the properties for drug activity and kinetic factors depend on amino acid substitutions and specific to substrates. The inclusion of information from neighboring residues from the mutants enhanced our understanding to the activity of multidrug resistant proteins. Further, we have combined amino acid properties using multiple regression technique, which showed a correlation of up to 0.99 between amino acid properties and activity. In addition, we have utilized Naïve Bayes classifier for distinguishing between decrease and increase in IC50 upon mutations using wild type, mutant and neighboring residues, which showed a 10-fold cross-validation accuracy of 86%. Further, we have developed multiple regression models for predicting IC50 upon mutations with a maximum correlation of 0.92. The present method could be used for identifying the mutants in multidrug resistant proteins with enhanced specificity.

Insights into the binding specificity of wild type and mutated wheat germ agglutinin towards Neu5Acα(2-3)Gal: a study by in silico mutations and molecular dynamics simulations.

Wheat germ agglutinin (WGA) is a plant lectin, which specifically recognizes the sugars NeuNAc and GlcNAc. Mutated WGA with enhanced binding specificity can be used as biomarkers for cancer. In silico mutations are performed at the active site of WGA to enhance the binding specificity towards sialylglycans, and molecular dynamics simulations of 20 ns are carried out for wild type and mutated WGAs (WGA1, WGA2, and WGA3) in complex with sialylgalactose to examine the change in binding specificity. MD simulations reveal the change in binding specificity of wild type and mutated WGAs towards sialylgalactose and bound conformational flexibility of sialylgalactose. The mutated polar amino acid residues Asn114 (S114N), Lys118 (G118K), and Arg118 (G118R) make direct and water mediated hydrogen bonds and hydrophobic interactions with sialylgalactose. An analysis of possible hydrogen bonds, hydrophobic interactions, total pair wise interaction energy between active site residues and sialylgalactose and MM-PBSA free energy calculation reveals the plausible binding modes and the role of water in stabilizing different binding modes. An interesting observation is that the binding specificity of mutated WGAs (cyborg lectin) towards sialylgalactose is found to be higher in double point mutation (WGA3). One of the substituted residues Arg118 plays a crucial role in sugar binding. Based on the interactions and energy calculations, it is concluded that the order of binding specificity of WGAs towards sialylgalactose is WGA3 > WGA1 > WGA2 > WGA. On comparing with the wild type, double point mutated WGA (WGA3) exhibits increased specificity towards sialylgalactose, and thus, it can be effectively used in targeted drug delivery and as biological cell marker in cancer therapeutics.

Tertiary structure prediction of RNA-RNA complexes using a secondary structure and fragment-based method.

A method has been developed for predicting the tertiary structures of RNA-RNA complex structures using secondary structure information and a fragment assembly algorithm. The linker base pair and secondary structure potential derived from the secondary structure information are particularly useful for prediction. Application of this method to several kinds of RNA-RNA complex structures, including kissing loops, hammerhead ribozymes, and other functional RNAs, produced promising results. Use of the secondary structure potential effectively restrained the conformational search space, leading to successful prediction of kissing loop structures, which mainly consist of common structural elements. The failure to predict more difficult targets had various causes but should be overcome through such measures as tuning the balance of the energy contributions from the Watson-Crick and non- Watson-Crick base pairs, by obtaining knowledge about a wider variety of RNA structures.