Publications by authors named "Olli Yli-Harja"

135 Publications

Molecular interaction study of novel indoline derivatives with EGFR-kinase domain using multiple computational analysis.

J Biomol Struct Dyn 2021 Mar 22:1-10. Epub 2021 Mar 22.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, Tays Cancer Center, Tampere University Hospital, Tampere, Finland.

Epidermal growth factor receptors are constitutively overexpressed in breast cancer cells, which in turn stimulate many downstream signaling pathways that are involved in many carcinogenic processes. This makes EGFR a striking target for cancer therapy. This study focuses on the EGFR kinase domain inactivation by novel synthesized indoline derivatives. The compounds used are N-(2-hydroxy-5-nitrophenyl (4'-methyl phenyl) methyl) indoline (HNPMI), alkylaminophenols - 2-((3,4-Dihydroquinolin-1(2H)-yl) (p-tolyl) methyl) phenol (THTMP) and 2-((1, 2, 3, 4-Tetrahydroquinolin-1-yl) (4 methoxyphenyl) methyl) phenol (THMPP). To get a clear insight into the molecular interaction of EGFR and the three compounds, we have used ADME/Tox prediction, Flexible docking analysis followed by MM/GB-SA, QM/MM analysis, E-pharmacophore mapping of the ligands and Molecular dynamic simulation of protein-ligand complexes. All three compounds showed good ADME/Tox properties obeying the rules of drug-likeliness and showed high human oral absorption. Molecular docking was performed with the compounds and EGFR using Glide Flexible docking mode. This showed that the HNPMI was best among the three compounds and had interactions with key residue Lys 721. The protein-ligand complexes were stable when simulated for 100 ns using Desmond software. The interactions were further substantiated using QM/MM analysis and MM-GB/SA analysis in which HNPMI was scored as the best molecule. All the analyses were carried out with a reference molecule-Gefitinib which is a known standard inhibitor of EGFR. Thus, the study elucidates the potential role of the indoline derivatives as an anti-cancer agent against breast cancer by effectively inhibiting EGFR.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1900917DOI Listing
March 2021

Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status.

Front Artif Intell 2020 23;3:524339. Epub 2020 Dec 23.

Department of Mechatronics and Biomedical Computer Science, UMIT, Hall in Tyrol, IL, Austria.

The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the "intelligence" nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.
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http://dx.doi.org/10.3389/frai.2020.524339DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944138PMC
December 2020

Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning.

Sci Rep 2021 Jan 8;11(1):156. Epub 2021 Jan 8.

Predictive Society and Data Analytics Lab, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.
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http://dx.doi.org/10.1038/s41598-020-79375-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794581PMC
January 2021

Identifying the miRNA Signature Association with Aging-Related Senescence in Glioblastoma.

Int J Mol Sci 2021 Jan 6;22(2). Epub 2021 Jan 6.

BioMediTech Institute, Faculty of Medicine and Health Technology, Tampere University, ArvoYlpönkatu 34, 33520 Tampere, Finland.

Glioblastoma (GBM) is the most common malignant brain tumor and its malignant phenotypic characteristics are classified as grade IV tumors. Molecular interactions, such as protein-protein, protein-ncRNA, and protein-peptide interactions are crucial to transfer the signaling communications in cellular signaling pathways. Evidences suggest that signaling pathways of stem cells are also activated, which helps the propagation of GBM. Hence, it is important to identify a common signaling pathway that could be visible from multiple GBM gene expression data. microRNA signaling is considered important in GBM signaling, which needs further validation. We performed a high-throughput analysis using micro array expression profiles from 574 samples to explore the role of non-coding RNAs in the disease progression and unique signaling communication in GBM. A series of computational methods involving miRNA expression, gene ontology (GO) based gene enrichment, pathway mapping, and annotation from metabolic pathways databases, and network analysis were used for the analysis. Our study revealed the physiological roles of many known and novel miRNAs in cancer signaling, especially concerning signaling in cancer progression and proliferation. Overall, the results revealed a strong connection with stress induced senescence, significant miRNA targets for cell cycle arrest, and many common signaling pathways to GBM in the network.
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http://dx.doi.org/10.3390/ijms22020517DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7825621PMC
January 2021

Transcriptomic analysis of glioblastoma multiforme providing new insights into GPR17 signaling communication.

J Biomol Struct Dyn 2020 Nov 3:1-14. Epub 2020 Nov 3.

BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.

Glioblastoma Multiforme (GBM) is one of the most aggressive malignant tumors in the central nervous system, which arises due to the failure or crosstalk in the signaling networks. GPR17, an orphan G protein-coupled receptor is anticipated to be associated with the biology of the GBM disease progression. In the present study, we have identified the differential expressions of around 170 genes along with GPR17 through the RNA-Seq analysis of 169 GBM samples. Coordinated expression patterns of all other gene products with this receptor were analysed using gene ontology and protein-protein interaction data. Several crucial signaling components and genes that play a significant role in tumor progression have been identified among which GPR17 was found to be significantly interacting with about 30 different pathways. High-throughput molecular docking of GPR17 by homology-based model against differentially expressed proteins, showed effective recognition and binding of PX, SH3, and Ig-like domains besides Gi protein. Pathways of PI3, Src, Ptdn, Ras, cytoplasmic tyrosine kinases, phospholipases, nexins and other proteins possessing these structural domains are identified as critical signaling components of the complex GBM signaling network. Our findings also provide a mechanistic insight of GPR17-T0510-3657 interaction, which potentially regulates the interaction of PX domain and helical mPTS recognition domain-containing proteins. Overall, our results demonstrate that GPR17 mediated signaling networks could be used as a therapeutic target for GBM. Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2020.1841029DOI Listing
November 2020

Design and synthesis of novel quinic acid derivatives: cytotoxicity and anticancer effect on glioblastoma.

Future Med Chem 2020 Nov 30;12(21):1891-1910. Epub 2020 Oct 30.

Molecular Signaling Lab, Faculty of Medicine & Health Technology, Tampere University, Finland.

Quinic acid (QA) is a cyclic polyol exhibiting anticancer properties on several cancers. However, potential role of QA derivatives against glioblastoma is not well established. Sixteen novel QA derivatives and QA- encapsulated poly (lactic-co-glycolic acid) nanoparticles (QA--NPs) were screened for their anti-glioblastoma effect using standard cell and molecular biology methods. Presence of a tertiary hydroxy and silylether groups in the lead compound were identified for the antitumor activity. QA- have 90% inhibition with the IC of 10.66 μM and 28.22 μM for LN229 and SNB19, respectively. The induction of apoptosis is faster with the increased fold change of caspase 3/7 and reactive oxygen species. QA- and QA--NPs shows similar cytotoxicity effect, providing the opportunity to use QA- as a potential chemotherapeutic agent.
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http://dx.doi.org/10.4155/fmc-2020-0194DOI Listing
November 2020

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance.

Sci Rep 2020 10 7;10(1):16672. Epub 2020 Oct 7.

Predictive Society and Data Analytics Lab, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their hierarchical and connected organization as directed acyclic graphs (DAGs) and the lack of tools allowing to exploit this structural information explicitly. For this reason, we developed the R package GOxploreR. The main features of GOxploreR are (I) easy and direct access to structural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs including visualization capabilities and (IV) prioritizing of GO-terms. The underlying idea of GOxploreR is to exploit a graph-theoretical perspective of GO as manifested by its DAG-structure and the containing hierarchy levels for cumulating semantic information. That means all these features enhance the utilization of structural information of GO and complement existing analysis tools. Overall, GOxploreR provides exploratory as well as confirmatory tools for complementing any kind of analysis resulting in a list of GO-terms, e.g., from differentially expressed genes or gene sets, GWAS or biomarkers. Our R package GOxploreR is freely available from CRAN.
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http://dx.doi.org/10.1038/s41598-020-73326-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542435PMC
October 2020

Antiproliferative and apoptotic effects of indole derivative, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline in breast cancer cells.

Eur J Pharmacol 2020 Aug 21;881:173195. Epub 2020 May 21.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, Tays Cancer Center, Tampere University Hospital, P.O. Box 553, 33101, Tampere, Finland; Institute of Biosciences and Medical Technology, Tampere, Finland. Electronic address:

Indoline derivatives functions as an inhibitors of epidermal growth factor receptor (EGFR) with the anticancer potential against various cancers. We aim to investigate anti-breast cancer effects and mechanism of action of novel indoline derivatives. Molecular docking of seven indoline derivates with EGFR revealed, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline (HNPMI) as the top lead compound. RT-PCR analysis showed the downregulation of PI3K/S6K1 genes in breast cancer cells through the activation of EGFR with HNPMI. This compound found to have higher cytotoxicity than Cyclophosphamide, with the IC of 64.10 μM in MCF-7 and 119.99 μM in SkBr3 cells. HNPMI significantly reduced the cell proliferation of MCF-7 and SkBr3 cells, without affecting non-cancerous cells, H9C2. Induction of apoptosis was analyzed by Caspase-3 and -9, DNA fragmentation, AO/EtBr staining and flow cytometry assays. A fold change of 0.218- and 0.098- for caspase-3 and 0.478- and 0.269- for caspase-9 in MCF7 and SkBr3 cells was observed, respectively. Caspase mediated apoptosis caused DNA fragmentation in breast cancer cells upon HNPMI treatment. The structural elucidation of HNPMI by QSAR model and ADME-Tox suggests, a bi-molecular interaction of HNPMI-EGFR which is related to antiproliferative and apoptotic activity. The data concludes that, HNPMI-induced the apoptosis via EGFR signaling pathway in breast cancer cells. Thus, HNPMI might serve as a scaffold for developing a potential anti-breast cancer therapeutic agent.
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http://dx.doi.org/10.1016/j.ejphar.2020.173195DOI Listing
August 2020

Anticancer activity of THMPP: Downregulation of PI3K/ S6K1 in breast cancer cell line.

Saudi Pharm J 2020 Apr 19;28(4):495-503. Epub 2020 Mar 19.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, Tays Cancer Center, Tampere University Hospital, P.O. Box 553, 33101 Tampere, Finland.

Breast cancer is the most common cancer that majorly affects female. The present study is focused on exploring the potential anticancer activity of 2-((1, 2, 3, 4-Tetrahydroquinolin-1-yl) (4 methoxyphenyl) methyl) phenol (THMPP), against human breast cancer. The mechanism of action, activation of specific signaling pathways, structural activity relationship and drug-likeness properties of THMPP remains elusive. Cell proliferation and viability assay, caspase enzyme activity, DNA fragmentation and FITC/Annexin V, AO/EtBr staining, RT-PCR, QSAR and ADME analysis were executed to understand the mode of action of the drug. The effect of THMPP on multiple breast cancer cell lines (MCF-7 and SkBr3), and non-tumorigenic cell line (H9C2) was assessed by MTT assay. THMPP at IC concentration of 83.23 μM and 113.94 μM, induced cell death in MCF-7 and SkBr3 cells, respectively. Increased level of caspase-3 and -9, fragmentation of DNA, translocation of phosphatidylserine membrane and morphological changes in the cells confirmed the effect of THMPP in inducing the apoptosis. Gene expression analysis has shown that THMPP was able to downregulate the expression of PI3K/S6K1 genes, possibly via EGFR signaling pathway in both the cell lines, MCF-7 and SkBr3. Further, molecular docking also confirms the potential binding of THMPP with EGFR. QSAR and ADME analysis proved THMPP as an effective anti-breast cancer drug, exhibiting important pharmacological properties. Overall, the results suggest that THMPP induced cell death might be regulated by EGFR signaling pathway which augments THMPP being developed as a potential candidate for treating breast cancer.
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http://dx.doi.org/10.1016/j.jsps.2020.02.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132829PMC
April 2020

Glioblastoma Multiforme Stem Cell Cycle Arrest by Alkylaminophenol Through the Modulation of EGFR and CSC Signaling Pathways.

Cells 2020 03 10;9(3). Epub 2020 Mar 10.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University, P.O. Box 553, 33101 Tampere, Finland.

Cancer stem cells (CSCs), a small subpopulation of cells existing in the tumor microenvironment promoting cell proliferation and growth. Targeting the stemness of the CSC population would offer a vital therapeutic opportunity. 3,4-Dihydroquinolin-1(2)-yl)(-tolyl)methyl)phenol (THTMP), a small synthetic phenol compound, is proposed to play a significant role in controlling the CSC proliferation and survival. We assessed the potential therapeutic effects of THTMP on glioblastoma multiforme (GBM) and its underlying mechanism in various signaling pathways. To fully comprehend the effect of THTMP on the CSCs, CD133 GBM stem cell (GSC) and CD133 GBM Non-stem cancer cells (NSCC) population from LN229 and SNB19 cell lines was used. Cell cycle arrest, apoptosis assay and transcriptome analysis were performed for individual cell population. THTMP strongly inhibited NSCC and in a subtle way for GSC in a time-dependent manner and inhibit the resistance variants better than that of temozolomide (TMZ). THTMP arrest the CSC cell population at both G1/S and G2/M phase and induce ROS-mediated apoptosis. Gene expression profiling characterize THTMP as an inhibitor of the p53 signaling pathway causing DNA damage and cell cycle arrest in CSC population. We show that the THTMP majorly affects the EGFR and CSC signaling pathways. Specifically, modulation of key genes involved in Wnt, Notch and Hedgehog, revealed the significant role of THTMP in disrupting the CSCs' stemness and functions. Moreover, THTMP inhibited cell growth, proliferation and metastasis of multiple mesenchymal patient-tissue derived GBM-cell lines. THTMP arrests GBM stem cell cycle through the modulation of EGFR and CSC signaling pathways.
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http://dx.doi.org/10.3390/cells9030681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140667PMC
March 2020

Alkylamino Phenol Derivative Induces Apoptosis by Inhibiting EGFR Signaling Pathway in Breast Cancer Cells.

Anticancer Agents Med Chem 2020 ;20(7):809-819

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O. Box 553, 33101 Tampere, Finland

Background And Objective: The present study was carried out to evaluate the anticancer property of an alkylamino phenol derivative -2-((3,4-Dihydroquinolin-1(2H)-yl)(p-tolyl)methyl)phenol) (THTMP) against human breast cancer cells. The cytotoxicity of the THTMP was assessed to know its specificity towards breast cancer cells without affecting the normal cells.

Methods: The THTMP was synthesized and the cytotoxicity was assessed by MTT assay, Caspases enzyme activity, DNA fragmentation and FITC/Annexin V, AO/EtBr staining, RT-PCR and QSAR. In addition, ADME analysis was executed to understand the mode of action of THTMP.

Results: THTMP showed potential cytotoxic activity against the growth of MCF7 and SK-BR3 cells with the IC50 values of 87.92μM and 172.51μM, respectively. Interestingly, THTMP found to activate caspase 3 and caspase 9 enzymes in cancer cells, which are the key enzymes implicated in apoptosis. THTMP induced apoptosis in which 33% of the cells entered the late apoptotic stage after 24h of treatment. The results also revealed that the apoptotic response could be influenced by the association of THTMP with the Epidermal Growth Factor Receptor (EGFR) mediated inhibition of the Phosphatidylinositol 3-Kinase (PI3K)/S6K1 signaling pathway. In addition, docking was performed to study the binding mode of the THTMP, which shows better interaction with EGFR. The structural elucidation of THTMP by Quantitative Structure-Activity Relationship model (QSAR) and ADMET screening suggested, THTMP as an effective anticancer compound.

Conclusion: This work strengthens the potential of a promising drug-like compound, THTMP, for the discovery of anticancer drug against breast cancer.
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http://dx.doi.org/10.2174/1871520620666200213101407DOI Listing
January 2020

Combining deep learning with token selection for patient phenotyping from electronic health records.

Sci Rep 2020 01 29;10(1):1432. Epub 2020 Jan 29.

Predictive Society and Data Analytics Lab, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

Artificial intelligence provides the opportunity to reveal important information buried in large amounts of complex data. Electronic health records (eHRs) are a source of such big data that provide a multitude of health related clinical information about patients. However, text data from eHRs, e.g., discharge summary notes, are challenging in their analysis because these notes are free-form texts and the writing formats and styles vary considerably between different records. For this reason, in this paper we study deep learning neural networks in combination with natural language processing to analyze text data from clinical discharge summaries. We provide a detail analysis of patient phenotyping, i.e., the automatic prediction of ten patient disorders, by investigating the influence of network architectures, sample sizes and information content of tokens. Importantly, for patients suffering from Chronic Pain, the disorder that is the most difficult one to classify, we find the largest performance gain for a combined word- and sentence-level input convolutional neural network (ws-CNN). As a general result, we find that the combination of data quality and data quantity of the text data is playing a crucial role for using more complex network architectures that improve significantly beyond a word-level input CNN model. From our investigations of learning curves and token selection mechanisms, we conclude that for such a transition one requires larger sample sizes because the amount of information per sample is quite small and only carried by few tokens and token categories. Interestingly, we found that the token frequency in the eHRs follow a Zipf law and we utilized this behavior to investigate the information content of tokens by defining a token selection mechanism. The latter addresses also issues of explainable AI.
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http://dx.doi.org/10.1038/s41598-020-58178-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989657PMC
January 2020

Ensuring Quality Standards and Reproducible Research for Data Analysis Services in Oncology: A Cooperative Service Model.

Front Cell Dev Biol 2019 17;7:349. Epub 2019 Dec 17.

Institute of Biosciences and Medical Technology, Tampere, Finland.

Modern molecular high-throughput devices, e.g., next-generation sequencing, have transformed medical research. Resulting data sets are usually high-dimensional on a genomic-scale providing multi-factorial information from intertwined molecular and cellular activities of genes and their products. This genomics-revolution installed precision medicine offering breathtaking opportunities for patient's diagnosis and treatment. However, due to the speed of these developments the quality standards of the involved data analyses are lacking behind, as exemplified by the infamous Duke Saga. In this paper, we argue in favor of a two-stage cooperative serve model that couples data generation and data analysis in the most beneficial way from the perspective of a patient to ensure data analysis quality standards including reproducible research.
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http://dx.doi.org/10.3389/fcell.2019.00349DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929679PMC
December 2019

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies.

BMC Mol Cell Biol 2019 Dec 19;20(1):59. Epub 2019 Dec 19.

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 2, avenue de l'Université, Esch-sur-Alzette, L-4365, Luxembourg.

Background: Multicellular entities like mammalian tissues or microbial biofilms typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding how this cell-cell and metabolic coupling lead to functionally optimized structures is still limited.

Results: Here, we present a data-driven spatial framework to computationally investigate the development of yeast colonies as such a multicellular structure in dependence on metabolic capacity. For this purpose, we first developed and parameterized a dynamic cell state and growth model for yeast based on on experimental data from homogeneous liquid media conditions. The inferred model is subsequently used in a spatially coarse-grained model for colony development to investigate the effect of metabolic coupling by calibrating spatial parameters from experimental time-course data of colony growth using state-of-the-art statistical techniques for model uncertainty and parameter estimations. The model is finally validated by independent experimental data of an alternative yeast strain with distinct metabolic characteristics and illustrates the impact of metabolic coupling for structure formation.

Conclusions: We introduce a novel model for yeast colony formation, present a statistical methodology for model calibration in a data-driven manner, and demonstrate how the established model can be used to generate predictions across scales by validation against independent measurements of genetically distinct yeast strains.
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http://dx.doi.org/10.1186/s12860-019-0234-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923950PMC
December 2019

Battling Glioblastoma: A Novel Tyrosine Kinase Inhibitor with Multi-Dimensional Anti-Tumor Effect (Running Title: Cancer Cells Death Signalling Activation).

Cells 2019 12 12;8(12). Epub 2019 Dec 12.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University, BioMeditech and Tays Cancer Center, Tampere University Hospital, P.O. Box 553, 33101 Tampere, Finland.

Glioblastoma (GB), a grade IV glioma, with high heterogeneity and chemoresistance, obligates a multidimensional antagonist to debilitate its competence. Considering the previous reports on thioesters as antitumor compounds, this paper investigates on use of this densely functionalized sulphur rich molecule as a potent anti-GB agent. Bio-evaluation of 12 novel compounds, containing α-thioether ketone and orthothioester functionalities, identified that five analogs exhibited better cytotoxic profile compared to standard drug cisplatin. Detailed toxicity studies of top compound were evaluated in two cell lines, using cell viability test, apoptotic activity, oxidative stress and caspase activation and RNA-sequencing analysis, to obtain a comprehensive molecular profile of drug activity. The most effective molecule presented half maximal inhibitory concentration (IC) values of 27 μM and 23 μM against U87 and LN229 GB cells, respectively. Same compound effectively weakened various angiogenic pathways, mainly MAPK and JAK-STAT pathways, downregulating VEGF. Transcriptome analysis identified significant promotion of apoptotic genes, and genes involved in cell cycle arrest, with concurrent inhibition of various tyrosine kinase cascades and stress response genes. Docking and immunoblotting studies suggest EGFR as a strong target of the orthothioester identified. Therefore, orthothioesters can potentially serve as a multi-dimensional chemotherapeutic possessing strong cytotoxic, anti-angiogenic and chemo-sensitization activity, challenging glioblastoma pathogenesis.
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http://dx.doi.org/10.3390/cells8121624DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6953096PMC
December 2019

Synthesis and preclinical validation of novel P2Y1 receptor ligands as a potent anti-prostate cancer agent.

Sci Rep 2019 12 12;9(1):18938. Epub 2019 Dec 12.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O.Box 553, 33101, Tampere, Finland.

Purinergic receptor is a potential drug target for neuropathic pain, Alzheimer disease, and prostate cancer. Focusing on the structure-based ligand discovery, docking analysis on the crystal structure of P2Y receptor (P2YR) with 923 derivatives of 1-indolinoalkyl 2-phenolic compound is performed to understand the molecular insights of the receptor. The structural model identified the top novel ligands, 426 (compound 1) and 636 (compound 2) having highest binding affinity with the docking score of -7.38 and -6.92. We have reported the interaction efficacy and the dynamics of P2YR protein with the ligands. The best hits synthesized were experimentally optimized as a potent P2Y agonists. These ligands exhibits anti-proliferative effect against the PC-3 and DU-145 cells (IC = 15 µM - 33 µM) with significant increase in the calcium level in dose- and time-dependent manner. Moreover, the activation of P2YR induced the apoptosis via Capase3/7 and ROS signaling pathway. Thus it is evidenced that the newly synthesized ligands, as a P2YR agonists could potentially act as a therapeutic drug for treating prostate cancer.
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http://dx.doi.org/10.1038/s41598-019-55194-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6908675PMC
December 2019

Utilizing Social Media Data for Psychoanalysis to Study Human Personality.

Front Psychol 2019 15;10:2596. Epub 2019 Nov 15.

Faculty for Management, Institute for Intelligent Production, University of Applied Sciences Upper Austria, Steyr, Austria.

Social media data, for instance from Twitter or Facebook, provide a new type of data that consist of a mixture of text, image and video information. From a scientific point of view, the capabilities of this type of data from such microblogs are not well explored and to date it is largely unknown what principal knowledge can be extracted thereof. In this paper, we present a discussion of the capabilities of data from microblogs for performing a psychoanalysis. This could allow an analysis of the human personality of individual users. Such prospects raises serious concerns regarding the privacy of users of social media platforms.
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http://dx.doi.org/10.3389/fpsyg.2019.02596DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6873989PMC
November 2019

Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks.

Sci Rep 2019 05 24;9(1):7849. Epub 2019 May 24.

Predictive Society and Data Analytics Lab, Tampere University, Tampere, Korkeakoulunkatu 10, 33720, Tampere, Finland.

Modern research in the biomedical sciences is data-driven utilizing high-throughput technologies to generate big genomic data. The Library of Integrated Network-based Cellular Signatures (LINCS) is an example for a large-scale genomic data repository providing hundred thousands of high-dimensional gene expression measurements for thousands of drugs and dozens of cell lines. However, the remaining challenge is how to use these data effectively for pharmacogenomics. In this paper, we use LINCS data to construct drug association networks (DANs) representing the relationships between drugs. By using the Anatomical Therapeutic Chemical (ATC) classification of drugs we demonstrate that the DANs represent a systems pharmacogenomic landscape of drugs summarizing the entire LINCS repository on a genomic scale meaningfully. Here we identify the modules of the DANs as therapeutic attractors of the ATC drug classes.
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http://dx.doi.org/10.1038/s41598-019-44291-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534546PMC
May 2019

Alkylaminophenol Induces G1/S Phase Cell Cycle Arrest in Glioblastoma Cells Through p53 and Cyclin-Dependent Kinase Signaling Pathway.

Front Pharmacol 2019 2;10:330. Epub 2019 Apr 2.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, Tampere, Finland.

Glioblastoma (GBM) is the most common type of malignant brain tumor in adults. We show here that small molecule 2-[(3,4-dihydroquinolin-1(2H)-yl)(p-tolyl)methyl]phenol (THTMP), a potential anticancer agent, increases the human glioblastoma cell death. Its mechanism of action and the interaction of selective signaling pathways remain elusive. Three structurally related phenolic compounds were tested in multiple glioma cell lines in which the potential activity of the compound, THTMP, was further validated and characterized. Upon prolonged exposer to THTMP, all glioma cell lines undergo p53 and cyclin-dependent kinase mediated cell death with the IC concentration of 26.5 and 75.4 μM in LN229 and Snb19, respectively. We found that THTMP strongly inhibited cell growth in a dose and in time dependent manner. THTMP treatment led to G1/S cell cycle arrest and apoptosis induction of glioma cell lines. Furthermore, we identified 3,714 genes with significant changes at the transcriptional level in response to THTMP. Further, a transcriptional analysis (RNA-seq) revealed that THTMP targeted the p53 signaling pathway specific genes causing DNA damage and cell cycle arrest at G1/S phase explained by the decrease of cyclin-dependent kinase 1, cyclin A2, cyclin E1 and E2 in glioma cells. Consistently, THTMP induced the apoptosis by regulating the expression of Bcl-2 family genes and reactive oxygen species while it also changed the expression of several anti-apoptotic genes. These observations suggest that THTMP exerts proliferation activity inhibition and pro-apoptosis effects in glioma through affecting cell cycle arrest and intrinsic apoptosis signaling. Importantly, THTMP has more potential at inhibiting GBM cell proliferation compared to TMZ, the current chemotherapy treatment administered to GBM patients; thus, we propose that THTMP may be an alternative therapeutic option for glioblastoma.
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http://dx.doi.org/10.3389/fphar.2019.00330DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454069PMC
April 2019

In vitro anti-glioblastoma activity of L-valine derived boroxazolidones.

Eur J Pharmacol 2019 Jul 11;854:194-200. Epub 2019 Apr 11.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O. Box 553, 33101 Tampere, Finland. Electronic address:

In the present study, a series of L-valine derived boroxazolidones, previously synthesized and reported to have residual activity in a human epithelial cell line, have been evaluated in vitro for their anti-glioblastoma activity. A boroxazolidone derivative containing 2,4-difluorophenyl moieties (6) was found to have higher cytotoxicity than the standard drug, Temozolomide (TMZ). Compound 6 was found to exhibit dose-dependent growth inhibitory effects with an IC of 49 μM and 53 μM for LN229 and SNB19 cells, respectively. Additionally, 6 was assessed for its role in apoptosis, caspase 3/7 activation and oxidative stress in SNB19 and LN229 cells. SNB19 cells treated with 6 showed 45.3% apoptosis in the population, while TMZ had 24.7%. In LN229 cells, the percentage of apoptotic cells treated with compound 6 and TMZ were the same. Both 6 and TMZ induced apoptosis through the activation of caspase 3/7 in SNB19 and LN229 cells. Interestingly, 6 exhibited a higher effectivity in promoting reactive oxygen species production in LN229, while it was 6-fold less in SNB19. Boroxazolidone-treated GBM cell lines increased reactive oxygen species production, suggesting that such species may be interlinked with the observed programmed cell death. Additionally, the treatment of both GBM cell lines with 6 led to G2/M phase arrest. The magnitude of anti-GBM effect of 6 is significantly higher than the known chemotherapeutic agent TMZ. This work further demonstrates the anticancer properties of L-valine derived boroxazolidones, adding another potential derivative to the collection of promising chemotherapeutic agents for GBM treatment.
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http://dx.doi.org/10.1016/j.ejphar.2019.04.020DOI Listing
July 2019

Global Genetics Research in Prostate Cancer: A Text Mining and Computational Network Theory Approach.

Front Genet 2019 14;10:70. Epub 2019 Feb 14.

Predictive Society and Data Analysis Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.

Prostate cancer is the most common cancer type in men in Finland and second worldwide. In this paper, we analyze almost 150, 000 published papers about prostate cancer, authored by ten thousands of scientists worldwide, with an integrated text mining and computational network theory approach. We demonstrate how to integrate text mining with network analysis investigating research contributions of countries and collaborations within and between countries. Furthermore, we study the time evolution of individually and collectively studied genes. Finally, we investigate a collaboration network of Finland and compare studied genes with globally studied genes in prostate cancer genetics. Overall, our results provide a global overview of prostate cancer research in genetics. In addition, we present a specific discussion for Finland. Our results shed light on trends within the last 30 years and are useful for translational researchers within the full range from genetics to public health management and health policy.
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http://dx.doi.org/10.3389/fgene.2019.00070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383410PMC
February 2019

2-(2-(2,4-dioxopentan-3-ylidene)hydrazineyl)benzonitrile as novel inhibitor of receptor tyrosine kinase and PI3K/AKT/mTOR signaling pathway in glioblastoma.

Eur J Med Chem 2019 Mar 22;166:291-303. Epub 2019 Jan 22.

Molecular Signaling Lab, Faculty of Medicine and Health Technology, Tampere University and BioMediTech, P.O. Box 553, 33101, Tampere, Finland. Electronic address:

Nerve growth factor receptor (NGFR), a member of kinase protein, is emerging as an important target for Glioblastoma (GBM) treatment. Overexpression of NGFR is observed in many metastatic cancers including GBM, promoting tumor migration and invasion. Hydrazones have been reported to effectively interact with receptor tyrosine kinases (RTKs). We report herein the synthesis of 23 arylhydrazones of active methylene compounds (AHAMCs) compounds and their anti-proliferative activity against GBM cell lines, LN229 and U87. Compound R234, 2-(2-(2,4-dioxopentan-3-ylidene)hydrazineyl)benzonitrile, was identified as the most active anti-neoplastic compound, with the IC value ranging 87 μM - 107 μM. Molecular docking simulations of the synthesized compounds into the active site of tyrosine receptor kinase A (TrkA), demonstrated a strong binding affinity with R234 and concurs well with the obtained biological results. R234 was found to be a negative regulator of PI3K/Akt/mTOR pathway and an enhancer of p53 expression. In addition, R234 treated GBM cells exhibited the downregulation of cyclins, cyclin-dependent kinases and other key molecules involved in cell cycle such as CCNE, E2F, CCND, CDK6, indicating that R234 induces cell cycle arrest at G1/S. R234 also exerted its apoptotic effects independent of caspase3/7 activity, in both cell lines. In U87 cells, R234 induced oxidative effects whereas LN229 cells annulled oxidative stress. The study thus concludes that R234, being a negative modulator of RTKs and cell cycle inhibitor, may represent a novel class of anti-GBM drugs.
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http://dx.doi.org/10.1016/j.ejmech.2019.01.021DOI Listing
March 2019

Data Analytics Applications for Streaming Data From Social Media: What to Predict?

Front Big Data 2018 11;1. Epub 2018 Sep 11.

Department for Biomedical Computer Science and Mechatronics, UMIT - The Health and Lifesciences University, Hall in Tyrol, Austria.

Social media in general provide great opportunities for mining massive amounts of text, image, and video-based data. However, what questions can be addressed from analyzing such data? In this review, we are focusing on microblogging services and discuss applications of streaming data from the scientific literature. We will focus on text-based approaches because they represent by far the largest cohort of studies and we present a taxonomy of studied problems.
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http://dx.doi.org/10.3389/fdata.2018.00002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931880PMC
September 2018

Decane-1,2-diol derivatives as potential antitumor agents for the treatment of glioblastoma.

Eur J Pharmacol 2018 Oct 1;837:105-116. Epub 2018 Sep 1.

Molecular Signaling Lab, Computational Systems Biology Research Group, BioMediTech and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. Electronic address:

Glioblastoma remains the most common and aggressive type of malignant brain tumor among adults thus, considerable attention has been given to discovery of novel anti-tumor drugs for its treatment. This study reports the synthesis of a series of twelve novel decane-1,2-diol derivatives and evaluation of its anti-tumor activity in mammalian glioblastoma cell lines, U87 and LN229. Starting from decane-1,2-diol, several derivatives were prepared using a diversity oriented synthesis approach through which a small library composed of esters, silyl ethers, sulfonates, sulfites, sulfates, ketals, and phosphonates was built. The decane-1,2-diol ditosylated derivative, DBT, found to have higher cytotoxicity than the standard drug cisplatin, has IC value of 52 µM in U87 and 270 µM in LN229. Migration analysis of U87 cell line treated with the DBT indicated its ability to effectively suppress proliferation during initial hours of treatment and decrease anti-proliferative property over time. Additionally, DBT was assessed for its role in apoptosis, oxidative stress and caspase 3/7 activation in U87. Interestingly, our experiments indicated that its cytotoxicity is independent of Reactive oxygen species induced caspase 3/7 activity. The compound also exhibited caspase independent apoptosis activity in U87. DBT treatment led to G1/S cell cycle arrest and apoptosis induction of glioma cell lines. In addition, we identified 1533 genes with significant changes at the transcriptional level, in response to DBT. A molecular docking study accounting for the interaction of DBT with NMDA receptor disclosed several hydrogen bonds and charged residue interactions with 17 amino acids, which might be the basis of the DBT cytotoxicity observed. We conclude that this molecule exerts its cytotoxicity via caspase 3/7 independent pathways in glioblastoma cells. Concisely, simple decane-1,2-diol derivatives might serve as scaffolds for the development of effective anti-glioblastoma agents.
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http://dx.doi.org/10.1016/j.ejphar.2018.08.041DOI Listing
October 2018

Anticancer activity study of A adenosine receptor agonists.

Life Sci 2018 Jul 13;205:155-163. Epub 2018 May 13.

Molecular Signaling Lab, Computational Systems Biology Research Group, Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, P.O.Box 553, 33101 Tampere, Finland. Electronic address:

Aims: A adenosine receptor (AAR) signalling activation seems to mediate anticancer effect, and it has been targeted for drug development. The identification of potent and selective AAR agonists could be crucial for cancer drug development.

Materials And Methods: In the present study was determined the in vitro activity of known 1-3 and newly 4-6 synthesized compounds with high AAR affinity and selectivity (K in the low nanomolar range) in binding studies. Effect of known and novel AAR agonists on human prostate cancer (PC3), hepatocellular carcinoma (Hep G2), and epithelial colorectal carcinoma (Caco-2) cells were analysed by cytotoxicity assay, dose and time dependent inhibitor assay, migration, apoptosis, autophagy and reactive oxygen species (ROS) assays.

Key Findings: Results show that the anticancer effect is not due to AAR activation alone. In fact, the more active and selective agonist versus AAR, compound 1, results inactive on cancer cells such as compounds 2-4. Moreover, results show that the novel compound 5, at micromolar concentration range (IC = 28.0 μM), inhibits the growth of PC3, Hep G2, and Caco-2 cells and their migration in time- and dose- dependent manner. The mechanism involved in cell death is attributable to apoptosis. At the same time compound 5 promotes autophagy, which induce apoptosis producing autophagic cell death. Further investigation revealed that compound 5 elevates the level of ROS in all cancer cells tested, suggesting the involvement of ROS in cell death.

Significance: These results show that the new compound 5 exerts inhibitory effect on cancer cells through differential effect and may serve as a potential anticancer agent.
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http://dx.doi.org/10.1016/j.lfs.2018.05.028DOI Listing
July 2018

characterization of arylhydrazones of active methylene derivatives.

Saudi Pharm J 2018 Mar 2;26(3):430-436. Epub 2018 Jan 2.

Molecular Signaling Lab, CSB, BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland.

Arylhydrazones of active methylene compounds (AHAMCs) are potent chemotherapy agents for the cancer treatment. AHAMCs enhance the apoptotic cell death and antiproliferation properties in cancer cells. In this study, a series of AHAMCs, 13 compounds, was assayed for cytotoxicity, apoptosis, externalization of phosphatidylserine, heterogeneity and cellular calcium level changes. The cytotoxicity study against HEK293T cells suggests that AHAMCs have significant cytotoxic effect over the concentrations. Top 5 compounds, 5-(2-(2-hydroxyphenyl) hydrazono)pyrimidine-2,4,6(1,3,5)-trione (), 4-hydroxy-5-(2-(2,4,6-trioxo-tetrahydro-pyrimidin-5(6H) ylidene)hydrazinyl)benzene-1,3-disulfonic acid (), 5-chloro-3-(2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl)-2-hydroxybenzenesulfonic acid (), 5-(2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl)-4-hydroxybenzene-1,3-disulfonic acid () and 2-(2-sulfophenylhydrazo)malononitrile () were chosen for the pharmacodynamics study. Among these, compound exhibited the better cytotoxic effect with the IC of 50.86 ± 2.5 mM. DNA cleavage study revealed that induces cell death through apoptosis and shows more effects after 24 and/or 48 h. Independent validation of apoptosis by following the externalization of phosphatidylserine using Annexin-V is also in agreement with the potential activity of . Single cell image analysis of Annexin-V bound cells confirms the presence of mixture of early, mid and late apoptotic cells in the population of the cells treated with and a decreased trend in cell-to-cell variation over the phase was also identified. Additionally, intracellular calcium level measurements identified the Ca up-regulation in compound treated cells. A brief inspection of the effect of the compound against multiple human brain astrocytoma cells showed a better cell growth inhibitory effect at micro molar level. These systematic studies provide insights in the development of novel AHAMACs compounds as potential cell growth inhibitors for cancer treatment.
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http://dx.doi.org/10.1016/j.jsps.2017.12.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5856940PMC
March 2018

In vitro characterization of alkylaminophenols-induced cell death.

Eur J Pharmacol 2018 Feb 21;820:229-234. Epub 2017 Dec 21.

Molecular Signaling Lab, Computational Systems Biology Research Group, BioMediTech and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, P.O.Box 553, 33101 Tampere, Finland. Electronic address:

Alkylaminophenols are synthetic derivatives well known for their anticancer activity. In the previous studies, we described the activity of the series of Alkylaminophenols derivatives and their ability to induce cell death for many cancer cell lines. However, temporal heterogeneity in cell death induced by lead compounds, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline (Compound I) and 2-((3,4-dihydroquinolin-1(2H)-yl) (4-methoxyphenyl) methyl) phenol (Compound II), has never been tested on osteosarcoma cells (U2OS). Here, we address the level of cell-to-cell heterogeneity by examine whether differences in the type of compounds could influence its effects on cell death of U2OS. Here, we applied imaging, computational methods and biochemical methods to study heterogeneity, apoptosis, reactive oxygen species and caspase. Our results demonstrate that the Hill coefficient of dose-response curve of Compound II is greater than compound I in treated U2OS cells. Both Compounds trigger not only apoptotic cell death but also necro-apoptotic and necrotic cell death. The percentage of these sub-populations varies depending on compounds in which greater variance is induced by compound II than Compound I. We also identified the accumulation of compounds-induced reactive oxygen species during the treatment. This resulted in caspase 3/7 activation in turn induced apoptosis. In summary, the screening of Compound I and II molecules for heterogeneity, apoptosis, reactive oxygen species and caspase has identified compound II as promising anti-osteosarcoma cancer agent. Compound II could be a promising lead compound for future antitumor agent development.
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http://dx.doi.org/10.1016/j.ejphar.2017.12.049DOI Listing
February 2018

Lessons from the Human Genome Project: Modesty, Honesty, and Realism.

Front Genet 2017 23;8:184. Epub 2017 Nov 23.

Institute of Biosciences and Medical Technology, Tampere University of Technology, Tampere, Finland.

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http://dx.doi.org/10.3389/fgene.2017.00184DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703740PMC
November 2017

Identification of novel GPR17-agonists by structural bioinformatics and signaling activation.

Int J Biol Macromol 2018 Jan 18;106:901-907. Epub 2017 Aug 18.

Molecular Signaling Lab, Computational Systems Biology Research Group, Signal Processing Department, Tampere University of Technology, P.O. Box 553, 33101, Tampere, Finland. Electronic address:

G Protein-coupled Receptor 17 (GPR17) is phylogenetically related to the purinergic receptors emerged as a potential drug target for multiple sclerosis, Parkinson disease, Alzheimer disease and cancer. Unfortunately, the crystal structure of GPR17 is unresolved. With the interest in structure-based ligand discovery, we modeled the structure of GPR17. The model allowed us to identify two novel agonists, AC1MLNKK and T0510.3657 that selectively activate GPR17 which exhibit better interaction properties than previously known ligand, MDL29951. We report detailed protein-ligand interactions and the dynamics of GPR17-ligand interaction by molecular docking and molecular dynamics experiments. Ex vivo validation of GPR17-ligand interaction provides evidence that ligand T0510-3657 and AC1MLNKK inhibit the cAMP levels in GPR17-HEK293T cells, with a pEC of 4.79 and 4.64, respectively. In silico and ex vivo validation experiments provided the deep understanding of ligand binding with GPR17 and the present findings reported here may lead to use these two compounds as a potential activator of GPR17 for therapeutic intervention.
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http://dx.doi.org/10.1016/j.ijbiomac.2017.08.088DOI Listing
January 2018