1
|
Hosseini-Gerami L, Ficulle E, Humphryes-Kirilov N, Airey DC, Scherschel J, Kananathan S, Eastwood BJ, Bose S, Collier DA, Laing E, Evans D, Broughton H, Bender A. Mechanism of action deconvolution of the small-molecule pathological tau aggregation inhibitor Anle138b. Alzheimers Res Ther 2023; 15:52. [PMID: 36918909 PMCID: PMC10012450 DOI: 10.1186/s13195-023-01182-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/06/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND A key histopathological hallmark of Alzheimer's disease (AD) is the presence of neurofibrillary tangles of aggregated microtubule-associated protein tau in neurons. Anle138b is a small molecule which has previously shown efficacy in mice in reducing tau aggregates and rescuing AD disease phenotypes. METHODS In this work, we employed bioinformatics analysis-including pathway enrichment and causal reasoning-of an in vitro tauopathy model. The model consisted of cultured rat cortical neurons either unseeded or seeded with tau aggregates derived from human AD patients, both of which were treated with Anle138b to generate hypotheses for its mode of action. In parallel, we used a collection of human target prediction models to predict direct targets of Anle138b based on its chemical structure. RESULTS Combining the different approaches, we found evidence supporting the hypothesis that the action of Anle138b involves several processes which are key to AD progression, including cholesterol homeostasis and neuroinflammation. On the pathway level, we found significantly enriched pathways related to these two processes including those entitled "Superpathway of cholesterol biosynthesis" and "Granulocyte adhesion and diapedesis". With causal reasoning, we inferred differential activity of SREBF1/2 (involved in cholesterol regulation) and mediators of the inflammatory response such as NFKB1 and RELA. Notably, our findings were also observed in Anle138b-treated unseeded neurons, meaning that the inferred processes are independent of tau pathology and thus represent the direct action of the compound in the cellular system. Through structure-based ligand-target prediction, we predicted the intracellular cholesterol carrier NPC1 as well as NF-κB subunits as potential targets of Anle138b, with structurally similar compounds in the model training set known to target the same proteins. CONCLUSIONS This study has generated feasible hypotheses for the potential mechanism of action of Anle138b, which will enable the development of future molecular interventions aiming to reduce tau pathology in AD patients.
Collapse
Affiliation(s)
- Layla Hosseini-Gerami
- Centre for Molecular Informatics, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
- AbsoluteAi Ltd, London, UK
| | - Elena Ficulle
- Eli Lilly and Company, Windlesham, UK
- Zifo RnD Solutions, London, UK
| | | | - David C Airey
- Eli Lilly and Company, Corporate Centre, Indianapolis, IN, USA
| | | | | | - Brian J Eastwood
- Eli Lilly and Company, Windlesham, UK
- Eli Lilly and Company, Bracknell, UK
- Eli Lilly and Company (Retired), Bracknell, UK
| | - Suchira Bose
- Eli Lilly and Company, Windlesham, UK
- Eli Lilly and Company, Bracknell, UK
| | - David A Collier
- Eli Lilly and Company, Windlesham, UK
- Eli Lilly and Company, Bracknell, UK
- Social, Genetic and Developmental Psychiatry Centre, IoPPN, Kings's College London and Genetic and Genomic Consulting Ltd, Farnham, UK
| | - Emma Laing
- Eli Lilly and Company, Windlesham, UK
- GSK, Stevenage, UK
| | - David Evans
- Eli Lilly and Company, Windlesham, UK
- DeepMind, London, UK
| | | | - Andreas Bender
- Centre for Molecular Informatics, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK.
| |
Collapse
|
2
|
Zhu Y, Yang H, Han L, Mervin LH, Hosseini-Gerami L, Li P, Wright P, Trapotsi MA, Liu K, Fan TP, Bender A. In silico prediction and biological assessment of novel angiogenesis modulators from traditional Chinese medicine. Front Pharmacol 2023; 14:1116081. [PMID: 36817116 PMCID: PMC9937659 DOI: 10.3389/fphar.2023.1116081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/20/2023] [Indexed: 02/05/2023] Open
Abstract
Uncontrolled angiogenesis is a common denominator underlying many deadly and debilitating diseases such as myocardial infarction, chronic wounds, cancer, and age-related macular degeneration. As the current range of FDA-approved angiogenesis-based medicines are far from meeting clinical demands, the vast reserve of natural products from traditional Chinese medicine (TCM) offers an alternative source for developing pro-angiogenic or anti-angiogenic modulators. Here, we investigated 100 traditional Chinese medicine-derived individual metabolites which had reported gene expression in MCF7 cell lines in the Gene Expression Omnibus (GSE85871). We extracted literature angiogenic activities for 51 individual metabolites, and subsequently analysed their predicted targets and differentially expressed genes to understand their mechanisms of action. The angiogenesis phenotype was used to generate decision trees for rationalising the poly-pharmacology of known angiogenesis modulators such as ferulic acid and curculigoside and validated by an in vitro endothelial tube formation assay and a zebrafish model of angiogenesis. Moreover, using an in silico model we prospectively examined the angiogenesis-modulating activities of the remaining 49 individual metabolites. In vitro, tetrahydropalmatine and 1 beta-hydroxyalantolactone stimulated, while cinobufotalin and isoalantolactone inhibited endothelial tube formation. In vivo, ginsenosides Rb3 and Rc, 1 beta-hydroxyalantolactone and surprisingly cinobufotalin, restored angiogenesis against PTK787-induced impairment in zebrafish. In the absence of PTK787, deoxycholic acid and ursodeoxycholic acid did not affect angiogenesis. Despite some limitations, these results suggest further refinements of in silico prediction combined with biological assessment will be a valuable platform for accelerating the research and development of natural products from traditional Chinese medicine and understanding their mechanisms of action, and also for other traditional medicines for the prevention and treatment of angiogenic diseases.
Collapse
Affiliation(s)
- Yingli Zhu
- Department of Clinical Chinese Pharmacy, School of Chinese Material Medica, Beijing University of Chinese Medicine, Beijing, China,Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom,Department of Pharmacology, University of Cambridge, Cambridge, United Kingdom
| | - Hongbin Yang
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom
| | - Liwen Han
- Engineering Research Center of Zebrafish Models for Human Diseases and Drug Screening of Shandong Province, Biology Institute, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China,School of Pharmacy and Pharmaceutical Science, Shandong First Medical University, Shandong Academy of Medical Sciences, Jinan, China
| | - Lewis H. Mervin
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom
| | - Layla Hosseini-Gerami
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom
| | - Peihai Li
- Engineering Research Center of Zebrafish Models for Human Diseases and Drug Screening of Shandong Province, Biology Institute, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
| | - Peter Wright
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom
| | - Maria-Anna Trapotsi
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom
| | - Kechun Liu
- Engineering Research Center of Zebrafish Models for Human Diseases and Drug Screening of Shandong Province, Biology Institute, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
| | - Tai-Ping Fan
- Department of Pharmacology, University of Cambridge, Cambridge, United Kingdom,*Correspondence: Tai-Ping Fan, ; Andreas Bender,
| | - Andreas Bender
- Department of Chemistry, Center for Molecular Science Informatics, University of Cambridge, Cambridge, United Kingdom,*Correspondence: Tai-Ping Fan, ; Andreas Bender,
| |
Collapse
|
3
|
Development and validation of an RNA-seq-based transcriptomic risk score for asthma. Sci Rep 2022; 12:8643. [PMID: 35606385 PMCID: PMC9126925 DOI: 10.1038/s41598-022-12199-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 05/04/2022] [Indexed: 11/30/2022] Open
Abstract
Recent progress in RNA sequencing (RNA-seq) allows us to explore whole-genome gene expression profiles and to develop predictive model for disease risk. The objective of this study was to develop and validate an RNA-seq-based transcriptomic risk score (RSRS) for disease risk prediction that can simultaneously accommodate demographic information. We analyzed RNA-seq gene expression data from 441 asthmatic and 254 non-asthmatic samples. Logistic least absolute shrinkage and selection operator (Lasso) regression analysis in the training set identified 73 differentially expressed genes (DEG) to form a weighted RSRS that discriminated asthmatics from healthy subjects with area under the curve (AUC) of 0.80 in the testing set after adjustment for age and gender. The 73-gene RSRS was validated in three independent RNA-seq datasets and achieved AUCs of 0.70, 0.77 and 0.60, respectively. To explore their biological and molecular functions in asthma phenotype, we examined the 73 genes by enrichment pathway analysis and found that these genes were significantly (p < 0.0001) enriched for DNA replication, recombination, and repair, cell-to-cell signaling and interaction, and eumelanin biosynthesis and developmental disorder. Further in-silico analyses of the 73 genes using Connectivity map shows that drugs (mepacrine, dactolisib) and genetic perturbagens (PAK1, GSR, RBM15 and TNFRSF12A) were identified and could potentially be repurposed for treating asthma. These findings show the promise for RNA-seq risk scores to stratify and predict disease risk.
Collapse
|
4
|
Schneidewind T, Brause A, Schölermann B, Sievers S, Pahl A, Sankar MG, Winzker M, Janning P, Kumar K, Ziegler S, Waldmann H. Combined morphological and proteome profiling reveals target-independent impairment of cholesterol homeostasis. Cell Chem Biol 2021; 28:1780-1794.e5. [PMID: 34214450 DOI: 10.1016/j.chembiol.2021.06.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 03/11/2021] [Accepted: 06/08/2021] [Indexed: 12/19/2022]
Abstract
Unbiased profiling approaches are powerful tools for small-molecule target or mode-of-action deconvolution as they generate a holistic view of the bioactivity space. This is particularly important for non-protein targets that are difficult to identify with commonly applied target identification methods. Thereby, unbiased profiling can enable identification of novel bioactivity even for annotated compounds. We report the identification of a large bioactivity cluster comprised of numerous well-characterized drugs with different primary targets using a combination of the morphological Cell Painting Assay and proteome profiling. Cluster members alter cholesterol homeostasis and localization due to their physicochemical properties that lead to protonation and accumulation in lysosomes, an increase in lysosomal pH, and a disturbed cholesterol homeostasis. The identified cluster enables identification of modulators of cholesterol homeostasis and links regulation of genes or proteins involved in cholesterol synthesis or trafficking to physicochemical properties rather than to nominal targets.
Collapse
Affiliation(s)
- Tabea Schneidewind
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany; Technical University Dortmund, Faculty of Chemistry and Chemical Biology, Otto-Hahn-Strasse 6, Dortmund 44227, Germany
| | - Alexandra Brause
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Beate Schölermann
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Sonja Sievers
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Axel Pahl
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Muthukumar G Sankar
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Michael Winzker
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Petra Janning
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Kamal Kumar
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Slava Ziegler
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany
| | - Herbert Waldmann
- Max-Planck Institute of Molecular Physiology, Department of Chemical Biology, Otto-Hahn-Strasse 11, Dortmund 44227, Germany; Technical University Dortmund, Faculty of Chemistry and Chemical Biology, Otto-Hahn-Strasse 6, Dortmund 44227, Germany.
| |
Collapse
|
5
|
The Utility of Resolving Asthma Molecular Signatures Using Tissue-Specific Transcriptome Data. G3-GENES GENOMES GENETICS 2020; 10:4049-4062. [PMID: 32900903 PMCID: PMC7642926 DOI: 10.1534/g3.120.401718] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
An integrative analysis focused on multi-tissue transcriptomics has not been done for asthma. Tissue-specific DEGs remain undetected in many multi-tissue analyses, which influences identification of disease-relevant pathways and potential drug candidates. Transcriptome data from 609 cases and 196 controls, generated using airway epithelium, bronchial, nasal, airway macrophages, distal lung fibroblasts, proximal lung fibroblasts, CD4+ lymphocytes, CD8+ lymphocytes from whole blood and induced sputum samples, were retrieved from Gene Expression Omnibus (GEO). Differentially regulated asthma-relevant genes identified from each sample type were used to identify (a) tissue-specific and tissue-shared asthma pathways, (b) their connection to GWAS-identified disease genes to identify candidate tissue for functional studies, (c) to select surrogate sample for invasive tissues, and finally (d) to identify potential drug candidates via connectivity map analysis. We found that inter-tissue similarity in gene expression was more pronounced at pathway/functional level than at gene level with highest similarity between bronchial epithelial cells and lung fibroblasts, and lowest between airway epithelium and whole blood samples. Although public-domain gene expression data are limited by inadequately annotated per-sample demographic and clinical information which limited the analysis, our tissue-resolved analysis clearly demonstrated relative importance of unique and shared asthma pathways, At the pathway level, IL-1b signaling and ERK signaling were significant in many tissue types, while Insulin-like growth factor and TGF-beta signaling were relevant in only airway epithelial tissue. IL-12 (in macrophages) and Immunoglobulin signaling (in lymphocytes) and chemokines (in nasal epithelium) were the highest expressed pathways. Overall, the IL-1 signaling genes (inflammatory) were relevant in the airway compartment, while pro-Th2 genes including IL-13 and STAT6 were more relevant in fibroblasts, lymphocytes, macrophages and bronchial biopsies. These genes were also associated with asthma in the GWAS catalog. Support Vector Machine showed that DEGs based on macrophages and epithelial cells have the highest and lowest discriminatory accuracy, respectively. Drug (entinostat, BMS-345541) and genetic perturbagens (KLF6, BCL10, INFB1 and BAMBI) negatively connected to disease at multi-tissue level could potentially repurposed for treating asthma. Collectively, our study indicates that the DEGs, perturbagens and disease are connected differentially depending on tissue/cell types. While most of the existing literature describes asthma transcriptome data from individual sample types, the present work demonstrates the utility of multi-tissue transcriptome data. Future studies should focus on collecting transcriptomic data from multiple tissues, age and race groups, genetic background, disease subtypes and on the availability of better-annotated data in the public domain.
Collapse
|
6
|
Natarajan A, Thangarajan R, Kesavan S. Repurposing Drugs by In Silico Methods to Target BCR Kinase Domain in Chronic Myeloid Leukemia. Asian Pac J Cancer Prev 2019; 20:3399-3406. [PMID: 31759365 PMCID: PMC7063026 DOI: 10.31557/apjcp.2019.20.11.3399] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Targeted therapy in the form of highly selective tyrosine kinase inhibitors (TKIs) has transformed the treatment of chronic myeloid leukemia (CML). However, mutations in the kinase domain contribute to drug resistance against TKIs which compromises the treatment response. Our aim is to explore regions outside the BCR-ABL oncoprotein to identify potential therapeutic targets to curb drug resistance by targeting growth factor receptor-bound protein-2 (Grb-2) which binds to BCR-ABL at the phosphorylated tyrosine (Y177) thereby activating the Ras and PI3K/AKT signaling pathway. METHODS We have used in silico methods to repurpose drugs for identifying their potential to inhibit the binding of Grb-2 with Y177 by occupying the active binding site of the BCR domain. RESULTS Differentially expressed genes from GEO dataset were found to be associated with hematopoietic cell lineage, NK cell-mediated cytotoxicity, NF-κB and chemokine signaling, cytokine-cytokine receptor interaction, histidine metabolism and transcriptional misregulation in cancer. The fold recognition method of SPARKS-X tool was used to model the BCR domain (Z-score = 8.21). Connectivity Map generated a drug list based on the gene expression profile, which were docked with BCR. Schrodinger XP glide docking identified Diphosphopyridine nucleotide, Hesperidin, Butirosin, Ovoflavin, and Nor-dihydroguaiaretic acid to show strong interaction in close proximity to the active binding pocket containing Y177 of the target protein and was further validated using iGEMDOCK and Parallelized Open Babel and AutoDock suite Pipeline (POAP). CONCLUSION Our study not only extends our current knowledge about repurposing drugs for newer indications but also provides a route towards combinatorial therapy with standard drugs used for CML treatment. However, the efficacy of these repurposed drugs needs to be further investigated using in vitro and in vivo studies.<br />.
Collapse
Affiliation(s)
- Aparna Natarajan
- Department of Molecular Oncology, Cancer Institute (WIA), Adyar, Chennai, India
| | | | - Sabitha Kesavan
- Department of Molecular Oncology, Cancer Institute (WIA), Adyar, Chennai, India
| |
Collapse
|
7
|
Connectivity map identifies luteolin as a treatment option of ischemic stroke by inhibiting MMP9 and activation of the PI3K/Akt signaling pathway. Exp Mol Med 2019; 51:1-11. [PMID: 30911000 PMCID: PMC6434019 DOI: 10.1038/s12276-019-0229-z] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 10/25/2018] [Accepted: 11/19/2018] [Indexed: 12/22/2022] Open
Abstract
This study aimed to explore potential new drugs in the treatment of ischemic stroke by Connectivity Map (CMap) and to determine the role of luteolin on ischemic stroke according to its effects on matrix metalloproteinase-9 (MMP9) and PI3K/Akt signaling pathway. Based on published gene expression data, differentially expressed genes were obtained by microarray analysis. Potential compounds for ischemic stroke therapy were obtained by CMap analysis. Cytoscape and gene set enrichment analysis (GSEA) were used to discover signaling pathways connected to ischemic stroke. Cell apoptosis and viability were, respectively, evaluated by flow cytometry and an MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide) assay. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis were used to test the expression of MMP9 and the PI3K/Akt signaling pathway-related proteins in human brain microvascular endothelial cells (HBMECs) and tissues. Additionally, the infarct volume after middle cerebral artery occlusion (MCAO) was determined by a TTC (2,3,5-triphenyltetrazolium chloride) assay. The microarray and CMap analyses identified luteolin as a promising compound for future therapies for ischemic stroke. Cytoscape and GSEA showed that the PI3K/Akt signaling pathway was crucial in ischemic stroke. Cell experiments revealed that luteolin enhanced cell viability and downregulated apoptosis via inhibiting MMP9 and activating the PI3K/Akt signaling pathway. Experiments performed in vivo also demonstrated that luteolin reduced the infarct volume. These results suggest that luteolin has potential in the treatment of ischemic stroke through inhibiting MMP9 and activating PI3K/Akt signaling pathway.
Collapse
|
8
|
Musa A, Ghoraie LS, Zhang SD, Glazko G, Yli-Harja O, Dehmer M, Haibe-Kains B, Emmert-Streib F. A review of connectivity map and computational approaches in pharmacogenomics. Brief Bioinform 2018; 19:506-523. [PMID: 28069634 PMCID: PMC5952941 DOI: 10.1093/bib/bbw112] [Citation(s) in RCA: 93] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.
Collapse
Affiliation(s)
- Aliyu Musa
- Predictive Medicine and Analytics Lab, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
| | - Laleh Soltan Ghoraie
- Bioinformatics and Computational Genomics Laboratory, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
| | - Shu-Dong Zhang
- Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, University of Ulster, C-TRIC Building, Altnagelvin Area Hospital, Glenshane Road, Derry/Londonderry, Northern Ireland, UK
| | - Galina Glazko
- University of Rochester Department of Biostatistics and Computational Biology, Rochester, New York, USA
| | - Olli Yli-Harja
- Computational Systems Biology, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
| | - Matthias Dehmer
- Institute for Bioinformatics and Translational Research, UMIT- The Health and Life Sciences University, Eduard Wallnoefer Zentrum 1, Hall in Tyrol, Austria
| | - Benjamin Haibe-Kains
- Bioinformatics and Computational Genomics Laboratory, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
- Ontario Institute of Cancer Research, Toronto, ON, Canada
| | - Frank Emmert-Streib
- Predictive Medicine and Analytics Lab, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
| |
Collapse
|
9
|
Hu HH, Deng H, Ling S, Sun H, Kenakin T, Liang X, Fang Y. Chemical genomic analysis of GPR35 signaling. Integr Biol (Camb) 2018; 9:451-463. [PMID: 28425521 DOI: 10.1039/c7ib00005g] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
GPR35, a family A orphan G protein-coupled receptor, has been implicated in inflammatory, neurological, and cardiovascular diseases. However, not much is known about the signaling and functions of GPR35. We performed a label-free kinome short hairpin RNA screen and identified a putative signaling network of GPR35 in HT-29 cells, some of which was validated using gene expression, biochemical and cellular assays. The results showed that GPR35 induced hypoxia-inducible factor 1α, and was involved in synaptic transmission, sensory perception, the immune system, and morphogenetic processes. Collectively, our data suggest that GPR35 may play an important role in response to hypoxic stress and be a potential target for the treatment of inflammatory, cardiovascular, and neurological disorders.
Collapse
Affiliation(s)
- Heidi Haibei Hu
- Biochemical Technologies, Corning R&D Corporation, Corning Incorporated, Corning, NY 14831, USA.
| | | | | | | | | | | | | |
Collapse
|
10
|
Jang YJ, Son HJ, Choi YM, Ahn J, Jung CH, Ha TY. Apigenin enhances skeletal muscle hypertrophy and myoblast differentiation by regulating Prmt7. Oncotarget 2017; 8:78300-78311. [PMID: 29108230 PMCID: PMC5667963 DOI: 10.18632/oncotarget.20962] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Accepted: 08/27/2017] [Indexed: 12/19/2022] Open
Abstract
Apigenin, a natural flavone abundant in various plant-derived foods including parsley and celery, has been shown to prevent inflammation and inflammatory diseases. However, the effect of apigenin on skeletal muscle hypertrophy and myogenic differentiation has not previously been elucidated. Here, we investigated the effects of apigenin on quadricep muscle weight and running distance using C57BL/6 mice on an accelerating treadmill. Apigenin stimulated mRNA expression of MHC (myosin heavy chain) 1, MHC2A, and MHC2B in the quadricep muscles of these animals. GPR56 (G protein-coupled receptor 56) and its ligand collagen III were upregulated by apigenin supplementation, together with enhanced PGC-1α, PGC-1α1, PGC-1α4, IGF1, and IGF2 expression. Prmt7 protein expression increased in conjunction with Akt and mTORC1 activation. Apigenin treatment also upregulated FNDC5 (fibronectin type III domain containing 5) mRNA expression and serum irisin levels. Furthermore, apigenin stimulated C2C12 myogenic differentiation and upregulated total MHC, MHC2A, and MHC2B expression. These events were attributable to an increase in Prmt7-p38-myoD expression and Akt and S6K1 phosphorylation. We also observed that Prmt7 regulates both PGC-1α1 and PGC-1α4 expression, resulting in a subsequent increase in GPR56 expression and mTORC1 activation. Taken together, these findings suggest that apigenin supplementation can promote skeletal muscle hypertrophy and myogenic differentiation by regulating the Prmt7-PGC-1α-GPR56 pathway, as well as the Prmt7-p38-myoD pathway, which may contribute toward the prevention of skeletal muscle weakness.
Collapse
Affiliation(s)
- Young Jin Jang
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea
| | - Hyo Jeong Son
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea
| | - Yong Min Choi
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea
| | - Jiyun Ahn
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea.,Division of Food Biotechnology, University of Science and Technology, Daejeon, Republic of Korea
| | - Chang Hwa Jung
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea.,Division of Food Biotechnology, University of Science and Technology, Daejeon, Republic of Korea
| | - Tae Youl Ha
- Division of Nutrition and Metabolism Research, Korea Food Research Institute, Seongnam, Republic of Korea.,Division of Food Biotechnology, University of Science and Technology, Daejeon, Republic of Korea
| |
Collapse
|
11
|
Sirci F, Napolitano F, Pisonero-Vaquero S, Carrella D, Medina DL, di Bernardo D. Comparing structural and transcriptional drug networks reveals signatures of drug activity and toxicity in transcriptional responses. NPJ Syst Biol Appl 2017; 3:23. [PMID: 28861278 PMCID: PMC5572457 DOI: 10.1038/s41540-017-0022-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Revised: 06/27/2017] [Accepted: 07/07/2017] [Indexed: 02/07/2023] Open
Abstract
We performed an integrated analysis of drug chemical structures and drug-induced transcriptional responses. We demonstrated that a network representing three-dimensional structural similarities among 5452 compounds can be used to automatically group together drugs with similar scaffolds, physicochemical parameters and mode-of-action. We compared the structural network to a network representing transcriptional similarities among a subset of 1309 drugs for which transcriptional response were available in the Connectivity Map data set. Analysis of structurally similar, but transcriptionally different drugs sharing the same MOA enabled us to detect and remove weak and noisy transcriptional responses, greatly enhancing the reliability of transcription-based approaches to drug discovery and drug repositioning. Cardiac glycosides exhibited the strongest transcriptional responses with a significant induction of pathways related to epigenetic regulation, which suggests an epigenetic mechanism of action for these drugs. Drug classes with the weakest transcriptional responses tended to induce expression of cytochrome P450 enzymes, hinting at drug-induced drug resistance. Analysis of transcriptionally similar, but structurally different drugs with unrelated MOA, led us to the identification of a 'toxic' transcriptional signature indicative of lysosomal stress (lysosomotropism) and lipid accumulation (phospholipidosis) partially masking the target-specific transcriptional effects of these drugs. We found that this transcriptional signature is shared by 258 compounds and it is associated to the activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy. Finally, we built a predictive Random Forest model of these 258 compounds based on 128 physicochemical parameters, which should help in the early identification of potentially toxic drug candidates. Transcriptional responses to drug treatment can reveal mechanism of action and off-target effects thus enabling drug repositioning, but only if measured in the appropriate cells at clinically relevant concentrations. A team led by Diego di Bernardo and Diego Medina generated a network representing structural similarities among compounds to automatically group together drugs with similar scaffolds and MOA. By comparing the structural drug network with a transcriptional drug network based on similarities in transcriptional response, the team observed broad differences between the two. This observation led to the identification of a transcriptional signature related lysosomal stress and phospholipidosis, and a physicochemical model to identify such compounds. These results provide general guidelines to prevent erroneous conclusion when using transcriptional responses of small molecules for drug discovery and drug repositioning
Collapse
Affiliation(s)
- Francesco Sirci
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy
| | - Francesco Napolitano
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy
| | - Sandra Pisonero-Vaquero
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy
| | - Diego Carrella
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy
| | - Diego L Medina
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy
| | - Diego di Bernardo
- Telethon Institute of Genetics and Medicine (TIGEM), System Biology and Bioinformatics lab. and High Content Screening facility, Via Campi Flegrei 34, 80078 Pozzuoli (NA), Italy.,Department of Chemical, Materials and Industrial Production Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
| |
Collapse
|
12
|
Grammer AC, Lipsky PE. Drug Repositioning Strategies for the Identification of Novel Therapies for Rheumatic Autoimmune Inflammatory Diseases. Rheum Dis Clin North Am 2017; 43:467-480. [DOI: 10.1016/j.rdc.2017.04.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
|
13
|
Mohd Fauzi F, John CM, Karunanidhi A, Mussa HY, Ramasamy R, Adam A, Bender A. Understanding the mode-of-action of Cassia auriculata via in silico and in vivo studies towards validating it as a long term therapy for type II diabetes. JOURNAL OF ETHNOPHARMACOLOGY 2017; 197:61-72. [PMID: 27452659 DOI: 10.1016/j.jep.2016.07.058] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Revised: 07/13/2016] [Accepted: 07/21/2016] [Indexed: 05/23/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Cassia auriculata (CA) is used as an antidiabetic therapy in Ayurvedic and Siddha practice. This study aimed to understand the mode-of-action of CA via combined cheminformatics and in vivo biological analysis. In particular, the effect of 10 polyphenolic constituents of CA in modulating insulin and immunoprotective pathways were studied. MATERIALS AND METHODS In silico target prediction was first employed to predict the probability of the polyphenols interacting with key protein targets related to insulin signalling, based on a model trained on known bioactivity data and chemical similarity considerations. Next, CA was investigated in in vivo studies where induced type 2 diabetic rats were treated with CA for 28 days and the expression levels of genes regulating insulin signalling pathway, glucose transporters of hepatic (GLUT2) and muscular (GLUT4) tissue, insulin receptor substrate (IRS), phosphorylated insulin receptor (AKT), gluconeogenesis (G6PC and PCK-1), along with inflammatory mediators genes (NF-κB, IL-6, IFN-γ and TNF-α) and peroxisome proliferators-activated receptor gamma (PPAR-γ) were determined by qPCR. RESULTS In silico analysis shows that several of the top 20 enriched targets predicted for the constituents of CA are involved in insulin signalling pathways e.g. PTPN1, PCK-α, AKT2, PI3K-γ. Some of the predictions were supported by scientific literature such as the prediction of PI3K for epigallocatechin gallate. Based on the in silico and in vivo findings, we hypothesized that CA may enhance glucose uptake and glucose transporter expressions via the IRS signalling pathway. This is based on AKT2 and PI3K-γ being listed in the top 20 enriched targets. In vivo analysis shows significant increase in the expression of IRS, AKT, GLUT2 and GLUT4. CA may also affect the PPAR-γ signalling pathway. This is based on the CA-treated groups showing significant activation of PPAR-γ in the liver compared to control. PPAR-γ was predicted by the in silico target prediction with high normalisation rate although it was not in the top 20 most enriched targets. CA may also be involved in the gluconeogenesis and glycogenolysis in the liver based on the downregulation of G6PC and PCK-1 genes seen in CA-treated groups. In addition, CA-treated groups also showed decreased cholesterol, triglyceride, glucose, CRP and Hb1Ac levels, and increased insulin and C-peptide levels. These findings demonstrate the insulin secretagogue and sensitizer effect of CA. CONCLUSION Based on both an in silico and in vivo analysis, we propose here that CA mediates glucose/lipid metabolism via the PI3K signalling pathway, and influence AKT thereby causing insulin secretion and insulin sensitivity in peripheral tissues. CA enhances glucose uptake and expression of glucose transporters in particular via the upregulation of GLUT2 and GLUT4. Thus, based on its ability to modulate immunometabolic pathways, CA appears as an attractive long term therapy for T2DM even at relatively low doses.
Collapse
Affiliation(s)
- Fazlin Mohd Fauzi
- Department of Pharmacology and Chemistry, Faculty of Pharmacy, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia; Center for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW Cambridge, United Kingdom.
| | - Cini Mathew John
- Department of Pharmacology and Chemistry, Faculty of Pharmacy, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia; Department of Physiology and Pharmacology, Faculty of Medicine, University of Calgary, 3330 Hospital Dr. NW, Calgary, AB, Canada T2N 4N1
| | - Arunkumar Karunanidhi
- Department of Medical Microbiology and Parasitology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
| | - Hamse Y Mussa
- Center for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW Cambridge, United Kingdom
| | - Rajesh Ramasamy
- Immunology Unit, Department of Pathology, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
| | - Aishah Adam
- Department of Pharmacology and Chemistry, Faculty of Pharmacy, Universiti Teknologi MARA, 42300 Bandar Puncak Alam, Selangor Darul Ehsan, Malaysia
| | - Andreas Bender
- Center for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, CB2 1EW Cambridge, United Kingdom
| |
Collapse
|
14
|
Perualila-Tan NJ, Shkedy Z, Talloen W, Göhlmann HWH, Moerbeke MV, Kasim A. Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery. J Bioinform Comput Biol 2016; 14:1650018. [DOI: 10.1142/s0219720016500189] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.
Collapse
Affiliation(s)
- Nolen Joy Perualila-Tan
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Center for Statistics, Hasselt University, Belgium
| | - Ziv Shkedy
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Center for Statistics, Hasselt University, Belgium
| | | | | | - Marijke Van Moerbeke
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Center for Statistics, Hasselt University, Belgium
| | - Adetayo Kasim
- Wolfson Research Institute for Health and Wellbeing, Durham University, United Kingdom
| | | |
Collapse
|
15
|
Li H, Cowie A, Johnson JA, Webster D, Martyniuk CJ, Gray CA. Determining the mode of action of anti-mycobacterial C17 diyne natural products using expression profiling: evidence for fatty acid biosynthesis inhibition. BMC Genomics 2016; 17:621. [PMID: 27514659 PMCID: PMC4981992 DOI: 10.1186/s12864-016-2949-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 07/18/2016] [Indexed: 11/10/2022] Open
Abstract
Background The treatment of microbial infections is becoming increasingly challenging because of limited therapeutic options and the growing number of pathogenic strains that are resistant to current antibiotics. There is an urgent need to identify molecules with novel modes of action to facilitate the development of new and more effective therapeutic agents. The anti-mycobacterial activity of the C17 diyne natural products falcarinol and panaxydol has been described previously; however, their mode of action remains largely undetermined in microbes. Gene expression profiling was therefore used to determine the transcriptomic response of Mycobacterium smegmatis upon treatment with falcarinol and panaxydol to better characterize the mode of action of these C17 diynes. Results Our analyses identified 704 and 907 transcripts that were differentially expressed in M. smegmatis after treatment with falcarinol and panaxydol respectively. Principal component analysis suggested that the C17 diynes exhibit a mode of action that is distinct to commonly used antimycobacterial drugs. Functional enrichment analysis and pathway enrichment analysis revealed that cell processes such as ectoine biosynthesis and cyclopropane-fatty-acyl-phospholipid synthesis were responsive to falcarinol and panaxydol treatment at the transcriptome level in M. smegmatis. The modes of action of the two C17 diynes were also predicted through Prediction of Activity Spectra of Substances (PASS). Based upon convergence of these three independent analyses, we hypothesize that the C17 diynes inhibit fatty acid biosynthesis, specifically phospholipid synthesis, in mycobacteria. Conclusion Based on transcriptomic responses, it is suggested that the C17 diynes act differently than other anti-mycobacterial compounds in M. smegmatis, and do so by inhibiting phospholipid biosynthesis. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2949-y) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Haoxin Li
- Department of Biological Sciences, University of New Brunswick, PO Box 5050, 100 Tucker Park Road, E2L 4L5, Saint John, NB, Canada
| | - Andrew Cowie
- Department of Biological Sciences, University of New Brunswick, PO Box 5050, 100 Tucker Park Road, E2L 4L5, Saint John, NB, Canada
| | - John A Johnson
- Department of Biological Sciences, University of New Brunswick, PO Box 5050, 100 Tucker Park Road, E2L 4L5, Saint John, NB, Canada
| | - Duncan Webster
- Department of Medicine, Division of Infectious Diseases, Saint John Regional Hospital, 400 University Ave, E2L 4L4, Saint John, NB, Canada
| | - Christopher J Martyniuk
- Department of Biological Sciences, University of New Brunswick, PO Box 5050, 100 Tucker Park Road, E2L 4L5, Saint John, NB, Canada.,Present address: Center for Environmental and Human Toxicology & Department of Physiological Sciences, UF Genetics Institute, College of Veterinary Medicine, University of Florida, 1333 Center Drive, 32610-0144, Gainesville, FL, USA
| | - Christopher A Gray
- Department of Biological Sciences, University of New Brunswick, PO Box 5050, 100 Tucker Park Road, E2L 4L5, Saint John, NB, Canada. .,Department of Chemistry, University of New Brunswick, PO Box 4400, 30 Dineen Drive, E3B 5A3, Fredericton, NB, Canada.
| |
Collapse
|
16
|
Wang L, Yu Y, Yang J, Zhao X, Li Z. Dissecting Xuesaitong's mechanisms on preventing stroke based on the microarray and connectivity map. MOLECULAR BIOSYSTEMS 2016; 11:3033-9. [PMID: 26305988 DOI: 10.1039/c5mb00379b] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Elucidating action mechanisms of Chinese medicines has remained a challenging task due to the chemical and biological complexity that needs to be resolved. In this study we applied a gene expression data and connectivity map (CMAP) based approach to study action mechanisms of a Chinese medicine Xuesaitong injection (XST) on preventing cerebral ischemia-reperfusion injury. XST is a standardized patent Chinese medicine of Panax notoginseng roots and it has long been used for the effective prevention and treatment of stroke in China. However, more research is needed to understand the mechanisms underlying its effects against ischemic stroke. We first evaluated the effect of XST against ischemic stroke in an ischemia-reperfusion rat animal model and dissected its mechanisms based on gene expression data of injured brain. The results showed that treatment with XST significantly attenuated infarct area and histological damage. Based upon pathway analysis and the CMAP query of microarray data, anti-inflammatory response and anti-platelet coagulation were found as the major mechanisms of XST against stroke, which were further validated in vitro and with pharmacological assays of serum. We demonstrated the feasibility of applying the combination of the microarray with the CMAP in identifying mechanisms of Chinese medicine.
Collapse
Affiliation(s)
- Linli Wang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | | | | | | | | |
Collapse
|
17
|
Jia Z, Liu Y, Guan N, Bo X, Luo Z, Barnes MR. Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery. BMC Genomics 2016; 17:414. [PMID: 27234029 PMCID: PMC4884357 DOI: 10.1186/s12864-016-2737-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 05/11/2016] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. RESULTS We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . CONCLUSIONS In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and repositioning, allowing the grouping and prioritisation of drug repositioning candidates on the basis of putative mode of action.
Collapse
Affiliation(s)
- Zhilong Jia
- Department of Chemistry and Biology, College of Science, National University of Defense Technology, Changsha, Hunan, 410073, People's Republic of China
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK
| | - Ying Liu
- Hunan Key Laboratory of Medical Epigenomics, Department of Dermatology, Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, People's Republic of China
| | - Naiyang Guan
- College of Computer, National University of Defense Technology, Changsha, 410073, People's Republic of China
- National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, 410073, People's Republic of China
| | - Xiaochen Bo
- Beijing Institute of Radiation Medicine, Beijing, 100850, People's Republic of China
| | - Zhigang Luo
- College of Computer, National University of Defense Technology, Changsha, 410073, People's Republic of China.
- National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, 410073, People's Republic of China.
| | - Michael R Barnes
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
| |
Collapse
|
18
|
Wang S, Xu G, Deng L, Gu Z. Transcriptomic study on the impact of temporomandibular joint internal derangement in the condylar cartilage of rabbits. GENOMICS DATA 2015; 5:364-5. [PMID: 26484287 PMCID: PMC4583689 DOI: 10.1016/j.gdata.2015.06.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Revised: 06/26/2015] [Accepted: 06/29/2015] [Indexed: 11/30/2022]
Abstract
Internal derangement (ID) in the temporomandibular joint (TMJ) compromises a group of clinical problems, and holds a relative high prevalence in populations. However, the temporal genomic change in gene expression of condylar cartilage during continuous ID remains unclear. Here we reported the differentially expressed gene pattern in condylar cartilage of rabbits with ID from 1 to 8 weeks by microarray analysis. The whole genome project was deposited at GenBank under the accession PRJNA278127. The microarray analysis showed that 6478 genes have more than two-fold changes among all the tested transcripts. Many inflammation gene increased rapidly in the early stage while decrease later. On the contrary, the bone construction related genes showed a low level at first and increased at later period in the ID progression. Besides, the current study found some genes such as HLA2G, which had never been reported, might be relevant with ID.
Collapse
Affiliation(s)
- Shuhua Wang
- School of Stomatology, Zhejiang Chinese Medical University, Hangzhou, China
| | - Gaoli Xu
- Department of Oral and Maxillofacial Surgery, School of Stomatology, Zhejiang Chinese Medical University, Hangzhou, China
| | - Liquan Deng
- Key Laboratory of Stomatology, School of Stomatology, Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhiyuan Gu
- School of Stomatology, Zhejiang Chinese Medical University, Hangzhou, China
| |
Collapse
|
19
|
Cichonska A, Rousu J, Aittokallio T. Identification of drug candidates and repurposing opportunities through compound-target interaction networks. Expert Opin Drug Discov 2015; 10:1333-45. [PMID: 26429153 DOI: 10.1517/17460441.2015.1096926] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
INTRODUCTION System-wide identification of both on- and off-targets of chemical probes provides improved understanding of their therapeutic potential and possible adverse effects, thereby accelerating and de-risking drug discovery process. Given the high costs of experimental profiling of the complete target space of drug-like compounds, computational models offer systematic means for guiding these mapping efforts. These models suggest the most potent interactions for further experimental or pre-clinical evaluation both in cell line models and in patient-derived material. AREAS COVERED The authors focus here on network-based machine learning models and their use in the prediction of novel compound-target interactions both in target-based and phenotype-based drug discovery applications. While currently being used mainly in complementing the experimentally mapped compound-target networks for drug repurposing applications, such as extending the target space of already approved drugs, these network pharmacology approaches may also suggest completely unexpected and novel investigational probes for drug development. EXPERT OPINION Although the studies reviewed here have already demonstrated that network-centric modeling approaches have the potential to identify candidate compounds and selective targets in disease networks, many challenges still remain. In particular, these challenges include how to incorporate the cellular context and genetic background into the disease networks to enable more stratified and selective target predictions, as well as how to make the prediction models more realistic for the practical drug discovery and therapeutic applications.
Collapse
Affiliation(s)
- Anna Cichonska
- a 1 University of Helsinki, Institute for Molecular Medicine Finland FIMM , Helsinki, Finland.,b 2 Aalto University, Helsinki Institute for Information Technology HIIT, Department of Computer Science , Espoo, Finland
| | - Juho Rousu
- c 3 Aalto University, Helsinki Institute for Information Technology HIIT, Department of Computer Science , Espoo, Finland
| | - Tero Aittokallio
- d 4 University of Helsinki, Institute for Molecular Medicine Finland FIMM , Helsinki, Finland +358 5 03 18 24 26 ; .,e 5 University of Turku, Department of Mathematics and Statistics , Turku, Finland
| |
Collapse
|
20
|
Fuchs JE, Bender A, Glen RC. Cheminformatics Research at the Unilever Centre for Molecular Science Informatics Cambridge. Mol Inform 2015; 34:626-633. [PMID: 26435758 PMCID: PMC4583778 DOI: 10.1002/minf.201400166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2014] [Accepted: 12/16/2014] [Indexed: 11/12/2022]
Abstract
The Centre for Molecular Informatics, formerly Unilever Centre for Molecular Science Informatics (UCMSI), at the University of Cambridge is a world-leading driving force in the field of cheminformatics. Since its opening in 2000 more than 300 scientific articles have fundamentally changed the field of molecular informatics. The Centre has been a key player in promoting open chemical data and semantic access. Though mainly focussing on basic research, close collaborations with industrial partners ensured real world feedback and access to high quality molecular data. A variety of tools and standard protocols have been developed and are ubiquitous in the daily practice of cheminformatics. Here, we present a retrospective of cheminformatics research performed at the UCMSI, thereby highlighting historical and recent trends in the field as well as indicating future directions.
Collapse
Affiliation(s)
- Julian E Fuchs
- Centre for Molecular Informatics, Department of Chemistry, University of CambridgeLensfield Road, Cambridge CB2 1EW, UK phone/fax: +44 (0)1223 336472/+44 (0)1223 763076
| | - Andreas Bender
- Centre for Molecular Informatics, Department of Chemistry, University of CambridgeLensfield Road, Cambridge CB2 1EW, UK phone/fax: +44 (0)1223 336472/+44 (0)1223 763076
| | - Robert C Glen
- Centre for Molecular Informatics, Department of Chemistry, University of CambridgeLensfield Road, Cambridge CB2 1EW, UK phone/fax: +44 (0)1223 336472/+44 (0)1223 763076
| |
Collapse
|
21
|
Abstract
INTRODUCTION Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology. AREAS COVERED This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects. EXPERT OPINION The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.
Collapse
Affiliation(s)
- Violeta I Pérez-Nueno
- a Harmonic Pharma, Espace Transfert , 615 rue du Jardin Botanique, 54600 Villers lès Nancy, France +33 354 958 604 ; +33 383 593 046 ;
| |
Collapse
|