Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach

Fan, Shengjun; Geng, Qiang; Pan, Zhenyu; Li, Xin; Tie, Lu; Pan, Yan; Li, Xuejun

doi:10.1186/1752-0509-6-152

Cited by 33 publications

(21 citation statements)

References 51 publications

(63 reference statements)

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“…To acquire high-quality human cancer signaling, we manually curated cancer signaling molecules thoroughly [48], [49]. All the over-represented genes obtained from the virtual RDSs were mapped to portray the context-specific sub-communities and the remodeled signaling regulatory networks were redistributed according to their subcellular localization.…”

Section: Resultsmentioning

confidence: 99%

“…Briefly, a map of human cancer signaling was firstly obtained from Cui et al , which united manually curated signaling molecules including BioCarta (http://www.biocarta.com/) [62], literature-mined signaling network [63], Cancer Cell Map including cancer mutated genes obtained from COSMIC database and other high-throughput profiling, methylated genes in cancer stem cells, cancer associated gene set acquired from plasmID (http://plasmid.hms.harvard.edu/) and Online Mendelian Inheritance in Man (OMIM, http://www.ncbi.nlm.nih.gov/omim). Subsequently, Human Protein Reference Database (HPRD, http://www.hprd.org/) [49] and REACTOME (http://www.reactome.org/) databases were appended. After adding connections between signaling molecules based on SysBiomics platform (http://biomine.cigb.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, Fan and colleagues also performed a network-based pathway analysis using gene co-expression models to specify the off-target effects for torcetrapib. They highlighted that IL-2 Receptor Beta Chain in T cell Activation, Platelet-Derived Growth Factor Receptor (PDGFR) beta signaling pathway, IL2-mediated signaling events, ErbB signaling pathway and signaling events mediated by Hepatocyte Growth Factor Receptor (HGFR, c-Met) were answered for the adverse cardiovascular effects associated with torcetrapib [49]. Thus, pathway-based signaling regulatory networks had been widely applied to complex diseases, which led to identifying diseases-susceptibility pathways for therapeutic interventions [50], [51], [52].…”

Section: Introductionmentioning

confidence: 99%

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Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

et al. 2013

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BackgroundUlcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups.Methodology/Principal FindingsIn this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks.ResultsOverall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one.ConclusionsThe present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis, which was of significant importance to monitor disease progression and improve therapeutic interventions.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

et al. 2013

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“…For instance, the off-target effects of the drug candidates are the main cause of toxicity and side effects and responsible for high attrition rate in drug development. Using reverse docking strategy, the off-targets can be predicted by identifying all possible binding proteins of the drug candidates in the host system [77].…”

Section: • Computational Drug Discovery Approachesmentioning

confidence: 99%

Development of Broad-Spectrum Antibiofilm Drugs: Strategies and Challenges

et al. 2015

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The severity of many chronic bacterial infections is mainly due to the biofilm mode of life adapted by pathogenic bacteria. The bacteria in biofilm-stage exhibit high resistance to host immune responses and antimicrobials, which complicates the treatment process and results in life threatening conditions. Most of the chronic infections are polymicrobial in nature. In order to combat the polymicrobial biofilm infections and to increase the efficiency of antimicrobials, there is an urgent need for broad-spectrum antibiofilm drugs. This review discusses the clinical needs and current status of broad-spectrum antibiofilm drugs with special emphasis on prospective strategies and hurdles in the process of new drug discovery.

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“…Furthermore, the obtained potential off-targets of torcetrapib were identified by employing the reverse docking strategy. The results suggested that plateletderived growth factor receptor (PDGFR), hepatocyte growth factor receptor (HGFR), interleukin-2 (IL-2) receptor, and epidermal growth factor receptor (ErbB1) tyrosine kinase were highly relevant to unfavorable adverse effects [76].…”

Section: Reviewmentioning

confidence: 99%

Computational methods for drug design and discovery: focus on China

Zheng

Liu

Yue

et al. 2013

Trends in Pharmacological Sciences

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In the past decades, China's computational drug design and discovery research has experienced fast development through various novel methodologies. Application of these methods spans a wide range, from drug target identification to hit discovery and lead optimization. In this review, we firstly provide an overview of China's status in this field and briefly analyze the possible reasons for this rapid advancement. The methodology development is then outlined. For each selected method, a short background precedes an assessment of the method with respect to the needs of drug discovery, and, in particular, work from China is highlighted. Furthermore, several successful applications of these methods are illustrated. Finally, we conclude with a discussion of current major challenges and future directions of the field.

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Clarifying off-target effects for torcetrapib using network pharmacology and reverse docking approach

Cited by 33 publications

References 51 publications

Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

Development of Broad-Spectrum Antibiofilm Drugs: Strategies and Challenges

Computational methods for drug design and discovery: focus on China

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