Browsing by Author "Yang, Jinn-Moon"

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3D-interologs: A protein-protein interacting evolution database across multiple species
(2009)
Yang, Jinn-Moon
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Chen, Yung-Chiang
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Lo, Yu-Shu
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生物科技學系
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Department of Biological Science and Technology
The 3D-interologs database records the evolution of protein-protein interactions database across multiple species Based on "3D-domain interologs' and a new scoring function, we infer 173,294 protein-protein interactions by using 1,895 three-dimensional (3D) structure heterodimers to search the UmProt database (4,826.134 protein sequences) For a protein-protein interaction, the 3D-interologs database shows functional annotations (e if. Gene Ontology annotations), interacting domains and binding models (e.g hydrogen-bond interactions and conserved residues). Additionally, this database provides couple-conserved residues and the interacting evolution by exploring the micro logs across multiple species Experimental results reveal that the proposed scoring function obtains good agreement for the binding affinity of 275 mutated residues from the ASEdb The precision and recall of our method are 052 and 0.34, respectively, by using 563 non-redundant heterodimers to search on the Integr8 database (549 completely deciphered genomes) The proposed method can infer many of the interactions that would not have been identified from sequence similarity alone The 3D-interologs database comprises 15,024 species and 283,980 protein-protein interactions, including 173,294 interactions (61%) discovered from 3D-domain interologs and 110,686 interactions (39%) summarized from the IntAct database The 3D-interologs database is available at hop//3D-Interologs life.nctu.edu.tw
3D-interologs: an evolution database of physical protein- protein interactions across multiple genomes
(2010-12-01)
Lo, Yu-Shu
;
Chen, Yung-Chiang
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Yang, Jinn-Moon
;
生物科技學系
;
生物資訊及系統生物研究所
Background: Comprehensive exploration of protein-protein interactions is a challenging route to understand biological processes. For efficiently enlarging protein interactions annotated with residue-based binding models, we proposed a new concept "3D-domain interolog mapping" with a scoring system to explore all possible protein pairs between the two homolog families, derived from a known 3D-structure dimmer (template), across multiple species. Each family consists of homologous proteins which have interacting domains of the template for studying domain interface evolution of two interacting homolog families. Results: The 3D-interologs database records the evolution of protein-protein interactions database across multiple species. Based on "3D-domain interolog mapping" and a new scoring function, we infer 173,294 protein-protein interactions by using 1,895 three-dimensional (3D) structure heterodimers to search the UniProt database (4,826,134 protein sequences). The 3D-interologs database comprises 15,124 species and 283,980 protein-protein interactions, including 173,294 interactions (61%) and 110,686 interactions (39%) summarized from the IntAct database. For a protein-protein interaction, the 3D-interologs database shows functional annotations (e. g. Gene Ontology), interacting domains and binding models (e. g. hydrogen-bond interactions and conserved residues). Additionally, this database provides couple-conserved residues and the interacting evolution by exploring the interologs across multiple species. Experimental results reveal that the proposed scoring function obtains good agreement for the binding affinity of 275 mutated residues from the ASEdb. The precision and recall of our method are 0.52 and 0.34, respectively, by using 563 non-redundant heterodimers to search on the Integr8 database (549 complete genomes). Conclusions: Experimental results demonstrate that the proposed method can infer reliable physical protein-protein interactions and be useful for studying the protein-protein interaction evolution across multiple species. In addition, the top-ranked strategy and template interface score are able to significantly improve the accuracies of identifying protein-protein interactions in a complete genome. The 3D-interologs database is available at http://3D-interologs.life.nctu.edu.tw.
3D-partner: a web server to infer interacting partners and binding models
(2007-07-01)
Chen, Yung-Chiang
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Lo, Yu-Shu
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Hsu, Wen-Chang
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Yang, Jinn-Moon
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生物科技學系
The 3D-partner is a web tool to predict interacting partners and binding models of a query protein sequence through structure complexes and a new scoring function. 3D-partner first utilizes IMPALA to identify homologous structures (templates) of a query from a heterodimer profile library. The interacting-partner sequence profiles of these templates are then used to search interacting candidates of the query from protein sequence databases (e. g. SwissProt) by PSI-BLAST. We developed a new scoring function, which includes the contact-residue interacting score (e. g. the steric, hydrogen bonds, and electrostatic interactions) and the template consensus score (e. g. couple-conserved residue and the template similarity scores), to evaluate how well the interfaces between the query and interacting candidates. Based on this scoring function, 3D-partner provides the statistic significance, the binding models (e. g. hydrogen bonds and conserved amino acids) and functional annotations of interacting partners. The correlation between experimental energies and predicted binding affinities of our scoring function is 0.91 on 275 mutated residues from the ASEdb. The average precision of the server is 0.72 on 563 queries and the execution time of this server for a query is similar to 15s on average. These results suggest that the 3D-partner server can be useful in protein-protein interaction predictions and binding model visualizations. The server is available online at: http://3D-partner.life.nctu.edu.tw.
5-Demethyltangeretin is more potent than tangeretin in inhibiting dimethylbenz(a)anthracene (DMBA)/12-O-tetradecanoylphorbol-13-acetate (TPA)-induced skin tumorigenesis
(2014-11-01)
Ma, Nianhan
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Lai, Ching-Shu
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Chung, Chih-Han
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Yang, Jinn-Moon
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Hsu, Kai-Cheng
5-Demethyltangeretin (5-DTAN), an autohydrolysis product of tangeretin (TAN) found in citrus peel, exhibited more potent anti-proliferative activity in human cancer cells than TAN itself. In this study, we investigated the anti-tumor promoting effect and underlying molecular mechanism of 5-DTAN on 7,12-dimethyl-benz(a)anthracene (DMBA)-induced and 12-O-tetradecanoylphorbol-13-acetate (TPA)-promoted skin carcinogenesis. Application of 5-DTAN prior to each TPA-treatment was more effective than that of TAN on reducing the number, incidence and size of papillomas in DMBA-initiated mouse skin. Moreover, 5-DTAN suppressed cyclooxygenase-2 (COX-2) protein expression more strongly than TAN through interfering with phosphatidylinositiol 3-kinase (PI3K)/Akt signaling and further activation of transcription factor NF-kappa B. Taken together, these results revealed for the first time the in vivo chemopreventive efficacy of 5-DTAN on inhibition of skin carcinogenesis through promoting apoptosis and molecular interactions with residues of PI3K, COX-2, and AKT that may potentially serve as a novel functional agent capable of preventing inflammation-associated tumorigenesis. (C) 2014 Elsevier Ltd. All rights reserved.
7-Chloro-6-piperidin-1-yl-quinoline-5,8-dione (PT-262), a novel ROCK inhibitor blocks cytoskeleton function and cell migration
(2011-04-01)
Tsai, Chih-Chien
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Liu, Huei-Fang
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Hsu, Kai-Cheng
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Yang, Jinn-Moon
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Chen, Chinpiao
The 5,8-quinolinediones are precursors for producing multiple types of bioactive products. In this study, we investigated a new compound derived from 5,8-quinolinediones, 7-chloro-6-piperidin-1-yl-quinoline-5,8-dione (designated as PT-262), which markedly induced cytoskeleton remodeling and migration inhibition in lung carcinoma cells. Comparison with various cytoskeleton inhibitors, including paclitaxel, colchicine and phallacidin, the cell morphology following treatment with PT-262 was similar to phallacidin on the cell elongation and abnormal actin polymerization. However, PT-262 did not directly bind to actin filaments. ROCK (Rho-associated coiled-coil forming protein kinase) is a downstream effector of RhoA to mediate the phosphorylation of myosin light chain (MLC) and cytoskeleton reorganization. The RhoA-ROCK-MLC pathway has been shown to promote cancer cell migration and metastasis. Interestingly. PT-262 was more effective on inhibiting ROCK kinase activities than specific ROCK inhibitors Y-27632 and H-1152. PT-262 induced cytoskeleton remodeling and migration inhibition in A549 lung carcinoma cells. The total MLC and phosphorylated MLC proteins and stress fibers were blocked after treatment with PT-262. Nonetheless, the RhoA protein and GTPase activity were not altered by PT-262. A computational model suggests that PT-262 interacts with the ATP-binding site of ROCK protein. Together, these findings demonstrate that PT-262 is a new ROCK inhibitor. (C) 2011 Elsevier Inc. All rights reserved.
A Gaussian Evolutionary Method for predicting protein-protein interaction sites
(2007)
Liu, Kang-Ping
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Yang, Jinn-Moon
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生物資訊及系統生物研究所
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Institude of Bioinformatics and Systems Biology
Protein-protein interactions play a pivotal role in modem molecular biology. Identifying the protein-protein interaction sites is great scientific and practical interest for predicting protein-protein interactions. In this study, we proposed a Gaussian Evolutionary Method (GEM) to optimize 18 features, including ten atomic solvent and eight protein 2(nd) structure features, for predicting protein-protein interaction sites. The training set consists of 104 unbound proteins selected from PDB and the predicted successful rate is 65.4% (68/104) proteins in the training dataset. These 18 parameters were then applied to a test set with 50 unbound proteins. Based on the threshold obtained from the training set, our method is able to predict the binding sites for 98% (49/50) proteins and yield 46% successful prediction and 42.3% average specificity. Here, a binding-site prediction is considered successful if 50% predicted area is indeed located in protein-protein interface (i.e. the specificity is more than 0.5). We believe that the optimized parameters of our method are useful for analyzing protein-protein interfaces and for interfaces prediction methods and protein-protein docking methods.
A homologous mapping method for three-dimensional reconstruction of protein networks reveals disease-associated mutations
(2018-03-19)
Huang, Sing-Han
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Lo, Yu-Shu
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Luo, Yong-Chun
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Tseng, Yu-Yao
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Yang, Jinn-Moon
Background: One of the crucial steps toward understanding the associations among molecular interactions, pathways, and diseases in a cell is to investigate detailed atomic protein-protein interactions (PPIs) in the structural interactome. Despite the availability of large-scale methods for analyzing PPI networks, these methods often focused on PPI networks using genome-scale data and/or known experimental PPIs. However, these methods are unable to provide structurally resolved interaction residues and their conservations in PPI networks. Results: Here, we reconstructed a human three-dimensional (3D) structural PPI network (hDiSNet) with the detailed atomic binding models and disease-associated mutations by enhancing our PPI families and 3D-domain interologs from 60,618 structural complexes and complete genome database with 6,352,363 protein sequences across 2274 species. hDiSNet is a scale-free network (gamma = 2.05), which consists of 5177 proteins and 19,239 PPIs with 5843 mutations. These 19,239 structurally resolved PPIs not only expanded the number of PPIs compared to present structural PPI network, but also achieved higher agreement with gene ontology similarities and higher co-expression correlation than the ones of 181,868 experimental PPIs recorded in public databases. Among 5843 mutations, 1653 and 790 mutations involved in interacting domains and contacting residues, respectively, are highly related to diseases. Our hDiSNet can provide detailed atomic interactions of human disease and their associated proteins with mutations. Our results show that the disease-related mutations are often located at the contacting residues forming the hydrogen bonds or conserved in the PPI family. In addition, hDiSNet provides the insights of the FGFR (EGFR)-MAPK pathway for interpreting the mechanisms of breast cancer and ErbB signaling pathway in brain cancer. Conclusions: Our results demonstrate that hDiSNet can explore structural-based interactions insights for understanding the mechanisms of disease-associated proteins and their mutations. We believe that our method is useful to reconstruct structurally resolved PPI networks for interpreting structural genomics and disease associations.
A novel EGFR inhibitor SP101 blocks survivin and tumor growth in the human non-small cell lung carcinoma
(2015-04-01)
Chao, Jui-I
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Wang, Su-Pei
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Wu, Ya-Hui
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Yang, Jinn-Moon
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Chen, Chinpiao
A site-moiety map and virtual screening approach for discovery of novel 5-LOX inhibitors
(2020-06-29)
Hsu, Kai-Cheng
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HuangFu, Wei-Chun
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Lin, Tony Eight
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Chao, Min-Wu
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Sung, Tzu-Ying
The immune system works in conjunction with inflammation. Excessive inflammation underlies various human diseases, such as asthma, diabetes and heart disease. Previous studies found that 5-lipoxygenase (5-LOX) plays a crucial role in metabolizing arachidonic acid into inflammatory mediators and is a potential therapeutic target. In this study, we performed an in silico approach to establish a site-moiety map (SiMMap) to screen for new 5-LOX inhibitors. The map is composed of several anchors that contain key residues, moiety preferences, and their interaction types (i.e., electrostatic (E), hydrogen-bonding (H), and van der Waals (V) interactions) within the catalytic site. In total, we identified one EH, one H, and five V anchors, within the 5-LOX catalytic site. Based on the SiMMap, three 5-LOX inhibitors (YS1, YS2, and YS3) were identified. An enzyme-based assay validated inhibitory activity of YS1, YS2, and YS3 against 5-LOX with an IC50 value of 2.7, 4.2, and 5.3 mu M, respectively. All three inhibitors significantly decrease LPS-induced TNF-alpha and IL-6 production, which suggests its potential use an anti-inflammatory agent. In addition, the identified 5-LOX inhibitors contain a novel scaffold. The discovery of these inhibitors presents an opportunity for designing specific anti-inflammatory drugs.
Alternative splicing in human cancer cells is modulated by the amiloride derivative 3,5-diamino-6-chloro-N-(N-(2,6-dichlorobenzoyl)carbamimidoyl)pyrazine-2-carboxide
(1970-01-01)
Lee, Chien-Chin
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Chang, Wen-Hsin
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Chang, Ya-Sian
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Yang, Jinn-Moon
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Chang, Chih-Shiang
Alternative splicing (AS) is a process that enables the generation of multiple protein isoforms with different biological properties from a single mRNA. Cancer cells often use the maneuverability conferred by AS to produce proteins that contribute to growth and survival. In our previous studies, we identified that amiloride modulates AS in cancer cells. However, the effective concentration of amiloride required to modulate AS is too high for use in cancer treatment. In this study, we used computational algorithms to screen potential amiloride derivatives for their ability to regulate AS in cancer cells. We found that 3,5-diamino-6-chloro-N-(N-(2,6-dichlorobenzoyl)carbamimidoyl)pyrazine-2-carboxamide (BS008) can regulate AS of apoptotic gene transcripts, including HIPK3, SMAC, and BCL-X, at a lower concentration than amiloride. This splicing regulation involved various splicing factors, and it was accompanied by a change in the phosphorylation state of serine/arginine-rich proteins (SR proteins). RNA sequencing was performed to reveal that AS of many other apoptotic gene transcripts, such as AATF, ATM, AIFM1, NFKB1, and API5, was also modulated by BS008. In vivo experiments further indicated that treatment of tumor-bearing mice with BS008 resulted in a marked decrease in tumor size. BS008 also had inhibitory effects in vitro, either alone or in a synergistic combination with the cytotoxic chemotherapeutic agents sorafenib and nilotinib. BS008 enabled sorafenib dose reduction without compromising antitumor activity. These findings suggest that BS008 may possess therapeutic potential for cancer treatment.
An integrated approach with new strategies for QSAR models and lead optimization
(2017-01-01)
Hsu, Hui-Hui
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Hsu, Yen-Chao
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Chang, Li-Jen
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Yang, Jinn-Moon
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生物科技學系
Background: Computational drug design approaches are important for shortening the time and reducing the cost for drug discovery and development. Among these methods, molecular docking and quantitative structure activity relationship (QSAR) play key roles for lead discovery and optimization. Here, we propose an integrated approach with core strategies to identify the protein-ligand hot spots for QSAR models and lead optimization. These core strategies are: 1) to generate both residue-based and atom-based interactions as the features; 2) to identify compound common and specific skeletons; and 3) to infer consensus features for QSAR models. Results: We evaluated our methods and new strategies on building QSAR models of human acetylcholinesterase (huAChE). The leave-one-out cross validation values q(2) and r(2) of our huAChE QSAR model are 0.82 and 0.78, respectively. The experimental results show that the selected features (resides/atoms) are important for enzymatic functions and stabling the protein structure by forming key interactions (e.g., stack forces and hydrogen bonds) between huAChE and its inhibitors. Finally, we applied our methods to arthrobacter globiformis histamine oxidase (AGHO) which is correlated to heart failure and diabetic. Conclusions: Based on our AGHO QSAR model, we identified a new substrate verified by bioassay experiments for AGHO. These results show that our methods and new strategies can yield stable and high accuracy QSAR models. We believe that our methods and strategies are useful for discovering new leads and guiding lead optimization in drug discovery.
An Integrated Genomic Strategy to Identify CHRNB4 as a Diagnostic/Prognostic Biomarker for Targeted Therapy in Head and Neck Cancer
(2020-05-01)
Chuang, Yi-Hsuan
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Lee, Chia-Hwa
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Lin, Chun-Yu
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Liu, Chia-Lin
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Huang, Sing-Han
Although many studies have shown the association between smoking and the increased incidence and adverse prognosis of head and neck squamous cell carcinoma (HNSCC), the mechanisms and pharmaceutical targets involved remain unclear. Here, we integrated gene expression signatures, genetic alterations, and survival analyses to identify prognostic indicators and therapeutic targets for smoking HNSCC patients, and we discovered that the FDA-approved drug varenicline inhibits the target for cancer cell migration/invasion. We first identified 18 smoking-related and prognostic genes for HNSCC by using RNA-Seq and clinical follow-up data. One of these genes, CHRNB4 (neuronal acetylcholine receptor subunit beta-4), increased the risk of death by approximately threefold in CHRNB4-high expression smokers compared to CHRNB4-low expression smokers (log rank, p = 0.00042; hazard ratio, 2.82; 95% CI, 1.55-5.14), former smokers, and non-smokers. Furthermore, we examined the functional enrichment of co-regulated genes of CHRNB4 and its 246 frequently occurring copy number alterations (CNAs). We found that these genes were involved in promoting angiogenesis, resisting cell death, and sustaining proliferation, and contributed to much worse outcomes for CHRNB4-high patients. Finally, we performed CHRNB4 gene editing and drug inhibition assays, and the results validate these observations. In summary, our study suggests that CHRNB4 is a prognostic indicator for smoking HNSCC patients and provides a potential new therapeutic drug to prevent recurrence or distant metastasis.
Anchor-based classification and type-C inhibitors for tyrosine kinases
(2015-06-16)
Hsu, Kai-Cheng
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Sung, Tzu-Ying
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Lin, Chih-Ta
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Chiu, Yi-Yuan
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Hsu, John T. -A.
Tyrosine kinases regulate various biological processes and are drug targets for cancers. At present, the design of selective and anti-resistant inhibitors of kinases is an emergent task. Here, we inferred specific site-moiety maps containing two specific anchors to uncover a new binding pocket in the C-terminal hinge region by docking 4,680 kinase inhibitors into 51 protein kinases, and this finding provides an opportunity for the development of kinase inhibitors with high selectivity and anti-drug resistance. We present an anchor-based classification for tyrosine kinases and discover two type-C inhibitors, namely rosmarinic acid (RA) and EGCG, which occupy two and one specific anchors, respectively, by screening 118,759 natural compounds. Our profiling reveals that RA and EGCG selectively inhibit 3% (EGFR and SYK) and 14% of 64 kinases, respectively. According to the guide of our anchor model, we synthesized three RA derivatives with better potency. These type-C inhibitors are able to maintain activities for drug-resistant EGFR and decrease the invasion ability of breast cancer cells. Our results show that the type-C inhibitors occupying a new pocket are promising for cancer treatments due to their kinase selectivity and anti-drug resistance.
Anti-influenza drug discovery
(2007-07-01)
Hsu, John T.-A.
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Hsieh, Hsing-Pang
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Hung, Hui-Chen
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Ju, Yi Wei
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Tseng, Sung-Nain
Antigenic sites of H1N1 influenza virus hemagglutinin revealed by natural isolates and inhibition assays
(2012-09-28)
Huang, Jhang-Wei
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Lin, Wei-Fan
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Yang, Jinn-Moon
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生物科技學系
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生物資訊及系統生物研究所
The antigenic sites of hemagglutinin (HA) are crucial for understanding antigenic drift and vaccine strain selection for influenza viruses. In 1982,32 epitope residues (called laboratory epitope residues) were proposed for antigenic sites of H1N1 HA based on the monoclonal antibody-selected variants. Interestingly, these laboratory epitope residues only cover 28% (23/83) mutation positions for 9 H1N1 vaccine strain comparisons (from 1977 to 2009). Here, we propose the entropy and likelihood ratio to model amino acid diversity and antigenic variant score for inferring 41 H1N1 HA epitope residues (called natural epitope residues) with statistically significant scores according to 1572 HA sequences and 197 pairs of HA sequences with hemagglutination inhibition (HI) assays of natural isolates. By combining both natural and laboratory epitope residues, we identified 62 (11 overlapped) residues clustered into five antigenic sites (i.e., A-E) which are highly correlated to the antigenic sites of H3N2 HA. Our method recognizes sites A, B and C as critical sites for escaping from neutralizing antibodies in H1N1 virus. Experimental results show that the accuracies of our models are 81.2% and 82.2% using 41 and 62 epitope residues, respectively, for predicting antigenic variants on 197 paring HA sequences. In addition, our model can detect the emergence of epidemic strains and reflect the genetic diversity and antigenic variant between the vaccine and circulating strains. Finally, our model is theoretically consistent with the evolution rates of H3N2 and H1N1 viruses and is often consistent to WHO vaccine strain selections. We believe that our models and the inferred antigenic sites of HA are useful for understanding the antigenic drift and evolution of influenza A H1N1 virus. (C) 2012 Elsevier Ltd. All rights reserved.
ATRIPPI: AN ATOM-RESIDUE PREFERENCE SCORING FUNCTION FOR PROTEIN-PROTEIN INTERACTIONS
(2010-06-01)
Liu, Kang-Ping
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Hsu, Kai-Cheng
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Huang, Jhang-Wei
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Chang, Lu-Shian
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Yang, Jinn-Moon
We present an ATRIPPI model for analyzing protein-protein interactions. This model is a 167-atom-type and residue-specific interaction preferences with distance bins derived from 641 co-crystallized protein-protein interfaces. The ATRIPPI model is able to yield physical meanings of hydrogen bonding, disulfide bonding, electrostatic interactions, van der Waals and aromatic-aromatic interactions. We applied this model to identify the native states and near-native complex structures on 17 bound and 17 unbound complexes from thousands of decoy structures. On average, 77.5% structures (155 structures) of top rank 200 structures are closed to the native structure. These results suggest that the ATRIPPI model is able to keep the advantages of both atom-atom and residue-residue interactions and is a potential knowledge-based scoring function for protein-protein docking methods. We believe that our model is robust and provides biological meanings to support protein-protein interactions.
ATRIPPI: An atom-residue preference scoring function for protein-protein interactions
(2009)
Liu, Kang-Ping
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Chang, Lu-Shian
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Yang, Jinn-Moon
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生物科技學系
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Department of Biological Science and Technology
We present an ATRIPPI model for analyzing protein-protein interactions. This model is a 167-atom-type and residue-specific interaction preferences with distance bins derived from 641 co-crystallized protein-protein interfaces. The ATRIPPI model is able to yield physical meanings of hydrogen bonding, disulfide bonding, electrostatic interactions, van der Wools and aromatic-aromatic interactions. We applied this model to identify the native states and near-native complex structures on 17 bound and 17 unbound complexes from thousands of decoy structures. On average, 77.5% structures (155 structures) of top rank 200 structures are closed to the native structure. These results suggest that the ATRIPPI model is able to keep the advantages of both atom-atom and residue-residue interactions and is a potential knowledge-based scoring function for protein-protein docking methods. We believe that our model is robust and provides biological meanings to support protein-protein interactions.
Aurintricarboxylic acid inhibits influenza virus neuraminidase
(2009-02-01)
Hung, Hui-Chen
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Tseng, Ching-Ping
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Yang, Jinn-Moon
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Ju, Yi-Wei
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Tseng, Sung-Nain
There is a continuing threat that the highly pathogenic avian influenza virus will cause future influenza pandemics. In this study, we screened a library of compounds that are biologically active and structurally diverse for inhibitory activity against influenza neuraminidase (NA). We found that aurintricarboxylic acid (ATA) is a potent inhibitor of NA activity of both group-1 and group-2 influenza viruses with IC(50)S (effective concentration to inhibit NA activity by 50%) values at low micromolar concentrations. ATA was equally potent in inhibiting the NA activity derived from wild-type NA and its H274Y mutant which renders NA resistance to inhibition by oseltamivir. Although ATA is structurally distinct from sialic acid, molecular modeling experiments suggested that ATA binds to NA at the enzyme's substrate binding site. These results indicate that ATA may be a good starting material for the design of a novel class of NA inhibitors for the treatment influenza viruses. (C) 2008 Elsevier B.V. All rights reserved.
Boolean function network analysis of time course liver transcriptome data to reveal novel circadian transcriptional regulators in mammals
(2019-11-01)
Simak, Maria
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Lu, Henry Horng-Shing
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Yang, Jinn-Moon
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生物資訊及系統生物研究所
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統計學研究所
Background: Many biological processes in mammals are subject to circadian control at the molecular level. Disruption of circadian rhythms has been demonstrated to be associated with a wide range of diseases, such as diabetes mellitus, mental disorders, and cancer. Although the core circadian genes are well established, there are multiple reports of novel peripheral circadian regulators. The goal of this study was to provide a comprehensive computational analysis to identify novel potential circadian transcriptional regulators. Methods: To fulfill the aforementioned goal, we applied a Boolean function network method to analyze the microarray time course mouse and rat liver datasets available in the literature. The inferred direct pairwise relations were further investigated using the functional annotation tool. This approach generated a list of transcription factors (TFs) and cofactors, which were associated with significantly enriched circadian gene ontology (GO) categories. Results: As a result, we identified 93 transcriptional circadian regulators in mouse and 95 transcriptional circadian regulators in rat. Of these, 19 regulators in mouse and 21 regulators in rat were known, whereas the rest were novel. Furthermore, we validated novel circadian TFs with bioinformatics databases, previous large-scale circadian studies, and related small-scale studies. Moreover, according to predictions inferred from ChIP-Seq experiments reported in the database, 40 of our candidate circadian regulators were confirmed to have circadian genes as direct regulatory targets. In addition, we annotated candidate circadian regulators with disorders that were often associated with disruptions of circadian rhythm in the literature. Conclusion: In summary, our computational analysis, which was followed by an extensive verification by means of a literature review, can contribute to translational study from endocrinology to cancer research and provide insights for future investigation.
CAPIH: A Web interface for comparative analyses and visualization of host-HIV protein-protein interactions
(2009-08-12)
Lin, Fan-Kai
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Pan, Chia-Lin
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Yang, Jinn-Moon
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Chuang, Trees-Juen
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Chen, Feng-Chi
Background: The Human Immunodeficiency Virus type one (HIV-1) is the major causing pathogen of the Acquired Immune Deficiency Syndrome (AIDS). A large number of HIV-1-related studies are based on three non-human model animals: chimpanzee, rhesus macaque, and mouse. However, the differences in host-HIV-1 interactions between human and these model organisms have remained unexplored. Description: Here we present CAPIH (Comparative Analysis of Protein Interactions for HIV-1), the first web-based interface to provide comparative information between human and the three model organisms in the context of host-HIV-1 protein interactions. CAPIH identifies genetic changes that occur in HIV-1-interacting host proteins. In a total of 1,370 orthologous protein sets, CAPIH identifies similar to 86,000 amino acid substitutions, similar to 21,000 insertions/deletions, and similar to 33,000 potential post-translational modifications that occur only in one of the four compared species. CAPIH also provides an interactive interface to display the host-HIV-1 protein interaction networks, the presence/absence of orthologous proteins in the model organisms in the networks, the genetic changes that occur in the protein nodes, and the functional domains and potential protein interaction hot sites that may be affected by the genetic changes. The CAPIH interface is freely accessible at http://bioinfo-dbb.nhri.org.tw/capih. Conclusion: CAPIH exemplifies that large divergences exist in disease-associated proteins between human and the model animals. Since all of the newly developed medications must be tested in model animals before entering clinical trials, it is advisable that comparative analyses be performed to ensure proper translations of animal-based studies. In the case of AIDS, the host-IV-1 protein interactions apparently have differed to a great extent among the compared species. An integrated protein network comparison among the four species will probably shed new lights on AIDS studies.