Browsing by Author "Chiu, HC"

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A site-based method for prediction of protein orthologous relations
(2004)
Chiu, HC
;
Hu, YJ
;
資訊工程學系
;
Department of Computer Science
Making accurate functional predictions for genes plays an important role in the era of proteomics. The most reliable functional information is extracted from orthologs in other species when annotating an unknown gene. Here a site-based approach is proposed to predict orthologous relations. The method first identifies important sites that confer specificity of paralogs in the multiple sequence alignment of homologous proteins. It then predicts orthologous relations for unannotated proteins based on the important sites found. When applied to the bacterial transcription factor PurR/LacI family and the protein kinase AGC family, our method was able to identify, with few false positives, the important sites that agree with those obtained from biological experiments. We also tested it on the AGC family, the a proteasome family, the glycoprotein hormone family and the growth hormone family to demonstrate its ability to predict orthologs. Compared with other prediction methods based on phylogenetic analysis or hidden Markov models, our method not only has competitive predictive accuracy, but also provides valuable biological information of important sites associated with orthologs which can be further studied in biological experiments.
Prediction of orthologous relationship by functionally important sites
(2005-06-01)
Chiu, HC
;
Chang, CA
;
Hu, YJ
;
生物科技學系
;
資訊工程學系
Making accurate functional predictions plays an important role in the era of proteomics. Reliable functional information can be extracted from orthologs in other species when annotating an unknown gene. Here a site-based approach called PORFIS is proposed to predict orthologous relationship. When applied to the bacterial. transcription factor PurR/Lacl family and the protein kinase AGC family, our method was able to identify, with few false positives, the important sites that agree with those verified by biological experiments. We also tested it on the alpha-proteasome family, the glycoprotein hormone family and the growth hormone family to demonstrate its ability to predict orthologous relationship. Compared with other prediction methods based on phylogenetic analysis or hidden Markov models, PORFIS not only has competitive prediction accuracy, but also provides valuable biological information of functionally important sites associated with orthologs which can be further studied in biological experiments. (c) 2005 Elsevier Ireland Ltd. All rights reserved.
Synthesis of dextran-(5-FU)-galactosamine conjugate through a tripeptide spacer group and its in vitro properties
(2000-07-01)
Guu, JA
;
Juang, TM
;
Hsiue, GH
;
Chiu, HC
;
應用化學系
In this study, conjugation of 5-fluorouracil (5-FU) and galactosamine with dextran via Glycyl-L-Leucyl-Glycine (Gly-Leu-Gly) tripeptidyl spacer was performed first by activation of dextran with p-nitrophenyl chloroformate, followed by aminolysis of Glycyl-L-Leucyl-Glycyl-5flurouracil (Gly-Leu-Gly-5-FU) and galactosamine with activated dextrans. Preparation of Gly-Leu-Gly-5-FU was carried out by sequential reactions of peptide synthesis in solution phases and coupling with 5-FU in the presence of diethylphosphoric cyanide. The release of 5-FU from the conjugates upon the exposure of polymeric prodrugs to papain implied that the attachment of 5-FU with the tripeptidyl spacer, Gly-Leu-Gly, was capable of being liberated by cathepsin B in lysosomes of targeted cells. The observation that the cytoxicity in vitro from the incubation of dextran-5-FU conjugate containing galactosamine residues with Hep-3B cells is higher than that in the void of galactosamine indicated the occurrence of specific binding of the targeting moieties with its receptors on cell membrane, leading to an enhanced cellular uptake of the conjugate via receptor-mediated endocytosis.
Using functionally important sites to identify orthologous relations
(2003)
Chiu, HC
;
Hu, YJ
;
資訊工程學系
;
Department of Computer Science
Making accurate functional predictions for genes plays an important role in the era of proteomics. The most reliable functional information is extracted from orthologs in other species when annotating an unknown gene. Here a site-based approach is proposed to predict orthologous relations. The method first identifies important sites that confer specificity of paralogs in the multiple sequence alignment of homologous proteins. It then predicts orthologous relations for unannotated proteins based on the important sites found. When applied to the bacterial transcription factor PurR/LacI family and the protein kinase AGC group family, our method was able to identify with few false positives; the important sites that agree with those obtained from biological experiments. We also tested it on the AGC group family, the alpha-proteasome family, the glycoprotein hormone family and the growth hormone family to demonstrate its ability to predict orthologs. Compared with other prediction methods based on phylogenetic analysis or hidden Markov models, our method not only has competitive prediction accuracy, but also provides valuable biological information of important sites associated with orthologs which can be further studied in biological experiments.