Rabbit Anti-Human CASP5 (a.a. 261-360) Polyclonal antibody

Objectives: The efficacy of gene overexpression of CASP5, a caspase family member, in angiogenesis in vitro and its mechanisms were clarified. Methods: Human full-length CASP5 gene was delivered into human microvascular endothelial HMEC-1 cells by recombinant lentivirus. The infection was estimated by green fluorescent protein. MTT method was used to analyze the efficacy of gene overexpression in cell proliferation ability, and Matrigel was used to estimate its effects in angiogenesis ability of cells. Meanwhile, Western blot was used to analyze the effects of CASP5 gene overexpression on the expression levels of angpt-1, angpt-2, Tie2 and VEGF-1 in the cells, which were signaling pathway factors related to angiogenesis. Results: Recombinant lentivirus containing human full-length CASP5 gene was packed and purified successfully, with virus titer of 1x10(8) TU/ml. The recombinant lentivirus was used to infect HMEC-1 cells with MOI of 1, leading to a cell infection rate of 100%. There were no significant effects of CASP5 gene overexpression on both cell proliferation ability and the expression level of angpt-1. Meanwhile, expressions of angpt-2 and VEGF-1 were both enhanced, while Tie2 expression was inhibited. Results indicated that CASP5 gene overexpression promoted angiogenesis of HMEC-1 cells. Conclusion: CASP5 gene overexpression significantly promoted angiogenesis ability of HMEC-1 cells, which was probably achieved by inhibiting angpt-1/Tie2 and promoting VEGF-1 signal pathway.

A novel method for predicting the secondary structures of proteins from amino acid sequence has been presented. The protein secondary structure seqlets that are analogous to the words in natural language have been extracted. These seqlets will capture the relationship between amino acid sequence and the secondary structures of proteins and further form the protein secondary structure dictionary. To be elaborate, the dictionary is organism-specific. Protein secondary structure prediction is formulated as an integrated word segmentation and part of speech tagging problem. The word-lattice is used to represent the results of the word segmentation and the maximum entropy model is used to calculate the probability of a seqlet tagged as a certain secondary structure type. The method is markovian in the seqlets, permitting efficient exact calculation of the posterior probability distribution over all possible word segmentations and their tags by viterbi algorithm. The optimal segmentations and their tags are computed as the results of protein secondary structure prediction. The method is applied to predict the secondary structures of proteins of four organisms respectively and compared with the PHD method. The results show that the performance of this method is higher than that of PHD by about 3.9% Q(3) accuracy and 4.6% SOV accuracy. Combining with the local similarity protein sequences that are obtained by BLAST can give better prediction. The method is also tested on the 50 CASP5 target proteins with Q(3) accuracy 78.9% and SOV accuracy 77.1%. A web server for protein secondary structure prediction has been constructed which is available at http://www.insun.hit.edu.cn:81/demos/biology/index.html.