中国科技论文在线

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2010年07月28日

【期刊论文】Proteomics Characterization of the Cytotoxicity Mechanism of Ganoderic Acid D and Computer-automated Estimation of the Possible Drug Target Network*

曹志伟， Qing-Xi Yue‡§， Zhi-Wei Cao§¶， Shu-Hong Guan‡， Xiao-Hui Liu， Lin Tao¶， Wan-Ying Wu‡， Yi-Xue Li¶， Peng-Yuan Yang， Xuan Liu‡**， and De-An Guo‡ ‡‡

，-0001，（）：

-1年11月30日

摘要

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2010年07月28日

【期刊论文】Computer prediction of drug resistance mutations in proteins

曹志伟， Zhi Wei Cao， Lian Yi Han， Chan Juan Zheng， Zhi Lang Ji， Xin Chen， Hong Huang Lin and Yu Zong Chen

DDT • Volume 10, Number 7 • April 2005，-0001，（）：

-1年11月30日

摘要

Drug resistance is of increasing concern in the treatment of infectious diseases and cancer. Mutation in drug-interacting disease proteins is one of the primary causes for resistance particularly against anti-infectious drugs. Prediction of resistance mutations in these proteins is valuable both for the molecular dissection of drug resistance mechanisms and for predicting features that guide the design of new agents to counter resistant strains. Several protein structure-and sequence-based computer methods have been explored for mechanistic study and prediction of resistance mutations. These methods and their usefulness are reviewed here.

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2010年07月28日

【期刊论文】Structure modeling and spatial epitope analysis for HA protein of the novel H1N1 influenza virus

曹志伟， Consortium for Influenza Study at Shanghai (WU Di，， XU TianLei， SUN Jing， DAI JianXin， DING GuoHui， HE YunGang， ZHOU ZhengFeng， XIONG Hui， DONG Hui， JIN WeiRong， BIAN Chao， JIN Li， WANG HongYan， WANG XiaoNing， YANG Zhong， ZHONG Yang， WANG Hao， CHE XiaoYan， HUANG Zhong， LAN Ke， SUN Bing， WU Fan， YUAN ZhenAn， ZHANG Xi， ZHOU XiaoNong， ZHOU JiaHai， MA ZhiYong， TONG GuangZhi， GUO YaJun， ZHAO GuoPing， †， LI YiXue， † & CAO ZhiWei， †)

Consortium for Influenza Study at Shanghai. Chinese Science Bulletin | July 2009 | vol. 54 | no. 13，-0001，（）：

-1年11月30日

摘要

In recent months, a novel influenza virus H1N1 broke out around the world. With bioinformatics technology, the 3D structure of HA protein was obtained, and the epitope residues were predicted with the method developed in our group for this novel flu virus. 58 amino acids were identified as potential epitope residues, the majority of which clustered at the surface of the globular head of HA protein. Although it is located at the similar position, the epitope of HA protein for the novel H1N1 flu virus has obvious differences in the electrostatic potential compared to that of HA proteins from previous flu viruses.

novel H1N1 influenza virus,， HA protein,， spatial epitope,， bioinformatics

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2010年07月28日

【期刊论文】Reconstruction and Analysis of Human Liver-Specific Metabolic Network Based on CNHLPP Data

曹志伟， Jing Zhao， †， #， ⊥ Chao Geng， § Lin Tao， † Duanfeng Zhang， ‡ Ying Jiang， § Kailin Tang， † Ruixin Zhu， ‡ Hong Yu， † Weidong Zhang， # Fuchu He， *， § Yixue Li， | and Zhiwei Cao*， ‡， ♦

1648 Journal of Proteome Research 2010, 9, 1648-1658，-0001，（）：

-1年11月30日

摘要

Liver is the largest internal organ in the body that takes central roles in metabolic homeostasis, detoxification of various substances, as well as in the synthesis and storage of nutrients. To fulfill these complex tasks, thousands of biochemical reactions are going on in liver to cope with a wide range of foods and environmental variations, which are densely interconnected into an intricate metabolic network. Here, the first human liver-specific metabolic network was reconstructed according to proteomics data from Chinese Human Liver Proteome Project (CNHLPP), and then investigated in the context of the genome-scale metabolic network of Homo sapiens. Topological analysis shows that this organ-specific metabolic network exhibits similar features as organism-specific networks, such as power-law degree distribution, small-world property, and bow-tie structure. Furthermore, the structure of liver network exhibits a modular organization where the modules are formed around precursors from primary metabolism or hub metabolites from derivative metabolism, respectively. Most of the modules are dominated by one major category of metabolisms, while enzymes within same modules have a tendency of being expressed concertedly at protein level. Network decomposition and comparison suggest that the liver network overlays a predominant area in the global metabolic network of H. sapiens genome; meanwhile the human network may develop extra modules to gain more specialized functionality out of liver. The results of this study would permit a high-level interpretation of the metabolite information flow in human liver and provide a basis for modeling the physiological and pathological metabolic states of liver.

Metabolic network • Human Liver Proteome Project • Network reconstruction • Network topology • Network modularity

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