单核苷酸多态性（SNP）对人类红细胞代谢影响的计算机模型驱动评估。
In silico model-driven assessment of the effects of single nucleotide polymorphisms (SNPs) on human red blood cell metabolism.
作者信息
Jamshidi Neema, Wiback Sharon J, Palsson B Bernhard Ø
机构信息
Department of Bioengineering, University of California-San Diego, La Jolla, California 92093-0412, USA.
出版信息
Genome Res. 2002 Nov;12(11):1687-92. doi: 10.1101/gr.329302.
The completion of the human genome project and the construction of single nucleotide polymorphism (SNP) maps have lead to significant efforts to find SNPs that can be linked to pathophysiology. In silico models of complete biochemical reaction networks relate a cell's individual reactions to the function of the entire network. Sequence variations can in turn be related to kinetic properties of individual enzymes, thus allowing an in silico model-driven assessment of the effects of defined SNPs on overall cellular functions. This process is applied to defined SNPs in two key enzymes of human red blood cell metabolism: glucose-6-phosphate dehydrogenase and pyruvate kinase. The results demonstrate the utility of in silico models in providing insight into differences between red cell function in patients with chronic and nonchronic anemia. In silico models of complex cellular processes are thus likely to aid in defining and understanding key SNPs in human pathophysiology.
人类基因组计划的完成以及单核苷酸多态性（SNP）图谱的构建，促使人们做出巨大努力去寻找与病理生理学相关的SNP。完整生化反应网络的计算机模拟模型将细胞的个体反应与整个网络的功能联系起来。序列变异进而可能与个体酶的动力学特性相关，从而能够基于计算机模拟模型评估特定SNP对整体细胞功能的影响。这一过程应用于人类红细胞代谢的两种关键酶中的特定SNP：葡萄糖-6-磷酸脱氢酶和丙酮酸激酶。结果表明，计算机模拟模型有助于深入了解慢性和非慢性贫血患者红细胞功能的差异。因此，复杂细胞过程的计算机模拟模型可能有助于定义和理解人类病理生理学中的关键SNP。
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