首页> 外文会议>ISBRA 2013 >Conservation and Network Analysis of the (4beta+alpha) Fold of the Immunoglobulin-Binding B1 Domain of Protein G to Elucidate the Key Determinants of Structure, Folding and Stability
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Conservation and Network Analysis of the (4beta+alpha) Fold of the Immunoglobulin-Binding B1 Domain of Protein G to Elucidate the Key Determinants of Structure, Folding and Stability

机译:蛋白G免疫球蛋白结合B1结构域的(4Beta +α)折叠的保护和网络分析,以阐明结构,折叠和稳定性的关键决定因素

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Proteins fold from an ensemble of denatured states by a restriction of conformational space to form the initial native-like topology followed by further stabilizing secondary and tertiary interactions. It is believed that the formation of the initial native-like topology is guided by an evolutionarily conserved set of amino acids. Residues are typically conserved in a superfamily of proteins because they make critical interactions that are more important in maintaining the common fold. This could lead to residues clustering together in a hydrophobic core to stabilize the initial native-like topology [1,2]. This network of conserved amino acids has been the target of computational and experimental research which seeks to investigate the link between conserved amino acids and how they facilitate rapid and correct folding of a protein into its native state [3, 4, 5]. Using bioinformatics approaches we can determine and assess which amino acids are conserved for the fold of a protein. This type of analysis is highly useful and important in understanding the tertiary structure of proteins and becomes significantly more powerful when supported with experimental data. The application of network science has also become important in the study of protein structure and folding [2, 3, 6, 7, 8, 9].
机译:通过限制构象空间来形成变性状态的蛋白质,以形成初始天然样拓扑,然后进一步稳定二次和叔相互作用。据信初始天然拓扑的形成是由进化保守的氨基酸引导的。残留物通常在蛋白质的超家族中保守,因为它们在保持共同折叠方面具有更重要的关键相互作用。这可能导致疏水芯中的残留物聚集在一起,以稳定初始天然样拓扑[1,2]。该保守氨基酸网络一直是计算和实验研究的目标,寻求研究保守氨基酸之间的联系以及它们如何促进蛋白质的快速和正确折叠到其天然状态[3,4,5]。使用生物信息学方法,我们可以确定和评估哪些氨基酸被保守用于蛋白质的折叠。这种类型的分析非常有用,在理解蛋白质的三级结构并且在用实验数据支持时变得明显更强大。网络科学的应用在蛋白质结构和折叠的研究中也变得重要[2,3,6,7,8,9]。

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