首页> 外文会议>International symposium on bioinformatics research and applications >Conservation and Network Analysis of the (4β+α) Fold of the Immunoglobulin-Binding Bl Domain of Protein G to Elucidate the Key Determinants of Structure, Folding and Stability
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Conservation and Network Analysis of the (4β+α) Fold of the Immunoglobulin-Binding Bl Domain of Protein G to Elucidate the Key Determinants of Structure, Folding and Stability

机译:蛋白质G的免疫球蛋白结合Bl结构域的(4β+α)折叠的保守性和网络分析,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. 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. 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.
机译:通过限制构象空间,蛋白质从变性状态的集合中折叠以形成初始的天然样拓扑,然后进一步稳定二级和三级相互作用。据信,最初的天然样拓扑结构的形成是由进化上保守的氨基酸组指导的。残基通常在蛋白质的超家族中是保守的,因为它们会产生关键的相互作用,而这些相互作用对于保持共同的折叠更为重要。这可能导致残基在疏水核中聚集在一起,从而稳定了初始的类似自然的拓扑结构。这种保守氨基酸网络一直是计算和实验研究的目标,该研究旨在研究保守氨基酸之间的联系以及它们如何促进蛋白质快速正确地折叠成天然状态。使用生物信息学方法,我们可以确定和评估哪些氨基酸在蛋白质折叠中是保守的。这种类型的分析对于理解蛋白质的三级结构非常有用,并且非常重要,当得到实验数据的支持时,它的功能将大大增强。网络科学的应用在蛋白质结构和折叠研究中也变得很重要。

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