Ion Channel Biology Laboratory, AU-KBC Research Centre, Madras Institute of Technology, Anna University, Chromepet, Chennai, Tamil Nadu, 600 044, India.
Protein J. 2018 Jun;37(3):237-247. doi: 10.1007/s10930-018-9773-y.
In Oryza sativa (rice) there are seven members in the NRAMP (natural resistance- associated macrophage protein) family of transporter proteins. They have been identified as OsNRAMP1, OsNRAMP2, OsNRAMP3, OsNRAMP4, OsNRAMP5, OsNRAMP6 and OsNRAMP7. Several metal ions like Zn, Mn, Fe, Cd etc. have been studied to be transported via NRAMP transporter proteins in rice plant. In spite of this, very little information is available regarding these transporters. Hence it is important to computationally predict and characterize the OsNRAMP family of transporters for studying and understanding their molecular insights in future studies. For this purpose, various in silico methods and tools were used for the characterization of OsNRAMP family of transporter proteins. Physico-chemical properties of the protein sequences were calculated, putative transmembrane domains (TMDs) and conserved motif signatures were determined and their interaction partners were predicted. 3D models of all the members of OsNRAMP transporters were generated using online structure prediction tool followed by their analysis. In silico microarray analysis was done to understand the expression pattern of these transporters in rice plant. Currently, only limited knowledge is available about the structural and functional aspects of these transporters, hence this study would provide more theoretical information about them.
在水稻（Oryza sativa）中，天然抗性相关巨噬细胞蛋白（NRAMP）家族的转运蛋白有七个成员。它们被鉴定为 OsNRAMP1、OsNRAMP2、OsNRAMP3、OsNRAMP4、OsNRAMP5、OsNRAMP6 和 OsNRAMP7。已经研究了几种金属离子，如 Zn、Mn、Fe、Cd 等，通过水稻植物中的 NRAMP 转运蛋白进行运输。尽管如此，关于这些转运蛋白的信息仍然很少。因此，对 OsNRAMP 家族的转运蛋白进行计算预测和特征分析对于未来的研究了解它们的分子机制非常重要。为此，使用了各种计算方法和工具来对 OsNRAMP 家族的转运蛋白进行特征分析。计算了蛋白序列的理化性质，确定了推定的跨膜结构域（TMD）和保守的基序特征，并预测了它们的相互作用伙伴。使用在线结构预测工具生成了所有 OsNRAMP 转运蛋白成员的 3D 模型，并对其进行了分析。通过计算微阵列分析了解了这些转运蛋白在水稻中的表达模式。目前，关于这些转运蛋白的结构和功能方面的知识还很有限，因此这项研究将为它们提供更多的理论信息。
