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Prediction of protein active and/or binding site using time-frequency analysis: Application to ras oncogene proteins

机译:使用时频分析预测蛋白质活性和/或结合位点:在Ras癌基因蛋白的应用

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Cancer cells contain genetic damage that can lead to tumorigenesis. Genetic damage found in cancer cells is of two types: dominant and the genes are termed proto-oncogenes; and recessive and the genes are termed tumor or growth suppressors, recessive oncogenes or anti-oncogenes. Oncogene proteins are a specific group of growth factors that promotes uncontrolled cell growth and proliferation. These proteins are derived from normal proto-oncogenes via a limited number of modifications, i.e mutations, insertions or deletions. Because proto-oncogenes control the cell cycle, it is obvious that should a proto-oncogene be mutated the potential for an unregulated cell cycle results. Therefore, a structure-function analysis of oncogene proteins is of great importance in understanding cell transformation that causes cancer development. In this paper we present and discuss the use of two related computational techniques for analysis of ras oncongene protein example. We showed that the methods are efficient for accurate prediction of the protein active/binding site locations critical for its bioactivity, i.e. cell transformation.
机译:癌细胞含有可能导致肿瘤鉴定的遗传损伤。癌细胞中发现的遗传破坏是两种类型的:显性和基因被称为原型癌症;并且隐性和基因被称为肿瘤或生长抑制剂,隐性癌基因或抗癌变。癌基因蛋白是促进不受控制的细胞生长和增殖的特定生长因子组。这些蛋白质通过有限数量的修饰,即突变,插入或缺失来源于正常的原型癌基因。由于原癌基因控制细胞周期,因此显然,如果原癌基因应该突变未调节的细胞周期结果的可能性。因此,癌基因蛋白的结构函数分析对于了解导致癌症发展的细胞转化非常重要。在本文中,我们展示并探讨了两种相关计算技术的使用,以分析Ras Oncongene蛋白实例。我们表明,该方法对于精确预测其对其生物活性至关重要的蛋白质活性/结合位点位置的准确预测,即细胞转化。

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