Mishra Hrishikesh, Lahiri Tapobrata
Division of Applied Science and Indo-Russian Center for Biotechnology, Indian Institute of Information Technology, Allahabad, India.
Bioinformation. 2011 May 7;6(4):158-61. doi: 10.6026/97320630006158.
Current work targeted to predicate parametric relationship between aggregate and individual property of a protein. In this approach, we considered individual property of a protein as its Surface Roughness Index (SRI) which was shown to have potential to classify SCOP protein families. The bulk property was however considered as Intensity Level based Multi-fractal Dimension (ILMFD) of ordinary microscopic images of heat denatured protein aggregates which was known to have potential to serve as protein marker. The protocol used multiple ILMFD inputs obtained for a protein to produce a set of mapped outputs as possible SRI candidates. The outputs were further clustered and largest cluster centre after normalization was found to be a close approximation of expected SRI that was calculated from known PDB structure. The outcome showed that faster derivation of individual protein's surface property might be possible using its bulk form, heat denatured aggregates.
当前的工作旨在预测蛋白质的聚集性质与个体性质之间的参数关系。在这种方法中，我们将蛋白质的个体性质视为其表面粗糙度指数（SRI），该指数已被证明具有对SCOP蛋白质家族进行分类的潜力。然而，整体性质被视为热变性蛋白质聚集体普通显微镜图像的基于强度水平的多重分形维数（ILMFD），已知其具有作为蛋白质标记物的潜力。该方案使用为一种蛋白质获得的多个ILMFD输入来生成一组映射输出作为可能的SRI候选值。输出进一步聚类，归一化后最大的聚类中心被发现是根据已知PDB结构计算出的预期SRI的近似值。结果表明，使用其整体形式，即热变性聚集体，可能更快地推导单个蛋白质的表面性质。
