Saberi Fathi S M
Department of Physics, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran.
J Biol Phys. 2016 Oct;42(4):621-636. doi: 10.1007/s10867-016-9429-0. Epub 2016 Sep 13.
Knowledge regarding the 3D structure of a protein provides useful information about the protein's functional properties. Particularly, structural similarity between proteins can be used as a good predictor of functional similarity. One method that uses the 3D geometrical structure of proteins in order to compare them is the similarity value (SV). In this paper, we introduce a new definition of the SV measure for comparing two proteins. To this end, we consider the mass of the protein's atoms and concentrate on the number of protein's atoms to be compared. This defines a new measure, called the weighted similarity value (WSV), adding physical properties to geometrical properties. We also show that our results are in good agreement with the results obtained by TM-SCORE and DALILITE. WSV can be of use in protein classification and in drug discovery.
关于蛋白质三维结构的知识为蛋白质的功能特性提供了有用信息。特别是，蛋白质之间的结构相似性可作为功能相似性的良好预测指标。一种利用蛋白质三维几何结构进行比较的方法是相似性值（SV）。在本文中，我们引入了一种用于比较两种蛋白质的SV测量的新定义。为此，我们考虑蛋白质原子的质量，并专注于要比较的蛋白质原子数量。这定义了一种新的测量方法，称为加权相似性值（WSV），它将物理性质添加到几何性质中。我们还表明，我们的结果与通过TM-SCORE和DALILITE获得的结果高度一致。WSV可用于蛋白质分类和药物发现。
