Gelfand I, Kister A, Kulikowski C, Stoyanov O
Department of Mathematics, Rutgers University, New Brunswick, NJ 08903, USA.
Protein Eng. 1998 Nov;11(11):1015-25. doi: 10.1093/protein/11.11.1015.
A new algorithmic method for identifying a geometric invariant of protein structures, termed geometrical core, is developed. The method used the matrix of C(alpha)-C(alpha) distances and does not require the usual superposition of structures. The result of applying the algorithm to 53 immunoglobulin structures led to the identification of two geometrical core sets of C(alpha) atoms positions for the V(L) and V(H) domains. Based on these geometric invariants a preferred coordinate system for the immunoglobulin family is constructed which serves as a basis for structural prediction. The X-ray atom coordinates for all available immunoglobulin structures are transformed to the preferred coordinate system. An affine symmetry between the V(L) and V(H) domains is defined and computed for each of the 53 immunoglobulin structures.
开发了一种用于识别蛋白质结构几何不变量的新算法方法，称为几何核心。该方法使用Cα-Cα距离矩阵，不需要通常的结构叠加。将该算法应用于53个免疫球蛋白结构的结果，导致识别出V(L)和V(H)结构域的两个Cα原子位置的几何核心集。基于这些几何不变量，构建了免疫球蛋白家族的优选坐标系，作为结构预测的基础。所有可用免疫球蛋白结构的X射线原子坐标都被转换到优选坐标系。为53个免疫球蛋白结构中的每一个定义并计算了V(L)和V(H)结构域之间的仿射对称性。
