Yueh-Lin Tsai, Hsin-Wei Wang, Tun-Wen Pai, Wen-Shyong Tzou, and Margaret Dah-Tsyr Chang
Flexible conformation, surface comparison, deformation invariant, geodesic distance, local shape descriptor
Protein functions are highly correlated to structural conformation of biomolecular components, and especially some specific functions of proteins would be evoked by deforming the surface conformation to interact with other proteins. It is therefore important to identify the similarity and congruence between the original protein surface and its deformed conformation. Most existing comparison methods treat protein structures as rigid bodies. Though these approaches possessed translation and rotation invariant characteristics, the deformation problems could not be solved by conventional methods. To solve these problems, we proposed two local shape descriptors based on geodesic distances with deformation invariant characteristics. The first descriptor is the Linear Geodesic Vector (LGV) obtained by taking average geodesic distance among the target residue and its sequentially neighbouring residues, and the second descriptor is the Conformational Geodesic Adjacency Matrix (CGAM) formulated by preserving the geodesic distances among the target residue and its surface neighbouring residues within a specified radius. Each vector or matrix represents corresponding local shape characteristics of a protein surface and it can be adopted as a shape profile for efficient protein surface comparison. Correlation coefficients are computed for the evaluation of surface similarity between two protein surfaces. In this paper, we collected 36 bound/unbound antigens and domain swapping proteins to evaluate the performance of protein surface comparison on deformed proteins. The results have shown that the deformed proteins could be correctly identified with an average rank of 1.05, and the proposed methods can handle the phenomena of self-connection on surface caused by large topological changes.
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