Molecular Surface Representation Using 3D Zernike Descriptors for Protein Shape Comparison and Docking

Abstract

The tertiary structures of proteins have been solved in an increasing pace in recent years. To capitalize the enormous efforts paid for accumulating the structure data, efficient and effective computational methods need to be developed for comparing, searching, and investigating interactions of protein structures. We introduce the 3D Zernike descriptor (3DZD), an emerging technique to describe molecular surfaces. The 3DZD is a series expansion of mathematical three-dimensional function, and thus a tertiary structure is represented compactly by a vector of coefficients of terms in the series. A strong advantage of the 3DZD is that it is invariant to rotation of target object to be represented. These two characteristics of the 3DZD allow rapid comparison of surface shapes, which is sufficient for real-time structure database screening. In this article, we review various applications of the 3DZD, which have been recently proposed.

A Comparative Study of 2D UMI and 3D Zernike Shape Descriptor for ATS Drugs Identification

“…Many molecular descriptors have been proposed; they are derived from different theories and approaches with the aim of predicting biological and physicochemical properties of molecules, such as 3D Zernike descriptors [20,21], shape impact descriptor [22], local intersection volume [23], and path-space ratio [24].…”

Preparation of Translated, Scaled, and Rotated ATS Drugs 3D Molecular Structure for the Validation of 3D Moment Invariants-based Molecular Descriptors

“…MI is a special case of Moments, which is a scalar quantities used to characterize a function and to capture its crucial features [42]. The first application of MI to represent molecular structure is 3D Zernike descriptors [43]. Although it was introduced to represent the molecular surface of protein structure, it provides an adequate motivation for further exploration of engaging MI as a numerical representation of molecule in the computer system, whether it is for molecular structure or for molecular surface.…”

“…Second, due to its rotation and translation invariance properties, molecular structures need not be aligned for comparison. Lastly, the resolution of the description of molecular structures can be easily and naturally adjusted by changing the order of shape descriptors [43,44].…”

A new definition and properties of the similarity value between two protein structures

“…In sequence similarity, a technique called homology modeling is used based on the structure of a known protein as a template to predict the structure of an unknown protein [3]. If structural information of the protein exists, there are methods that have been developed to compare the structures [4][5][6][7][8][9][10][11][12][13].…”