title: Potential for protein surface shape analysis using spherical harmonics and 3D Zernike descriptors.
abstract: With structure databases expanding at a rapid rate, the task at hand is to provide reliable clues to their molecular function and to be able to do so on a large scale. This, however, requires suitable encodings of the molecular structure which are amenable to fast screening. To this end, moment-based representations provide a compact and nonredundant description of molecular shape and other associated properties. In this article, we present an overview of some commonly used representations with specific focus on two schemes namely spherical harmonics and their extension, the 3D Zernike descriptors. Key features and differences of the two are reviewed and selected applications are highlighted. We further discuss recent advances covering aspects of shape and property-based comparison at both global and local levels and demonstrate their applicability through some of our studies.
authors.affiliation: Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.
authors.forename: Vishwesh
authors.initials: V
authors.lastname: Venkatraman
authors.forename: Lee
authors.initials: L
authors.lastname: Sael
authors.forename: Daisuke
authors.initials: D
authors.lastname: Kihara
mesh_terms: D001665:Binding Sites; D003198:Computer Simulation; D030562:Databases, Protein; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D012984:Software; D013499:Surface Properties
chemical_list: D011506:Proteins