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Potential for Protein Surface Shape Analysis Using Spherical Harmonics and 3D Zernike Descriptors

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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.

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Acknowledgments

This work is supported by grants from the National Institutes of Health (R01 GM075004) and National Science Foundation (DMS0604776, DMS800568).

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Authors and Affiliations

  1. Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA

    Vishwesh Venkatraman & Daisuke Kihara

  2. Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA

    Lee Sael & Daisuke Kihara

  3. Markey Center for Structural Biology, Purdue University, West Lafayette, IN, 47907, USA

    Vishwesh Venkatraman & Daisuke Kihara

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  1. Vishwesh Venkatraman
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  2. Lee Sael
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  3. Daisuke Kihara
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Correspondence to Daisuke Kihara.

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Venkatraman, V., Sael, L. & Kihara, D. Potential for Protein Surface Shape Analysis Using Spherical Harmonics and 3D Zernike Descriptors. Cell Biochem Biophys 54, 23–32 (2009). https://doi.org/10.1007/s12013-009-9051-x

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