Literature DB >> 19254186

The application of 3D Zernike moments for the description of "model-free" molecular structure, functional motion, and structural reliability.

Scott Grandison1, Carl Roberts, Richard J Morris.   

Abstract

Protein structures are not static entities consisting of equally well-determined atomic coordinates. Proteins undergo continuous motion, and as catalytic machines, these movements can be of high relevance for understanding function. In addition to this strong biological motivation for considering shape changes is the necessity to correctly capture different levels of detail and error in protein structures. Some parts of a structural model are often poorly defined, and the atomic displacement parameters provide an excellent means to characterize the confidence in an atom's spatial coordinates. A mathematical framework for studying these shape changes, and handling positional variance is therefore of high importance. We present an approach for capturing various protein structure properties in a concise mathematical framework that allows us to compare features in a highly efficient manner. We demonstrate how three-dimensional Zernike moments can be employed to describe functions, not only on the surface of a protein but throughout the entire molecule. A number of proof-of-principle examples are given which demonstrate how this approach may be used in practice for the representation of movement and uncertainty.

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Year:  2009        PMID: 19254186     DOI: 10.1089/cmb.2008.0083

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  8 in total

1.  Fingerprint-based structure retrieval using electron density.

Authors:  Shuangye Yin; Nikolay V Dokholyan
Journal:  Proteins       Date:  2011-01-03

2.  Fragmentation-tree density representation for crystallographic modelling of bound ligands.

Authors:  Gerrit G Langer; Guillaume X Evrard; Ciaran G Carolan; Victor S Lamzin
Journal:  J Mol Biol       Date:  2012-03-23       Impact factor: 5.469

3.  Comprehensive analysis of lectin-glycan interactions reveals determinants of lectin specificity.

Authors:  Daniel E Mattox; Chris Bailey-Kellogg
Journal:  PLoS Comput Biol       Date:  2021-10-06       Impact factor: 4.475

4.  Using diffusion distances for flexible molecular shape comparison.

Authors:  Yu-Shen Liu; Qi Li; Guo-Qin Zheng; Karthik Ramani; William Benjamin
Journal:  BMC Bioinformatics       Date:  2010-09-24       Impact factor: 3.169

5.  Superposition-free comparison and clustering of antibody binding sites: implications for the prediction of the nature of their antigen.

Authors:  Lorenzo Di Rienzo; Edoardo Milanetti; Rosalba Lepore; Pier Paolo Olimpieri; Anna Tramontano
Journal:  Sci Rep       Date:  2017-03-24       Impact factor: 4.379

6.  Antibody Specific B-Cell Epitope Predictions: Leveraging Information From Antibody-Antigen Protein Complexes.

Authors:  Martin Closter Jespersen; Swapnil Mahajan; Bjoern Peters; Morten Nielsen; Paolo Marcatili
Journal:  Front Immunol       Date:  2019-02-26       Impact factor: 7.561

7.  Quantitative Characterization of Binding Pockets and Binding Complementarity by Means of Zernike Descriptors.

Authors:  Lorenzo Di Rienzo; Edoardo Milanetti; Josephine Alba; Marco D'Abramo
Journal:  J Chem Inf Model       Date:  2020-02-25       Impact factor: 4.956

8.  Binding site identification of G protein-coupled receptors through a 3D Zernike polynomials-based method: application to C. elegans olfactory receptors.

Authors:  Lorenzo Di Rienzo; Luca De Flaviis; Giancarlo Ruocco; Viola Folli; Edoardo Milanetti
Journal:  J Comput Aided Mol Des       Date:  2022-01-01       Impact factor: 3.686

  8 in total

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