Literature DB >> 18023220

Pocket extraction on proteins via the Voronoi diagram of spheres.

Donguk Kim1, Cheol-Hyung Cho, Youngsong Cho, Joonghyun Ryu, Jonghwa Bhak, Deok-Soo Kim.   

Abstract

Proteins consist of atoms. Given a protein, the automatic recognition of depressed regions, called pockets, on the surface of proteins is important for protein-ligand docking and facilitates fast development of new drugs. Recently, computational approaches have emerged for recognizing pockets from the geometrical point of view. Presented in this paper is a geometric method for the pocket recognition which is based on the Voronoi diagram for atoms. Given a Voronoi diagram, the proposed algorithm transforms the atomic structure to meshes which contain the information of the proximity among atoms, and then recognizes depressions on the surface of a protein using the meshes.

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Year:  2007        PMID: 18023220     DOI: 10.1016/j.jmgm.2007.10.002

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  11 in total

1.  Prediction of ligand-binding sites of proteins by molecular docking calculation for a random ligand library.

Authors:  Yoshifumi Fukunishi; Haruki Nakamura
Journal:  Protein Sci       Date:  2011-01       Impact factor: 6.725

2.  Balancing target flexibility and target denaturation in computational fragment-based inhibitor discovery.

Authors:  Theresa J Foster; Alexander D MacKerell; Olgun Guvench
Journal:  J Comput Chem       Date:  2012-05-28       Impact factor: 3.376

Review 3.  Computational methods in drug discovery.

Authors:  Gregory Sliwoski; Sandeepkumar Kothiwale; Jens Meiler; Edward W Lowe
Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

4.  Protein pocket detection via convex hull surface evolution and associated Reeb graph.

Authors:  Rundong Zhao; Zixuan Cang; Yiying Tong; Guo-Wei Wei
Journal:  Bioinformatics       Date:  2018-09-01       Impact factor: 6.937

5.  Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey.

Authors:  Tiago Simões; Daniel Lopes; Sérgio Dias; Francisco Fernandes; João Pereira; Joaquim Jorge; Chandrajit Bajaj; Abel Gomes
Journal:  Comput Graph Forum       Date:  2017-06-01       Impact factor: 2.078

6.  AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters.

Authors:  Joseph Katigbak; Haotian Li; David Rooklin; Yingkai Zhang
Journal:  J Chem Inf Model       Date:  2020-02-11       Impact factor: 4.956

7.  fpocket: online tools for protein ensemble pocket detection and tracking.

Authors:  Peter Schmidtke; Vincent Le Guilloux; Julien Maupetit; Pierre Tufféry
Journal:  Nucleic Acids Res       Date:  2010-05-16       Impact factor: 16.971

8.  Optimal ligand descriptor for pocket recognition based on the Beta-shape.

Authors:  Jae-Kwan Kim; Chung-In Won; Jehyun Cha; Kichun Lee; Deok-Soo Kim
Journal:  PLoS One       Date:  2015-04-02       Impact factor: 3.240

9.  Fpocket: an open source platform for ligand pocket detection.

Authors:  Vincent Le Guilloux; Peter Schmidtke; Pierre Tuffery
Journal:  BMC Bioinformatics       Date:  2009-06-02       Impact factor: 3.169

10.  Protein molecular surface mapped at different geometrical resolutions.

Authors:  Dan V Nicolau; Ewa Paszek; Florin Fulga; Dan V Nicolau
Journal:  PLoS One       Date:  2013-03-14       Impact factor: 3.240

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