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

Kim JK, Won CI, Cha J, Lee K, Kim DS - PLoS ONE (2015)

Bottom Line: Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex.In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms.The performance of the proposed algorithm is verified by a benchmark test.

View Article: PubMed Central - PubMed

Affiliation: Voronoi Diagram Research Center, Hanyang University, Seoul, Korea.

ABSTRACT
Structure-based virtual screening is one of the most important and common computational methods for the identification of predicted hit at the beginning of drug discovery. Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex. In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms. We investigate six candidates for a shape descriptor for a ligand using statistical analysis: the minimum enclosing sphere, three measures from the principal component analysis of atoms, the van der Waals volume, and the beta-shape volume. Among them, the van der Waals volume of a ligand is the optimal shape descriptor for pocket recognition and best tunes the pocket recognition algorithm based on the beta-shape for efficient virtual screening. The performance of the proposed algorithm is verified by a benchmark test.

No MeSH data available.


Two different conformations of two ligands: the native state and the minimum energy state.The minimized energy conformation is calculated by MM2 in ChemOffice software. (a) and (b) the native and the minimum energy conformations of 1hwi, respectively; (c) and (d) those of 1v0p.
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pone.0122787.g008: Two different conformations of two ligands: the native state and the minimum energy state.The minimized energy conformation is calculated by MM2 in ChemOffice software. (a) and (b) the native and the minimum energy conformations of 1hwi, respectively; (c) and (d) those of 1v0p.

Mentions: A ligand may have rotational bonds that can generate various conformations. In this experiment, we used two conformations for each ligand to check the effect of a ligand’s conformation change: i) the native conformation found in the crystal structure and ii) the minimum energy conformation that was calculated by the MM2 method using ChemOffice software [66]. Fig. 8 shows two such examples.


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

Kim JK, Won CI, Cha J, Lee K, Kim DS - PLoS ONE (2015)

Two different conformations of two ligands: the native state and the minimum energy state.The minimized energy conformation is calculated by MM2 in ChemOffice software. (a) and (b) the native and the minimum energy conformations of 1hwi, respectively; (c) and (d) those of 1v0p.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383629&req=5

pone.0122787.g008: Two different conformations of two ligands: the native state and the minimum energy state.The minimized energy conformation is calculated by MM2 in ChemOffice software. (a) and (b) the native and the minimum energy conformations of 1hwi, respectively; (c) and (d) those of 1v0p.
Mentions: A ligand may have rotational bonds that can generate various conformations. In this experiment, we used two conformations for each ligand to check the effect of a ligand’s conformation change: i) the native conformation found in the crystal structure and ii) the minimum energy conformation that was calculated by the MM2 method using ChemOffice software [66]. Fig. 8 shows two such examples.

Bottom Line: Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex.In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms.The performance of the proposed algorithm is verified by a benchmark test.

View Article: PubMed Central - PubMed

Affiliation: Voronoi Diagram Research Center, Hanyang University, Seoul, Korea.

ABSTRACT
Structure-based virtual screening is one of the most important and common computational methods for the identification of predicted hit at the beginning of drug discovery. Pocket recognition and definition is frequently a prerequisite of structure-based virtual screening, reducing the search space of the predicted protein-ligand complex. In this paper, we present an optimal ligand shape descriptor for a pocket recognition algorithm based on the beta-shape, which is a derivative structure of the Voronoi diagram of atoms. We investigate six candidates for a shape descriptor for a ligand using statistical analysis: the minimum enclosing sphere, three measures from the principal component analysis of atoms, the van der Waals volume, and the beta-shape volume. Among them, the van der Waals volume of a ligand is the optimal shape descriptor for pocket recognition and best tunes the pocket recognition algorithm based on the beta-shape for efficient virtual screening. The performance of the proposed algorithm is verified by a benchmark test.

No MeSH data available.