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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.


Related in: MedlinePlus

The idea of pocket recognition using the beta-shape.(a) Empty tangent balls defining the exposure intervals of each atom on the boundary. (b) The pocket {σ1, σ2, } where β2 < βθ ≤ β3. (c) The pocket {σ1, σ2, σ3, , , } where β3 < βθ ≤ β4.
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pone.0122787.g002: The idea of pocket recognition using the beta-shape.(a) Empty tangent balls defining the exposure intervals of each atom on the boundary. (b) The pocket {σ1, σ2, } where β2 < βθ ≤ β3. (c) The pocket {σ1, σ2, σ3, , , } where β3 < βθ ≤ β4.

Mentions: Fig. 2 shows a two-dimensional schematic diagram showing the idea of pocket recognition using the beta-shape. Suppose that the figure depicts a subset of the beta-shape corresponding to the probe of water. Consider that the small circle σ or σ* is an atom on the molecular boundary and the shaded region is the molecular interior. The atoms on the slanted wall in the left are numbered σ1 through σ6, and those on the vertical wall are numbered through . There are four dotted circles β1, β2, β3 and β4 in Fig. 2(a) where each is in contact with the boundary of the three atoms. For convenience, suppose that β1, β2, β3 and β4 also denote the radii of the corresponding circles where 0 ≤ β1 < β2 < β3 < β4. Let π be a spherical open probe with the radius βπ.


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

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

The idea of pocket recognition using the beta-shape.(a) Empty tangent balls defining the exposure intervals of each atom on the boundary. (b) The pocket {σ1, σ2, } where β2 < βθ ≤ β3. (c) The pocket {σ1, σ2, σ3, , , } where β3 < βθ ≤ β4.
© Copyright Policy
Related In: Results  -  Collection

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

pone.0122787.g002: The idea of pocket recognition using the beta-shape.(a) Empty tangent balls defining the exposure intervals of each atom on the boundary. (b) The pocket {σ1, σ2, } where β2 < βθ ≤ β3. (c) The pocket {σ1, σ2, σ3, , , } where β3 < βθ ≤ β4.
Mentions: Fig. 2 shows a two-dimensional schematic diagram showing the idea of pocket recognition using the beta-shape. Suppose that the figure depicts a subset of the beta-shape corresponding to the probe of water. Consider that the small circle σ or σ* is an atom on the molecular boundary and the shaded region is the molecular interior. The atoms on the slanted wall in the left are numbered σ1 through σ6, and those on the vertical wall are numbered through . There are four dotted circles β1, β2, β3 and β4 in Fig. 2(a) where each is in contact with the boundary of the three atoms. For convenience, suppose that β1, β2, β3 and β4 also denote the radii of the corresponding circles where 0 ≤ β1 < β2 < β3 < β4. Let π be a spherical open probe with the radius βπ.

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.


Related in: MedlinePlus