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Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Voet A, Berenger F, Zhang KY - PLoS ONE (2013)

Bottom Line: This method was implemented in a software called EleKit.This is especially true for the more polar SMPPIIs.Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

View Article: PubMed Central - PubMed

Affiliation: Zhang Initiative Research Unit, Institute Laboratories, RIKEN, Wako, Saitama, Japan.

ABSTRACT
One of the underlying principles in drug discovery is that a biologically active compound is complimentary in shape and molecular recognition features to its receptor. This principle infers that molecules binding to the same receptor may share some common features. Here, we have investigated whether the electrostatic similarity can be used for the discovery of small molecule protein-protein interaction inhibitors (SMPPIIs). We have developed a method that can be used to evaluate the similarity of electrostatic potentials between small molecules and known protein ligands. This method was implemented in a software called EleKit. Analyses of all available (at the time of research) SMPPII structures indicate that SMPPIIs bear some similarities of electrostatic potential with the ligand proteins of the same receptor. This is especially true for the more polar SMPPIIs. Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

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Overview of the bit-mask construction in EleKit.(1) a near-or-inside mask of RP is created, (2) a near-but-not-inside mask of LP is created, (3) a near-but-not-inside mask of LSM is created, (4) the logical conjunction of the three masks is used to select points to correlate from the electrostatic potentials of LP and LSM.
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pone-0075762-g002: Overview of the bit-mask construction in EleKit.(1) a near-or-inside mask of RP is created, (2) a near-but-not-inside mask of LP is created, (3) a near-but-not-inside mask of LSM is created, (4) the logical conjunction of the three masks is used to select points to correlate from the electrostatic potentials of LP and LSM.

Mentions: The EleKit method is shown schematically in figure 1. First, the electrostatic potentials around and are computed using APBS (parameters listed in table 1) and stored in 3D grids. Since only the area where and intersect is most likely to be relevant for molecular recognition, a bit mask is created on the electrostatic potential grids (figure 2). The goal of this mask is to take into account only those points in space that are not only in the solvent region around and but also near the interface atoms of RP. To create this mask, a distance cutoff is needed. This distance is used when dilating (a morphological mathematical operation) the molecular surface. Based on the hydrogen bond length (∼2.5Å) and the facts that enough points are needed for correlation and that the local similarity is our focus, a cutoff value ranging from 1.4 Å to 3.5 Å seems reasonable. All experiments reported in this study were performed with an intermediate cutoff value of 2.0 Å. Using 3.0 Å or 4.0 Å would have very little impact on the results (data not shown). Finally, the similarity between electrostatic potentials of and is assessed by correlating values at the grid points within the mask using the Spearman rank-order correlation coefficient (). Additional similarity scores (Carbo index [33], Hodgkin index [34], Pearson's r and a Tanimoto score) are also calculated.


Electrostatic similarities between protein and small molecule ligands facilitate the design of protein-protein interaction inhibitors.

Voet A, Berenger F, Zhang KY - PLoS ONE (2013)

Overview of the bit-mask construction in EleKit.(1) a near-or-inside mask of RP is created, (2) a near-but-not-inside mask of LP is created, (3) a near-but-not-inside mask of LSM is created, (4) the logical conjunction of the three masks is used to select points to correlate from the electrostatic potentials of LP and LSM.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3794991&req=5

pone-0075762-g002: Overview of the bit-mask construction in EleKit.(1) a near-or-inside mask of RP is created, (2) a near-but-not-inside mask of LP is created, (3) a near-but-not-inside mask of LSM is created, (4) the logical conjunction of the three masks is used to select points to correlate from the electrostatic potentials of LP and LSM.
Mentions: The EleKit method is shown schematically in figure 1. First, the electrostatic potentials around and are computed using APBS (parameters listed in table 1) and stored in 3D grids. Since only the area where and intersect is most likely to be relevant for molecular recognition, a bit mask is created on the electrostatic potential grids (figure 2). The goal of this mask is to take into account only those points in space that are not only in the solvent region around and but also near the interface atoms of RP. To create this mask, a distance cutoff is needed. This distance is used when dilating (a morphological mathematical operation) the molecular surface. Based on the hydrogen bond length (∼2.5Å) and the facts that enough points are needed for correlation and that the local similarity is our focus, a cutoff value ranging from 1.4 Å to 3.5 Å seems reasonable. All experiments reported in this study were performed with an intermediate cutoff value of 2.0 Å. Using 3.0 Å or 4.0 Å would have very little impact on the results (data not shown). Finally, the similarity between electrostatic potentials of and is assessed by correlating values at the grid points within the mask using the Spearman rank-order correlation coefficient (). Additional similarity scores (Carbo index [33], Hodgkin index [34], Pearson's r and a Tanimoto score) are also calculated.

Bottom Line: This method was implemented in a software called EleKit.This is especially true for the more polar SMPPIIs.Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

View Article: PubMed Central - PubMed

Affiliation: Zhang Initiative Research Unit, Institute Laboratories, RIKEN, Wako, Saitama, Japan.

ABSTRACT
One of the underlying principles in drug discovery is that a biologically active compound is complimentary in shape and molecular recognition features to its receptor. This principle infers that molecules binding to the same receptor may share some common features. Here, we have investigated whether the electrostatic similarity can be used for the discovery of small molecule protein-protein interaction inhibitors (SMPPIIs). We have developed a method that can be used to evaluate the similarity of electrostatic potentials between small molecules and known protein ligands. This method was implemented in a software called EleKit. Analyses of all available (at the time of research) SMPPII structures indicate that SMPPIIs bear some similarities of electrostatic potential with the ligand proteins of the same receptor. This is especially true for the more polar SMPPIIs. Retrospective analysis of several successful SMPPIIs has shown the applicability of EleKit in the design of new SMPPIIs.

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