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Generative Topographic Mapping of the Docking Conformational Space.

Dragos Horvath1, Gilles Marcou2, Alexandre Varnek3

  • 1Laboratoire de Chemoinformatique, UMR7140 CNRS/Univ. of Strasbourg, 1, rue Blaise Pascal, 67000 Strasbourg, France. dhorvath@unistra.fr.

Molecules (Basel, Switzerland)
|June 21, 2019
PubMed
Summary

Generative Topographic Mapping (GTM) was adapted for molecular docking, creating Contact (CF) and Hybrid (Hy) maps. Hybrid maps effectively distinguished native ligand poses and predicted binding potency, outperforming traditional scoring methods.

Keywords:
conformational space mapscontact fingerprintsdockinggenerative topographic mapping

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Area of Science:

  • Computational chemistry and cheminformatics
  • Drug discovery and molecular modeling

Background:

  • Generative Topographic Mapping (GTM) has been used to explore the conformational space of flexible molecules.
  • Adapting GTM for molecular docking requires characterizing ligands based on their interactions within a binding site.

Purpose of the Study:

  • To adapt the polyvalent mapping technique of GTM for the molecular docking problem.
  • To develop and evaluate 'Contact' (CF) and 'Hybrid' (Hy) maps for analyzing docking results.
  • To assess the ability of these maps to discriminate native from non-native ligand poses and predict binding potency.

Main Methods:

  • Contact fingerprints (CF) were used to describe ligand-protein interactions.
  • GTM was applied to reduce the dimensionality of CF vectors, creating a 'Contact' (CF) map.
  • A 'Hybrid' (Hy) map was constructed by combining CFs with ligand fragment descriptors.
  • Docking simulations of ligands into the CDK2 ATP-binding site were performed using the S4MPLE program.
  • The maps were evaluated based on their ability to discriminate native poses (RMSD < 2Å) and to differentiate ligands by potency.

Main Results:

  • Both CF and Hy maps were tested for their ability to discriminate native ligand poses.
  • The maps were also challenged to distinguish between potent binders and decoys based on their binding information.
  • Hybrid maps demonstrated superior performance in both challenges compared to CF maps.
  • Hybrid maps outperformed classical energy and individual contact satisfaction scores in discriminating ligands by potency.
  • The visualization of docking conformational space (CS) offers intuitive analysis and potential applications in highlighting key contacts and monitoring convergence.

Conclusions:

  • The adapted GTM technique, particularly the Hybrid map, shows promise for enhancing molecular docking accuracy.
  • This approach provides an effective method for pose discrimination and potency prediction in drug discovery.
  • The intuitive visualization of docking conformational space offers valuable insights for computational drug design.