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DOCK 6: combining techniques to model RNA-small molecule complexes.

P Therese Lang1, Scott R Brozell, Sudipto Mukherjee

  • 1Graduate Program in Chemistry and Chemical Biology, University of California, San Francisco, California 94143, USA.

RNA (New York, N.Y.)
|April 17, 2009
PubMed
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The DOCK suite can be adapted for RNA-ligand docking, achieving high accuracy in recreating binding poses. Optimized parameters and scoring functions improve success rates for structure-based RNA drug design.

Area of Science:

  • Computational Chemistry
  • Structural Biology
  • Drug Discovery

Background:

  • Growing interest in RNA therapeutics necessitates tools for RNA-targeted drug design.
  • Existing protein-ligand docking algorithms require adaptation for nucleic acids.

Purpose of the Study:

  • To validate the DOCK suite's ability to accurately predict RNA-ligand binding poses.
  • To assess the performance of DOCK with optimized parameters and scoring functions for RNA targets.

Main Methods:

  • Compiled a test set of experimentally determined RNA-ligand complexes.
  • Utilized the DOCK suite with optimized parameters and a minimal scoring function.
  • Rescored docked conformations using implicit solvent models (AMBER GB/SA, PB/SA) with explicit water and ions.

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Main Results:

  • DOCK successfully recreated binding poses within 2 Å heavy-atom RMSD for 70% (≤7 rotatable bonds) and 26% (≤13 rotatable bonds) of the test set.
  • Rescoring with implicit solvent models improved success rates to 80% (PB/SA, ≤7 bonds), 58% (GB/SA, ≤13 bonds), and 47% (PB/SA, ≤13 bonds).

Conclusions:

  • The DOCK suite is a viable tool for structure-based drug design targeting RNA.
  • RNA-ligand interactions present unique electrostatic properties that can be managed through appropriate potential functions.
  • New DOCK functions can be readily incorporated to address emerging scientific challenges.