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Estimation of Drug-Target Residence Times by τ-Random Acceleration Molecular Dynamics Simulations.

Daria B Kokh1, Marta Amaral2,3, Joerg Bomke4

  • 1Molecular and Cellular Modeling Group , Heidelberg Institute for Theoretical Studies , Heidelberg 69118 , Germany.

Journal of Chemical Theory and Computation
|May 18, 2018
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Summary

Predicting drug residence time is difficult. A new method, τ-random acceleration molecular dynamics (τRAMD), efficiently ranks drug candidates by residence time and reveals dissociation mechanisms for improved drug design.

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Area of Science:

  • Computational chemistry
  • Drug discovery
  • Molecular dynamics

Background:

  • Drug-target residence time (τ) is crucial for drug efficacy but challenging to predict computationally.
  • This parameter is often overlooked in early drug design stages.
  • HSP90α N-terminal domain is a pharmaceutically significant target with a flexible binding site.

Purpose of the Study:

  • To introduce an efficient computational method, τ-random acceleration molecular dynamics (τRAMD), for predicting drug-target residence times.
  • To enable ranking of drug candidates based on residence time.
  • To gain insights into ligand-target dissociation mechanisms.

Main Methods:

  • Application of τ-random acceleration molecular dynamics (τRAMD) simulations.
  • Assessment on a dataset of 70 diverse drug-like ligands targeting the N-terminal domain of HSP90α.
  • Analysis of ligand-target dissociation trajectories.

Main Results:

  • τRAMD achieved high accuracy in predicting relative residence times (2.3τ for 78% of compounds).
  • Accurate predictions (less than 2.0τ) were obtained within congeneric series.
  • Dissociation trajectory analysis identified key features influencing unbinding rates, such as transient polar interactions and steric hindrance.

Conclusions:

  • τRAMD is an efficient computational tool for ranking drug candidates by residence time.
  • The method provides insights into ligand-target dissociation mechanisms.
  • τRAMD is expected to be widely applicable for improving drug residence times during lead optimization.