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Uncertainty Quantification in Alchemical Free Energy Methods.

Agastya P Bhati1, Shunzhou Wan1, Yuan Hu2

  • 1Centre for Computational Science, Department of Chemistry , University College London , 20 Gordon Street , London WC1H 0AJ , United Kingdom.

Journal of Chemical Theory and Computation
|April 22, 2018
PubMed
Summary
This summary is machine-generated.

Alchemical free energy methods predict binding affinities but lack uncertainty quantification. Ensemble simulations provide a reliable error estimation for these molecular dynamics methods, regardless of simulation length.

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Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Drug discovery

Background:

  • Alchemical free energy methods are crucial for predicting ligand-protein binding affinities.
  • Numerous variants exist, but reproducibility and uncertainty quantification are under-discussed.
  • Molecular dynamics (MD) simulations are key to these methods.

Purpose of the Study:

  • To systematically assess uncertainty quantification for popular alchemical free energy methods.
  • To evaluate both absolute and relative free energy predictions.
  • To identify reliable error estimation strategies.

Main Methods:

  • Application of a systematic uncertainty quantification protocol.
  • Testing various alchemical free energy methods.
  • Utilizing ensemble simulations (multiple independent MD runs).

Main Results:

  • Ensemble simulations provide a reliable measure of error estimation.
  • This finding is independent of the specific alchemical free energy method used.
  • The necessity of ensemble methods holds true irrespective of simulation duration.

Conclusions:

  • Ensemble simulations are fundamental for robust uncertainty quantification in alchemical free energy calculations.
  • This approach enhances the reliability of binding affinity predictions.
  • Further research should incorporate ensemble methods for accurate error estimation.