Unknown

Dataset Information

0

What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling.


ABSTRACT: We introduce the self-relative binding free energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model. The results of this validation provide evidence that a significant fraction of the errors observed in benchmark studies reflect the statistical fluctuations of unconverged estimates rather than the models' accuracy. Furthermore, we find that ligand reorganization is a significant contributing factor to the statistical variance of binding free energy estimates and that metadynamics-accelerated conformational sampling of the torsional degrees of freedom of the ligand can drastically reduce the time to convergence.

SUBMITTER: Khuttan S 

PROVIDER: S-EPMC10867849 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

What to Make of Zero: Resolving the Statistical Noise from Conformational Reorganization in Alchemical Binding Free Energy Estimates with Metadynamics Sampling.

Khuttan Sheenam S   Gallicchio Emilio E  

Journal of chemical theory and computation 20240122 3


We introduce the self-relative binding free energy (self-RBFE) approach to evaluate the intrinsic statistical variance of dual-topology alchemical binding free energy estimators. The self-RBFE is the relative binding free energy between a ligand and a copy of the same ligand, and its true value is zero. Nevertheless, because the two copies of the ligand move independently, the self-RBFE value produced by a finite-length simulation fluctuates and can be used to measure the variance of the model.  ...[more]

Similar Datasets

| S-EPMC4999896 | biostudies-literature
| S-EPMC6874299 | biostudies-literature
| S-EPMC7542909 | biostudies-literature
| S-EPMC9674988 | biostudies-literature
| S-EPMC5824625 | biostudies-literature
2024-03-22 | GSE262110 | GEO
| S-EPMC10160108 | biostudies-literature
| S-EPMC4780711 | biostudies-literature
| S-EPMC5826560 | biostudies-literature
| S-EPMC6591532 | biostudies-literature