Multimap targeted free energy estimation
arXiv:2302.07683 · doi:10.1073/pnas.2304308120
Abstract
We present a new method to compute free energies at a quantum mechanical (QM) level of theory from molecular simulations using cheap reference potential energy functions, such as force fields. To overcome the poor overlap between the reference and target distributions, we generalize targeted free energy perturbation (TFEP) to employ multiple configuration maps. While TFEP maps have been obtained before from an expensive training of a normalizing flow neural network (NN), our multimap estimator allows us to use the same set of QM calculations to both optimize the maps and estimate the free energy, thus removing almost completely the overhead due to training. A multimap extension of the multistate Bennett acceptance ratio estimator is also derived for cases where samples from two or more states are available. Furthermore, we propose a one-epoch learning policy that can be used to efficiently avoid overfitting when computing the loss function is expensive compared to generating data. Finally, we show how our multimap approach can be combined with enhanced sampling strategies to overcome the pervasive problem of poor convergence due to slow degrees of freedom. We test our method on the HiPen dataset of drug-like molecules and fragments, and we show that it can accelerate the calculation of the free energy difference of switching from a force field to a DFTB3 potential by about 3 orders of magnitude compared to standard FEP and by a factor of about 8 compared to previously published nonequilibrium calculations.
arXiv commentMain Text: 12 pages, 5 figures, 7 equations. Supplemental Material: 17 pages, 5 figures, 22 equations
References in corpus (22)
- PyTorch: An Imperative Style, High-Performance Deep Learning Library
- Decoupled Weight Decay Regularization
- Escaping free-energy minima
- A nonequilibrium equality for free energy differences
- PLUMED 2: New feathers for an old bird
- Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method
- Statistically optimal analysis of samples from multiple equilibrium states
- Path ensembles averages in systems driven far-from-equilibrium
- Multidimensional replica-exchange method for free-energy calculations
- Rethinking Metadynamics: from bias potentials to probability distributions
- Enhanced sampling methods for molecular dynamics simulations
- Normalizing Flows for Probabilistic Modeling and Inference
- MADE: Masked Autoencoder for Distribution Estimation
- Best Practices for Alchemical Free Energy Calculations
- Masked Autoregressive Flow for Density Estimation
- Targeted free energy perturbation
- Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. I. Weighted Thermodynamics Perturbation
- Targeted free energy estimation via learned mappings
- Skipping the Replica Exchange Ladder with Normalizing Flows
- Using bijective maps to improve free energy estimates
- Using reweighting and free energy surface interpolation to predict solid-solid phase diagrams
- Configurational mapping significantly increases the efficiency of solid-solid phase coexistence calculations via molecular dynamics: Determining the FCC-HCP coexistence line of Lennard-Jones particles