Enhanced Sampling in Free Energy Calculations: Combining SGLD with the Bennett’s Acceptance Ratio and Enveloping Distribution Sampling Methods

The accurate and reliable prediction of protein-ligand binding affinities can play a central role in the drug discovery process as well as in personalised medicine. Of considerable importance during lead optimisation are the alchemical free energy methods that furnish estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large dataset comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling) but are equally applicable to free energy perturbation calculations for which we expect essentially very similar results. Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behaviour. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

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SAMPL7 TrimerTrip Host-Guest Binding Affinities from Extensive Alchemical and End-Point Free Energy Calculations

10.26434/chemrxiv.12400715.v1 ◽

2020 ◽

Author(s):

Zhe Huai ◽

Huaiyu Yang ◽

Xiao Li ◽

Zhaoxi Sun

Keyword(s):

Free Energy ◽

Computational Modelling ◽

Free Energy Calculations ◽

Binding Affinities ◽

Enhanced Sampling ◽

New Host ◽

Energy Calculations ◽

Configurational Space ◽

End Point ◽

Guest Binding

<p>The prediction of host-guest binding affinities with computational modelling is still a challenging task. In the 7<sup>th</sup> statistical assessment of the modeling of proteins and ligands (SAMPL) challenge, a new host named TrimerTrip is synthesized and the thermodynamic parameters of 16 structurally diverse guests binding to the host are characterized. The challenge provides only structures of the host and the guests, which indicates that the predictions of both the binding poses and the binding affinities are under assessment. In this work, starting from the binding poses obtained from our previous enhanced sampling simulations in the configurational space, we perform extensive alchemical and end-point free energy calculations to calculate the host-guest binding affinities. The alchemical predictions with two widely accepted charge schemes (i.e. AM1-BCC and RESP) are in good agreement with the experimental reference, while the end-point estimates show significant deviations. Surprisingly, the end-point MM/PBSA method seems very powerful in reproducing the experimental rank of binding affinities. Although the length of our simulations is already very long and the intermediate spacing is very dense, the convergence behavior is not very good, which may arise from the flexibility of the host molecule. Enhanced sampling techniques in the configurational space may be required to obtain fully converged sampling. Further, as the length of sampling in alchemical free energy calculations already achieves several hundred ns, performing direct simulations of the binding/unbinding event in the physical space could be more useful and insightful. More details about the binding pathway and mechanism could be obtained in this way. </p>

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