TIES 20: Relative Binding Free Energy with a Flexible Superimposition Algorithm and Partial Ring Morphing.

Mateusz K Bieniek,Peter V Coveney,Agastya P Bhati,Shunzhou Wan

doi:10.1021/acs.jctc.0c01179

Mateusz K Bieniek, Peter V Coveney + Show 2 more

Open Access

https://doi.org/10.1021/acs.jctc.0c01179

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Abstract

The TIES (Thermodynamic Integration with Enhanced Sampling) protocol is a formally exact alchemical approach in computational chemistry to the calculation of relative binding free energies. The validity of TIES relies on the correctness of matching atoms across compared pairs of ligands, laying the foundation for the transformation along an alchemical pathway. We implement a flexible topology superimposition algorithm which uses an exhaustive joint-traversal for computing the largest common component(s). The algorithm is employed to enable matching and morphing of partial rings in the TIES protocol along with a validation study using 55 transformations and five different proteins from our previous work. We find that TIES 20 with the RESP charge system, using the new superimposition algorithm, reproduces the previous results with mean unsigned error of 0.75 kcal/mol with respect to the experimental data. Enabling the morphing of partial rings decreases the size of the alchemical region in the dual-topology transformations resulting in a significant improvement in the prediction precision. We find that increasing the ensemble size from 5 to 20 replicas per λ window only has a minimal impact on the accuracy. However, the non-normal nature of the relative free energy distributions underscores the importance of ensemble simulation. We further compare the results with the AM1-BCC charge system and show that it improves agreement with the experimental data by slightly over 10%. This improvement is partly due to AM1-BCC affecting only the charges of the atoms local to the mutation, which translates to even fewer morphed atoms, consequently reducing issues with sampling and therefore ensemble averaging. TIES 20, in conjunction with the enablement of ring morphing, reduces the size of the alchemical region and significantly improves the precision of the predicted free energies.

Highlights

While the age of exascale computing is emerging, the field of drug discovery is increasingly using the maximum computational means available to complement its life-cycle.[1]
It was explained that this approach was employed in order to decrease the size of the alchemical region when this criterion led to the deletion of a link atom dividing the MCS into two or more disjoint fragments
The more notable cases include MCL1 and PTP1B. Such small issues were mostly avoided here, in several cases the net charge limit had to be adjusted in line with the previous study, without which the size of the alchemical region represented most of the molecule

Summary

Introduction

While the age of exascale computing is emerging, the field of drug discovery is increasingly using the maximum computational means available to complement its life-cycle.[1]. Whereas physics based free energy computations have been historically prohibitively expensive, they are becoming increasingly viable, bringing their application to the different stages of drug development, hit to lead and lead optimization stages, and increasingly virtual high throughput screening. These calculations can offset the large costs associated with bringing novel drugs to market, while their combination of scalability and performance is relevant in urgent situations such as that brought about by the COVID-19 pandemic. Relative binding free energy (RBFE) calculations are one of the increasingly utilized physics based methods. The practice has been to only apply TI for studying relatively small transformations, in principle, it should be able to handle larger structural changes than are possible with FEP

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