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SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations

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Abstract

The SAMPL challenges focus on testing and driving progress of computational methods to help guide pharmaceutical drug discovery. However, assessment of methods for predicting binding affinities is often hampered by computational challenges such as conformational sampling, protonation state uncertainties, variation in test sets selected, and even lack of high quality experimental data. SAMPL blind challenges have thus frequently included a component focusing on host–guest binding, which removes some of these challenges while still focusing on molecular recognition. Here, we report on the results of the SAMPL7 blind prediction challenge for host–guest affinity prediction. In this study, we focused on three different host–guest categories—a familiar deep cavity cavitand series which has been featured in several prior challenges (where we examine binding of a series of guests to two hosts), a new series of cyclodextrin derivatives which are monofunctionalized around the rim to add amino acid-like functionality (where we examine binding of two guests to a series of hosts), and binding of a series of guests to a new acyclic TrimerTrip host which is related to previous cucurbituril hosts. Many predictions used methods based on molecular simulations, and overall success was mixed, though several methods stood out. As in SAMPL6, we find that one strategy for achieving reasonable accuracy here was to make empirical corrections to binding predictions based on previous data for host categories which have been studied well before, though this can be of limited value when new systems are included. Additionally, we found that alchemical free energy methods using the AMOEBA polarizable force field had considerable success for the two host categories in which they participated. The new TrimerTrip system was also found to introduce some sampling problems, because multiple conformations may be relevant to binding and interconvert only slowly. Overall, results in this challenge tentatively suggest that further investigation of polarizable force fields for these challenges may be warranted.

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Abbreviations

SAMPL:

Statistical Assessment of the Modeling of Proteins and Ligands

AM1-BCC:

Austin model 1 bond charge correction

RESP:

Restrained electrostatic potential

REST:

Replica exchange with solute tempering

FSDAM:

Fast switching double annihilation method

B2PLYPD3:

Beck 2-parameter Lee–Yang–Parr D3 exchange-correlation functional [1]

B3PW91:

Becke 3-parameter Perdew–Wang 91 exchange-correlation functional [2]

GAFF:

Generalized AMBER force field

CGenFF:

CHARMM generalized force field

AMOEBA:

Atomic multipole optimized energetics for biomolecular simulations

DDM:

Double decoupling method

DFT:

Density functional theory

QM/MM:

Mixed quantum mechanics and molecular mechanics

MMPBSA:

Molecular mechanics Poisson–Boltzmann/solvent accessible surface area

MMGBSA:

Molecular mechanics generalized born/solvent accessible surface area

TIP3P:

Transferable interaction potential three-point

TIP4PEw:

Transferable interaction potential four-point Ewald

OPC3:

Optimal 3-point charge

SEM:

Standard error of the mean

RMSE:

Root mean squared error

MAE:

Mean absolute error

ME:

Mean signed error

\(\tau \) :

Kendall’s rank correlation coefficient (Tau)

\({R}^{2}\) :

Coefficient of determination (R-squared)

QM:

Quantum Mechanics

MM:

Molecular Mechanics

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Acknowledgements

MA and DLM gratefully acknowledge support from NIH Grant R01GM124270 supporting the SAMPL Blind Challenges. We appreciate the laboratories of Michael K. Gilson (UCSD), Lyle Isaacs (Maryland) and Bruce Gibb (Tulane) for providing experimental data for the challenge. We are also grateful to OpenEye Scientific for providing a free academic software license for use in this work.

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Authors and Affiliations

  1. Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA

    Martin Amezcua, Léa El Khoury & David L. Mobley

  2. Department of Chemistry, University of California, Irvine, CA, 92697, USA

    David L. Mobley

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  1. Martin Amezcua
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  2. Léa El Khoury
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Correspondence to David L. Mobley.

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DLM is a Member of the Scientific Advisory Board of OpenEye Scientific Software, and DLM is an Open Science Fellow with Silicon Therapeutics.

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Amezcua, M., El Khoury, L. & Mobley, D.L. SAMPL7 Host–Guest Challenge Overview: assessing the reliability of polarizable and non-polarizable methods for binding free energy calculations. J Comput Aided Mol Des 35, 1–35 (2021). https://doi.org/10.1007/s10822-020-00363-5

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