Absolute and Relative Binding Free Energy Calculations of Nucleotides to Multiple Protein Classes

Polyphosphate nucleotides, such as ATP, ADP, GTP, and GDP, play a crucial role in modulating protein functions through binding and/or catalytically activating proteins (enzymes). However, accurately calculating the binding free energies for these charged and flexible ligands poses challenges due to slow conformational relaxation and the limitations of force fields. In this study, we examine the accuracy and reliability of alchemical free energy simulations with fixed-charge force fields for the binding of four nucleotides to nine proteins of various classes, including kinases, ATPases, and GTPases. Our results indicate that the alchemical simulations effectively reproduce experimental binding free energies for all proteins that do not undergo significant conformational changes between their triphosphate nucleotide-bound and diphosphate nucleotide-bound states, with 87.5% (7 out of 8) of the absolute binding free energy results for 4 proteins within ±2 kcal/mol of experimental values and 88.9% (8 out of 9) of the relative binding free energy results for 9 proteins within ±3 kcal/mol of experimental values. However, our calculations show significant inaccuracies when divalent ions are included, suggesting that nonpolarizable force fields may not accurately capture interactions involving these ions. Additionally, the presence of highly charged and flexible ligands necessitates extensive conformational sampling to account for the long relaxation times associated with long-range electrostatic interactions. The simulation strategy presented here, along with its demonstrated accuracy across multiple protein classes, will be valuable for predicting the binding of nucleotides or their analogs to protein targets.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2024-12-19
DOI
https://doi.org/10.1021/acs.jctc.4c01440
Citations
3
Primary Topic
Molecular Junctions and Nanostructures
Type
article
Field-Weighted Citation Impact
0.63

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article

Absolute and Relative Binding Free Energy Calculations of Nucleotides to Multiple Protein Classes

Xiaolin Cheng, Apoorva Purohit
3 citations
Journal of Chemical Theory and Computation
Molecular Junctions and Nanostructures
0.63
article

Absolute and Relative Binding Free Energy Calculations of Nucleotides to Multiple Protein Classes

Xiaolin Cheng, Apoorva Purohit
article en
3 citations

Abstract

Polyphosphate nucleotides, such as ATP, ADP, GTP, and GDP, play a crucial role in modulating protein functions through binding and/or catalytically activating proteins (enzymes). However, accurately calculating the binding free energies for these charged and flexible ligands poses challenges due to slow conformational relaxation and the limitations of force fields. In this study, we examine the accuracy and reliability of alchemical free energy simulations with fixed-charge force fields for the binding of four nucleotides to nine proteins of various classes, including kinases, ATPases, and GTPases. Our results indicate that the alchemical simulations effectively reproduce experimental binding free energies for all proteins that do not undergo significant conformational changes between their triphosphate nucleotide-bound and diphosphate nucleotide-bound states, with 87.5% (7 out of 8) of the absolute binding free energy results for 4 proteins within ±2 kcal/mol of experimental values and 88.9% (8 out of 9) of the relative binding free energy results for 9 proteins within ±3 kcal/mol of experimental values. However, our calculations show significant inaccuracies when divalent ions are included, suggesting that nonpolarizable force fields may not accurately capture interactions involving these ions. Additionally, the presence of highly charged and flexible ligands necessitates extensive conformational sampling to account for the long relaxation times associated with long-range electrostatic interactions. The simulation strategy presented here, along with its demonstrated accuracy across multiple protein classes, will be valuable for predicting the binding of nucleotides or their analogs to protein targets.

Journal of Chemical Theory and ComputationVol. 21(4)
EP Analytics (United States) (US), The Ohio State University (US)
National Institutes of Health, National Institute of General Medical Sciences
Affordable and clean energy
Openalex Percentile: Top 30%
Molecular Junctions and Nanostructures
0.63
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