Computing the Dissociation Constant from Molecular Dynamics Simulations with Corrections for the Large Pressure Fluctuations—Aquaglyceroporins Have High Affinity for Their Substrate Glycerol

In this paper, we consider the inevitable large fluctuations of pressure in typical molecular dynamics (MD) simulations of ligand-protein binding problems. In simulations under the constant pressure of one bar, the pressure artifactually fluctuates over the range of ±100 bars or more. This artifact can cause gross inaccuracy in the apparent binding affinity computed as the ratio of the probability for the ligand to be bound inside the protein and the probability for the ligand to be outside the protein. Based on statistical thermodynamics, we derive a correction factor for the ligand-protein binding affinity to compensate for the artifactual pressure fluctuations. The correction factor depends on the change in the system volume between the bound and the unbound states of the ligand. We conducted four sets of MD simulations for glycerol affinities with four aquaglyceroporins: AQP10, AQP3, AQP7, and GlpF. Without the correction factor, the apparent affinity of glycerol with each of these four aquaglyceroporins is computed directly from the simulations to be very low (~1/M). With the correction factor applied, glycerol's affinity is computed to be 1/mM to 1/µM. In conclusion, glycerol has high affinity for its native facilitator aquaglyceroporins, which is in contrast to the current literature not correcting the artifactual consequences of the large pressure fluctuations in typical in silico experiments.

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Journal
Biomolecules
Published
2026-01-21
DOI
https://doi.org/10.3390/biom16010174
Primary Topic
Protein Structure and Dynamics
Type
article
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article

Computing the Dissociation Constant from Molecular Dynamics Simulations with Corrections for the Large Pressure Fluctuations—Aquaglyceroporins Have High Affinity for Their Substrate Glycerol

Liao Y. Chen, Hans R. Loja, Md Mohsin
Biomolecules
Protein Structure and Dynamics
article

Computing the Dissociation Constant from Molecular Dynamics Simulations with Corrections for the Large Pressure Fluctuations—Aquaglyceroporins Have High Affinity for Their Substrate Glycerol

Liao Y. Chen, Hans R. Loja, Md Mohsin
article en

Abstract

In this paper, we consider the inevitable large fluctuations of pressure in typical molecular dynamics (MD) simulations of ligand-protein binding problems. In simulations under the constant pressure of one bar, the pressure artifactually fluctuates over the range of ±100 bars or more. This artifact can cause gross inaccuracy in the apparent binding affinity computed as the ratio of the probability for the ligand to be bound inside the protein and the probability for the ligand to be outside the protein. Based on statistical thermodynamics, we derive a correction factor for the ligand-protein binding affinity to compensate for the artifactual pressure fluctuations. The correction factor depends on the change in the system volume between the bound and the unbound states of the ligand. We conducted four sets of MD simulations for glycerol affinities with four aquaglyceroporins: AQP10, AQP3, AQP7, and GlpF. Without the correction factor, the apparent affinity of glycerol with each of these four aquaglyceroporins is computed directly from the simulations to be very low (~1/M). With the correction factor applied, glycerol's affinity is computed to be 1/mM to 1/µM. In conclusion, glycerol has high affinity for its native facilitator aquaglyceroporins, which is in contrast to the current literature not correcting the artifactual consequences of the large pressure fluctuations in typical in silico experiments.

BiomoleculesVol. 16(1)
The University of Texas at San Antonio (US)
Life below water
Openalex Percentile: Top 82%
Protein Structure and Dynamics
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Computing the Dissociation Constant from Molecular Dynamics Simulations with Corrections for the Large Pressure Fluctuations—Aquaglyceroporins Have High Affinity for Their Substrate Glycerol — Liao Y. Chen, Hans R. Loja, et al. · Biomolecules (2026) | TGRS Research Map | TGRS