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THE USE OF EXPANDED ENSEMBLE FOR THE PREDICTION OF WATER-ORGANIC SOLVENT PARTITION COEFFICIENTS OF SMALL DRUG-LIKE MOLECULES
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2025-08
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Chemistry
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https://doi.org/10.34944/czvb-9w86
Abstract
The logarithm of the partition coefficient (logP) between water and a nonpolarsolvent is commonly used to characterize a molecule’s hydrophobicity. This metric serves as a key predictor of lipophilicity and membrane permeability— critical factors in determining a molecule’s bioavailability. As a result, accurate prediction of logP values has become a central focus in drug discovery. Free Energy Perturbation (FEP) methods are popular molecular mechanics approaches for predicting logP values. However, challenges remain, including sensitivity to force field choice and difficulties in adequately sampling complex free energy landscapes. Expanded Ensemble (EE) is an advanced FEP-based technique that enhances sampling and parallelization by allowing the system to explore multiple thermodynamic ensembles during a single simulation. This method has shown considerable flexibility and accuracy in computing various free energies, such as binding and mutation free energies. In this work, I evaluate the performance of Expanded Ensemble simulations in predicting logP values for drug-like molecules. I also examine how the choice of solvent and force field influences the accuracy and reliability of EE predictions. Chapter 2 describes the work conducted as part of the SAMPL9 logP blind challenge. Chapter 3 details the evaluation of a large dataset using two different force fields.
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