Free-energy studies of ligand-binding affinities
(2023)- Abstract
- In drug discovery, it is of utmost importance to accurately calculate the free energies of binding ligands to various protein targets, such as enzymes and receptors. We have assessed and used computational tools for this aim, most of them based on molecular dynamics (MD) simulations. We mostly used molecular mechanics (MM) in order to model the protein—ligand interactions, which is more approximate than quantum-mechanical (QM) methods, but necessary to reduce the computational cost when doing calculations on protein—ligand systems, which often contain tens of thousand of atoms.
In one study of a large set of protein—ligand complexes, we tried to improve the free energies of binding by using MD simulations with QM-derived charges,... (More) - In drug discovery, it is of utmost importance to accurately calculate the free energies of binding ligands to various protein targets, such as enzymes and receptors. We have assessed and used computational tools for this aim, most of them based on molecular dynamics (MD) simulations. We mostly used molecular mechanics (MM) in order to model the protein—ligand interactions, which is more approximate than quantum-mechanical (QM) methods, but necessary to reduce the computational cost when doing calculations on protein—ligand systems, which often contain tens of thousand of atoms.
In one study of a large set of protein—ligand complexes, we tried to improve the free energies of binding by using MD simulations with QM-derived charges, which sometimes led to improved results, but not always. We also ran QM/MM simulations on casein-kinase 2 (CK2), where the ligand and a few surrounding residues were treated at the QM level, and the rest of the system at the MM level. However, those results were unsatisfying. Furthermore, it is important and challenging to accurately model the large entropic contribution to ligand-binding free energies. This entropy largely stems from the fluctuation of the protein and ligand. We tried to estimate this entropy with methods based on fluctuations of interaction energies. We also saw how a combination of theoretical and experimental methods can shed light on phenomena like entropy—entropy compensation and halogen bonding. Additionally, we compared how MD and grand-canonical Monte Carlo (GCMC) can be used to assess dynamics and thermodynamics of protein—ligand binding for both buried and solvent-exposed binding sites. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/9b0b1b60-c233-4709-ad14-98b4bf1d73f0
- author
- Ekberg, Vilhelm LU
- supervisor
-
- Ulf Ryde LU
- Mikael Akke LU
- opponent
-
- Professor Coveney, Peter, University College London
- organization
- publishing date
- 2023
- type
- Thesis
- publication status
- published
- subject
- keywords
- free energy perturbation, drug design, ligand-binding affinity, entropy, molecular mechanics, molecular dynamics
- pages
- 154 pages
- publisher
- Lunds universitet, Media-Tryck
- defense location
- Hall A, Chemical Centre, Lund University (KC:A)
- defense date
- 2023-09-26 13:00:00
- ISBN
- 978-91-7422-962-2
- 978-91-7422-963-9
- project
- Free-energy studies of ligand-binding affinities
- language
- English
- LU publication?
- yes
- id
- 9b0b1b60-c233-4709-ad14-98b4bf1d73f0
- date added to LUP
- 2023-08-29 10:26:28
- date last changed
- 2023-09-01 11:15:32
@phdthesis{9b0b1b60-c233-4709-ad14-98b4bf1d73f0,
abstract = {{In drug discovery, it is of utmost importance to accurately calculate the free energies of binding ligands to various protein targets, such as enzymes and receptors. We have assessed and used computational tools for this aim, most of them based on molecular dynamics (MD) simulations. We mostly used molecular mechanics (MM) in order to model the protein—ligand interactions, which is more approximate than quantum-mechanical (QM) methods, but necessary to reduce the computational cost when doing calculations on protein—ligand systems, which often contain tens of thousand of atoms. <br/>In one study of a large set of protein—ligand complexes, we tried to improve the free energies of binding by using MD simulations with QM-derived charges, which sometimes led to improved results, but not always. We also ran QM/MM simulations on casein-kinase 2 (CK2), where the ligand and a few surrounding residues were treated at the QM level, and the rest of the system at the MM level. However, those results were unsatisfying. Furthermore, it is important and challenging to accurately model the large entropic contribution to ligand-binding free energies. This entropy largely stems from the fluctuation of the protein and ligand. We tried to estimate this entropy with methods based on fluctuations of interaction energies. We also saw how a combination of theoretical and experimental methods can shed light on phenomena like entropy—entropy compensation and halogen bonding. Additionally, we compared how MD and grand-canonical Monte Carlo (GCMC) can be used to assess dynamics and thermodynamics of protein—ligand binding for both buried and solvent-exposed binding sites.}},
author = {{Ekberg, Vilhelm}},
isbn = {{978-91-7422-962-2}},
keywords = {{free energy perturbation; drug design; ligand-binding affinity; entropy; molecular mechanics; molecular dynamics}},
language = {{eng}},
publisher = {{Lunds universitet, Media-Tryck}},
school = {{Lund University}},
title = {{Free-energy studies of ligand-binding affinities}},
url = {{https://lup.lub.lu.se/search/files/156152167/Vilhelm_Ekberg_avhandling_spikning.pdf}},
year = {{2023}},
}