Prediction of SAMPL4 host-guest binding affinities using funnel metadynamics
(2014) In Journal of Computer-Aided Molecular Design 28(4). p.443-454- Abstract
- Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110: 6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding... (More)
- Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110: 6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host-guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300-400 ns per ligand, we show that the errors due to inadequate sampling are below 1 kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11 kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4552281
- author
- Hsiao, Ya-Wen and Söderhjelm, Pär LU
- organization
- publishing date
- 2014
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Funnel metadynamics, Binding affinity, CGENFF, GAFF, NAMD
- in
- Journal of Computer-Aided Molecular Design
- volume
- 28
- issue
- 4
- pages
- 443 - 454
- publisher
- Springer
- external identifiers
-
- wos:000337043500010
- scopus:84902793534
- ISSN
- 1573-4951
- DOI
- 10.1007/s10822-014-9724-4
- language
- English
- LU publication?
- yes
- additional info
- The information about affiliations in this record was updated in December 2015. The record was previously connected to the following departments: Theoretical Chemistry (S) (011001039)
- id
- 53890904-19f8-4768-96f2-953ee3b1f94d (old id 4552281)
- date added to LUP
- 2016-04-01 13:27:53
- date last changed
- 2023-04-06 07:22:18
@article{53890904-19f8-4768-96f2-953ee3b1f94d,
abstract = {{Accurately predicting binding affinities between ligands and macromolecules has been a much sought-after goal. A tremendous amount of resources can be saved in the pharmaceutical industry through accurate binding-affinity prediction and hence correct decision-making for the drug discovery processes. Owing to the structural complexity of macromolecules, one of the issues in binding affinity prediction using molecular dynamics is the adequate sampling of the conformational space. Recently, the funnel metadynamics method (Limongelli et al. in Proc Natl Acad Sci USA 110: 6358, 2013) was developed to enhance the sampling of the ligand at the binding site as well as in the solvated state, and offer the possibility to predict the absolute binding free energy. We apply funnel metadynamics to predict host-guest binding affinities for the cucurbit[7]uril host as part of the SAMPL4 blind challenge. Using total simulation times of 300-400 ns per ligand, we show that the errors due to inadequate sampling are below 1 kcal/mol. However, despite the large investment in terms of computational time, the results compared to experiment are not better than a random guess. As we obtain differences of up to 11 kcal/mol when switching between two commonly used force fields (with automatically generated parameters), we strongly believe that in the pursuit of accurate binding free energies a more careful force-field parametrization is needed to address this type of system.}},
author = {{Hsiao, Ya-Wen and Söderhjelm, Pär}},
issn = {{1573-4951}},
keywords = {{Funnel metadynamics; Binding affinity; CGENFF; GAFF; NAMD}},
language = {{eng}},
number = {{4}},
pages = {{443--454}},
publisher = {{Springer}},
series = {{Journal of Computer-Aided Molecular Design}},
title = {{Prediction of SAMPL4 host-guest binding affinities using funnel metadynamics}},
url = {{http://dx.doi.org/10.1007/s10822-014-9724-4}},
doi = {{10.1007/s10822-014-9724-4}},
volume = {{28}},
year = {{2014}},
}