Binding affinities in the SAMPL3 trypsin and host-guest blind tests estimated with the MM/PBSA and LIE methods.
(2012) In Journal of Computer-Aided Molecular Design 26(5). p.527-541- Abstract
- We have estimated affinities for the binding of 34 ligands to trypsin and nine guest molecules to three different hosts in the SAMPL3 blind challenge, using the MM/PBSA, MM/GBSA, LIE, continuum LIE, and Glide score methods. For the trypsin challenge, none of the methods were able to accurately predict the experimental results. For the MM/GB(PB)SA and LIE methods, the rankings were essentially random and the mean absolute deviations were much worse than a null hypothesis giving the same affinity to all ligand. Glide scoring gave a Kendall's τ index better than random, but the ranking is still only mediocre, τ = 0.2. However, the range of affinities is small and most of the pairs of ligands have an experimental affinity difference that is... (More)
- We have estimated affinities for the binding of 34 ligands to trypsin and nine guest molecules to three different hosts in the SAMPL3 blind challenge, using the MM/PBSA, MM/GBSA, LIE, continuum LIE, and Glide score methods. For the trypsin challenge, none of the methods were able to accurately predict the experimental results. For the MM/GB(PB)SA and LIE methods, the rankings were essentially random and the mean absolute deviations were much worse than a null hypothesis giving the same affinity to all ligand. Glide scoring gave a Kendall's τ index better than random, but the ranking is still only mediocre, τ = 0.2. However, the range of affinities is small and most of the pairs of ligands have an experimental affinity difference that is not statistically significant. Removing those pairs improves the ranking metric to 0.4-1.0 for all methods except CLIE. Half of the trypsin ligands were non-binders according to the binding assay. The LIE methods could not separate the inactive ligands from the active ones better than a random guess, whereas MM/GBSA and MM/PBSA were slightly better than random (area under the receiver-operating-characteristic curve, AUC = 0.65-0.68), and Glide scoring was even better (AUC = 0.79). For the first host, MM/GBSA and MM/PBSA reproduce the experimental ranking fairly good, with τ = 0.6 and 0.5, respectively, whereas the Glide scoring was considerably worse, with a τ = 0.4, highlighting that the success of the methods is system-dependent. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2273535
- author
- Mikulskis, Paulius LU ; Genheden, Samuel LU ; Rydberg, Patrik LU ; Sandberg, Lars ; Olsen, Lars and Ryde, Ulf LU
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Computer-Aided Molecular Design
- volume
- 26
- issue
- 5
- pages
- 527 - 541
- publisher
- Springer
- external identifiers
-
- wos:000305684900007
- pmid:22198518
- scopus:84859444429
- pmid:22198518
- ISSN
- 1573-4951
- DOI
- 10.1007/s10822-011-9524-z
- 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
- 05e490b3-4532-4c8e-9d16-7d0865bbefc5 (old id 2273535)
- date added to LUP
- 2016-04-01 15:02:08
- date last changed
- 2023-01-12 03:46:44
@article{05e490b3-4532-4c8e-9d16-7d0865bbefc5, abstract = {{We have estimated affinities for the binding of 34 ligands to trypsin and nine guest molecules to three different hosts in the SAMPL3 blind challenge, using the MM/PBSA, MM/GBSA, LIE, continuum LIE, and Glide score methods. For the trypsin challenge, none of the methods were able to accurately predict the experimental results. For the MM/GB(PB)SA and LIE methods, the rankings were essentially random and the mean absolute deviations were much worse than a null hypothesis giving the same affinity to all ligand. Glide scoring gave a Kendall's τ index better than random, but the ranking is still only mediocre, τ = 0.2. However, the range of affinities is small and most of the pairs of ligands have an experimental affinity difference that is not statistically significant. Removing those pairs improves the ranking metric to 0.4-1.0 for all methods except CLIE. Half of the trypsin ligands were non-binders according to the binding assay. The LIE methods could not separate the inactive ligands from the active ones better than a random guess, whereas MM/GBSA and MM/PBSA were slightly better than random (area under the receiver-operating-characteristic curve, AUC = 0.65-0.68), and Glide scoring was even better (AUC = 0.79). For the first host, MM/GBSA and MM/PBSA reproduce the experimental ranking fairly good, with τ = 0.6 and 0.5, respectively, whereas the Glide scoring was considerably worse, with a τ = 0.4, highlighting that the success of the methods is system-dependent.}}, author = {{Mikulskis, Paulius and Genheden, Samuel and Rydberg, Patrik and Sandberg, Lars and Olsen, Lars and Ryde, Ulf}}, issn = {{1573-4951}}, language = {{eng}}, number = {{5}}, pages = {{527--541}}, publisher = {{Springer}}, series = {{Journal of Computer-Aided Molecular Design}}, title = {{Binding affinities in the SAMPL3 trypsin and host-guest blind tests estimated with the MM/PBSA and LIE methods.}}, url = {{https://lup.lub.lu.se/search/files/4307865/3412383.pdf}}, doi = {{10.1007/s10822-011-9524-z}}, volume = {{26}}, year = {{2012}}, }