Docking and scoring of metallo-beta-lactamases inhibitors

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Docking and scoring of metallo-beta-lactamases inhibitors. / Olsen, Lars; Pettersson, Ingrid; Hemmingsen, Lars; Adolph, Hans-Werner; Jørgensen, Flemming Steen.

In: Journal of Computer - Aided Molecular Design, Vol. 18, No. 4, 2004, p. 287-302.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Olsen, L, Pettersson, I, Hemmingsen, L, Adolph, H-W & Jørgensen, FS 2004, 'Docking and scoring of metallo-beta-lactamases inhibitors', Journal of Computer - Aided Molecular Design, vol. 18, no. 4, pp. 287-302. <http://www.ncbi.nlm.nih.gov/pubmed/15562992>

APA

Olsen, L., Pettersson, I., Hemmingsen, L., Adolph, H-W., & Jørgensen, F. S. (2004). Docking and scoring of metallo-beta-lactamases inhibitors. Journal of Computer - Aided Molecular Design, 18(4), 287-302. http://www.ncbi.nlm.nih.gov/pubmed/15562992

Vancouver

Olsen L, Pettersson I, Hemmingsen L, Adolph H-W, Jørgensen FS. Docking and scoring of metallo-beta-lactamases inhibitors. Journal of Computer - Aided Molecular Design. 2004;18(4):287-302.

Author

Olsen, Lars ; Pettersson, Ingrid ; Hemmingsen, Lars ; Adolph, Hans-Werner ; Jørgensen, Flemming Steen. / Docking and scoring of metallo-beta-lactamases inhibitors. In: Journal of Computer - Aided Molecular Design. 2004 ; Vol. 18, No. 4. pp. 287-302.

Bibtex

@article{dc9ea7a72e4e4657893dce38422b969a,
title = "Docking and scoring of metallo-beta-lactamases inhibitors",
abstract = "The performance of the AutoDock, GOLD and FlexX docking programs was evaluated for docking of dicarboxylic acid inhibitors into metallo-beta-lactamases (MBLs). GOLD provided the best overall performance, with RMSDs between experimental and docked structures of 1.8-2.6 A and a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. GOLD was selected for a test including a broad spectrum of inhibitors for which experimental MBL-inhibitor binding affinities are available. This study revealed that (1) for most compound classes (dicarboxylic acids, tetrazoles, sulfonylhydrazones, and peptide-like compounds) there is a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores, (2) the correlation only holds within a given class, that is, scores of compounds from different classes cannot be directly compared, (3) for some compound classes (e.g. small sulphur compounds) there is no direct correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. Using partial least squares methods, a model with R2 = 0.82 and Q2 = 0.78 for the training set was obtained based on the GOLD score and descriptors associated with binding of the IMP-1 inhibitors to the enzyme. The external Q2 for the test set is 0.73. This final model for prediction of IMP-1 MBL-inhibitor affinity handled all known classes of MBL-inhibitors, except small sulphur compounds.",
keywords = "Computational Biology, Enzyme Inhibitors, Ligands, Models, Molecular, Protein Binding, Software, Succinic Acids, beta-Lactamases",
author = "Lars Olsen and Ingrid Pettersson and Lars Hemmingsen and Hans-Werner Adolph and J{\o}rgensen, {Flemming Steen}",
year = "2004",
language = "English",
volume = "18",
pages = "287--302",
journal = "Journal of Computer-Aided Molecular Design",
issn = "0920-654X",
publisher = "Springer",
number = "4",

}

RIS

TY - JOUR

T1 - Docking and scoring of metallo-beta-lactamases inhibitors

AU - Olsen, Lars

AU - Pettersson, Ingrid

AU - Hemmingsen, Lars

AU - Adolph, Hans-Werner

AU - Jørgensen, Flemming Steen

PY - 2004

Y1 - 2004

N2 - The performance of the AutoDock, GOLD and FlexX docking programs was evaluated for docking of dicarboxylic acid inhibitors into metallo-beta-lactamases (MBLs). GOLD provided the best overall performance, with RMSDs between experimental and docked structures of 1.8-2.6 A and a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. GOLD was selected for a test including a broad spectrum of inhibitors for which experimental MBL-inhibitor binding affinities are available. This study revealed that (1) for most compound classes (dicarboxylic acids, tetrazoles, sulfonylhydrazones, and peptide-like compounds) there is a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores, (2) the correlation only holds within a given class, that is, scores of compounds from different classes cannot be directly compared, (3) for some compound classes (e.g. small sulphur compounds) there is no direct correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. Using partial least squares methods, a model with R2 = 0.82 and Q2 = 0.78 for the training set was obtained based on the GOLD score and descriptors associated with binding of the IMP-1 inhibitors to the enzyme. The external Q2 for the test set is 0.73. This final model for prediction of IMP-1 MBL-inhibitor affinity handled all known classes of MBL-inhibitors, except small sulphur compounds.

AB - The performance of the AutoDock, GOLD and FlexX docking programs was evaluated for docking of dicarboxylic acid inhibitors into metallo-beta-lactamases (MBLs). GOLD provided the best overall performance, with RMSDs between experimental and docked structures of 1.8-2.6 A and a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. GOLD was selected for a test including a broad spectrum of inhibitors for which experimental MBL-inhibitor binding affinities are available. This study revealed that (1) for most compound classes (dicarboxylic acids, tetrazoles, sulfonylhydrazones, and peptide-like compounds) there is a good correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores, (2) the correlation only holds within a given class, that is, scores of compounds from different classes cannot be directly compared, (3) for some compound classes (e.g. small sulphur compounds) there is no direct correlation between the experimentally determined MBL-inhibitor affinities and the GOLD scores. Using partial least squares methods, a model with R2 = 0.82 and Q2 = 0.78 for the training set was obtained based on the GOLD score and descriptors associated with binding of the IMP-1 inhibitors to the enzyme. The external Q2 for the test set is 0.73. This final model for prediction of IMP-1 MBL-inhibitor affinity handled all known classes of MBL-inhibitors, except small sulphur compounds.

KW - Computational Biology

KW - Enzyme Inhibitors

KW - Ligands

KW - Models, Molecular

KW - Protein Binding

KW - Software

KW - Succinic Acids

KW - beta-Lactamases

M3 - Journal article

C2 - 15562992

VL - 18

SP - 287

EP - 302

JO - Journal of Computer-Aided Molecular Design

JF - Journal of Computer-Aided Molecular Design

SN - 0920-654X

IS - 4

ER -

ID: 38393938