A 3D-QSAR-driven approach to binding mode and affinity prediction

Research output: Contribution to journal › Journal article › peer-review

Standard

A 3D-QSAR-driven approach to binding mode and affinity prediction. / Tosco, Paolo; Balle, Thomas.

In: Journal of Chemical Information and Modeling, Vol. 52, No. 2, 2012, p. 302-307.

Research output: Contribution to journal › Journal article › peer-review

Harvard

Tosco, P & Balle, T 2012, 'A 3D-QSAR-driven approach to binding mode and affinity prediction', Journal of Chemical Information and Modeling, vol. 52, no. 2, pp. 302-307. https://doi.org/10.1021/ci200411s

APA

Tosco, P., & Balle, T. (2012). A 3D-QSAR-driven approach to binding mode and affinity prediction. Journal of Chemical Information and Modeling, 52(2), 302-307. https://doi.org/10.1021/ci200411s

Vancouver

Tosco P, Balle T. A 3D-QSAR-driven approach to binding mode and affinity prediction. Journal of Chemical Information and Modeling. 2012;52(2):302-307. https://doi.org/10.1021/ci200411s

Author

Tosco, Paolo ; Balle, Thomas. / A 3D-QSAR-driven approach to binding mode and affinity prediction. In: Journal of Chemical Information and Modeling. 2012 ; Vol. 52, No. 2. pp. 302-307.

Bibtex

@article{4da2ff16517f4d469deaafdbdc69a2c0,
title = "A 3D-QSAR-driven approach to binding mode and affinity prediction",
abstract = "A method for predicting the binding mode of a series of ligands is proposed. The procedure relies on three-dimensional quantitative structure-activity relationships (3D-QSAR) and does not require structural knowledge of the binding site. Candidate alignments are automatically built and ranked according to a consensus scoring function. 3D-QSAR analysis based on the selected binding mode enables affinity prediction of new drug candidates having less than 10 rotatable bonds.",
keywords = "Former Faculty of Pharmaceutical Sciences",
author = "Paolo Tosco and Thomas Balle",
year = "2012",
doi = "10.1021/ci200411s",
language = "English",
volume = "52",
pages = "302--307",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",
number = "2",

}

RIS

TY - JOUR

T1 - A 3D-QSAR-driven approach to binding mode and affinity prediction

AU - Tosco, Paolo

AU - Balle, Thomas

PY - 2012

Y1 - 2012

N2 - A method for predicting the binding mode of a series of ligands is proposed. The procedure relies on three-dimensional quantitative structure-activity relationships (3D-QSAR) and does not require structural knowledge of the binding site. Candidate alignments are automatically built and ranked according to a consensus scoring function. 3D-QSAR analysis based on the selected binding mode enables affinity prediction of new drug candidates having less than 10 rotatable bonds.

AB - A method for predicting the binding mode of a series of ligands is proposed. The procedure relies on three-dimensional quantitative structure-activity relationships (3D-QSAR) and does not require structural knowledge of the binding site. Candidate alignments are automatically built and ranked according to a consensus scoring function. 3D-QSAR analysis based on the selected binding mode enables affinity prediction of new drug candidates having less than 10 rotatable bonds.

KW - Former Faculty of Pharmaceutical Sciences

U2 - 10.1021/ci200411s

DO - 10.1021/ci200411s

M3 - Journal article

C2 - 22087561

VL - 52

SP - 302

EP - 307

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 2

ER -

ID: 37536555