Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformationCitation formats

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Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformation. / Blundell, Charles D.; Packer, Martin J.; Almond, Andrew.

In: Bioorganic and Medicinal Chemistry, Vol. 21, No. 17, 01.09.2013, p. 4976-4987.

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Blundell, Charles D. ; Packer, Martin J. ; Almond, Andrew. / Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformation. In: Bioorganic and Medicinal Chemistry. 2013 ; Vol. 21, No. 17. pp. 4976-4987.

Bibtex

@article{5a99a5a2147b4550ba6a741a939faeae,
title = "Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformation",
abstract = "Accurate unbound solution 3D-structures of ligands provide unique opportunities for medicinal chemistry and, in particular, a context to understand binding thermodynamics and kinetics. Previous methods of deriving these 3D-structures have had neither the accuracy nor resolution needed for drug design and have not yet realized their potential. Here, we describe and apply a NMR methodology to the aminoglycoside streptomycin that can accurately quantify accessible 3D-space and rank the occupancy of observed conformers to a resolution that enables medicinal chemistry understanding and design. Importantly, it is based upon conventional small molecule NMR techniques and can be performed in physiologically-relevant solvents. The methodology uses multiple datasets, an order of magnitude more experimental data than previous NMR approaches and a dynamic model during refinement, is independent of computational chemistry and avoids the problem of virtual conformations. The refined set of solution 3D-shapes for streptomycin can be grouped into two major families, of which the most populated is almost identical to the 30S ribosomal subunit bioactive shape. We therefore propose that accurate unbound ligand solution conformations may, in some cases, provide a subsidiary route to bioactive shape without crystallography. This experimental technique opens up new opportunities for drug design and more so when complemented with protein co-crystal structures, SAR data and pharmacophore modeling. {\textcopyright} 2013 Elsevier Ltd. All rights reserved.",
keywords = "Aminoglycoside, Antibiotic 30S ribosomal subunit, Bioactive conformation, Ligand binding, NMR, Pharmacophore, Preorganization, Solution conformation, Streptomycin, Virtual screening",
author = "Blundell, {Charles D.} and Packer, {Martin J.} and Andrew Almond",
year = "2013",
month = sep,
day = "1",
doi = "10.1016/j.bmc.2013.06.056",
language = "English",
volume = "21",
pages = "4976--4987",
journal = "Bioorganic & Medicinal Chemistry",
issn = "0968-0896",
publisher = "Elsevier BV",
number = "17",

}

RIS

TY - JOUR

T1 - Quantification of free ligand conformational preferences by NMR and their relationship to the bioactive conformation

AU - Blundell, Charles D.

AU - Packer, Martin J.

AU - Almond, Andrew

PY - 2013/9/1

Y1 - 2013/9/1

N2 - Accurate unbound solution 3D-structures of ligands provide unique opportunities for medicinal chemistry and, in particular, a context to understand binding thermodynamics and kinetics. Previous methods of deriving these 3D-structures have had neither the accuracy nor resolution needed for drug design and have not yet realized their potential. Here, we describe and apply a NMR methodology to the aminoglycoside streptomycin that can accurately quantify accessible 3D-space and rank the occupancy of observed conformers to a resolution that enables medicinal chemistry understanding and design. Importantly, it is based upon conventional small molecule NMR techniques and can be performed in physiologically-relevant solvents. The methodology uses multiple datasets, an order of magnitude more experimental data than previous NMR approaches and a dynamic model during refinement, is independent of computational chemistry and avoids the problem of virtual conformations. The refined set of solution 3D-shapes for streptomycin can be grouped into two major families, of which the most populated is almost identical to the 30S ribosomal subunit bioactive shape. We therefore propose that accurate unbound ligand solution conformations may, in some cases, provide a subsidiary route to bioactive shape without crystallography. This experimental technique opens up new opportunities for drug design and more so when complemented with protein co-crystal structures, SAR data and pharmacophore modeling. © 2013 Elsevier Ltd. All rights reserved.

AB - Accurate unbound solution 3D-structures of ligands provide unique opportunities for medicinal chemistry and, in particular, a context to understand binding thermodynamics and kinetics. Previous methods of deriving these 3D-structures have had neither the accuracy nor resolution needed for drug design and have not yet realized their potential. Here, we describe and apply a NMR methodology to the aminoglycoside streptomycin that can accurately quantify accessible 3D-space and rank the occupancy of observed conformers to a resolution that enables medicinal chemistry understanding and design. Importantly, it is based upon conventional small molecule NMR techniques and can be performed in physiologically-relevant solvents. The methodology uses multiple datasets, an order of magnitude more experimental data than previous NMR approaches and a dynamic model during refinement, is independent of computational chemistry and avoids the problem of virtual conformations. The refined set of solution 3D-shapes for streptomycin can be grouped into two major families, of which the most populated is almost identical to the 30S ribosomal subunit bioactive shape. We therefore propose that accurate unbound ligand solution conformations may, in some cases, provide a subsidiary route to bioactive shape without crystallography. This experimental technique opens up new opportunities for drug design and more so when complemented with protein co-crystal structures, SAR data and pharmacophore modeling. © 2013 Elsevier Ltd. All rights reserved.

KW - Aminoglycoside

KW - Antibiotic 30S ribosomal subunit

KW - Bioactive conformation

KW - Ligand binding

KW - NMR

KW - Pharmacophore

KW - Preorganization

KW - Solution conformation

KW - Streptomycin

KW - Virtual screening

U2 - 10.1016/j.bmc.2013.06.056

DO - 10.1016/j.bmc.2013.06.056

M3 - Article

VL - 21

SP - 4976

EP - 4987

JO - Bioorganic & Medicinal Chemistry

JF - Bioorganic & Medicinal Chemistry

SN - 0968-0896

IS - 17

ER -