Homology-Modelling Protein–Ligand Interactions: Allowing for Ligand-Induced Conformational Change

Dalton, James A. R.; Jackson, Richard M.

doi:10.1016/j.jmb.2010.04.047

Cited by 26 publications

(23 citation statements)

References 44 publications

(70 reference statements)

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“…It was also proved that applying this methodology more accurate ligand-protein models were obtained, with respect to docking in already refined models [73]. Recently Thomas et al developed homology models for the acetylcholine muscarinic receptors M₁R-M₅R, again using the β₂-adrenergic receptor as template, and highlighted how optimizing the binding site with ligand information has a stronger impact on the quality of the final model than target-template sequence similarity [74].…”

Section: Integral Binding-site Modeling and Refinementmentioning

confidence: 99%

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description

Spyrakis

Cavasotto

2015

Archives of Biochemistry and Biophysics

106

104

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Section: Integral Binding-site Modeling and Refinementmentioning

confidence: 99%

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description

Spyrakis

Cavasotto

2015

Archives of Biochemistry and Biophysics

106

104

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“…Such approaches often require expert knowledge and time-consuming manual intervention, and hence call for the development of fully automatic homology modelling pipelines. Dalton and Jackson [21] have developed and assessed two variants of LSM, both yielding significantly more accurate complex models than docking into static homology models, regardless of whether or not the ligand had been incorporated into the modelling process. The most successful variant utilises geometric hashing and shape-based superposition of the ligand to be built onto a known ligand in a template structure, prior to the modelling procedure.…”

Section: Lsm: Ligand-steered Modellingmentioning

confidence: 99%

Modelling three-dimensional protein structures for applications in drug design

Schmidt

Bergner

Schwede

2014

Drug Discovery Today

138

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A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.

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“…Recently, Dalton et. al presented a “hybrid-template modeling” method which includes the ligand bound to the template at the beginning of homology modeling [91]. This method appears to be very promising when a suitable protein-ligand template can be identified.…”

Section: Molecular Modeling Of Off-target Binding On a Structural mentioning

confidence: 99%

Structure-based systems biology for analyzing off-target binding

Xie

Bourne

2011

Current Opinion in Structural Biology

135

113

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Here off-target binding implies the binding of a small molecule of therapeutic interest to a protein target other than the primary target for which it was intended. Increasingly such off-targeting appears to be the norm rather than the exception, rational drug design notwithstanding, and can lead to detrimental side-effects, or opportunities to reposition a therapeutic agent to treat a different condition. Not surprisingly, there is significant interest in determining a priori what off-targets exist on a proteome-wide scale. Beyond determining putative off-targets is the need to understand the impact of such binding on the complete biological system, with the ultimate goal of being able to predict the phenotypic outcome. While a very ambitious goal, some progress is being made.

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Homology-Modelling Protein–Ligand Interactions: Allowing for Ligand-Induced Conformational Change

Cited by 26 publications

References 44 publications

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description

Open challenges in structure-based virtual screening: Receptor modeling, target flexibility consideration and active site water molecules description

Modelling three-dimensional protein structures for applications in drug design

Structure-based systems biology for analyzing off-target binding

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