Structure-Based Strategies for Drug Design and Discovery

Kuntz, Irwin D.

doi:10.1126/science.257.5073.1078

Cited by 935 publications

(644 citation statements)

References 104 publications

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“…23,24 DOCK calculates possible binding orientations given the structures of ligand and receptor molecules; often, a large database of compounds is searched against a target protein, where each compound is treated as a ligand and the target is treated as the receptor. Simple scoring methods are used to identify the most favorable binding modes of a given molecule and then to rank the molecules.…”

Section: Viewdockmentioning

confidence: 99%

UCSF Chimera—A visualization system for exploratory research and analysis

et al. 2004

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Abstract:The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from

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Section: Viewdockmentioning

confidence: 99%

UCSF Chimera—A visualization system for exploratory research and analysis

et al. 2004

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“…In 2003, Cavasotto and coworkers demonstrated the applicability of this scoring function to the identification of the binding site of retinal in bovine rhodopsin and to the discrimination between binders and nonbinders of rhodopsin [67]. Similarly, using molecular databases spiked with known binders, a number of studies based on combinations of different scoring functions (such as Gold [68], Dock [69], CScore (Tripos), Fresno [70], Score [71], FlexX [72], and PMF [66]) have demonstrated the applicability of molecular docking at GPCR models to virtual screening [9,10,73]. In agreement with the expectations set by these studies, a variety of docking programs and scoring functions have been successfully applied to the discovery of novel ligands for a plethora of GPCRs, including neurorokinin [74,75], adrenergic [76], chemokine [75,77], dopamine [75], serotonin [75,78], cannabinoid [79], and free fatty acid receptors [80], among others.…”

Section: Structure-based Methodologiesmentioning

confidence: 99%

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Costanzi

Tikhonova

Harden

2008

J Comput Aided Mol Des

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SummaryAccurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

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“…However, it depends on the technique used to search and sample molecular configurations, whether the potential molecular flexibility inherent to the energy function will be reflected in the energies and structures of the receptor-ligand complex that are obtained. The most commonly used search and sampling techniques are energy minimization, which only relaxes local strain in a molecular structure, and MC or MD simulation combined with high temperature annealing to extend the search (Goodsell & Olson, 1990;Kuntz, 1992;Stoddard & Koshland, 1992;Hodgkin et al 1993). Although the introduction of flexibility will in general improve the molecular model, it will only do so if the assumption of molecular rigidity is the accuracy limiting factor.…”

Section: Flexibility Of Ligand and Receptormentioning

confidence: 99%