Strategies for 3D pharmacophore-based virtual screening

Seidel, Thomas; Ibis, Gökhan; Bendix, Fabian; Wolber, Gerhard

doi:10.1016/j.ddtec.2010.11.004

Cited by 116 publications

(79 citation statements)

References 32 publications

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“…All feature groups are graphically represented by three-dimensional volumetric feature density clouds, which are statistically characterized by occurrence frequency and interaction patterns with the protein. The dynophore algorithm was implemented within the LigandScout framework (63,64,70).…”

Section: Site-directed Mutagenesis and Generation Of Stable Cellmentioning

confidence: 99%

Ligand Binding Ensembles Determine Graded Agonist Efficacies at a G Protein-coupled Receptor

Böck

Bermudez

Krebs

et al. 2016

Journal of Biological Chemistry

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G protein-coupled receptors constitute the largest family of membrane receptors and modulate almost every physiological process in humans. Binding of agonists to G protein-coupled receptors induces a shift from inactive to active receptor conformations. Biophysical studies of the dynamic equilibrium of receptors suggest that a portion of receptors can remain in inactive states even in the presence of saturating concentrations of agonist and G protein mimetic. However, the molecular details of agonist-bound inactive receptors are poorly understood.Here we use the model of bitopic orthosteric/allosteric (i.e. dualsteric) agonists for muscarinic M 2 receptors to demonstrate the existence and function of such inactive agonist⅐receptor complexes on a molecular level. Using all-atom molecular dynamics simulations, dynophores (i.e. a combination of static three-dimensional pharmacophores and molecular dynamics-based conformational sampling), ligand design, and receptor mutagenesis, we show that inactive agonist⅐receptor complexes can result from agonist binding to the allosteric vestibule alone, whereas the dualsteric binding mode produces active receptors. Each agonist forms a distinct ligand binding ensemble, and different agonist efficacies depend on the fraction of purely allosteric (i.e. inactive) versus dualsteric (i.e. active) binding modes. We propose that this concept may explain why agonist⅐receptor complexes can be inactive and that adopting multiple binding modes may be generalized also to small agonists where binding modes will be only subtly different and confined to only one binding site.Specific and coordinated cell-to-cell communication regulates the flow of information between cells, and proper information processing ensures physiological functions of biological systems. G protein-coupled receptors (GPCRs), 8 constituting the largest class of membrane proteins in mammals, are essential mediators of chemically and light-encoded information (1-4). GPCRs sense a great variety of extracellular stimuli, e.g. neurotransmitters and hormones, and subsequently translate this information into an intracellular response via G proteins, ␤-arrestins, and possibly GPCR-interacting proteins (2-5). Because of their abundance and relevance in regulating the majority of (patho-)physiological processes in humans, GPCRs have for a long time represented the most important drug targets being addressed by at least a third of all currently marketed drugs (6, 7).Agonist binding leads to receptor activation, which is followed by intracellular G protein recruitment and subsequent cell signaling. Breakthroughs in GPCR crystallography have led to inactive and active crystal structures of the same receptor protein. Among these are rhodopsin (8 -10) and more recently the ␤ 2 -adrenergic (11-14), M 2 muscarinic (15, 16), and -opioid receptors (17, 18). These structures most likely represent energetically favored, relatively stable inactive and active receptor⅐ligand complexes. Despite the diversity of crystallized receptors, a common...

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Section: Site-directed Mutagenesis and Generation Of Stable Cellmentioning

confidence: 99%

Ligand Binding Ensembles Determine Graded Agonist Efficacies at a G Protein-coupled Receptor

Böck

Bermudez

Krebs

et al. 2016

Journal of Biological Chemistry

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“…The active site was determined by selecting all residues with any atom within 7 Å from the outside atoms the co-crystallized ligand for 2QBS, and the analogue residues for the other two PDB structures using the sequence alignment and structure overlay functionality of the software tool MOE [68] provided by the Chemical Computing Group (http://www.chemcomp.com/). Docking was performed without any constraints and all compounds were minimized using LigandScout's [66,69,70] general purpose MMFF94 implementation after docking. In order to get the most probable binding poses, a 3D pharmacophore was developed using LigandScout.…”

Section: Molecular Modellingmentioning

confidence: 99%

New 4-[(5-arylidene-2-arylimino-4-oxo-3-thiazolidinyl)methyl]benzoic acids active as protein tyrosine phosphatase inhibitors endowed with insulinomimetic effect on mouse C2C12 skeletal muscle cells

Ottanà

Maccari

Amuso

et al. 2012

European Journal of Medicinal Chemistry

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a b s t r a c tIn pursuing our research targeting the identification of potent inhibitors of PTP1B and LMW-PTP, we have identified new 4-[(5-arylidene-2-arylimino-4-oxo-3-thiazolidinyl)methyl]benzoic acids endowed with interesting in vitro inhibitory profiles. Most compounds proved to be inhibitors of PTP1B and LMW-PTP isoform IF1. The tested inhibitors also showed selectivity towards PTP1B over the closely related TC-PTP. These compounds were found to activate the insulin-mediated signalling on mouse C2C12 skeletal muscle cells by increasing the phosphorylation levels of the insulin receptor and promoting cellular 2-deoxyglucose uptake.Interestingly, 4-{[5-(4-benzyloxybenzylidene)-2-(4-trifluoromethylphenylimino)-4-oxo-3-thiazolidinyl] methyl}benzoic acid (7d), the best in vitro inhibitor of PTP1B and the isoform IF1 of LMW-PTP, provided the highest activation level of the insulin receptor and was found to be endowed with an excellent insulinomimetic effect on the selected cells. This compound therefore represents an interesting lead compound for developing novel PTP1B and LMW-PTP inhibitors which could be achieved by improving both its pharmacological profile and its potentiating effects on insulin signalling.

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“…The careful arrangement of chemical feature markers in 3D space to search molecules that fulfill the required interactions is one of the most successful approaches of VS and has led to many success stories for retrospective explanation of ligand affinity and subsequently to prospective ligand design [15][16][17][18][19][20]. While ligand-based pharmacophore creation has been introduced in the early days of molecular modeling, structure-based 3D pharmacophore design has been introduced more recently: The program LigandScout [21][22][23] derives pharmacophores from protein-ligand complexes, interprets ligand geometries, assigns correct hybridization states and applies a set of rules that classifies plausible protein-ligand interactions. For subsequent VS, a computationally efficient pattern-matching algorithm was implemented that allows for geometrically highly accurate VS. Other programs such as catalyst [24], MOE [25] and phase [26] use cascading n-point pharmacophore fingerprints for pharmacophore-molecule superpositioning.…”

Section: Methods For Virtual Screeningmentioning

confidence: 99%

In silico virtual screening approaches for anti-viral drug discovery

Murgueitio

Bermudez

Mortier

et al. 2012

Drug Discovery Today: Technologies

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Despite the considerable advances in medical and pharmaceutical research during the past years, diseases caused by viruses have remained a major burden to public health. Virtual in silico screening has repeatedly proven to be useful to meet the special challenges of antiviral drug discovery. Large virtual compound libraries are filtered by different computational screening methods such as docking, ligand-based similarity searches or pharmacophore-based screening, reducing the number of candidate molecules to a smaller set of promising candidates that are then tested biologically. This rational approach makes the drug discovery process more goal-oriented and saves resources in terms of time and money. In this review we discuss how different virtual screening techniques can be applied to antiviral drug discovery, present recent success stories in this field and finally address the main differences between the methods.:

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Strategies for 3D pharmacophore-based virtual screening

Cited by 116 publications

References 32 publications

Ligand Binding Ensembles Determine Graded Agonist Efficacies at a G Protein-coupled Receptor

Ligand Binding Ensembles Determine Graded Agonist Efficacies at a G Protein-coupled Receptor

New 4-[(5-arylidene-2-arylimino-4-oxo-3-thiazolidinyl)methyl]benzoic acids active as protein tyrosine phosphatase inhibitors endowed with insulinomimetic effect on mouse C2C12 skeletal muscle cells

In silico virtual screening approaches for anti-viral drug discovery

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