Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

Laurie, Alasdair T. R.; Jackson, Richard M.

doi:10.1093/bioinformatics/bti315

Cited by 915 publications

(753 citation statements)

References 44 publications

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“…The degree of conservation is subdivided into nine grades, with grade 1 being the least and grade 9 being most conserved. Ligand binding sites (LBS) were identified with the Q-SiteFinder (Laurie & Jackson, 2005) (http://www.modelling.leeds.ac.uk/qsitefinder/) that evaluates the interaction energy between a CH 3 van der Waals probe and the protein (Laurie & Jackson, 2005). The resulting binding sites were formed from clusters of probes and ranked according to the sum of total binding energies for each cluster.…”

Section: Methodsmentioning

confidence: 99%

“…Among the ten best LBS reported by Q-SiteFinder (Laurie & Jackson, 2005), five were chosen on the basis of the number of conserved residues around the LBS ( Table 2). Note that the sites are not numbered sequentially, but the numbers represent the original ranking reported by QSiteFinder, whereby the highest ranking binding site is denoted as site 1.…”

Section: Predicted Lbsmentioning

confidence: 99%

See 1 more Smart Citation

Large-scale analysis of influenza A virus sequences reveals potential drug target sites of non-structural proteins

Darapaneni

Prabhaker

Kukol

2009

Journal of General Virology

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Section: Methodsmentioning

confidence: 99%

Section: Predicted Lbsmentioning

confidence: 99%

Large-scale analysis of influenza A virus sequences reveals potential drug target sites of non-structural proteins

Darapaneni

Prabhaker

Kukol

2009

Journal of General Virology

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“…In Table I, a short summary is given on some PS methods used in this study. These methods are citation-classics (Q-SiteFinder 24 and Pass 26 ), and a novel, promising program Sitehound 23 is also included. The PS algorithms use either geometrical or simplified, chemical grid-based search routines, and represent the putative binding pockets as a cluster of probe spheres.…”

Section: Introductionmentioning

confidence: 99%

Toward prediction of functional protein pockets using blind docking and pocket search algorithms

Hetényi

Spoel

2011

Protein Science

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Location of functional binding pockets of bioactive ligands on protein molecules is essential in structural genomics and drug design projects. If the experimental determination of ligand-protein complex structures is complicated, blind docking (BD) and pocket search (PS) calculations can help in the prediction of atomic resolution binding mode and the location of the pocket of a ligand on the entire protein surface. Whereas the number of successful predictions by these methods is increasing even for the complicated cases of exosites or allosteric binding sites, their reliability has not been fully established. For a critical assessment of reliability, we use a set of ligand-protein complexes, which were found to be problematic in previous studies. The robustness of BD and PS methods is addressed in terms of success of the selection of truly functional pockets from among the many putative ones identified on the surfaces of ligand-bound and ligand-free (holo and apo) protein forms. Issues related to BD such as effect of hydration, existence of multiple pockets, and competition of subsidiary ligands are considered. Practical cases of PS are discussed, categorized and strategies are recommended for handling the different situations. PS can be used in conjunction with BD, as we find that a consensus approach combining the techniques improves predictive power.

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“…The active site residues of the UBE2D4 protein are identified using CASTp [45], Q-site Finder [46] and SiteMap [47] tools. The protein-protein docking of the UBE2D4 with its natural substrate ubiquitin ligase CHIP is carried out using PatchDock server [48] to identify the binding site region and residues in the UBE2D4 protein.…”

Section: Active Site Predictionmentioning

confidence: 99%

Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery–a structure-based approach

et al. 2016

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Cancer progression is a global burden. The incidence and mortality now reach 30 million deaths per year. Several pathways of cancer are under investigation for the discovery of effective therapeutics. The present study highlights the structural details of the ubiquitin protein 'Ubiquitin-conjugating enzyme E2D4' (UBE2D4) for the novel lead structure identification in cancer drug discovery process. The evaluation of 3D structure of UBE2D4 was carried out using homology modelling techniques. The optimized structure was validated by standard computational protocols. The active site region of the UBE2D4 was identified using computational tools like CASTp, Q-site Finder and SiteMap. The hydrophobic pocket which is responsible for binding with its natural receptor ubiquitin ligase CHIP (C-terminal of Hsp 70 interacting protein) was identified through proteinprotein docking study. Corroborating the results obtained from active site prediction tools and protein-protein docking study, the domain of UBE2D4 which is responsible for cancer cell progression is sorted out for further docking study. Virtual screening with large structural database like CB_Div Set and Asinex BioDesign small molecular structural database was carried out. The obtained new ligand molecules that have shown affinity towards UBE2D4 were considered for ADME prediction studies. The identified new ligand molecules with acceptable parameters of docking, ADME are considered as potent UBE2D4 enzyme inhibitors for cancer therapy.

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Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites

Abstract: Both Q-SiteFinder and Pocket-Finder have been made available online at http://www.bioinformatics.leeds.ac.uk/qsitefinder and http://www.bioinformatics.leeds.ac.uk/pocketfinder

Cited by 915 publications

References 44 publications

Large-scale analysis of influenza A virus sequences reveals potential drug target sites of non-structural proteins

Large-scale analysis of influenza A virus sequences reveals potential drug target sites of non-structural proteins

Toward prediction of functional protein pockets using blind docking and pocket search algorithms

Targeting the ubiquitin-conjugating enzyme E2D4 for cancer drug discovery–a structure-based approach

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