3DLigandSite: predicting ligand-binding sites using similar structures

By Mark N. Wass, Lawrence A. Kelley, Michael J.E. Sternberg. 2010

640 citations recorded by the source corpus.

3DLigandSite is a web server for the prediction of ligand-binding sites. It is based upon successful manual methods used in the eighth round of the Critical Assessment of techniques for protein Structure Prediction (CASP8). 3DLigandSite utilizes protein-structure prediction to provide structural models for proteins that have not been solved. Ligands bound to structures similar to the query are superimposed onto the model and used to predict the binding site. In benchmarking against the CASP8 targets 3DLigandSite obtains a Matthew’s correlation co-efficient (MCC) of 0.64, and coverage and accuracy of 71 and 60%, respectively, similar results to our manual performance in CASP8. In further benchmarking using a large set of protein structures, 3DLigandSite obtains an MCC of 0.68. The web server enables users to submit either a query sequence or structure. Predictions are visually displayed via an interactive Jmol applet. 3DLigandSite is available for use at http://www.sbg.bio.ic.ac.uk/3dligandsite.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure (2018, neutral): “3DLigandSite [37] 2010 Template Yes – – –”
Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment (2013, background): “The second structure-based approach is to infer ligand-binding information from the known template proteins, which have similar global and/or local structure to the query (Brylinski and Skolnick, 2008; Roche et al., 2011; Roy et al., 2012; Roy and Zhang, 2012; Wass et al., 2010).”
firestar—advances in the prediction of functionally important residues (2011, methodology): “(7) The combined results from the HHsearch and PSIBLAST searches are displayed on the main output page and the predicted functional residues are highlighted (example output shown, see Figure 1).”
The FTMap family of web servers for determining and characterizing ligand binding hot spots of proteins (2015, methodology): “These methods include 3DLigandSite 61 and FINDSITE 62 .”
Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement (2012, neutral): “Some of them use known protein-ligand complexes as templates (Brylinski and Skolnick, 2008; Glaser et al., 2003; Oh et al., 2009; Tseng and Li, 2011; Wass et al., 2010; Xie and Bourne, 2008), whereas others utilize purely sequence-based homology information (Capra et al., 2009; Huang and Schroeder,…”
Assessment of ligand binding residue predictions in CASP9 (2011, background): “…from sequence, based on sequence conservation,2–7 geometric criteria of the protein surface,8–12 or homology transfer from known structures.13 –17 The function prediction category (FN) was introduced in the 6th Critical Assessment of Protein Structure Prediction (CASP), where predictions for…”
PDBe-KB: collaboratively defining the biological context of structural data (2021, neutral): “Dey Interaction interfaces ISR 3DLigandSite (21) M.”
PrankWeb: a web server for ligand binding site prediction and visualization (2019, methodology): “This is the avenue taken by 3DLigandSite (11), COFAC-TOR (12,13), COACH (14) ISMBLAB-LIG (15) and LI-BRA (16).”
FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins (2011, methodology): “modelling, such as 3D LigandSite [ 15 ] (CASP9- FN017, FN415, FN057, FN072), Mariner1 (CASP8 - FN450) [16] and MetSite [17]; surface accessibility used by the LIGSI-TE csc [18] method and physiochemical properties utilised”
Assessment of ligand binding site predictions in CASP10 (2014, background): “…structure-pocket alignment and binding site clustering guided by the template ligands; CNIO combines predictions from Firestar and 3DLigandSite,12 which clusters superimposed ligands from homologous structures to identify the binding residues; Cofactor_human requires human assistance to…”