LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

By Bingding Huang, M. Schroeder. BMC Structural Biology, 2006

451 citations recorded by the source corpus.

BackgroundIdentifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed.ResultsWe present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcscis based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcscperforms slightly better than the other tools and achieves a success rate of 71% and 75%, respectively.ConclusionThe use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcscand its source code is available at scoppi.biotec.tu-dresden.de/pocket.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/8a7ee9e0645ffbdb8ab8e4f8a38965982f44332d

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Citations in the corpus

The FTMap family of web servers for determining and characterizing ligand binding hot spots of proteins (2015, methodology): “This category includes methods such as POCKET 56 , LIGSITE 57,58 , PASS 59 and CASTp 60 .”
Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation than the Rest of the Protein Surface (2013, methodology): “Identifying pockets on protein surfaces We implemented our modified version of the LIGSITE [28]”
Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure (2009, methodology): “A similar approach uses the average conservation of all residues near the pocket (‘‘Dist-Cons’’) [1] to rank the pockets and assign rank-based scores to residues.”
MOLE 2.0: advanced approach for analysis of biomacromolecular channels (2013, methodology): “These methods are used in numerous software tools, such as POCKET [24], LIGSITE [25,26], dxTuber [27], HOLLOW [28], 3V [29], CAVER 1.”
PointSite: a point cloud segmentation tool for identification of protein ligand binding atoms (2019, methodology): “MetaPocket2 [18, 47] [47, 18] is a meta server to identify LBS based on the identification results from the eight popular pocket-centric methods: LIGSITEcsc [19], PASS [3], Q-SiteFinder [26], SURFNET [25], Fpocket (version 1) [28], GHECOM [22], ConCavity [5] and POCASA [45].”
Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement (2012, unknown): “, 2010; Xie and Bourne, 2008), whereas others utilize purely sequence-based homology information (Capra et al., 2009; Huang and Schroeder, 2006; Laskowski, 1995).”
Roll: a new algorithm for the detection of protein pockets and cavities with a rolling probe sphere (2010, methodology): “Two extensions of LIGSITE, LIGSITEcs using the protein’s Connolly Surface (Connolly, 1983) and LIGSITEcsc (Huang et al., 2006) ranking pockets with the degree of conservation obtained from the ConSurf-HSSP database (Glaser et al., 2005), were developed, but LIGSITEcsc is no longer a purely geometric”
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 LIGSITE [18] method and physiochemical properties utilised by SCREEN [19].”
MetaPocket: A Meta Approach to Improve Protein Ligand Binding Site Prediction (2009, unknown): “In our previous work (Huang and Schroeder, 2006), we made two extensions to LIGSITE.”
Fast Docking on Graphics Processing Units via Ray-Casting (2013, methodology): “Solvent points which lie on a line between two protein points are then marked as ‘‘pocket’’ (to denote concave regions on the protein surface); this approach was originally used in the LigASite software [36].”
Selectivity by Small-Molecule Inhibitors of Protein Interactions Can Be Driven by Protein Surface Fluctuations (2015, unknown): “Our implementation differs from the original LIGSITE algorithm (50) in that our search is restricted to the”