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Items: 1 to 20 of 117


APoc: large-scale identification of similar protein pockets.

Gao M, Skolnick J.

Bioinformatics. 2013 Mar 1;29(5):597-604. doi: 10.1093/bioinformatics/btt024. Epub 2013 Jan 17.


A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction.

Hoffmann B, Zaslavskiy M, Vert JP, Stoven V.

BMC Bioinformatics. 2010 Feb 22;11:99. doi: 10.1186/1471-2105-11-99.


Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets.

Ashford P, Moss DS, Alex A, Yeap SK, Povia A, Nobeli I, Williams MA.

BMC Bioinformatics. 2012 Mar 14;13:39. doi: 10.1186/1471-2105-13-39.


A comprehensive survey of small-molecule binding pockets in proteins.

Gao M, Skolnick J.

PLoS Comput Biol. 2013 Oct;9(10):e1003302. doi: 10.1371/journal.pcbi.1003302. Epub 2013 Oct 24.


LIGSIFT: an open-source tool for ligand structural alignment and virtual screening.

Roy A, Skolnick J.

Bioinformatics. 2015 Feb 15;31(4):539-44. doi: 10.1093/bioinformatics/btu692. Epub 2014 Oct 21.


Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0.

Zhu X, Xiong Y, Kihara D.

Bioinformatics. 2015 Mar 1;31(5):707-13. doi: 10.1093/bioinformatics/btu724. Epub 2014 Oct 29.


iAlign: a method for the structural comparison of protein-protein interfaces.

Gao M, Skolnick J.

Bioinformatics. 2010 Sep 15;26(18):2259-65. doi: 10.1093/bioinformatics/btq404. Epub 2010 Jul 11.


Comprehensive identification of "druggable" protein ligand binding sites.

An J, Totrov M, Abagyan R.

Genome Inform. 2004;15(2):31-41.


Fpocket: an open source platform for ligand pocket detection.

Le Guilloux V, Schmidtke P, Tuffery P.

BMC Bioinformatics. 2009 Jun 2;10:168. doi: 10.1186/1471-2105-10-168.


aCSM: noise-free graph-based signatures to large-scale receptor-based ligand prediction.

Pires DE, de Melo-Minardi RC, da Silveira CH, Campos FF, Meira W Jr.

Bioinformatics. 2013 Apr 1;29(7):855-61. doi: 10.1093/bioinformatics/btt058. Epub 2013 Feb 8.


Predicting gene ontology functions from protein's regional surface structures.

Liu ZP, Wu LY, Wang Y, Chen L, Zhang XS.

BMC Bioinformatics. 2007 Dec 11;8:475.


The distribution of ligand-binding pockets around protein-protein interfaces suggests a general mechanism for pocket formation.

Gao M, Skolnick J.

Proc Natl Acad Sci U S A. 2012 Mar 6;109(10):3784-9. doi: 10.1073/pnas.1117768109. Epub 2012 Feb 21.


Identification and analysis of conserved pockets on protein surfaces.

Cammisa M, Correra A, Andreotti G, Cubellis MV.

BMC Bioinformatics. 2013;14 Suppl 7:S9. doi: 10.1186/1471-2105-14-S7-S9. Epub 2013 Apr 22.


Self-organizing fuzzy graphs for structure-based comparison of protein pockets.

Reisen F, Weisel M, Kriegl JM, Schneider G.

J Proteome Res. 2010 Dec 3;9(12):6498-510. doi: 10.1021/pr100719n. Epub 2010 Oct 22.


fPOP: footprinting functional pockets of proteins by comparative spatial patterns.

Tseng YY, Chen ZJ, Li WH.

Nucleic Acids Res. 2010 Jan;38(Database issue):D288-95. doi: 10.1093/nar/gkp900. Epub 2009 Oct 30.


MSPocket: an orientation-independent algorithm for the detection of ligand binding pockets.

Zhu H, Pisabarro MT.

Bioinformatics. 2011 Feb 1;27(3):351-8. doi: 10.1093/bioinformatics/btq672. Epub 2010 Dec 6.


Pocketome via comprehensive identification and classification of ligand binding envelopes.

An J, Totrov M, Abagyan R.

Mol Cell Proteomics. 2005 Jun;4(6):752-61. Epub 2005 Mar 9.


eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.

Brylinski M.

PLoS Comput Biol. 2014 Sep 18;10(9):e1003829. doi: 10.1371/journal.pcbi.1003829. eCollection 2014 Sep.


Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

Capra JA, Laskowski RA, Thornton JM, Singh M, Funkhouser TA.

PLoS Comput Biol. 2009 Dec;5(12):e1000585. doi: 10.1371/journal.pcbi.1000585. Epub 2009 Dec 4.

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