Literature DB >> 21537951

Beyond structural genomics: computational approaches for the identification of ligand binding sites in protein structures.

Dario Ghersi1, Roberto Sanchez.   

Abstract

Structural genomics projects have revealed structures for a large number of proteins of unknown function. Understanding the interactions between these proteins and their ligands would provide an initial step in their functional characterization. Binding site identification methods are a fast and cost-effective way to facilitate the characterization of functionally important protein regions. In this review we describe our recently developed methods for binding site identification in the context of existing methods. The advantage of energy-based approaches is emphasized, since they provide flexibility in the identification and characterization of different types of binding sites.

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Year:  2011        PMID: 21537951      PMCID: PMC3127736          DOI: 10.1007/s10969-011-9110-6

Source DB:  PubMed          Journal:  J Struct Funct Genomics        ISSN: 1345-711X


  61 in total

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Journal:  J Chem Inf Model       Date:  2007-09-27       Impact factor: 4.956

4.  Identifying and characterizing binding sites and assessing druggability.

Authors:  Thomas A Halgren
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5.  Automated identification of binding sites for phosphorylated ligands in protein structures.

Authors:  Dario Ghersi; Roberto Sanchez
Journal:  Proteins       Date:  2012-07-07

6.  TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.

Authors:  A C Wallace; N Borkakoti; J M Thornton
Journal:  Protein Sci       Date:  1997-11       Impact factor: 6.725

7.  Protein clefts in molecular recognition and function.

Authors:  R A Laskowski; N M Luscombe; M B Swindells; J M Thornton
Journal:  Protein Sci       Date:  1996-12       Impact factor: 6.725

8.  The X-ray crystal structures of human alpha-phosphomannomutase 1 reveal the structural basis of congenital disorder of glycosylation type 1a.

Authors:  Nicholas R Silvaggi; Chunchun Zhang; Zhibing Lu; Jianying Dai; Debra Dunaway-Mariano; Karen N Allen
Journal:  J Biol Chem       Date:  2006-03-15       Impact factor: 5.157

9.  Detection of pockets on protein surfaces using small and large probe spheres to find putative ligand binding sites.

Authors:  Takeshi Kawabata; Nobuhiro Go
Journal:  Proteins       Date:  2007-08-01

10.  Fpocket: an open source platform for ligand pocket detection.

Authors:  Vincent Le Guilloux; Peter Schmidtke; Pierre Tuffery
Journal:  BMC Bioinformatics       Date:  2009-06-02       Impact factor: 3.169

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  15 in total

1.  SiteComp: a server for ligand binding site analysis in protein structures.

Authors:  Yingjie Lin; Seungyeul Yoo; Roberto Sanchez
Journal:  Bioinformatics       Date:  2012-02-24       Impact factor: 6.937

Review 2.  Pocket-based drug design: exploring pocket space.

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Journal:  AAPS J       Date:  2012-11-22       Impact factor: 4.009

3.  AutoSite: an automated approach for pseudo-ligands prediction-from ligand-binding sites identification to predicting key ligand atoms.

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Journal:  Bioinformatics       Date:  2016-06-26       Impact factor: 6.937

4.  Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey.

Authors:  Tiago Simões; Daniel Lopes; Sérgio Dias; Francisco Fernandes; João Pereira; Joaquim Jorge; Chandrajit Bajaj; Abel Gomes
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Review 5.  Bioinformatics and variability in drug response: a protein structural perspective.

Authors:  Jennifer L Lahti; Grace W Tang; Emidio Capriotti; Tianyun Liu; Russ B Altman
Journal:  J R Soc Interface       Date:  2012-05-02       Impact factor: 4.118

6.  Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics.

Authors:  Richard D Smith; Heather A Carlson
Journal:  J Chem Inf Model       Date:  2021-02-18       Impact factor: 4.956

7.  PepSite: prediction of peptide-binding sites from protein surfaces.

Authors:  Leonardo G Trabuco; Stefano Lise; Evangelia Petsalaki; Robert B Russell
Journal:  Nucleic Acids Res       Date:  2012-05-16       Impact factor: 16.971

8.  POVME 2.0: An Enhanced Tool for Determining Pocket Shape and Volume Characteristics.

Authors:  Jacob D Durrant; Lane Votapka; Jesper Sørensen; Rommie E Amaro
Journal:  J Chem Theory Comput       Date:  2014-09-29       Impact factor: 6.006

9.  Exploring the composition of protein-ligand binding sites on a large scale.

Authors:  Nickolay A Khazanov; Heather A Carlson
Journal:  PLoS Comput Biol       Date:  2013-11-21       Impact factor: 4.475

10.  Ionic channels as targets for drug design: a review on computational methods.

Authors:  Gregorio Fernández-Ballester; Asia Fernández-Carvajal; José Manuel González-Ros; Antonio Ferrer-Montiel
Journal:  Pharmaceutics       Date:  2011-12-09       Impact factor: 6.321

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