Literature DB >> 20034113

Mapping of ligand-binding cavities in proteins.

C David Andersson1, Brian Y Chen, Anna Linusson.   

Abstract

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs. 2009 Wiley-Liss, Inc.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20034113      PMCID: PMC2957484          DOI: 10.1002/prot.22655

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  58 in total

1.  Mapping of protein surface cavities and prediction of enzyme class by a self-organizing neural network.

Authors:  M Stahl; C Taroni; G Schneider
Journal:  Protein Eng       Date:  2000-02

2.  CASTp: Computed Atlas of Surface Topography of proteins.

Authors:  T Andrew Binkowski; Shapor Naghibzadeh; Jie Liang
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

3.  Protein folding and association: insights from the interfacial and thermodynamic properties of hydrocarbons.

Authors:  A Nicholls; K A Sharp; B Honig
Journal:  Proteins       Date:  1991

4.  Method for comparing the structures of protein ligand-binding sites and application for predicting protein-drug interactions.

Authors:  Ryoichi Minai; Yo Matsuo; Hiroyuki Onuki; Hiroshi Hirota
Journal:  Proteins       Date:  2008-07

5.  A simple and fuzzy method to align and compare druggable ligand-binding sites.

Authors:  Claire Schalon; Jean-Sébastien Surgand; Esther Kellenberger; Didier Rognan
Journal:  Proteins       Date:  2008-06

6.  Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design.

Authors:  J Liang; H Edelsbrunner; C Woodward
Journal:  Protein Sci       Date:  1998-09       Impact factor: 6.725

7.  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

8.  The neighbor-joining method: a new method for reconstructing phylogenetic trees.

Authors:  N Saitou; M Nei
Journal:  Mol Biol Evol       Date:  1987-07       Impact factor: 16.240

9.  A graph-theoretic approach to the identification of three-dimensional patterns of amino acid side-chains in protein structures.

Authors:  P J Artymiuk; A R Poirrette; H M Grindley; D W Rice; P Willett
Journal:  J Mol Biol       Date:  1994-10-21       Impact factor: 5.469

10.  Solvent-accessible surfaces of proteins and nucleic acids.

Authors:  M L Connolly
Journal:  Science       Date:  1983-08-19       Impact factor: 47.728

View more
  9 in total

Review 1.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

Authors:  Peter Csermely; Tamás Korcsmáros; Huba J M Kiss; Gábor London; Ruth Nussinov
Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

2.  FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins.

Authors:  Daniel B Roche; Stuart J Tetchner; Liam J McGuffin
Journal:  BMC Bioinformatics       Date:  2011-05-16       Impact factor: 3.307

3.  FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions.

Authors:  Daniel B Roche; Maria T Buenavista; Liam J McGuffin
Journal:  PLoS One       Date:  2012-05-30       Impact factor: 3.240

4.  Identification of distant drug off-targets by direct superposition of binding pocket surfaces.

Authors:  Marcel Schumann; Roger S Armen
Journal:  PLoS One       Date:  2013-12-31       Impact factor: 3.240

Review 5.  Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

Authors:  Daniel Barry Roche; Danielle Allison Brackenridge; Liam James McGuffin
Journal:  Int J Mol Sci       Date:  2015-12-15       Impact factor: 5.923

6.  Quantitative Characterization of Binding Pockets and Binding Complementarity by Means of Zernike Descriptors.

Authors:  Lorenzo Di Rienzo; Edoardo Milanetti; Josephine Alba; Marco D'Abramo
Journal:  J Chem Inf Model       Date:  2020-02-25       Impact factor: 4.956

7.  The landscape of the prion protein's structural response to mutation revealed by principal component analysis of multiple NMR ensembles.

Authors:  Deena M A Gendoo; Paul M Harrison
Journal:  PLoS Comput Biol       Date:  2012-08-09       Impact factor: 4.475

8.  Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

Authors:  Stéphanie Pérot; Leslie Regad; Christelle Reynès; Olivier Spérandio; Maria A Miteva; Bruno O Villoutreix; Anne-Claude Camproux
Journal:  PLoS One       Date:  2013-06-20       Impact factor: 3.240

9.  Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

Authors:  Adriana Isvoran; Dana Craciun; Virginie Martiny; Olivier Sperandio; Maria A Miteva
Journal:  BMC Pharmacol Toxicol       Date:  2013-06-14       Impact factor: 2.483

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.