Literature DB >> 15728116

Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons.

Richard J Morris1, Rafael J Najmanovich, Abdullah Kahraman, Janet M Thornton.   

Abstract

MOTIVATION: An increasing number of protein structures are being determined for which no biochemical characterization is available. The analysis of protein structure and function assignment is becoming an unexpected challenge and a major bottleneck towards the goal of well-annotated genomes. As shape plays a crucial role in biomolecular recognition and function, the examination and development of shape description and comparison techniques is likely to be of prime importance for understanding protein structure-function relationships.
RESULTS: A novel technique is presented for the comparison of protein binding pockets. The method uses the coefficients of a real spherical harmonics expansion to describe the shape of a protein's binding pocket. Shape similarity is computed as the L2 distance in coefficient space. Such comparisons in several thousands per second can be carried out on a standard linux PC. Other properties such as the electrostatic potential fit seamlessly into the same framework. The method can also be used directly for describing the shape of proteins and other molecules. AVAILABILITY: A limited version of the software for the real spherical harmonics expansion of a set of points in PDB format is freely available upon request from the authors. Binding pocket comparisons and ligand prediction will be made available through the protein structure annotation pipeline Profunc (written by Roman Laskowski) which will be accessible from the EBI website shortly.

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Year:  2005        PMID: 15728116     DOI: 10.1093/bioinformatics/bti337

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  54 in total

1.  Real-time ligand binding pocket database search using local surface descriptors.

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2.  The Recognition of Identical Ligands by Unrelated Proteins.

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Journal:  ACS Chem Biol       Date:  2015-10-12       Impact factor: 5.100

3.  Structure- and sequence-based function prediction for non-homologous proteins.

Authors:  Lee Sael; Meghana Chitale; Daisuke Kihara
Journal:  J Struct Funct Genomics       Date:  2012-01-22

4.  PatchSearch: a web server for off-target protein identification.

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Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

5.  Detecting local ligand-binding site similarity in nonhomologous proteins by surface patch comparison.

Authors:  Lee Sael; Daisuke Kihara
Journal:  Proteins       Date:  2012-01-24

6.  Ligand binding site similarity identification based on chemical and geometric similarity.

Authors:  Haibo Tu; Tieliu Shi
Journal:  Protein J       Date:  2013-06       Impact factor: 2.371

7.  Protein pocket and ligand shape comparison and its application in virtual screening.

Authors:  Matthias Wirth; Andrea Volkamer; Vincent Zoete; Friedrich Rippmann; Olivier Michielin; Matthias Rarey; Wolfgang H B Sauer
Journal:  J Comput Aided Mol Des       Date:  2013-06-27       Impact factor: 3.686

8.  Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments.

Authors:  Lei Xie; Philip E Bourne
Journal:  Proc Natl Acad Sci U S A       Date:  2008-04-02       Impact factor: 11.205

9.  Fast screening of protein surfaces using geometric invariant fingerprints.

Authors:  Shuangye Yin; Elizabeth A Proctor; Alexey A Lugovskoy; Nikolay V Dokholyan
Journal:  Proc Natl Acad Sci U S A       Date:  2009-09-17       Impact factor: 11.205

10.  On the role of physics and evolution in dictating protein structure and function.

Authors:  Jeffrey Skolnick; Mu Gao; Hongyi Zhou
Journal:  Isr J Chem       Date:  2014-08-01       Impact factor: 3.333

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