Literature DB >> 20205445

Protein pockets: inventory, shape, and comparison.

Ryan G Coleman1, Kim A Sharp.   

Abstract

The shape of the protein surface dictates what interactions are possible with other macromolecules, but defining discrete pockets or possible interaction sites remains difficult. First, there is the problem of defining the extent of the pocket. Second, one has to characterize the shape of each pocket. Third, one needs to make quantitative comparisons between pockets on different proteins. An elegant solution to these problems is to sort all surface and solvent points by travel depth and then collect a hierarchical tree of pockets. The connectivity of the tree is determined via the deepest saddle points between each pair of neighboring pockets. The resulting pocket surfaces tessellate the entire protein surface, producing a complete inventory of pockets. This method of identifying pockets also allows one to easily compute important shape metrics, including the problematic pocket volume, surface area, and mouth size. Pockets are also annotated with their lining residue lists and polarity and with other residue-based properties. Using this tree and the various shape metrics pockets can be merged, grouped, or filtered for further analysis. Since this method includes the entire surface, it guarantees that any pocket of interest will be found among the output pockets, unlike all previous methods of pocket identification. The resulting hierarchy of pockets is easy to visualize and aids users in higher level analysis. Comparison of pockets is done by using the shape metrics, avoiding the complex shape alignment problem. Example applications show that the method facilitates pocket comparison along mutational or time-dependent series. Pockets from families of proteins can be examined using multiple pocket tree alignments to see how ligand binding sites or how other pockets have changed with evolution. Our method is called CLIPPERS for complete liberal inventory of protein pockets elucidating and reporting on shape.

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Year:  2010        PMID: 20205445      PMCID: PMC2859996          DOI: 10.1021/ci900397t

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  84 in total

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3.  Comparison of protein active site structures for functional annotation of proteins and drug design.

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Review 4.  Computational identification of inhibitors of protein-protein interactions.

Authors:  Shijun Zhong; Alba T Macias; Alexander D MacKerell
Journal:  Curr Top Med Chem       Date:  2007       Impact factor: 3.295

5.  Binding response: a descriptor for selecting ligand binding site on protein surfaces.

Authors:  Shijun Zhong; Alexander D MacKerell
Journal:  J Chem Inf Model       Date:  2007-09-27       Impact factor: 4.956

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

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Journal:  Protein Sci       Date:  1998-09       Impact factor: 6.725

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Journal:  J Am Chem Soc       Date:  2003-04-09       Impact factor: 15.419

Review 9.  Water: now you see it, now you don't.

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Journal:  Structure       Date:  1993-12-15       Impact factor: 5.006

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Journal:  Proc Natl Acad Sci U S A       Date:  1997-12-09       Impact factor: 11.205

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3.  Binding site matching in rational drug design: algorithms and applications.

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Review 4.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

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

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7.  Structural and dynamic determinants of protein-peptide recognition.

Authors:  Onur Dagliyan; Elizabeth A Proctor; Kevin M D'Auria; Feng Ding; Nikolay V Dokholyan
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8.  Paclitaxel is an inhibitor and its boron dipyrromethene derivative is a fluorescent recognition agent for botulinum neurotoxin subtype A.

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Journal:  J Med Chem       Date:  2013-03-29       Impact factor: 7.446

9.  LpxI structures reveal how a lipid A precursor is synthesized.

Authors:  Louis E Metzger; John K Lee; Janet S Finer-Moore; Christian R H Raetz; Robert M Stroud
Journal:  Nat Struct Mol Biol       Date:  2012-10-07       Impact factor: 15.369

10.  Therapeutic Potential of Novel Mastoparan-Chitosan Nanoconstructs Against Clinical MDR Acinetobacter baumannii: In silico, in vitro and in vivo Studies.

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