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Mapping of ligand-binding cavities in proteins

Andersson, David C., 1978- (author)
Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC), KBC
Chen, Brian Y (author)
Linusson Jonsson, Anna, 1970- (author)
Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC), KBC
 (creator_code:org_t)
2009-11-12
2010
English.
In: Proteins. - : John Wiley & Sons, Inc. - 0887-3585 .- 1097-0134. ; 78:6, s. 1408-1422
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • 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.

Subject headings

NATURVETENSKAP  -- Kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences (hsv//eng)

Keyword

protein cavity comparison
physicochemical properties
alignment independent
SCREEN
principal component analysis
binding sites
medicinal chemistry
drug design
PCA clustering tree
bioinformatics

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Andersson, David ...
Chen, Brian Y
Linusson Jonsson ...
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NATURAL SCIENCES
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Proteins
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Umeå University

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