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Mapping of ligand‐binding cavities in proteins
Authors:C. David Andersson  Brian Y. Chen  Anna Linusson
Affiliation:1. Department of Chemistry, Ume? University, SE‐901 87 Ume?, Sweden;2. Computational Life Science Cluster (CLiC), KBC, Ume? University, SE‐901 87 Ume?, Sweden;3. Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Howard Hughes Institute, Columbia University, New York;4. Brian Y. Chen's current address is Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Howard Hughes Institute, Columbia University, New York
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. Proteins 2010. © 2009 Wiley‐Liss, Inc.
Keywords: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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