STAAR: Statistical analysis of aromatic rings

The statistical analysis of aromatic rings program allows for an automated search for anion‐π interactions between phenylalanine residues and carboxylic acid moieties of neighboring aspartic acid or glutamic acid residues in protein data bank (PDB) structures. The program is written in C++ and is av...

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Veröffentlicht in:Journal of computational chemistry 2013-03, Vol.34 (6), p.518-522
Hauptverfasser: Jenkins, David D., Harris, Jason B., Howell, Elizabeth E., Hinde, Robert J., Baudry, Jerome
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Sprache:eng
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Zusammenfassung:The statistical analysis of aromatic rings program allows for an automated search for anion‐π interactions between phenylalanine residues and carboxylic acid moieties of neighboring aspartic acid or glutamic acid residues in protein data bank (PDB) structures. The program is written in C++ and is available both as a standalone code and through a web implementation that allows users to upload and analyze biomolecular structures in PDB format. The program outputs lists of Phe/Glu or Phe/Asp pairs involved in potential anion‐π interactions, together with geometrical (distance and angle between the Phe's center of mass and Glu or Asp's center of charge) and energetic (quantum mechanical Kitaura‐Morokuma interaction energy between the residues) descriptions of each anion‐π interaction. Application of the program on the latest content of the PDB shows that anion‐π interactions are present in thousands of protein structures and can possess strong energies, as low as −8.72 kcal/mol. © 2012 Wiley Periodicals, Inc. Anion‐π interactions are nonbonded interactions between negatively charged species and resonant functional groups. Such interactions are investigated between PHE and GLU or ASP side chains in proteins using the new program STAAR. These interactions are found to be common and of potentially strong energies in protein structures. This article describes the STAAR program and its web implementation and summarizes the results obtained in applying it to the protein data bank.
ISSN:0192-8651
1096-987X
DOI:10.1002/jcc.23164