PSAIA – Protein Structure and Interaction Analyzer

In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm) for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA.Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results.PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format.In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis.Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.Analysis performed on small data sets have shown [1] that geometrical properties of the protein surface influence protein-protein interactions. For the analysis of larger data sets (e.g. the non-redundant set of PDB structures), tools that can process a wider range of structural information descriptors are necessary.It is also important to generate results that can be easily formatted for statistical analysis with standard software. Current software for protein analysis (standalone programs or web services) typically investigates a single aspect of molecular structure geometry and generates results only