interfaces. Only a few programs have been implemented to date on the web [19–21]. Some programs can be downloaded for local usage, such as PlotCor [22], CorrMut [19] and CRASP [23]. CysView is a web-based application tool that displays cysteine connectivity patterns in proteins [24]. ESBRI is a web tool which analyses the salt bridges in a protein structure [25]. However, the general absence of graphical analysis tools makes it difficult to analyze amino acid pair interactions and examine them with respect to structural data. Most amino acid pair interaction data presented in literature appears as 1D or 2D plots, thus effectively being projections of the total fold space onto a 1D or 2D subspace. No currently available method allows the user to view statistical information and visualize instantly the pdb structures that underpin the statistical information. In the present study we define each pair of amino acids in terms of (number of bins used in brackets): amino acid type 62(20), solvent accessibility (12), spatial distance (14), secondary structure 62(4), protein size (12) and sequence distance (6). We only consider a pair if the two amino acids are located in the same solvent accessibility bin and if the inter residue distance is less than 8.3 A˚. The resulting 8 dimensional fold tensor contains ,77.4 million cells. In our analysis of 8706 protein high resolution 3D chains (Fig. 1A), ,5.9 million amino acid pair observations were found and loaded into ,1.9 million cells in the fold tensor. Each of these cells contains the number of times a pair of two particular amino acids has been found at a location in fold space. The volume of a protein has been divided into eleven spherical layers of solvent accessibility. This concept is illustrated in Figure 1B. The presented programs ProExtract, ProPack and ProPair successfully identify known structural motifs and show their potential for finding novel packing preferences in proteins. In order to demonstrate the capabilities of this general data cube as well as the query programs we have studied the packing of disulphide bridges as well as charged amino acid pairs. These choices Amino Acid Pairs in Proteins represent only a very small fraction of the types and number of queries that ProPack and ProPair would allow. Previous studies report the geometrical configuration and/or statistical character- ization of amino acid residues participating in disulphide bridges [26–43] and salt bridges [44–48]. The present paper presents a bioinformatics approach that allows the user to carry out hyper dimensional analyses of amino acid pair interactions and their distribution in proteins with an incorporated graphical analysis tool, making possible the visualization of any conceivable combination of the 8 dimensions for each amino acid pair. Any interacting amino acid pair of interest can be visualized in its structural location within a particular structure. We aim at making these programs available on the web. Materials and Methods According to a recent comprehensive review [49], to establish a really useful statistical predictor (or model) for a protein system, we need to consider the following procedures: (i) construct or select a valid benchmark dataset to train and test the predictor; (ii) formulate the statistical samples with an effective mathematical expression that can truly reflect their intrinsic correlation with the attribute to be predicted or analyzed; (iii) introduce or develop a powerful algorithm (or engine) to operate the prediction or analysis; (iv) properly perform cross-validation tests to objectively evaluate the anticipated accuracy of the predictor; (v) establish a user-friendly web-server for the predictor that is accessible to the public. In this section we will describe how to deal with these steps. In statistical prediction, the following three cross-validation methods are often used to examine an analysis method or predictor for its effectiveness in practical application: independent dataset test, sub-sampling (5-fold or 10-fold cross-validation) test, and jackknife test [50]. As elucidated in Ref [49], among the three cross-validation methods, the jackknife test is deemed the least Figure 1. Protein chains resolution and solvent accessible shell concept. A) Histogram of the resolution of the 8706 protein chains used in this study. The average resolution is 1.93 A˚ as indicated by the dotted line. B) Spherical model of a globular protein displaying the solvent accessible shell concept: the protein residues are binned in solvent shells ranging from completely buried (SA = 0%) to full solvent exposure (SA = 100%) in steps of 10%, with 0% and .100% treated explicitly. doi:10.1371/journal.pone.0025638.g001 PLoS ONE | www.plosone.org 2 December 2011 | Volume 6 | Issue 12 | e25638