Amino Acid Pairs in Proteins Figure 3. Histograms displaying the abundance of selected amino acid residues (Asp, Glu, Lys, Arg, Cys) in each protein shell characterized by a specific solvent accessibility SA. For each SA bin is also displayed the relative abundance of each selected residue in a particular secondary structural element (a-helix, b-strand, turn and coil). The first and last bins contain the fraction of residues in completely buried protein shell (0% SA) and in a completely solvent accessible protein shell (100% SA), respectively. A) Distribution of 120553 Asp residues, B) Distribution of 141961 Glu residues, C) Distribution of 118362 Lys residues, D) Distribution of 107556 Arg residues, E) Distribution of 26066 Cys residues. doi:10.1371/journal.pone.0025638.g003 findings and the randomized value – a value above 1 indicates statistical significance. In the ratio plots all displayed data has been normalized (values between 0 and 1). As output, ProExtract created an index dataset which could be used to identify the specific interactions that gave rise to the counts in a tensor cell. The index set was an 8D MATLAB cell character array. Whenever a pair was registered, a string was added to the corresponding cell in the index array of the form ‘‘1AB- C0102A1030B’’ for the imaginary pair of amino acids 102A and 1030B in Protein Data Bank (PDB) structure 1ABC. When more than one pair was registered in the same cell, a new line was created for each pair in the cell. In this way it was possible to retrieve the protein(s) as well as the local fold context around an amino acid pair that contributed to the count in a particular cell. Completing both the 8D tensor for the observed pairs, the 10 times averaged reference dataset as well as the index array took approximately one week of computational time on one processor in a Lenovo Thinkpad T500 with an Intel Core 2 Duo P8600 CPU at 2.4 GHz and with 4 GB RAM, running 64-bit MATLAB. Bin definitions and functional atoms The first dimension of the dataset tensor had 20 amino acid bins: Ala, Arg, Asn, Asp, Cys, Gln, Glu, Gly, His, Ile, Leu, Lys, Met, Phe, Pro, Ser, Thr, Trp, Tyr, Val. The second dimension had 20 amino acid bins, identical to the first dimension. The third dimension had 12 solvent accessibility bins (SA in %): SA#0, 0,SA#10, 10,SA#20, 20,SA#30, 30,SA#40, 40,SA# 50, 50,SA#60, 60,SA#70, 70,SA#80, 80,SA#90, 90, SA#100, SA.100. The fourth dimension had 14 distance bins (D in A˚): D#1.75, 1.75,D#2.25, 2.25,D#2.75, 2.75,D#3.25, 3.25,D#3.75, 3.75,D#4.25, 4.25,D#4.75, 4.75,D#5.25, 5.25,D#5.75, 5.75,D#6.25, 6.25,D#6.75, 6.75,D#7.25, 7.25,D#7.75, 7.75,D#8.25. The fifth dimension had four secondary structure bins for AA1: a-helix, b-strand, turn and coil. The sixth dimension had four secondary structure bins for AA2, identical to the fifth dimension. The seventh dimension had 12 chain length bins: CL#0, 0,CL#100, 100,CL#200, 200, CL#300, 300,CL#400, 400,CL#500, 500,CL#600, 600, CL#700, 700,CL#800, 800,CL#900, 900,CL#1000, CL. 1000. The eighth dimension had 6 sequence distance bins: 0, 1, 2, 3, 4, .4. The functional atoms were for Ala CB, Arg NH1 and NH2, Asn ND2 and OD1, Asp OD1 and OD2, Cys SG, Gln NE2 and OE1, Glu OE1 and OE2, Gly CA, His ND1, Ile CG1 and CG2, Leu CG, Lys NZ, Met SD, Phe CZ, Pro CG, Ser OG, Thr OG1, Trp CE2, Tyr OH, Val CG1 and CG2 (atom nomenclature as described in the .ent files). ProPack ProPack is a query program that allows the user to access the 8 dimensional data tensor. After loading the tensors created by ProExtract, two tensors were available for the program, one based on the observed data and one from the randomized reference data. The user could then request access to the observed data (‘absolute mode’), the randomized data (‘reference mode’) or the ratio between the observed and the randomized data (‘ratio mode’). Finally, the user could select a so called ‘warp mode’, where the absolute data was displayed as a 3D topographic map colored according to the intensity of the ratio data. Red color codes for highly significant data, while dark blue codes for less significant data. The 8D tensor could be queried with any set of parameters. All dimensions that we are not querying are projected onto the subspace that we are visualizing. Therefore, if we intend to produce a 2D plot of the spatial distance (D) vs solvent accessibility (SA) of a specific amino acid pair e.g. Lys-Asp, we project the 4 remaining dimensions (SS1, SS2, CL, SD) onto the D-SA subspace. ProPack contains a multi dimensional query language that allows the user to pose more elaborate and specific questions: e.g. we could ask for a 2D plot of cysteine residues specifically located in coil segments. Our 2D plot could be distance vs. sequence distance between the two cysteine residues. The user could also query the structural preferences for sets of amino acids, such as Arg-Lys and the Asp-Glu pairs. ProPair ProPair is a query program that allows the user to select a particular set of cells in the data tensor. ProPair retrieved a list of proteins identified by the index dataset (vide supra) with pairs that corresponded to the given parameters. These pairs were presented to the user, with the possibility of being visualized using the Molviewer functionality in MATLAB. When interesting features had been located in the ProPack plots, it was thus possible to use ProPair to ‘‘go back to the source’’ and identify which amino acid pairs in which proteins contributed to those features. Results The resolution of the protein structures used in this study is displayed in Figure 1A. In Figure 1B is depicted a spherical model of a globular protein displaying the solvent accessible (SA) shell concept. The protein residues are binned in solvent shells ranging from totally buried (0% SA) to full solvent exposure in steps of 10%, with 0% and .100% treated explicitly. Amino acid residues distribution (Asp, Glu, Lys, Arg, Cys) In Figure 3 is displayed the solvent accessibility distribution for each amino acid residue together with the preference for being located in a particular secondary structural element (a-helix, b- strand, turn and coil). All amino acids will be mentioned using their 3 letter code. The distribution plots of the remaining amino acid residues can be found as supplementary information (Figure S2). In Figure 3A it can be seen that Asp prefers to be located in protein shells displaying solvent accessibility .0% up until ,60%. Its distribution peaks in the solvent shells displaying solvent accessibility .0% and #10% and with solvent accessibility .40 and #50%. Asp is rarely present in the completely buried core of the protein (0% SA). In solvent shells with SA beyond 60%, the propensity for Asp declines linearly with increasing SA. In Figure 3B it can be seen that the SA distribution of Glu is similar to the Asp distribution, although Glu is less frequent than Asp in PLoS ONE | www.plosone.org 6 December 2011 | Volume 6 | Issue 12 | e25638