## 3 Results
### Hydrophobicity-Based Ligand Binding Site and Protein-Protein Interface Determination  
Determination of ligand binding sites and protein-protein interfaces based on the hydrophobicity distribution provided by FOD model is possible using two methods. In the first method, the substrates (two or more individual structures: monomers, domains, complexes, etc.) are submitted to a global optimization procedure that aims to minimize the \(RD\) of the whole system by starting from some--possibly randomly-selected--conformation. Substrates can move in the space, subject to typical constraints, such as the requirement of having at least one non-bonded contact between them. Such a black box approach (requiring only the tertiary structure) is based on the assumption that hydrophobicity has dominant role in formation of the complex. For example--as mentioned in Section 3.1--chains with hydrophobic patches of significant size or composition present on the surface may \"want\" to assume a position in the quaternary structure where those patches would face other chains, shielding them from water. The second prediction method relies on an intermediate step (after \(T\) and \(O\) profile calculation) where the substrate structures are analyzed and promising candidates for the P-L or P-P interaction sites are selected among the residues. Other non-hydrophobic criteria may also be used here (or perhaps FOD is implemented as a scoring function in another program). Once such putative interface has been selected, a local optimization procedure may begin to construct the complex using it as its starting position. In this section we focus on the second approach, presenting how to use FOD to search for and present residues that may be involved in non-bonded interactions. Figure 6: Hydrophobicity density distribution resulting from MIR model simulation (NCN—non-covalent neighbors and smoothed most interacting residues—SMIR) for FdI (1 FXR) (**a,b**) and FdII (1 FXD) (**b,c**). Blue pentagons on (**b**) and blue spheres on (**a**) denote SMIRs in FdI (I12, Y35 and V56). Red pentagons on (**b**) and red spheres on (**c**) denote SMIRs in FdII (I2, M9, I17, I47 and V56). Discrepancies and outliers in the hydrophobicity profile of a protein (\(O\)) appearing when compared to the reference distribution (\(T\)) can be viewed from global and local perspective, which both provide insight into the characteristic of the molecule. This allows FOD model to act both as a feature exploration and a prediction tool. DKL (and by extension its derivative--the \(RD\)) by itself (without optimization) belongs to the first category. It primarily measures the global accordance/discordance of \(T\) vs. \(O\) and--if one desires such information--the influence of specific multi-residue parts of the chain (i.e., a helix or a strand) on the structure of the hydrophobic core. In other words, it revolves around the notion of a \"distribution\" (a data series). This type of analysis concerns the previous sections of Results regarding the ferredoxins. On the other hand, the local perspective focuses on individual residues with much lower regard for their position within the sequence or assigned secondary structure. Again, this involves observation of the differences between \(T\) and \(O\), but this time in a more direct fashion, yet still from the viewpoint of the whole molecule. Due to how these distributions are calculated--like with entropy--there is no universal cut-off at which one could say that, for example, \"the difference between \(T\) and \(O\) for this residue is high/low\" (single point accordance or discordance determination) or that \"values of \(T\) and \(O\) are both high/low for this residue\" (single point core or surface determination).