Sequences classified as having the conserved Kunitz domain and sequences are annotated as monolaris sequences that have six cysteine residues forming three disulfide bridges and a single Kunitz head. These 60 monolaris sequences can be further divided into subgroups categorized by variations in their Cys motif. The remaining Kunitz sequences from I. scapularis are defined as bilaris and penthalaris. In our study we focused on the most abundant Kunitz group from the I. scapularis sialome project by Ribeiro et al. : the monolaris group. We identified a Kunitz sequence that displays an unusal Cys motif when compared with the other monolaris and to previously reported Kunitz peptides. Since tick Kunitz peptides are known to inhibit serine proteases we performed an inhibitory screening demonstrating that this I. scapularis Kunitz inhibits several proteases as well as being a potent inhibitor of human skin b-tryptase. Furthermore, a phylogenetic analysis using several functionally described Kunitz protease inhibitors from hematophagous arthropods, nematodes and platyhelminthes reveals that this I. scapularis Kunitz is closely related to TdPI. We will, hereafter, refer to this I. scapularis Kunitz as tryptogalinin due to its high affinity for HSTb. Since the crystal structure of TdPI and its complex with trypsin has been solved, we used in silico methods to elucidate the biophysical principles that determine tryptogalinin��s protein fold, to predict its global tertiary structure and to hypothesize about its physicochemical interactions with serine proteases that account for its biochemical specificity �C when compared with TdPI. All these shortcomings suggested a robust technique must be applied in our docking methods. The CG protein-protein docking uses the Basdevant et al. potential. This CG model reduces each residue to one, two or three beads and uses only electrostatic and Van der Waals energy terms. We implemented it on a Monte Carlo search algorithm where, optionally, the search may be biased towards a desired goal by adding 888216-25-9 geometric constraints. Here, based on the TdPI-trypsin crystal, we added an cutoff Cobicistat between Lys13 and Asp191 for tryptogalinin. Starting from a configuration where both monomers are far apart, the algorithm first generates random
