The matrix metalloproteinases (MMPs) are a family of proteolytic enzymes, which have been the focus of a lot of research in recent years because of their involvement in various disease conditions. In this study, structures of 10 enzymes (MMP1, MMP2, MMP3, MMP7, MMP8, MMP9, MMP12, MMP13, MMP14, and MMP20) were examined with the intention of highlighting regions that could be potential sites for obtaining selectivity. For this purpose, the GRID/CPCA approach as implemented in GOLPE was used. Counterions were included to take into account the different electrostatic properties of the proteins, and the GRID calculations were performed, allowing the protein side chains to move in response to interaction with the probes. In the search for selectivity, the MMPs are known to be a very difficult case because the enzymes of this family are very similar. The well-known differences in the S1' pocket were observed, but in addition, the pockets S3 and S2 called for attention. This is an observation that emphasizes the need for design of inhibitors exploiting the unprimed side of the active site, if possible, in combination with the S1' site. Despite small differences, a rational usage of the findings described in this work should make it possible to use a combination of the features of the individual enzyme pockets, making most of the MMP enzymes possible targets for selective inhibition. The results suggest the possibility of distinguishing between 8 of the 10 enzymes by this approach.

In this work, eight different scoring functions have been combined with the aim of improving the prediction of protein-ligand binding conformations and affinities. The obtained scores were analyzed using multivariate statistical methods to generate expressions, with the ability (1) to select the best candidate between different docked conformations of an inhibitor (MultiSelect) and (2) to quantify the protein-ligand binding affinity (MultiScore). By use of the docking program GOLD, 40 different inhibitors were docked into the active site of three matrix metalloproteinases (MMP's), yielding a total of 120 enzyme-inhibitor complexes. For each complex, a single conformation of the inhibitor was selected using principal component analysis (PCA) for the scores obtained by the eight functions SCORE, LUDI, GRID, PMF_Score, D_Score, G_Score, ChemScore, and F_Score. Binding affinities were estimated based on partial least-squares projections onto latent structures (PLS) on the eight scores of each selected inhibitor conformation. By use of this procedure, R(2) = 0.78 and Q(2) = 0.78 were obtained when comparing experimental and calculated binding affinities. MultiSelect was evaluated by applying the same method for selecting docked conformations for 18 different protein-ligand complexes of known three-dimensional structure. In all cases, the selected ligand conformations were found to be very similar to the experimentally determined ligand conformations. A more general evaluation of MultiScore was performed using a set of 120 different protein-ligand complexes for which both the three-dimensional structures and the binding affinities were known. This approach allowed an evaluation of MultiScore independently of MultiSelect. The generality of the method was verified by obtaining R(2) = 0.68 and Q(2) = 0.67, when comparing calculated and experimental binding affinities for the 120 X-ray structures. In all cases, LUDI, SCORE, GRID, and F_Score were included as important functions, whereas the fifth function was PMF_Score and ChemScore for the MMP and X-ray models, respectively.

Matrix metalloproteinases are extracellular enzymes taking part in the remodeling of extracellular matrix. The structures of the catalytic domain of MMP1, MMP3, MMP7 and MMP8 are known, but structures of enzymes belonging to this family still remain to be determined. A general approach to the homology modeling of matrix metalloproteinases, exemplified by the modeling of MMP2, MMP9, MMP12 and MMP14 is described. The models were refined using an energy minimization procedure developed for matrix metalloproteinases. This procedure includes incorporation of parameters for zinc and calcium ions in the AMBER 4.1 force field, applying a non-bonded approach and a full ion charge representation. Energy minimization of the apoenzymes yielded structures with distorted active sites, while reliable three-dimensional structures of the enzymes containing a substrate in active site were obtained. The structural differences between the eight enzyme-substrate complexes were studied with particular emphasis on the active site, and possible sites for obtaining selectivity among the MMP's are discussed. Differences in the P1' pocket are well-documented and have been extensively exploited in inhibitor design. The present work indicates that selectivity could be further improved by considering the P2 pocket as well.

The pharmacology and regulation of Transient Receptor Potential Ankyrin 1 (TRPA1) ion channel activity is intricate due to the physiological function as an integrator of multiple chemical, mechanical, and temperature stimuli as well as differences in species pharmacology. In this study, we describe and compare the current inhibition efficacy of human TRPA1 on three different TRPA1 antagonists. We used a homology model of TRPA1 based on Kv1.2 to select pore vestibule residues available for interaction with ligands entering the vestibule. Site-directed mutation constructs were expressed in Xenopus oocytes and their functionality and pharmacology assessed to support and improve our homology model. Based on the functional pharmacology results we propose an antagonist-binding site in the vestibule of the TRPA1 ion channel. We use the results to describe the proposed intravestibular ligand-binding site in TRPA1 in detail. Based on the single site substitutions, we designed a human TRPA1 receptor by substituting several residues in the vestibule and adjacent regions from the rat receptor to address and explain observed species pharmacology differences. In parallel, the lack of effect on HC-030031 inhibition by the vestibule substitutions suggests that this molecule interacts with TRPA1 via a binding site not situated in the vestibule.