The Matrix metalloproteinase-2 (MMP2, gelatinase A, 72 kDa type IV collagenase) is involved in different functions such as reconstruction of the vasculature, angiogenesis, tissue repair, inflammation, tumor invasion and atherosclerotic plaque rupture. Mutations in the MMP2 gene are associated with Torg-Winchester syndrome, arthritis syndrome, multicentric osteolysis and other pathologies. Therefore, small molecule compounds targeting metalloproteinase-2 may be potential treatment for a variety of diseases related to abnormality functioning of MMP2.

OTAVAchemicals offers Matrix metalloproteinase-2 Targeted Library (627 compounds). It has been carefully designed with combination of ligand-based virtual screening methods - Bayesian statistics and k-nearest neighbors algorithm (k-NN).

For library design twelve training sets were developed on the base of known MMP2 inhibitors. These compounds were clustered and classified as active or inactive using k-NN based on molecular fingerprints to achieve more homogeneous training sets. The training sets were used for Bayesian modeling (based on molecular descriptors, such as number of hydrogen donors and acceptors, PSA, LogP, molecular weight, number of rotatable bonds, number of rings and fingerprints ECFP4, FCFP4, ECFP6 and FCFP6) and for compounds selection with k-NN algoritm (based on fingerprints ECFP4, FCFP4, ECFP6, FCFP6). The combination of Bayesian statistics and k-NN method should allow increasing the number of active compounds identified during screening. Top-scored compounds obtained from application of these methods were crossed and visually analyzed.

The designed MMP2 Targeted library comprises only drug-like compounds (PAINS compounds are filtered off) with chelator groups. It provides an excellent basis for drug discovery projects related with matrix metalloproteinase-2.

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