Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases which are involved in the proteolytic processing of several components of the extracellular matrix. As a consequence, MMPs are implicated in several physiological and pathological processes, like skeletal growth and remodelling, wound healing, cancer, arthritis, and multiple sclerosis, raising a very widespread interest toward this class of enzymes as potential therapeutic targets. Here, structure-function relationships are discussed to highlight the role of different MMP domains on substrate/inhibitor recognition and processing and to attempt the formulation of advanced guidelines, based on natural substrates, for the design of inhibitors more efficient in vivo.

A novel class of 2-(R)-phenylpropionamides has been recently reported to inhibit in vitro and in vivo interleukin-8 (CXCL8)-induced biological activities. These CXCL8 inhibitors are derivatives of phenylpropionic nonsteroidal antiinflammatory drugs (NSAIDs), high-affinity ligands for site II of human serum albumin (HSA). Up to date, only a limited number of in silico models for the prediction of albumin protein binding are available. A three-dimensional quantitative structure-property relationship (3D-QSPR) approach was used to model the experimental affinity constant (K(i)) to plasma proteins of 37 structurally related molecules, using physicochemical and 3D-pharmacophoric descriptors. Molecular docking studies highlighted that training set molecules preferentially bind site II of HSA. The obtained model shows satisfactory statistical parameters both in fitting and predicting validation. External validation confirmed the statistical significance of the chemometric model, which is a powerful tool for the prediction of HSA binding in virtual libraries of structurally related compounds.