Estudi del mecanisme molecular de la interacció fàrmac-receptor en proteïnes p38 MAPK

Abstract

In this work p38 protein kinases are studied. These proteins are involved in human diseases such as cancer, rheumatoid arthritis, or psoriasis. Among the group of p38 proteins, one can find 4 different proteins, where p38α is the most studied one and will be the reference of this work. This protein is relevant from the pharmacological point of view and the design of novel inhibitors is required. The structure consists of two large domains that are connected by the ATP binding region that forms the active site of the protein. The active site presents conformational changes depending on the inhibitor that is interaction. There are three main types of inhibitors of protein kinases: Type I, Type II, and Type I/II. The objective of this work is to establish a computational protocol to study the interaction between inhibitors of different types and p38α protein in order to be able to design new, more potent and selective inhibitors for this protein. In the first place, an assessment of which molecular docking software properly describes the interactions between the different proteins and inhibitors is performed. In order to answer this question, the SwissDock software will be compared to AutoDock. The interactions established by these inhibitors with the amino acids in the active center are studied in detail to determine the molecular basis of the inhibition process. Based on these interactions, computational tools are used to determine the pharmacophore of the drug and to use this information to design a more potent inhibitor for this protein. We have tried to design a more potent inhibitor for Type I, Type II, as for Type I / II. Based on the improved inhibitors, the interaction and selectivity between p38α protein inhibitors and the other three types of p38 protein (γ, β and Δ) are studied. Finally, computational results are compared with results based on the IC50 inhibitor Type I / II of the p38α protein, if there is a relationship between the study model and the experimental results, it will be used to see the limitations of the model. It is expected that the proposed computational protocol is sufficiently robust to identify new p38α protein inhibitors