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Abstract

The P-glycoprotein (P-gp) is responsible for the elimination of a wide variety of substances from the cell, thus it is thought to play an important role in detoxification functions. The P-gp also affects the ADMET (absorption, distribution, metabolism, excretion, and toxicity in pharmacokinetics) properties of drugs. It is involved in adverse drug-drug interactions and its overexpression is thought to be responsible for the presence of multidrug resistance (MDR) in cancer cells, which is considered to be the main reason for the failure of cancer therapies. Therefore, in silico approaches to understand the ligand binding interactions of the human p-glycoprotein (hP-gp) leading to early identification of P-gp active compounds are of great interest for drug development and toxicity assessment.
This dissertation summarises in three different studies how ligand- and structure-based methods can be used to solve the problem of elucidating the ligand–P-gp interactions and the transport mechanism, and to provide a rapid and accurate prediction of potential new P-gp ligands. In the first study, the ligand-based approach is described by developing a classification model to predict the activity of P-gp. The developed multiclass classifier showed a good classification performance and is a useful tool for saving significant time in the drug development pipeline, as it provides a rapid initial screening step for selecting predicted molecules that would interact with P-gp as inhibitors or substrates.
The second and third studies illustrate the structure-based approach of the target protein. The second study describes the construction of a homology model of the hP-gp and the use of molecular docking to identify binding modes of different compounds, either active (substrates and inhibitors) or non-active compounds. The study of the ligand–hP-gp complexes provided considerable insight into the drug binding mode for the set of investigated compounds. Different modes of interaction for different classes of compounds were revealed and consistency between the predicted interactions and available experimental data was demonstrated.
Finally, a series of molecular dynamics simulations of hP-gp in an explicit membrane and water environment were performed to investigate the effects of binding different compounds on the conformational dynamics of P-gp. The results showed a significant difference in the behaviour of P-gp in the presence of an active or non-active compound within the binding pocket. Different motion patterns were identified which could be correlated with the conformational changes leading to the activation of the translocation mechanism.