The significance of transport proteins for the pharmacokinetics and pharmacodynamics of drug molecules has been recognized during the past decade. The most important and best characterized is P-glycoprotein (P-gp), a typical multidrug transporter that belongs to the large class of the ABC-transport protein superfamily. P-gp holds an important physiological role as a natural detoxification system. It is actively involved in various processes such as lowering oral drug bioavailability, preventing drugs from penetrating across the blood-brain barrier, decreasing intracellular accumulation of anti-cancer and other cytotoxic agents, HIV-protease inhibitors and many more. P-gp is involved in resistance mechanisms of tumor and other cells to a broad spectrum of agents thus ranking it as a major multidrug resistance (MDR) protein. Hence pharmaceutical companies have a strong interest in identifying potential P-gp substrates at an early stage of the drug development process.

Together with experimental assays computational or in silico methods are very useful in achieving this purpose. In silico tools do not require compound synthesis and biological testing and can be applied to hypothetical compounds permitting the rapid exclusion of the likely failures and contributing simultaneously to a better understanding of drug-protein interactions.

In silico approaches to model drug-P-gp interactions have undergone several stages depending on particular knowledge of the structure and the structure-function relationship of the protein. Due to absence of 3D structural data of P-gp with sufficient resolution the ligand-based drug design approaches are mostly applied.

A number of QSAR and 3D-QSAR models have been developed based on the experimental MDR reversing activity data of different classes of compounds proven to interact with P-gp. These QSAR models use structural fragments and various physicochemical parameters. Mostly, lipophilicity (logP) and size (molar refractivity) were identified as the main determinants for P-gp recognition. 3D-QSAR models using Comparative Molecular Field (CoMFA) and Similarity Indices (CoMSIA) Analyses provide more detailed information pointing to the role of hydrophobicity as a space distributed molecular property and involve additionally hydrogen-bond (HB) acceptor molecular fields.

Accumulation of appropriate data about interactions of drugs with particular sites on P-gp stimulated in silico pharmacophore modeling for a more detailed elucidation of the structural features of the drugs responsible for activity. Several pharmacophore models have been developed. Almost all pharmacophore patterns involve at least two hydrophobic and one HB-acceptor points. Some of these models also consider HB-donor interactions of P-gp related drugs.

The recently published X-ray structures of the bacterial ABC-transporter MsbA from Escherichia coli and Vibrio cholerae gave rise to homology models of P-gp. Several 3D-models have been developed that could contribute to elucidation of the structure-function relationships of the transporter. Very recent results on in silico identification of the protein binding pockets confirm the hypothesis of the existence of multiple binding sites within the protein.