In recent years insulin-regulated aminopeptidase (IRAP) has emerged as a new therapeutic target for the treatment of Alzheimer’s disease and other memory-related disorders. So far, many potent and specific IRAP inhibitors had been disclosed, including peptides, peptidomimetics, and low-molecular-weight sulfonamides. In this thesis, various computational approaches such as docking, molecular dynamics (MD), linear interaction energy (LIE), and free energy perturbations (FEP) are used to understand the molecular basis for the binding of these inhibitors to the IRAP.

By applying MD and LIE, the binding mode of Ang IV and the critical role of its N-terminal tripeptide in the binding to IRAP were described. The stark difference in the binding properties of two stereoisomers of a peptidomimetic inhibitor, HA08 and HA09, was determined using MD simulations and LIE binding affinity estimations. With the help of the FEP method, we discriminate the most probable, between two alternative binding poses for the sulfonamide family of compounds. The binding modes of the HFI family of compounds (competitive inhibitors), and spiro-oxindole compounds (allosteric, uncompetitive inhibitors) were also proposed utilizing a combination of related computational approaches. In this thesis, the specificity of the diverse class of inhibitors and substrates (oxytocin and vasopressin) for IRAP compared to other M1 aminopetidase family members was disclosed as a result of the unique Gly-Ala-Met-Glu-Asn (GAMEN) loop orientation. The different studies performed along this thesis resulted in several proposed binding modes, which were evaluated by different free energy calculation approaches, namely LIE and FEP methods. In all cases, the calculated free energies are in excellent agreement with the experimental data, which strongly supports the final binding models here proposed.

These results of this thesis will be useful in future lead generation and optimization process and hopefully in the development of better cognitive enhancers for the treatment of dementia and other related diseases such as Alzheimer’s disease.