Identification of monoamine oxidase inhibitors using a molecular modelling approach
Abstract
Monoamine oxidase (MAO) is an enzyme located on the outer mitochondrial membrane and is considered to be a target for the treatment of diseases such as Parkinson’s disease and depression. MAO may be classified into two isoforms, MAO-A and MAO-B. Since MAO-A and MAO-B catalyzes the metabolism of serotonin and dopamine, respectively, MAO-A inhibitors are used in the therapy of depression while MAO-B inhibitors are useful in the treatment of Parkinson’s disease. The older nonselective and irreversible MAO inhibitors, however, are not frequently used because they may ellicit potentially dangerous side effects such as the “cheese reaction”. The cheese reaction occurs when irreversible MAO-A inhibitors block the metabolism of tyramine in the gastrointestinal tract. Excessive amounts of tyramine subsequently enter the systemic circulation and cause a hypertensive reaction. This problem may be overcome by the development of selective MAO-B inhibitors and reversible MAO-A inhibitors. Selective MAO-B inhibitors do not cause the cheese reaction, because tyramine is metabolized, in the intestines, by MAO-A. Tyramine also has the ability to displace reversible MAO-A inhibitors and can subsequently be normally metabolized, thus not causing the cheese reaction. Several research groups are therefore involved in the discovery of reversible MAO-A and MAO-B inhibitors. As mentioned above, such drugs may be used in the treatment of depression and Parkinson’s disease. One approach is the de novo design of novel molecules with affinities for MAO-A and MAO-B active sites. In a second approach, existing drugs may be re-appropriated as MAO inhibitors. With this approach, approved drugs are screened for the possibility that they, in addition to their action at the indicated target, also act as
inhibitors of MAO-A and/or MAO-B. Such drugs may then be applied as MAO inhibitors
in the treatment of depression and Parkinson’s disease. From a toxicological point of view, it is also of importance to identify MAO-A inhibitory activities among existing drugs as this will alert to the occurrence of potential side effects such as the cheese reaction. In this study the second approach will be followed. This study will screen a virtual library of approved drugs for inhibitory activity towards MAO-A and MAO-B. Molecular modeling may be used to screen virtual libraries of drugs as potential
inhibitors of the MAO enzymes. This may conveniently be achieved by employing
structure-based or ligand-based pharmacophore models. In this study a virtual library of approved drugs was screened for secondary inhibitory
activities towards the MAO isoforms with the use of structure-based pharmacophore
models. There are several advantages to this approach. Molecular modeling aims at
reducing the overall cost associated with the discovery and development of a new drug
by identifying the most promising candidates to focus the experimental efforts on. It aids
in understanding how a ligand binds to the active site of an enzyme. It is relatively
easier to re-register a drug for a second pharmacological activity. This approach may
also lead to drugs with a multi-target mode of action. The structure-based pharmacophores were constructed using the known crystallographic structures of MAO-A and MAO-B with the inhibitors, harmine and
safinamide, complexed in the active sites, respectively. Employing the MAO-A and
MAO-B structure-based pharmacophore model in the virtual screening of a library of
approved drugs, 45 compounds were found to map to the MAO-A and MAO-B
pharmacophore models. Among the hits, 29 compounds were selected for in vitro evaluation as MAO-A and MAO-B inhibitors. The IC50 values for these compounds were determined. After in vitro evaluation, 13 compounds showed inhibitory activity towards MAO. Of the 13 compounds 3 showed interesting inhibitory activities. These compounds included caffeine (IC50 = 0.761 μM for MAO-A and 5.08 μM for MAO-B), esomeprazole (IC50 = 23.2 μM for MAO-A and 48.3 μM for MAO-B) and leflunomide (IC50 = 19.1μM for MAO-A and 13.7 μM for MAO-B). The MAO inhibitory properties of caffeine and esomeprazole were further investigated. The reversibility of MAO inhibition by caffeine and esomeprazole were determined by dialysis and dilution studies. Sets of Lineweaver-Burk plots were constructed to determine the modes of binding of these inhibitors to the MAO enzymes. Both caffeine and esomeprazole were found to be reversible and competitive inhibitors of MAO. Dialysis of mixtures of caffeine with MAO-A and MAO-B resulted in the recovery of enzyme activity to levels of 97% and 96%, respectively. Dialysis of mixtures of esomeprazole with MAO-A and MAO-B resulted in the recovery of enzyme activity to levels of 93% and 88%, respectively. Similarly, dilution of mixtures containing esomeprazole and MAO-A/MAO-B resulted in the recovery of enzyme activity to levels of 94% and 87%, respectively. For the inhibition of MAO-A and MAO-B by caffeine and esomeprazole, the Lineweaver-Burk plots were indicative of a competitive mode of inhibition. In an attempt to gain further insignt, caffeine, esomeprazole and leflunomide were docked into models of the active sites of MAO-A and MAO-B. An analysis of the interactions between the enzyme models and the ligands were carried out and the results are discussed in the dissertation The results of the present study show that screening of a virtual database of molecules with a pharmacophore model may be useful in identifying existing drugs with potential MAO inhibitory activities. The search for new reversible MAO inhibitors for the treatment of diseases, including Parkinson’s disease and depression, may be facilitated by employing a virtual screening approach. Such an approach also may be more cost effective than de novo inhibitor design. In addition, the virtual screening approach may alert to potential side effects of existing drugs that may arise as a consequence of a secondary inhibition of MAO.
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