A Computational Study of Novel Kynurenine 3 Monooxygenase Inhibitors
Alzheimer’s Disease (AD) is a chronic, neurodegenerative condition that gradually affects an individual’s memory leading to dementia and ultimately death. Acetylcholinesterase inhibitors have been the mainstay of treatment for AD, but they are only able to control cognitive deficits. Such strategies only temporarily delay the symptoms and do not stop or reverse the progression of the disease. While AD was initially thought to be the result of plaque accumulation in the brain, this is being reexamined. The kynurenine pathway (KP) has been discovered to play a major role in many neurodegenerative diseases, including AD. The KP represents a major route for the catabolism of tryptophan (TRP) and accounts for most of the metabolism of TRP that is not committed to protein synthesis. Of particular interest in the KP is the KMO enzyme, which produces toxic metabolites. This accumulation leads to AD. It is believed that inhibiting KMO will lead to a decrease in the production of these toxic products downstream attenuating or improving the effects of AD. The objective of this study is to identify novel KMO inhibitors using computer aided drug design approaches. To accomplish this objective the following specific aims will be pursued: Aim 1: To determine the most thermodynamically stable conformations of each potentially novel potent inhibitors of KMO The molecular geometry for stable conformations must be calculated through energy-based methods in order to predict the corresponding molecular properties. Knowing the molecular geometry is critical for understanding structure-function relationships, as well as the design of novel drugs. Molecular mechanics will be used to explore the conformational space of potential KMO inhibitors. Each minimum energy structure will be characterized using quantum mechanics with frequency calculations. Based on ab initio and DFT full geometry optimization all stable conformations within an energy cut-off will be identified. In addition, conformational flexibility will be explored by plotting specific dihedral angles vs. the corresponding energy to generate a conformational energy profile. We hypothesize that generating a set of diverse conformations will yield the bioactive conformation that will further assist in discovery of a novel KMO inhibitor. Aim 2: To obtain a solvent equilibrated homology model of the substrate–free human KMO Understanding the conformational flexibility and tertiary structure of KMO is critical for structure-based drug design and interpreting structure-function relationship, which will be used in the design of novel therapeutics for disease. Various KMO inhibitor-bound KMO models will be generated in order to obtain accurate atomic descriptions of the inhibitor-specific catalytic site of KMO. For KMO, different homology models of human KMO will be constructed using the x-ray crystal structures of the substrate free and bound form of yKMOs. Aim 3: To better understand the specific molecular interactions between the KMO enzyme and bound inhibitors via docking and molecular dynamics simulations Docking and molecular dynamics simulations (MD) will be carried out to establish the specific molecular interactions that exist between the KMO enzyme and its bound inhibitors. Molecular modeling methodologies available through YASARA will be utilized. The chemical properties can be mapped to help identify the chemical space that contributes to inhibition. These docking algorithms will generate a score that attempt to distinguish between those potential inhibitors that bind strongly in the KMO binding pocket from those that bind weakly. Also, MD simulations will be carried out on compounds that are identified through docking using YASARA.
Hughes, Tamera Dionne