Discovery of LXR Agonists via Pharmacophore Space Mining

The goal of this proposal is to discover drug like liver X receptor LXR selective agonists that can halt and reverse the progression of Alzheimer s disease AD Recent work demonstrated that activation of the LXR signaling pathways leads to improved amyloid A turnover reduction in A plaque area and the reversal of cognitive social and olfactory deficits The research plan consists of two steps The first step is computer aided prediction of agonistic LXR selective binding blood brain barrier permeability and absence of side effects such as mutagenicity or binding to undesired targets This step relies on a novel method for pharmacophore analysis by examining the joint space of chemical compounds targets and chemical biological properties This joint space is defined using machine learning on the D geometry of spatial arrangement of pharmacophoric points using attributes such as donors acceptors aromatic rings and charged fragments The second step consists of biological assays to assess toxicity brain penetration potential and the ability to induce expression of the corresponding genes A dozen diverse compounds will have been tested through two iterations of the two steps of in silico prediction and assays at the end of Phase These initial leads will be augmented with additional de novo compounds and further scrutinized via behavioral assays dose response studies and more detailed sophisticated and mechanistic assays during Phase The outcome of this study will be new drug leads to potentially treat and prevent AD at different stages of cognitive decline and neurodegeneration Interleaving of computer aided screening of large chemical databases through novel machine learning based models with biological assays will identify drug like LXR selective agonists with minimal side effects These agonists will slow and reverse Alzheimer s Disease