P2‐044: the Development of High Throughput Screening Strategies to Identify Anti‐Proteopathic and Anti‐Immunopathic Agents for the Treatment of Alzheimer's Dementia

Although there is a need for new therapeutics, high throughput screening to identify such compounds is costly and time demanding. There is a need to identify and implement new techniques to permit in silico high throughput screening. Multiple in silico libraries have been developed and employed to identify compounds as putative therapeutics for Alzheimer's disease (AD). Four in silico libraries were put in place: 1. library of synthetic organic molecules (11.8 million); 2. library of plant-based natural products (2,000 entries); 3. library of known drug molecules (1,800 entries); and 4. library of small molecules endogenous to the human brain (1,200 entries). The ability of these compounds to bind to either the EVHHQK or LVFF motifs within beta-amyloid was assessed using an empirical force field energy minimization strategy. A select group of compounds identified in this screen were subsequently evaluated using in vitro assays, in order to validate the in silico screen. Within all four libraries, multiple hits capable of establishing energetically favourable interactions with either or both of the EVHHQK and LVFF motifs were identified. For example, within the plant-based natural product library screen, multiple polyphenols from apple peel and multiple phenylpropanoid plant metabolites (e.g. ferulic acid) were identified; within the known drug library screen, agents such as mefanamic acid were identified. A systemic in silico high throughput screening method for evaluating millions of compounds for their capacity to interact with varying “faces” of beta-amyloid has been developed and implemented.