Age-related cataract is a universal, slowly progressive, insidious blinding disease that affects 20 million Americans above the age of 65 years. Yet, it is unclear why cataract progresses faster in some vs other individuals who are seemingly protected and cataract free at an advanced age. The existence of differential progression rates of lens opacification among individuals implies the existence of protective as well as deleterious factors that are as yet poorly understood. We hypothesize that there are, among today?s clinically approved drugs, candidate drugs that have anti-cataract properties, and therefore could be developed as such, while others may have cataract promoting properties unbeknownst to patients and the medical community. To test this hypothesis, we propose to combine two innovative and complementary approaches, i.e. a computational approach to simultaneously identify, among clinically approved drugs, potentially anti- and pro-cataractogenic compounds, with an experimental approach geared at simultaneously identifying drugs that prevent or worsen in vitro generated oxidative stress and lens crystallin destabilization. Candidate drugs emerging from this dual approach will be tested in mouse models of age-related cataract. Using a multi-PI strategy consisting of a team of experts in computational drug repositioning, and a team of experts in high throughput screening of small molecules, animal models of age-related cataract, in oxidative stress and protein aggregation, we propose four focused and achievable goals over a four year period:
Aim 1 : Development of novel data-driven computational algorithms to identify repositioned anti-cataract drugs and cataract risk promoting drugs from all FDA-approved drugs.
Aim 2 : Testing of 2650 FDA approved clinical drugs from the Microsource Spectrum library for their efficacy or deleterious properties on protein aggregation/denaturation in three in vitro stress model systems, i.e. oxidative metabolic damage to gamma and beta crystallins, UV irradiation and whole lens in vitro incubation stress.
Aim 3 : Test the top candidate drugs emerging from the above in silico and experimental search for their potential therapeutic or deleterious activity on cataract progression in two mouse models of cataract, i.e. the LEGSKO/Gclm (Double knockout) DKO mouse and the alphaB crystallin R120G mutant knock-in mouse.
Aim 4 : Develop a comprehensive knowledge base and make all the data publicly available via interactive web application. The successful execution of this innovative program is expected to have a transformative impact in the cataract field by potentially repositioning known drugs toward both early cataract prevention as well cataract progression risk assessment.
We propose to develop an innovative strategy to identify which among today's FDA approved clinical drugs have the potential to be used for prevention of cataract progression, even though they have been developed to treat other diseases, such arthritis, Parkinson's disease or asthma. Simultaneously we will identify those drugs that actually represent an enhanced risk for cataract progression. The identification of these drugs will be achieved using a combination of computational and experimental drug prediction, and testing in mouse models that closely mimic cataract in humans.
