<br/>Polypharmacology has emerged as a new strategy for discovering novel therapeutics for complex diseases. Existing efforts in the rationale design of polypharmacology has three limitations: focus on a single clinical indication, difficulties in target selection, lead identification, and lead optimization, as well as ignorance of genome-wide drug-target interactions. Multi-indication therapeutics are needed for complex diseases such as cancer and Alzheimer’s disease, which have multiple pathological manifestations. The design and discovery of multi-indication drugs requires the knowledge of chemical-protein interactions across gene families and on a genome scale. We develop a new structural systems pharmacology platform 3D-REMAP that enhances our capability of identifying genome-wide chemical-protein interactions. We propose a strategy that uses the concept of drug repurposing to address challenges in designing safe dual-indication drugs that can synergistically achieve two desired clinical end points. As a proof-of-concept, we computationally predict and experimentally validate that levosimendan, a drug for heart failure that is associated with all existing anti-cancer therapies is active against lymphoma. We further identify biomarkers that predict patient’s response to levosimendan. This study demonstrates the potential of structural systems pharmacology in designing polypharmacology for precision medicine. Our approach may facilitate transforming conventional polypharmacology approach to a new one-drug-multi-target-multi-disease paradigm.<br/>

Rational design of cross-gene family multitarget kinase inhibitors for multi-indication polypharmacology

2019 Fall National Meeting

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