“QUANTIFYING POLY PHARMACOLOGY: SCORING FUNCTIONS AND COMPOSITE INDICES FOR AD MTDLS”

Abstract

Alzheimer’s disease (AD) is a complex, multifactorial neurodegenerative disorder characterized by amyloid-β aggregation, tau hyperphosphorylation, oxidative stress, mitochondrial dysfunction, and neuroinflammation. The failure of single-target therapies has shifted attention toward multi-target directed ligands (MTDLs), which aim to modulate multiple pathological pathways simultaneously. A critical challenge in developing and evaluating MTDLs lies in quantifying their degree of polypharmacology—how effectively a compound engages multiple targets with therapeutic relevance. Scoring functions and composite indices have emerged as promising approaches to measure and compare polypharmacological profiles. These methods integrate binding affinity data, pharmacokinetic parameters, and network-based interactions into numerical descriptors that capture both the breadth and balance of target modulation. Computational scoring functions, such as docking-based affinity predictions and machine learning models, allow rapid in silico assessment of polypharmacological potential. Meanwhile, composite indices combine multiple criteria—efficacy, selectivity, drug-likeness, and safety—to provide holistic evaluations of candidate molecules. In the context of AD, such metrics can guide the rational design and prioritization of MTDLs targeting cholinesterases, NMDA receptors, monoamine oxidases, and amyloidogenic proteins. Furthermore, polypharmacology scoring can help predict off-target liabilities and optimize therapeutic windows. This review highlights the methodological advances in quantifying polypharmacology, discusses their application in AD drug discovery, and proposes future perspectives on integrating systems biology, network pharmacology, and artificial intelligence for more precise evaluation of MTDLs. By refining these scoring strategies, researchers can accelerate the identification of safe and effective multi-target therapeutics, offering renewed hope in the battle against Alzheimer’s disease.