In Silico Tools to Score and Predict Cholesterol–Protein Interactions

Abstract

Cholesterol is structurally distinct from other lipids, which confers it with singular roles in membrane organization and protein function. As a signaling molecule, cholesterol engages in discrete interactions with transmembrane, peripheral, and certain soluble proteins to control cellular responses. Accordingly, the cholesterol–protein interface is central to cholesterol-related diseases and is an essential consideration in drug design. However, cholesterol’s hydrophobic, un-drug-like nature presents a unique challenge to traditional in silico analyses. In this Perspective, we survey a collection of tools designed to predict and evaluate cholesterol binding sites in proteins, including classical sequence motifs, molecular docking, template-based strategies, molecular dynamics simulations, and recent artificial intelligence approaches. We then comment on contemporary tools to evaluate ligand–protein interactions, their applicability to cholesterol, and the yet-untapped potential of cholesterol–protein interactions in human health and disease.