In Silico Tools to Score and Predict Cholesterol-Protein Interactions

J Med Chem. 2024 Dec 12;67(23):20765-20775. doi: 10.1021/acs.jmedchem.4c01885. Epub 2024 Dec 1.

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.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence
  • Binding Sites
  • Cholesterol* / chemistry
  • Cholesterol* / metabolism
  • Computer Simulation
  • Humans
  • Ligands
  • Molecular Docking Simulation
  • Molecular Dynamics Simulation
  • Protein Binding
  • Proteins / chemistry
  • Proteins / metabolism

Substances

  • Cholesterol
  • Proteins
  • Ligands