Brain shuttle peptides: From permeability assay toolbox to data-driven discovery

Area of Science:

• Neuroscience
• Pharmacology
• Biotechnology

Background:

• The blood-brain barrier (BBB) protects the central nervous system (CNS) but hinders drug delivery.
• Peptides offer potential as brain shuttles due to their transport capabilities.

Purpose of the Study:

• To review models for assessing peptide transport across the BBB.
• To guide researchers in selecting tools for studying peptide shuttles and brain distribution.

Main Methods:

• Overview of in vitro models (artificial membranes, BBB-on-a-chip) and in vivo models (brain perfusion, molecular imaging).
• Discussion of mass-based quantification techniques.
• Highlighting the role of machine learning in identifying BBB-crossing peptides.

Main Results:

• Various models can assess BBB permeability, transport mechanisms, and peptide distribution.
• Machine learning is increasingly used to predict peptide BBB potential.

Conclusions:

• Appropriate selection and combination of models are crucial for studying peptide BBB transport.
• This chapter provides methodological guidance for researchers in the field.