Title : Quo vadis cell-penetrating peptide?
Abstract:
This contribution discusses the state of the art with cell-penetrating peptides (CPPs). While CPPs from first generation exhibit only low cell and tissue selectivity, the peptides from the newer generation are characterized by an innate selectivity for distinct cells or specific properties for using tumor-cell-specific proteases, fenestrated capillaries, low pH or hypoxia. Because CPPs are also able to penetrate barriers such as the blood-brain barrier, skin, mucosa and different barriers at the eye, they are able to avoid the administration of drugs by injections with needles. Transport of drugs through blood-brain barrier opens possibilities to treat glioblastomas and other brain diseases. The transport through barriers at the eye enables treatment of various eye-diseases, mainly, retinopathies and infections. In addition to the internalization of drugs, also imaging of tumors, metastases or inflamed tissues remains an important field for the application of CPPs. For diagnostic use, CPPs can be coupled to sensitive markers, such as near infrared-fluorescence markers, nuclear-magnetic-resonance-sensitive Gadolinium-complexes or radionuclides. Imaging with labeled cell-selective CPPs enables not only the detection of tumors, metastases, thrombosis or inflammation but also the complete removal of diseased tissue by guided surgery.
Conjugation to polymers or nanoparticles changes biodistribution, protects CPPs against proteolytic degradation, improves handling and enables coupling of additional targeting molecules, which can greatly enhance the selectivity for diseased tissues. Such multifunctional pharmacological nanoparticles have been very promising in clinical trials. The ideal construct, the endpoint of CPP development, would be a self-navigating carrier system for intracellular drug delivery. Different methods of artificial intelligence (AI) can help to develop for a given illness the right carrier formed from right CPP, right cargo and coupled polymer. In contrast to many other trials with AI, the optimization has to start at the target disease and not with the CPP in general. Thus, the AI becomes a very complex algorithms and seems to be in many cases overtaxed.
