Development of nano-system to deliver the drugs into the brain against neuroinvasive pathogens
| Identifier | APVV-22-0084 |
|---|---|
| Funding scheme | Slovak research and development agency |
| Principal investigator at UVLF | Bhide Mangesh Ramesh, prof. MVSc., PhD. |
| Name of the project’s principal investigator | - |
| Project duration | 01.06.2023 – 30.06.2027 |
Infectious diseases of the central nervous system (CNS) continue to be a significant cause serious of morbidity and mortality. A major obstacle for treating brain diseases is the blood-brain barrier (BBB), which impedes reaching of therapeutic agents to the brain and target pathogens. Therefore, effective and targeted drug delivery systems reaching the CNS are desperately needed. This project aims to develop nanotechnology-based targeted drug delivery systems (nDDs) to fight against neuroinvasive pathogens using Borrelia and 3 viral agents (West Nile virus, Tick-borne encephalitis virus and SARS-CoV-2) as a proof-of-concept study. The nDDs will be made up of radially symmetric polyamidoamine (PAMAM) dendrimers coated with cyclic peptides (C7C peptides or CDR3 domain derived from the llama heavy chain antibody) that have high and specific binding to the pathogen. Dendrimers with the inherent antiborrelial or antiviral activity will be chosen from an existing collection of dendrimers available in our laboratory, while the C7C and CDR3 will be created using phage display technology. To enhance the distribution of nDDs across BBB, angiopep2 (a BBB-homing peptide) will also be conjugated on dendrimer surface. In the case of Borrelia, nDDS will be incorporated with antibiotic to achieve synergistic effect. The so-obtained nDDs will be characterized for their antibacterial/antiviral properties, pharmacological safety and ability to cross HEB. The success of this project will validate the proof-of-concept study to combine pathogen-specific peptide synthesis display technology with the nanotechnology based drug. We expect clinically useful pilot results for future translation of the best performing nDDs, and at the same time, research data of general scientific interest useful to the broad scientific community.