Designing of Novel Aptamer-Based AT1R Targeted Therapeutics Against Retinal Degeneration.
It is shown that retinal microglia express angiotensin II type-I receptor.
Thus its endogenous ligand Ang-II may activate directly AT1Rs on microglia to induce an activation response and may lead to increase retinal inflammatory factors production. Thus, targeting this activation pathway in diseases such as DR can be useful for the identification of novel therapeutic agents.
Since the therapeutic effects of aptamers on neurodegenerative diseases are well characterized, in the proposed project, virtual aptamer libraries will be constructed and these libraries will be screened at the binding sites of the AT1R. For this aim, we will write a Python script to generate libraries of oligonucleotides with lengths of 5 up to 10 (i.e., from 1024 (pentanucleotide) to 1048576 (decanucleotide) that will be all probable combinations of A, T, G, and C nucleotide sequences). Then, these oligonucleotides will be screened at the binding pocket of the AT1R and top-docking scored oligonucleotides will be used in molecular dynamics (MD) simulations. By this way, dynamic behavior of the protein-oligonucleotide complexes will be studied and binding free energies will be computed and sorted. As final step, based on binding free energy results (i.e., PBSA), top-scored oligonucleotides will be used in the designing the rigid and structural part of aptamer. In this step, the structural part of the aptamer will be designed by elongating the oligonucleotide using de novo designing techniques. This structural part of the aptamer will help in maintaining the optimal binding conformation of the recognition part of the aptamer. Moreover, computational predictions will be tested by in vitro experiments.
Novel therapeutic aptamer sequences will be identified, designed and tested using target-driven approaches. Validation of the results will be carried out with our collaborators (i.e., Dr. Zohreh Hosseizadeh). The core component of the proposed research is the ability to run multiple simulations, analyze them and communicate results between labs of Dr. Durdagi and Dr. Hosseizadeh. DC5 will be trained in protein-ligand interactions, machine-learning based design of therapeutics and subsequent virtual optimization. The DC5 will be also trained in development of new free-energy simulation techniques and programing/code writing.
- B4, supervisor: Nicolás Cuenca
Prpose: Training in CRISPR techniques
- B2 supervisor: Zohreh Hosseizadeh
Purpose: Validation of in silico results
- AP7, supervisor: Beatriz Llamusí
Purpose: business training
- B7, supervisor: Aileen Murphy
Purpose: economic training