Unit:
Κατεύθυνση ΒιοπληροφορικήLibrary of the School of Science
Author:
Travlos Nikiforos Nikitas
Supervisors info:
Δρ. Μαρία Ζερβού
Δρ. Θεοδώρα Καλογεροπούλου
Καθηγητής Κωνσταντίνος Βοργιάς
Original Title:
In silico μελέτες για την αναζήτηση επιλεκτικών αγωνιστών του υποδοχέα γλυκοκορτικοειδών
Translated title:
In-silico design of new and potent glucocorticoid receptor agonists
Summary:
Glucocorticoids (GCs) are among the most prescribed drugs worldwide for the treatment of numerous immune and inflammatory disorders. However, GC therapy is often accompanied by a wide range of adverse side effects. GCs anti-inflammatory effects are mediated through the glucocorticoid receptor (GR) mainly by inhibiting the pro-inflammatory transcription factor NF-kB action, a mechanism termed transrepression. On the other hand, it is widely accepted that the majority of side effects of GCs are triggered through the transactivation activity, a mechanism which refers to the direct binding of activated GR to DNA elements known as glucocorticoid responsive elements (GREs).
This study aimed at discovering new non-steroidal selective GR receptor agonists (SEGRA) that would preferably suppress NF-kB activity (transrepression pathway) while displaying a partial agonist profile in the transactivation pathway associated with undesirable side effects.
ZINC database (7.600.000 entries) was virtually screened against a generated ligand-based pharmacophore model based on known bioactive molecules with SEGRA profile. The ligand-based pharmacophore approach was adopted in an effort to identify potential hits of different sizes since the binding cavity of the GR-LBD is extremely flexible and can adapt to ligands of impressively different sizes.
A training set of 21 nonsteroidal SEGRAs was used to construct a merged pharmacophore model bearing their common features. The model was refined and validated by virtually screening a database consisting of 85 actives and 170 inactives as recovered from ChEMBL database.
The applied protocol included the pharmacophore-based virtual screening of Zinc database, the filtering of the retrieved compounds based on their physicochemical properties, and molecular docking studies at the GR-LBD active site by applying in silico docking algorithms of increasing accuracy (Glide HTVS -High Precision Virtual Screening, SP -Standard Precision, IFD-Induced Fit Docking). Two recently resolved crystal structures (pdb: 5G3J και pdb: 5G5W) were used for the SP and IFD docking calculations in order to expand the number of compounds of potential interest.
The final selection was guided by the binding affinity and the presence of critical interactions in the active site, the ADME profiling (high lipophilicity and low number of predicted metabolites) and chemotypes diversity. A set of 17 compounds was prioritized to be purchased for biological evaluation.
The research work of the current thesis was implemented at the Institute of Biology, Medicinal Chemistry and Biotechnology of the National Hellenic Research Foundation (2017-2018).
Main subject category:
Science
Keywords:
Glucocorticoids , GC, NF-kB, GR, SEGRA, pharmacophore, Docking, anti-inflammatory
