Drug repositioning to propose alternative modulators for glucocorticoid receptor through structure-based virtual...

Area of Science:

• Computational chemistry
• Drug discovery
• Molecular modeling

Background:

• Drug repositioning offers a strategy for identifying new therapeutic agents with improved safety profiles.
• Existing drugs targeting the human glucocorticoid receptor (hGR) often present persistent side effects.
• Novel modulators for hGR are needed to address limitations of current therapies.

Purpose of the Study:

• To employ structure-based pharmacophore modeling and molecular docking to screen existing drug libraries for novel hGR modulators.
• To identify potential drug candidates with unique scaffolds and reduced side effect profiles.
• To accelerate the discovery of new therapeutic solutions for hGR-related conditions.

Main Methods:

• Development of a shared pharmacophore model based on hGR crystal structures.
• Screening of small and large drug databases (including FDA-approved and investigational compounds).
• Structure-based virtual screening, molecular docking, and molecular dynamics simulations were utilized.

Main Results:

• The shared pharmacophore model successfully distinguished between hGR agonists and antagonists.
• A library of over 5000 compounds yielded 110 initial hits, with 54 meeting docking criteria.
• Nineteen nonsteroidal compounds with unique scaffolds were identified among the final hits.
• Molecular dynamics simulations confirmed stable binding conformations for selected candidates.

Conclusions:

• Structure-based pharmacophore modeling is an effective strategy for drug repositioning against hGR.
• The study identified promising nonsteroidal drug candidates for hGR modulation.
• These novel compounds represent potential alternatives with unique structures and potentially fewer side effects.