Fingerprint-based consensus virtual screening towards structurally new 5-HT(6)R ligands.

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Neuroscience

Background:

• The serotonin 6 receptor (5-HT6R) is a promising target for treating cognitive disorders.
• Identifying novel ligands with unique properties is crucial for drug development.

Purpose of the Study:

• To identify novel, non-basic 5-HT6R ligands using virtual screening.
• To characterize the activity and binding modes of newly discovered compounds.

Main Methods:

• Virtual screening employing three distinct molecular fingerprints.
• In vitro assays to determine 5-HT6R binding affinity (Ki).
• Molecular docking and dynamic simulations to assess binding interactions.
• In silico ADMET profiling for drug-likeness prediction.

Main Results:

• Two novel compounds exhibiting significant 5-HT6R activity (Ki values of 119 nM and 670 nM) were identified.
• These compounds lack a positive ionizable group, classifying them as atypical, non-basic ligands.
• Docking and simulations confirmed favorable interactions within the 5-HT6R binding site.
• In silico ADMET evaluation predicted good drug-like characteristics.

Conclusions:

• The study successfully identified novel, atypical non-basic 5-HT6R ligands with promising activity.
• Computational methods validated the binding poses and predicted favorable pharmacokinetic properties.
• These findings provide a foundation for further development of 5-HT6R modulators for cognitive disorders.