Discovery of Dual Targeting GSK-3β/HIV-1 Reverse Transcriptase Inhibitors as Neuroprotective Antiviral Agents.

Area of Science:

• Biochemistry and Pharmacology
• Neuroscience and Drug Discovery

Background:

• Glycogen synthase kinase-3 beta (GSK-3β) is a key kinase implicated in neurological disorders like Alzheimer's disease and HIV-associated dementia (HAD).
• GSK-3β upregulation in HIV-1 infection contributes to neuronal dysfunction, highlighting the need for dual inhibitors of GSK-3β and HIV-1 reverse transcriptase for neuroprotection.
• Currently, no GSK-3β inhibitors are approved, necessitating the exploration of novel therapeutic agents.

Purpose of the Study:

• To screen a panel of antiviral compounds for inhibitory activity against GSK-3β.
• To identify novel GSK-3β inhibitors with potential for neuroprotective therapy in HIV-1 patients.
• To develop and validate machine learning models for predicting GSK-3β inhibition.

Main Methods:

• Screening of various antiviral compounds against GSK-3β.
• Determination of IC50 values for identified inhibitors.
• Generation and validation of machine learning models for GSK-3β inhibition.

Main Results:

• The approved drugs etravirine and rilpivirine demonstrated GSK-3β inhibitory activity with IC50 values of 619 nM and 502 nM, respectively.
• Three lead compounds (11726169, 12326205, 12326207) were identified with IC50 < 1 microM.
• Compound 11726169 emerged as the most potent inhibitor, with an in vitro IC50 of 12.1 nM. Machine learning models were successfully validated.

Conclusions:

• Etravirine and rilpivirine exhibit previously unrecognized GSK-3β inhibitory activity.
• Compound 11726169 represents a highly potent GSK-3β inhibitor with therapeutic potential.
• Machine learning models offer a promising approach for the future optimization of GSK-3β inhibitors.