Glycogen synthase kinase-3 beta (GSK-3β or GSK-3B) is a serine-threonine kinase involved in various pathways and cellular processes. Alteration in GSK-3β activity is associated with several neurological diseases including Alzheimer's disease (AD), bipolar disorder, and rare diseases like Rett syndrome. GSK-3β is also implicated in HIV-associated dementia (HAD), as it is upregulated in HIV-1-infected cells and plays a role in neuronal dysfunction. Therefore, a small molecule that can inhibit both GSK-3β and HIV-1 reverse transcriptase could offer neuroprotective therapy for patients suffering from HIV-1. Despite this, there are no known GSK-3β inhibitors currently approved, thus prompting us to screen our panel of various antiviral compounds against this kinase to better understand its structure-activity relationship. We show for the first time that the approved drugs, etravirine and rilpivirine, possess GSK-3β activity (IC50 619 nM and 502 nM, respectively). We have also identified 3 lead molecules exhibiting IC50 < 1 μM (11726169, 12326205, and 12326207), with compound 11726169 being the most potent in vitro GSK-3β inhibitor (IC50 = 12.1 nM). We also describe the generation of machine learning models for GSK-3β inhibition and their validation with our data as an external test set and propose their use for the future optimization of such inhibitors.
Keywords: Alzheimer’s; CNS; GSK-3β; HIV; machine learning; neuroprotection.