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Updated: Jun 7, 2025

Identification of Cyclin-dependent Kinase 1 Specific Phosphorylation Sites by an In Vitro Kinase Assay
Published on: May 3, 2018
Enabling systemic identification and functionality profiling for Cdc42 homeostatic modulators
Satyaveni Malasala1,2, Fereshteh Azimian1,2, Yan-Hua Chen1,2,3
1Department of Chemistry and Biochemistry, College of Arts and Sciences, University of South Carolina, Columbia, SC, USA.
Abstract:
Maintaining body homeostasis is the ultimate key to health. There are rich resources of bioactive materials for the functionality of homeostatic modulators (HMs) from both natural and synthetic chemical repertories1-3. HMs are powerful modern therapeutics for human diseases including neuropsychiatric diseases, mental disorders, and drug addiction (e.g. Buspirone and benzodiazepines)4-7. However, the identification of therapeutic HMs are often unpredictable and limited to membrane protein receptors and ion channels. Based on a serendipitously encountered small molecule ZCL278 with partial agonist (PA) profile as a model compound8-10, the Mant-GTP fluorophore-based Cdc42-GEF (guanine nucleotide exchange factor) screening uncovered a near holistic spectrum of HMs for Cdc42, a cytoplasmic small GTPase in the Ras superfamily11,12. We categorized these HMs as functionally distinct, with some previously understudied classes: Class I-competitive PAs, Class II-hormetic agonists, Class III-bona fide inhibitors, Class IV-bona fide activators, and Class V-ligand-enhanced agonists. The model HMs elicited striking biological functionalities in modulating bradykinin activation of Cdc42 signaling as well as actin remodeling while they ameliorated Alzheimer's disease-like social behavior in mouse model. Furthermore, molecular structural modeling analyses led to the concept of preferential binding pocket order (PBPO) for profiling HMs that target Cdc42 complexed with intersectin (ITSN), a GEF selectively activating Cdc42. Remarkably, the PBPO enabled a prediction of HM class that mimics the pharmacological functionality. Therefore, our study highlights a model path to actively capture different classes of HM to broaden therapeutic landscape.
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