GSK-3 inhibitors are interesting candidates to develop anti-Alzheimer compounds. GSK-3β are also interesting as antiparasitic compounds active against Plasmodium falciparum, Trypanosoma brucei, and Leishmania donovani; the causative agents for Malaria, African Trypanosomiasis and Leishmaniosis. The high number of possible candidates creates the necessity of Quantitative Structure-Activity Relationship models in order to guide the GSK3 (Glycogen Synthase Kinase 3 inhibitor) synthesis. In this work, we revised different computational studies for a very large and heterogeneous series of GSK-3Is. First, we revised QSAR studies with conceptual parameters such as flexibility of rotation, probability of availability, etc. We then used the method of regression analysis and QSAR studies in order to understand the essential structural requirement for binding with receptor. Next, we reviewed 3D-QSAR, CoMFA and CoMSIA with different compounds to find out the structural requirements for GSK-3 inhibitory activity.
Keywords: QSAR, Alzheimer, SAR, parasitic, fungi, anti-Alzheimer compounds, GSK-3, Neurofibrillary tangles (NFTs), Docking, Thiadiazolidinone Derivatives, QSAR Modeling, Indirubin Analogues, Bisarylmaleimides, CDK-2, CDK-4, Image-Based Approach, Indirubin Derivatives, Multi-Target QSAR
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