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    Design of A New Candidate BACE-1 Inhibitor with Computational Chemistry Method in The Treatment of Alzheimer's Disease
    (Alanya Alaaddin Keykubat Üniversitesi, 2025) Atalay, Vildan; Dalyancı, Arzu
    In recent years, the incidence of Alzheimer's disease has increased with the increase in the elderly population all over the world. Alzheimer's disease is related to the abnormality and disorder of more than one system, its pathogenesis is complex. Therefore, there is no ideal drug currently used to prevent and treat Alzheimer's, and many studies on Alzheimer's are ongoing. In the related study, docking studies were performed with the 2WJO pdb id coded crystal structure of the BACE-1 enzyme, which is associated with Alzheimer's disease, with the Lupeol molecule and 32 newly designed Lupeol derivatives using Autodock Vina software. In this context, first of all, conformers and geometric optimizations of Lupeol and its derivatives were performed with Spartan'16 software. On the other hand, visualizations and interaction maps between protein and ligands were made by Discovery Studio Visualer software. As a result of docking studies, four molecules as L-28, L-23, L-27 and L-31 with higher binding energies than Lupeol structures are determined. In the derivatization studies, it has been determined that the design of more hydrophilic structures for the active site gives better binding energy. Experimental examination of the relevant molecules is recommended.
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    Öğe
    Protein Folding Problem: A New Approach with Evolutionary Algorithms
    (Alanya Alaaddin Keykubat Üniversitesi, 2025) Canatalay, Peren Jerfi; Namazova, Madina; Atalay, Vildan
    AlphaFold is transforming the field of structural biology by predicting three-dimensional (3D) structures from protein sequences. This remarkable achievement has even led to claims that the protein folding problem has been 'solved.' However, the protein folding problem encompasses more than just structure prediction from sequences. Currently, it is unknown whether the AlphaFold revolution will help solve other issues related to protein folding. In this study, we evaluate AlphaFold's ability to predict the impact of single mutations on protein stability (??G) and function. To explore this question, we subtract the pLDDT and metrics from AlphaFold predictions before and after a single mutation in a protein, correlating the predicted changes with experimentally known ??G values. Additionally, we correlate the same AlphaFold pLDDT metrics with fluorescence levels experimentally tested using a large-scale GFP mutant data set, which indicates the effect of single mutations on the structure. We find very weak or no correlation between AlphaFold output metrics and protein stability or fluorescence change. Our results suggest that AlphaFold may not be immediately applicable to other protein folding problems or applications.