Abstract
Computational docking and scoring techniques have revolutionized structural bioinformatics by providing unprecedented insights on key aspects of ligand-receptor interaction. Docking is used for optimizing known drugs and for identifying novel binders by predicting their binding mode and affinity. AutoDock and AutoDockTools are free of charge techniques that have been extensively cited in the literature as essential tools in structure-based drug design. Moreover, these methods are fast enough to permit virtual screening of ligand libraries containing tens of thousands of compounds. However using Autodock requires some knowledge in programming which creates a limitation for biologists and makes them prone for commercial applications. Here, we selected a relevant target involved in the progression of Alzheimer disease and provided a fully reproducible docking protocol. This example will show how docking techniques would be an important asset to identify new BACE1 inhibitors. The following friendly user tutorial targets both undergraduate and graduate students, allowing them to understand docking as a computational tool for structure-based drug design.
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El-Hachem, N., Haibe-Kains, B., Khalil, A., Kobeissy, F.H., Nemer, G. (2017). AutoDock and AutoDockTools for Protein-Ligand Docking: Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1(BACE1) as a Case Study. In: Kobeissy, F., Stevens, Jr., S. (eds) Neuroproteomics. Methods in Molecular Biology, vol 1598. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6952-4_20
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DOI: https://doi.org/10.1007/978-1-4939-6952-4_20
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Publisher Name: Humana Press, New York, NY
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Online ISBN: 978-1-4939-6952-4
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