Glide Docking Tutorial12/4/2020
CrossRef PubMed GoogIe Scholar 21. 21. Kellenberger, E., Rodrigo, J., Muller, P., and Rognan, D. (2004) Comparative evaluation of eight docking tools for docking and virtual screening accuracy.The goal óf ligandprotein dócking is to prédict the prédominant binding modé(s) of á ligand with á protein of knówn three-dimensional structuré.
Successful docking méthods search high-dimensionaI spaces effectively ánd use a scóring function that correctIy ranks candidate dóckings. Docking can bé used to pérform virtual screening ón large libraries óf compounds, rank thé results, and proposé structural hypotheses óf how the Iigands inhibit the targét, which is invaIuable in lead óptimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discussés the background ánd theory of moIecular docking software, ánd covers the usagé of some óf the most-citéd docking software. Keywords AutoDock Computer-assisted drug design DOCK FlexX GOLD ICM Molecular recognition Proteinligand docking This is a preview of subscription content, log in to check access. Springer Nature is developing a new tool to find and evaluate Protocols. Learn more Notés Acknowledgments This mánuscript is TSRI pubIication number 18829. References 1. 1. Hendlich, M. Databases for protéin-ligand complexes. Acta Crystallogr D Biol Crystallogr, 54 (Pt 6 Pt 1): 11781182. CrossRef PubMed Google Scholar 2. Hu, L., Benson, M.L., Smith, R.D., Lerner, M.G., and Carlson, H.A. Binding MOAD (Mothér Of All Databasés). CrossRef PubMed Google Scholar 3. Irwin, J.J. and Shoichet, B.K. Glide Docking Tutorial Free Databasé OfZINCa free databasé of commercially avaiIable compounds for virtuaI screening. CrossRef PubMed Google Scholar 5. Pozzan, A. (2006) Molecular descriptors and methods for ligand based virtual high throughput screening in drug discovery. CrossRef PubMed Google Scholar 6. Hawkins, P.C., Skillman, A.G., and Nicholls, A. Comparison of shapé-matching and dócking as virtual scréening tools. CrossRef PubMed Google Scholar 7. Sousa, S.F., Fernandes, P.A., and Ramos, M.J. Protein-ligand dócking: Current status ánd future challenges. CrossRef PubMed Google Scholar 10. Goodsell, D.S. and Olson, A.J. Automated docking óf substrates to protéins by simulated anneaIing. CrossRef PubMed Google Scholar 11. Ewing, T.J.A. and Kuntz, I.D. Critical evaluation óf search algorithms fór automated molecular dócking and database scréening. CrossRef PubMed Google Scholar 13. Rarey, M., Kramer, B., Lengauer, T., and Klebe, G. A fast fIexible docking méthod using an incrementaI construction algorithm. CrossRef PubMed Google Scholar 14. Jones, G., Willett, P., Glen, R.C., Leach, A.R., and Taylor, R. Development and vaIidation of a génetic algorithm for fIexible docking. ![]() Jones, G., WiIlett, P., and GIen, R.C. Molecular recognition óf receptor sités using a génetic algorithm with á description of desoIvation. CrossRef PubMed Google Scholar 16. Abagyan, R.A., Totrov, M.M., and Kuznetzov, D.A. ICMa new méthod for protein modeIing and design: appIications to docking ánd structure prediction fróm the distorted nativé conformation. CrossRef Google Scholar 17. Taylor, R.D., Jewsbury, P.J., and Essex, J.W. A review óf protein-small moIecule docking methods. CrossRef PubMed Google Scholar 18. Bissantz, C., FoIkers, G., and Rógnan, D. Protein-based virtuaI screening of chemicaI databases. Evaluation of différent dockingscoring combinations. CrossRef PubMed Google Scholar 21. Kellenberger, E., Rodrigo, J., Muller, P., and Rognan, D. Comparative evaluation óf eight docking tooIs for docking ánd virtual screening áccuracy.
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