Abstract
Molecular docking (MD) is one of the commonly used method to predict the orientation of two molecules bound in a stable complex. Elucidation of knowledge about the preferred molecular orientation helps in predicting the binding affinity between two test molecules. MD is the most widely used method in structure-based drug designing and also in biochemical investigations. There are two major steps involved in MD procedure: first is a search algorithm and second is a scoring function. The search algorithm can differentiate between conformational changes of the ligand through one of the techniques above, while scoring function usually classifies different shapes retrieved by the search algorithm. The most widely used computational programs in docking procedure are DOCK, GOLD, AutoDock, Surflex, FlexX, FTDOCK, etc. These methods differ from each other in implementation of the search algorithms and their scoring function differences. In this current chapter we demonstrated the molecular docking working procedure using an easily accessible and easy-to-use AutoDock software. A brief description of different experimental stages and interpretation of results are explained with the help of different screenshots.
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References
Adeniyi AA, Ajibade PA (2013) Comparing the suitability of autodock, gold and glide for the docking and predicting the possible targets of Ru(II)-based complexes as anticancer agents. Molecules 18(4):3760–3778
Banaganapalli B, Mulakayala C, D G, Mulakayala N, Pulaganti M, Shaik NA, Cm A, Rao RM, Al-Aama JY, Chitta SK (2013a) Synthesis and biological activity of new resveratrol derivative and molecular docking: dynamics studies on NFkB. Appl Biochem Biotechnol 171(7):1639–1657
Banaganapalli B, Mulakayala C, Pulaganti M, Mulakayala N, Anuradha CM, Suresh Kumar C, Shaik NA, Yousuf Al-Aama J, Gudla D (2013b) Experimental and computational studies on newly synthesized resveratrol derivative: a new method for cancer chemoprevention and therapeutics? OMICS 17(11):568–583
Bohm HJ (1992) The computer program LUDI: a new method for the de novo design of enzyme inhibitors. J Comput Aided Mol Des 6(1):61–78
Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L, Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York DM, Karplus M (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30(10):1545–1614
El-Hachem N, Haibe-Kains B, Khalil A, Kobeissy FH, Nemer G (2017) AutoDock and AutoDockTools for protein-ligand docking: Beta-site amyloid precursor protein cleaving enzyme 1(BACE1) as a case study. Methods Mol Biol 1598:391–403
Ewing SA, Dawson JE, Panciera RJ, Mathew JS, Pratt KW, Katavolos P, Telford SR 3rd (1997) Dogs infected with a human granulocytotropic Ehrlichia spp. (Rickettsiales: Ehrlichieae). J Med Entomol 34(6):710–718
Filikov AV, Mohan V, Vickers TA, Griffey RH, Cook PD, Abagyan RA, James TL (2000) Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR. J Comput Aided Mol Des 14(6):593–610
Hindle SA, Rarey M, Buning C, Lengaue T (2002) Flexible docking under pharmacophore type constraints. J Comput Aided Mol Des 16(2):129–149
James TL, Lind KE, Filikov AV, Mujeeb A (2000) Three-dimensional RNA structure-based drug discovery. J Biomol Struct Dyn 17(Suppl 1):201–205
Jiang S, Huang K, Liu W, Fu F, Xu J (2015) Combined autodock and comparative molecular field analysis study on predicting 5-lipoxygenase inhibitory activity of flavonoids isolated from Spatholobus suberectus Dunn. Z Naturforsch C 70(3–4):103–113
Judson RS (1996) Genetic algorithms and their uses in chemistry. In: Boyd DB, Lipkowitz K (eds) Reviews in computational chemistry, vol 10. Wiley, New York, pp 1–73
Kramer B, Rarey M, Lengauer T (1997) CASP2 experiences with docking flexible ligands using FlexX. Proteins (1):221–225
Kramer B, Rarey M, Lengauer T (1999) Evaluation of the FLEXX incremental construction algorithm for protein-ligand docking. Proteins 37(2):228–241
Kuntz ID (1992) Structure-based strategies for drug design and discovery. Science 257(5073):1078–1082
Morris GM, Goodsell DS, Huey R, Olson AJ (1996) Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4. J Comput Aided Mol Des 10(4):293–304
Morris GM, Huey R, Olson AJ (2008) Using AutoDock for ligand-receptor docking, Curr Protoc bioinformatics Chapter 8. Unitas 8:14
Schellhammer I, Rarey M (2004) FlexX-Scan: fast, structure-based virtual screening. Proteins 57(3):504–517
Spitzer R, Jain AN (2012) Surflex-Dock: Docking benchmarks and real-world application. J Comput Aided Mol Des 26(6):687–699
Taylor RD, Jewsbury PJ, Essex JW (2002) A review of protein-small molecule docking methods. J Comput Aided Mol Des 16(3):151–166
Vicente J, Chicote MT, Guerrero R, Jones PG, Ramirez De Arellano MC (1997) Gold(I) Complexes with N-Donor Ligands. 2.1 Reactions of Ammonium Salts with [Au(acac-κC2)(PR3)] To Give [Au(NH3)L]+, [(AuL)2(μ2-NH2)]+, [(AuL)4(μ4-N)]+, or [(AuL)3(μ3-O)]+. A New and Facile Synthesis of [Au(NH3)2]+ Salts. Crystal Structure of [{AuP(C6H4OMe-4)3}3(μ3-O)]CF3SO3. Inorg Chem 36(20):4438–4443
Westhead DR, Clark DE, Murray CW (1997) A comparison of heuristic search algorithms for molecular docking. J Comput Aided Mol Des 11(3):209–228
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Banaganapalli, B. et al. (2019). Molecular Docking. In: Shaik, N., Hakeem, K., Banaganapalli, B., Elango, R. (eds) Essentials of Bioinformatics, Volume I. Springer, Cham. https://doi.org/10.1007/978-3-030-02634-9_15
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