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Fundamentals of Drug Discovery
Molecular docking is also referred to as small molecular docking. Molecular docking is a study of how two or more molecular structures, for instance, drug and catalyst or macromolecule receptor, match along to be a perfect fit (Gane & Dean, 2000). Binding orientation of small-molecule drug candidates to their macromolecular targets predicts the affinity and activity of a given small molecule (Hakes, Lovell, Oliver, & Robertson, 2007).

Protein–protein docking is a simple procedure, which involves docking of two protein molecules without any need of experimental measurement. Flexible and rigid docking is followed in this type of docking (Ehrlich & Wadey, 2003). Shape complementarity is the most essential ingredient of the scoring functions for protein–protein docking (Chen & Weng, 2003). The steady rise in the number of protein structures elucidated has boosted the number of protein–protein docking studies, and intensive research is being carried out in the field. Many proteins that remain rigid after forming a complex can also be docked (Hakes et al., 2007).

Protein–ligand docking is the most commonly used docking technique. It predicts the position of a ligand when it is bound to its receptor molecule, in this case, a protein. The ligand might act as an inhibitor or a promoter. Large libraries of ligands are scanned to choose potential drug candidates (Smith, Engdahl, Dunbar, & Carlson, 2012).

AutoDock is a molecular docking suite consisting of automated docking tools. AutoDock consists of two main programs: AutoDock and AutoGrid. AutoDock docks the two molecules according to the grid, which is precalculated and set by AutoGrid. AutoDock is considered one of the best programs when it comes to docking and virtual screening (Park, Lee, & Lee, 2006). This section will give a brief overview of the steps followed in AutoDock 4.2 (Fig. 10.2). Various possible problems must be resolved before a protein can be used for AutoDock. This includes missing atoms, chain breaks, and alternate locations. Potential energy grids are used by different docking programs. These grids represent the energy calculations, and in their most basic form, the grid stashes two types of potentials: the electrostatic and the van der Waals force. The grid was formulated so that the information about the receptor's energy contributions could be stored on grid points. This allowed the necessity of it being read only during ligand scoring. More options can be explored in AutoDock, and the options may vary depending on the complexes that are being docked and also the complexity of the problem in hand.
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Figure 10.2. Steps in followed in docking analysis.

8.1 Advantages of docking
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The application of docking in a targeted drug-delivery system is a huge benefit. One can study the size, shape, charge distribution, polarity, hydrogen bonding, and hydrophobic interactions of both ligand (drug) and receptor (target site).

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Molecular docking helps in the identification of target sites of the ligand and the receptor molecule.

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Docking also helps in understanding of different enzymes and their mechanism of action.

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The “scoring” feature in docking helps in selecting the best fit or the best drug from an array of options.

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Not everything can be proved experimentally as traditional experimental methods for drug discovery take a long time. Molecular docking helps in moving the process of computer-aided drug designing faster and also provides every conformation possible based on the receptor and ligand molecule.

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Docking has a huge advantage when it comes to the study of protein interactions.

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There are millions of compounds, ligands, drugs, and receptors, the 3D structure of which has been crystallized. Virtual screening of these compounds can be made.

8.2 Limitations of docking
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In protein–small-molecule docking, there can be problems in the receptor structure. A reliable resolution value for small-molecule docking is below 1.2 Å (Gohlke & Klebe, 2002), while most crystallographic structures have a resolution between 1.5 and 2.5 Å. Increasing the use of homology models in docking should be looked at with care as they have even poorer resolution (Mihasan, 2010). Most applications accept and yield good results for structures below 2.2 Å. All the same, care should be taken while picking a structure.

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The scoring functions used in docking, almost all of them, do not take into account the role played by covalently bound inhibitors or ions (Mihasan, 2012).

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The methodology and research in protein–protein docking have to be greatly increased as the success in this field is greatly hampered by many false positives and false negatives (Moreira, Fernandes, & Ramos, 2010).

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