INTRODUCTION:

Drug design and Discovery:

The drug discovery process begun in the 19th century, by John Langley in 1905. In 1960, Hansch and Fujita introduced the concept of QSAR. In the drug discovery process, the first step is to identify an appropriate ‘druggable’ target, which can be a biomolecule or a protein receptor that is explicitly associated with a disease condition or pathology.

After the target has been identified, the next step involves target validation and the confirmation of its role in the disease progression. This is followed by testing of the target against different small molecule compounds to identify lead compounds which can interact with the target biomolecule and display the potential to either nullify or slow the disease development.¹

QSAR:

Quantitative structure-activity relationships (QSAR) have been applied for years in the development of relationships between physicochemical properties of chemical substances and their biological activities to obtain a reliable statistical model for prediction of the activities of new chemical entities. A quantitative structure-activity relationship (QSAR) is a mathematical relationship which correlates measurable or calculable molecular properties to some specific biological activity in terms of an equation.²

QSAR attempts to identify and quantify the physicochemical properties of a drug and to see whether any of these properties have an effect on the drugs biological activity. It helps to find consistent relationship between biological activity and molecular properties, so that these “rules” can be used to evaluate the activity of new compounds.³

Physicochemical parameters:

In QSAR modeling, the predictors consist of physio-chemical properties or theoretical molecular descriptors of chemicals the QSAR response – variable could be a biological activity of the chemicals. One of major uses of QSAR models is to predict previously unmeasured compounds and to help select a small set of compounds with interesting properties for a larger set. The other major use is to help finding explanation for a trend observe and to highlight improvements for synthesis.

Various parameters used in QSAR studies are:

Hydrophobicity: partition coefficient, π- substitution constant

Electronic parameter: Hammet constant, dipole moment

Stearic parameter: Taft’s constant, Ver loop steric parameter.⁴

Molecular Docking:

Molecular docking is a computational method used to predict the interaction of two molecules generating a binding model. It is a method which analyses the conformation and orientation (referred together as the “pose”) of molecules into the binding site of a macromolecular target. Searching algorithms generate possible poses, which are ranked by scoring functions.⁵

This method is one of the most frequently used methods in structure-based drug design, due to its ability to predict the binding-conformation of small molecule ligands to the appropriate target binding site. Characterization of the binding behavior plays an important role in rational design of drugs as well as to elucidate fundamental biochemical processes.⁶

Molecular docking is used for demonstration of the feasibility of any biochemical reaction as it is carried out before experimental part of any investigation. There are some areas, where molecular docking has revolutionized the findings. In particular, interaction between small molecules (ligand) and protein target (may be an enzyme) may predict the activation or inhibition of enzyme. Such type of information may provide a raw material for the rational drug designing. It has been significantly used for lead optimization, hit identifications and for studying drug-DNA interactions.⁷

AUTO-DOCK:

AutoDock is an automated suite of protein-ligand docking tools. AutoDock tools are abbreviated as ADT. It is designed to predict the protein interactions with small molecules such as drug molecule and substrate. The application of this tool is immense, ranging from structure-based drug design, lead molecule optimization, protein-ligand docking, protein-protein docking, analysis and validation of mechanism of action of drug molecules. AutoDock4 has two key programs to be executed, i.e., Autogrid4 and AutoDock4. Autogrid4 prepares a grid map of the amino acids presents within the Grid Box defined by the user. AutoDock4 then analyzes the interactions of those amino acids with the ligand molecule. AutoDock4 predicts the free binding energy with a scoring function based on the AMBER force field and linear regression analysis, additionally by referring to a large set of library data of known protein ligand interactions with their inhibition constants that were used in AutoDock³. It is found that the standard error in free binding energy in AutoDock4 is approximately 2.5kcal/mol.⁸

This protocol is presented to aid students and research scholars those who are interested in using AutoDock4 for learning and or research purpose. This protocol is considered to be adequate and effective by the authors, to use AutoDock4 for protein-ligand docking analysis. The discussed protocol can be used to study the interactions of selected ligand molecule (drug molecule) with chosen protein targets. Users, however, have to do a little preparative work on the protein molecule pdb file. Downloaded 3D structure of proteins from RCSB website has to be edited before docking in AutoDock4. Although a small discussion on the preparation of protein molecules is presented in this tutorial, users are advised to do further reading in the preparation of protein structures.⁹

Installation:

Download the installation files

“autodocksuite-4.2.5.1-i86Windows.exe and mgltools_win32_1.5.6_Setup.exe” from AutoDock website (http://autodock.scripps.edu/).

Run “mgltools_win32_1.5.6_Setup.exe” file and leave al the settings default and the installation folder should not be altered. Finish the installation with the default settings. Once the installation is finished, “AutoDockTools-1.5.6.exe” will be executed by default. Close the application and start the “AutoDockTools-1.5.6.exe” once again. Once the application is opened for the second time, a new folder “.mgltools” will be created automatically in the users folder (C:\Users\Guest\.mgltools). To successfully run the AutoDock software, the protein and ligand structures in their “.pdb” format have to be present within the “.mgltools” folder. Next, run the “autodocksuite-4.2.5.1-i86Windows.exe” file and select a custom folder for this. At the end of the installation, there will be two execution files created in the selected custom folder (i.e., AutoDock4. exe & autogrid4.exe). At this stage, the software is ready to be executed.¹⁰

Protein Molecule Preparation:

Protein molecules can be downloaded from Protein Data Bank website (www.rcsb.org). The downloaded protein structure in their “.pdb” format has to be edited to remove the non-amino acid residues, such as water molecules, ions, ligands that are in the complex. These can be removed using either PyMol software or WordPad. This is essential as these molecules interfere in the interaction between target molecule and protein in the software. Once the “.pdb” file is downloaded, right-click the file and open it with WordPad. Delete all the lines that begin with “HETATM” and “CONNECT” from the end of the line, these are the atoms that do not belong to amino acids and their interaction with the amino acids, respectively. The last line of the document should begin with “TER”. This document is now ready for Autodock analysis.¹¹

Executing AutoDock:

AutoDock software calculates and predicts the interaction between the ligand molecule and protein molecule based on predefined parameters. To be precise, the interactions between the molecules will be calculated at a user specified region in the protein. This region can be defined by users, using the Grip map option. Ultimately, the software predicts the interaction and binding energy of the ligand molecule and the amino acids present within the Grid Box only. Thus setting, the Grid Box at the binding site or active site or other essential regions of the protein is important.

Analysis in AutoDock can be divided into following categories; (a) Initializing molecules; (b) Running Auto Grid; (c) Running AutoDock; (d) Analyzing Interaction energy.¹²

(a)Initializing molecules - Initializing the molecule mainly includes addition of hydrogen atoms and addition of Kolman charge to the protein molecule. While for the ligand molecule, addition of Gasteiger charge, identifying aromatic carbons, detecting rotatable bonds, and setting TORSDOF value. The protein has to be initialized manually, while the ligand is automatically initialized when opened in the tool. Once the protein molecule is opened, it is important to change the view of the protein. It is essential that the protein is in “Ribbon view,” failing to do so, might result in errors in the later steps.¹³

(b)Running Auto Grid - AutoGrid has to be executed, to define the region/area in the protein to be analyzed for the interaction with the ligand molecule. In general, the region of interaction could be identified using prediction tools such as Q-Site finder and MetaPocket to identify the binding pockets on the surface of the proteins. Then, the GridBox is set in AutoDock to cover the identified binding sites. AutoDock only analyzes the interactions of ligand molecule and the amino acids that are present within the GridBox. So setting up, the GridBox is a crucial step.¹⁴

(c)Running AutoDock - Once Auto Grid is successfully completed, AutoDock can be executed. AutoDock calculates the interactions of the amino acid within the GridBox and ligand molecule.¹⁵

AutoDock calculations are performed in several steps:

Step 1—Coordinate File Preparation:

AutoDock4.2 is parameterized to use a model of the protein and ligand that includes polar hydrogen atoms, but not hydrogen atoms bonded to carbon atoms. An extended PDB format, termed PDBQT, is used for coordinate files, which includes atomic partial charges and atom types. The current AutoDock force field uses several atom types for the most common atoms, including separate types for aliphatic and aromatic carbon atoms, and separate types for polar atoms that form hydrogen bonds and those that do not. PDBQT files also include information on the torsional degrees of freedom. In cases where specific sidechains in the protein are treated as flexible, a separate PDBQT file is also created for the sidechain coordinates. AutoDockTools, the Graphical User Interface for AutoDock, may be used for creating PDBQT files from traditional PDB files.¹⁶

Step2—AutoGrid Calculation:

Rapid energy evaluation is achieved by precalculating atomic affinity potentials for each atom type in the ligand molecule being docked. In the AutoGrid procedure the protein is embedded in a three-dimensional grid and a probe atom is placed at each grid point. The energy of interaction of this single atom with the protein is assigned to the grid point. AutoGrid affinity grids are calculated for each type of atom in the ligand, typically carbon, oxygen, nitrogen and hydrogen, as well as grids of electrostatic and desolvation potentials. Then, during the AutoDock calculation, the energetics of a particular ligand configuration is evaluated using the values from the grids.¹⁷

Step 3—Docking using AutoDock:

Docking is carried out using one of several search methods. The most efficient method is a Lamarckian genetic algorithm (LGA), but traditional genetic algorithms and simulated annealing are also available. For typical systems, AutoDock is run several times to give several docked conformations, and analysis of the predicted energy and the consistency of results is combined to identify the best solution.¹⁸

Step 4—Analysis using AutoDockTools:

AutoDockTools includes a number of methods for analyzing the results of docking simulations, including tools for clustering results by conformational similarity, visualizing conformations, visualizing interactions between ligands and proteins, and visualizing the affinity potentials created by AutoGrid.¹⁹

Analyzing Interaction Energy:

Once AutoDock4.exe is successfully executed. The result will be given as the ten best confirmations. These can be viewed in the analyze options. The confirmations can be viewed in the order of their free energy binding, by choosing the “Play, ranked by energy” option. The ten conformations can be viewed by changing the conformations number. The interaction energy of the given conformation can also be viewed. The number of hydrogen bonds formed between the ligand and protein can be viewed.²⁰

CONCLUSION:

Molecular docking is an inexpensive, safe and easy to use tool which helps in investigating, interpreting, explaining and identification of molecular properties using three-dimensional structures. Since different models yield different results, it is necessary to have a small number of standard models which are applicable to very large systems. Molecular docking is used to predict the structural intermolecular complexes formed between two or more constituting molecules. These techniques are used in the field of computational chemistry, computerized biology and material used for molecular system ranges from small molecules to large biological molecules and material assembly. It is an open-source software for computational drug discovery that can be used to libraries of computer against potential drug targets.

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Received on 30.01.2022 Modified on 13.02.2022

Asian J. Research Chem. 2022; 15(2):129-132.

DOI: 10.52711/0974-4150.2022.00020