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Docking protocol

this is a document that you will use for studying molecular docking

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In silico Molecular Docking Protocol

Using AutoDock Vina

Prepared by: Jessa A. Payusan

Organic Synthesis Chemistry/Drug Design and Development Related Research Laboratory, Premier Research of Science and Mathematics, MSU-Iligan institute of Technology Iligan City, Philippines

May 2020

Docking Protocol ii

Table of Contents

Page

Title Page....................................................................................................................................... i - Introduction..................................................................................................................... Table of Contents........................................................................................................................ ii - Docking Protocol............................................................................................................. - I. Target Selection, Retrieval and Preparation......................................................... - i. Retrieval of target .pdb file from major databases.................................... - ii. Preparation of target .pdbqt file using AutoDock Tools 1.5.................. - iii. Setting-up the grid parameters................................................................ - II. Ligand Selection and Preparation - i. Construction of ligand via ChemBioDraw Ultra................ - ii. Optimization of ligand to .pdb file using ChemBio3D Ultra..................... - iii. Preparation of ligand .pdbqt file using AutoDock Tools 1.5.................

III. Molecular Docking ........................................................................................ - i. Preparation of the text file....................................................................... - ii. Running AutoDock Vina thru the Windows Command Prompt................... - iii. Splitting individual poses of the docking results......................................
- IV. Evaluating Docking Results................................................................................. - Molecular Viewer....................................................................................... i. Opening the target and resulting ligand in Biovia Discovery Studio - ii. Adding the ligand to the target receptor.................................................. - iii. Viewing the receptor-ligand interactions.................................................
References...................................................................................................................................

There are several excellent reviews of molecular docking methods7,17 and many publications comparing the performance of a variety of molecular docking tools18-29, often for virtual screening. It should be stressed that comparing docking methods is difficult 28 , and because there is evidence that some docking methods do better with certain classes of target than others.

Figure 1. A typical docking workflow showing the key steps to all docking protocols. The 3D structures for the target macromolecule and the small molecule must first be chosen, and then each structure must be prepared in accordance with the requirements of the docking methods being used. Following the docking, the results must be analyzed, selecting the modes with the best scores.

Figure 1 shows the key steps in docking that are common to all protocols. Docking involves finding the most favorable binding mode(s) of a ligand to the target of interest. The binding mode of a ligand with respect to the receptor can be uniquely defined by its state variables. These consist of its position (x-, y-, and z-translations), orientation, and if ligand is flexible, its confirmation (the torsion angles for each rotatable bond). Each of these state variables describes one degree of freedom in a multidimensional search space, and their bounds describe the extent of the search. Rigid body docking is faster than treating the ligand as flexible, because the size of the search space is much smaller, but if the conformation of the ligand is not correct, then there will be a lower probability of finding a complementary fit.

All docking methods require a scoring function to rank the various candidate binding modes, and a search method to explore the state variables. Scoring functions can be empirical, force fields based, or knowledge based, whereas search methods fall into two major categories:

Target Selection

Target Preparation

Ligand Selection

Ligand Preparation

Docking

Evaluating Docking Results

systematic and stochastic. Systematic search methods sample the search space at predefined

intervals and are deterministic. Stochastic search methods iteratively make random changes to the state variables until a user-defined termination criterion is met, so the outcome of the search varies. 7 Search methods can also be classified by how broadly they explore the search space, as

either local or global. Local search methods tend to find the nearest or local minimum energy of

the current conformation, whereas global methods search for the best or global minimum energy within the defined search space.

REQUIREMENTS:

The software and/or programs in this protocol run in Windows (Windows 7 and higher), although releases for other Operating Systems are available in most cases (Linux, MAC). In particular, the programs in this workflow run on 64-bit Windows 10 Home Single Language (version 1903) with an Intel® Core™ i5-8250U CPU @ 1 1 GHz Processor and 8 GB Installed RAM.

The tools and software involved are freely available for non-commercial uses:

▪ MGL Tools - mgltools.scripps/downloads ▪ AutoDock Vina - vina.scripps/download.html ▪ Discovery Studio Visualizer - 3dsbiovia/products/collaborative-science/biovia- discovery-studio/

In this protocol, the binding affinity of benzimidazole into the Human Angiotensin Converting Enzyme (PDB ID 1O86) will be used as an example.

Docking Protocol.............................................................................................................

I. Target Selection and Preparation

Ideally, the target structure should be experimentally determined, usually by either x-ray crystallography or nuclear magnetic resonance. Docking has been performed successfully against homology models36 -39, although the reliability of the docking results depends heavily on the quality and bias of the homology model.

In all x-ray crystal structures, there is a range of certainty with which atomic positions are

defined. This is quantified by the temperature factors (also known as B-values) assigned to each

atom in the PDB file. It is possible in some molecule viewers to color the atoms by B-value, which

can visually indicate regions with more structural ambiguity. To accelerate the scoring calculation, some docking methods pre-calculate grid maps to represent the receptor when calculating interaction energies with a ligand. A set of grid maps for a given receptor can be reused for docking a library of ligands, also saving time. In general, grid maps are not transferable from one docking tool to another. For AutoDock, a grid map (or grid box) needs to be computed for each type in the ligand or set of ligands being docked, in addition to electrostatic potential and desolvation grid maps. AutoDock is distributed with a GUI called AutoDockTools (ADT) which helps to prepare the target and ligand input files, and to set up the grid map (box).

c. Select the pdb file of the downloaded protein structure from the RSCB Protein Data Bank.

d. Click “Edit” and choose “Delete Water”.

e. Click “Edit” and choose “Hydrogens”. Under this option, click “Add”.

f. Select “Polar Only” then click “OK”.

for docking, including the prepared structures (ligand and target), executable files, scripts and docking outputs.

j. Select the ligand Lisinopril (LPR702) in the .pdbqt file by navigating the arrow below the molecule name under the dashboard.

k. To remove the LPR, click “Edit”, select “Delete”, then choose “Delete Selected Atoms”.

l. Save the resulting macromolecule by clicking “Save” and then selecting “Write PDBQT”. This will be the final prepared target file suitable for docking using AutoDock Vina. This must be saved in the same location with all your other necessary files. Here, we name the target macromolecule as “ace”.

c. Locate and highlight LPR702 ligand by navigating the molecule dashboard. The ligands are typically listed at the lower portion of sequence. Tick the square box to highlight the ligand LPR702.

d. Under “Grid”, click “Macromolecule”, then choose molecule 1o86. Click “Select Molecule” to continue.

g. Save the dimension settings by clicking “File”, then selecting “Close saving current”. The grid box dimensions will then be consequently used during actual docking.

Note: Many docking tools do not allow the target to be flexible, although this is a very important aspect of molecular recognition. 40 A target may adopt different conformations in the unbound and bound states, and with different classes of ligands. To tackle this and other problems, molecular dynamics has found an increasing number of applications in conjunction with molecular docking. These range from preparing the target before the docking, to accounting for receptor flexibility, solvent effects, and induced-fit, to calculating binding free energies and ranking docked ligands. 42

II. Ligand Selection and Preparation 48 The type of ligands chosen for docking will depend on the goal:

a) for lead discovery, crude filters such as net charge, molecular weight, polar surface

area, solubility, commercial availability, and price-per-compound can be applied to reduce the number of molecules to be docked.

b) for lead optimization, filters such as similarity thresholds, pharmacophores,

synthetic accessibility, and absorption, distribution, metabolism, excretion, and toxicology (ADME-Tox) properties are additionally applied.

c) for focused lead optimization, a custom library of analogs that are related to the

lead compound(s) is often constructed for docking, to inform and prioritize medicinal chemistry efforts.

AutoDock uses united-atom model for the ligand and receptor, in which only polar hydrogens are present. It also requires partial atomic charges to be assigned to the ligand. The AutoDock scoring functions were calibrated using Gasteiger charges 49 on the ligand, thus, to use the scoring functions correctly, the ligand must be assigned Gasteiger partial charges.

Most docking tools treat ligands flexibly, except for ring conformations. In general, the more rotatable bonds in a ligand, the more difficult and time-consuming the docking will tend to be. This is because the size of the search space increases exponentially with number of torsions. More highly branched torsion trees lead to more difficult searches than do linear torsion trees. Rotation of conjugated bonds, such as in amides, carbamates, ureas, etc., should be limited.

STEPS:

i. Construction of ligand via ChemBioDraw Ultra

a. Open ChemBioDraw Ultra 14 (or any version you have). Right click and select “Convert name to structure” (“Shift+Ctrl+N”). An alternative to this is by directly and manually constructing the structure using the main toolbars. Type the structure name you want to construct. In this case, we will use “Benzimidazole”.

b. Select the entire structure, right click and then select “Copy”.

ii. Optimization of ligand to .pdb file using ChemBio3D Ultra a. Open ChemBio3D Ultra 14 (or any version you have). Paste the copied chemical structure directly.

b. Under “Calculations”, select “MMMF94”, then choose “Perform MMMF Minimization”.

c. Simply click “Run” in the pop-up message.

Generally, the calculation is fairly quick. This is an energy minimization technique to optimize the ligand before preparation to suitable format for docking in AutoDock Vina. In an MMFF94 (Merck Molecular Force Field 94) energy minimization calculation, ChemBio3D examines your model and identifies its various atom types. It then calculates a new position of each atom so that the cumulative potential energy for your model is minimized. Having calculated each new position, ChemBio3D moves each atom in your model so that the total energy is at a minimum. MMFF94 & MMFF94s (designed by Merck), is particularly good with organic compounds. MMFF94 has specifically been parameterized for alkanes, alkenes, alcohols, phenols, ethers,

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