Docking
Virtual Screening Methodology for Structure-based Drug Designing

Virtual High Throughput Screening (vHTS), also known as Virtual Screening (VS) is one of the essential steps involved in in-silico drug designing. There are several bioinformatics tools that facilitate the virtual screening of thousands of compounds such as GOLD, GLIDE, Autodock Vina, and so on.
Despite all the processing done by these tools, a basic methodology is required for vHTS of thousands of compounds present in a database. In this article, we are presenting a few basic steps required for performing structure-based VS using bioinformatics tools. The complete schema is presented in Figure 1.
Figure 1 Basic steps involved in virtual screening.
Step 1. Prepare receptor
Download the structure of receptor protein from PDB. In case, the structure is not available, predict the structure using homology modeling or ab-initio methods of structure prediction. Search the literature to gather information about the binding pocket or binding residues of the protein of interest. Select a chain (or two) consisting of the binding region. If the structural details are not available in the literature, then go for binding pocket prediction using webservers or tools.
Step 2. Download compound databases such as the ZINC database of small molecules.
Download the .sdf or .mol2 files of compounds. Some databases allow downloading only smiles of the compounds, then download the smiles and use a web server or software to convert these smiles into .sfd/.mol2 files.
Step 3. Prepare receptor and ligands for docking
Depending upon the software you are using for VS, prepare the files of the receptor protein and the ligands. for example, Autodock Vina requires receptor and ligand files in .pdbqt format.
Step 4. Run VS
Load all the files in the software and run VS. Wait for the results.
Step 5. Select drug-like compounds
Select the drug-like molecules based on the binding affinity and interaction with binding residues. You can also select some lead-like molecules showing less binding affinity.
Step 6. Filtering
You can further filter obtained drug-like molecules based on their toxicity, ADME properties, poses, and so on.
Step 7. Compound selection
Select potential drug candidates for further in vitro experiments.
These are the basic steps involved in VS for structure-based drug designing. There are several bioinformatics tools other than those mentioned above that are used in VS including Discovery Studio, LigandScout, and so on.
Docking
What values are considered as good or bad in computational docking?

After performing computational docking, a question that comes to mind most is “what docking score is considered good or bad”. In this article, we will discuss this in detail. (more…)
Bioinformatics Programming
How to sort binding affinities based on a cutoff using vs_analysis.py script?

Previously, we have provided a Python script (vs_analysis.py) to analyze the virtual screening (VS) results of Autodock Vina. Now, we have updated this script to sort binding affinities based on user inputted cutoff value. (more…)
Docking
Virtual Screening using Autodock Vina: Frequently Asked Questions & Answers for Starters

Virtual Screening (VS) is one of the important techniques in bioinformatics. It can be easily performed using Autodock Vina. We have provided detailed articles on this topic. In this article, we are trying to answer some FAQs for beginners. (more…)
You must be logged in to post a comment Login