How to Use DataWarrior for Drug Discovery: Key Workflows From the Villoutreix Tutorials

DataWarrior is the triage step, not the model. Bruno Villoutreix’s tutorial series is the guided tour this note follows. Part 1 is a filter: a name pattern, then a substructure, then a row list you can export.

The practice set is the Wikipedia molecule import inside the program, on the order of 22,000 structures, depending on the version. No separate download URL is given here.

What the program is

DataWarrior is a free, open-source, chemistry-aware table. Academic and commercial use are both covered. It filters in real time on text, numbers, and structure. It draws 2D and 3D plots. It calculates properties, enumerates combinatorial libraries, runs PCA and t-SNE, and can dock into a pocket. Formats are SMILES, SDF (v2 and v3), CSV, tab-delimited text, and its own DWIR project file.

A lot of the interface is a right-click, a sub-window, or a pop-up. The useful mental model is a spreadsheet that knows what a molecule is.

Villoutreix’s series is about 85 minutes across 9 videos. Part 1 is the import-and-filter path summarized here. The videos are where the clicks are. This page does not restage them as screenshots.

The Part 1 filter

Import the Wikipedia structures from inside DataWarrior. Then:

1. Filter names with a regular expression. The examples are .*ib for kinase inhibitors, .*sartan for angiotensin receptor blockers, and .*azole for antifungals. Applied to the Wikipedia set, each suffix is a much smaller table.
2. Draw a fragment in the structure filter. The example is a piperazine or piperidine. Rows have to match the name rule and contain the fragment. The hit atoms are shown in red.
3. Make a row list. The example list is named cancer. Add a SMILES column. Drop columns you do not need, such as formula, molecular weight, and the structure depiction. Save tab-delimited text, cancer.txt.

Repeat with another suffix, such as .*azole, when you want a second set.

Where it sits in a project

Bring your own SDF or SMILES in, and merge assay or ADMET columns, once the Wikipedia exercise is familiar. The same two filters apply: a name or series pattern, and a scaffold. Plots are for activity, scatter, PCA or t-SNE, and the clusters you would otherwise miss in a table. The export is the clean SMILES-plus-metadata file that docking, QSAR, molecular dynamics, or a library design step can read.

Install DataWarrior from the official site, then follow the six clicks above on the Wikipedia set before you trust the same clicks on a project table. The program is the interactive layer in front of the modeling. It is not the model.