Read the property names before the colours
When a report arrives as a long table, it is easy to scan for reassuring labels and skip the headings. Slow down at the first column. SwissADME includes physicochemical descriptors, pharmacokinetic predictions, drug-likeness measures and medicinal-chemistry filters. They answer different questions. Pick one row and explain, in ordinary language, what it describes. If you cannot do that yet, read the tool documentation before giving the result a place in your conclusion. No single favourable entry sums up the entire compound. [1]
Save the compound and tool details
Save the exact molecular representation you submitted, not just the compound name. Keep it with the tool name, access date and downloaded output. Imagine comparing two reports a month later and finding different results. Without the submitted inputs, you may not know whether you are even comparing the same calculation. A small worksheet is enough: one compound identifier, one input, and a link to the saved report. Make this part of the routine while the browser tab is still open.
Compare the compound profiles
Before ranking compounds, decide what the comparison is for. A shortlist for further study needs an explanation of the properties you considered, not just a winner highlighted in green. The figure below uses invented values as a reading exercise; it is not a predictive model or an experimental dataset. Follow one compound across the figure rather than reading each column in isolation. Then ask what information you would still need before choosing a next step. State the reason for your comparison alongside the table.
Three profiles. Different questions.
| Compound | Molecular weight (g/mol) | Example logP | H-bond donors |
|---|---|---|---|
| A | 280 | 2.1 | 2 |
| B | 410 | 3.8 | 1 |
| C | 330 | 1.4 | 4 |
Explain the limits of the predictions
In a draft report, look for sentences that begin with “the compound is safe” or “the compound has good activity.” Does the output actually support that statement? The SwissADME paper describes computational models and their evaluation; a prediction is not a measurement in your laboratory. Name the tool and the particular property it predicted. Be specific about the uncertainty and the experimental work still needed. Careful wording does not weaken your discussion. It tells readers exactly what evidence you have. [1]
Use predictions to organize the next questions. Preserve the distinction between modeled properties and measured behavior.
Sources & further reading
Educational reading. Illustrations and example data are not Chemizen Labs research results or clinical guidance.