ADME Druglikeness Tool

Estimating physicochemical and ADME properties from a molecular representation to aid lead prioritization for medicinal chemists.

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Om dette verktøyet

This tool computes physicochemical and ADME-relevant metrics from a molecule input to support medicinal chemistry and early drug discovery teams. It returns standardized values such as molecular weight, logP, logS, TPSA, HBD/HBA counts, rotatable bonds, and aromatic ring count. Rule-based flags for Lipinski, Veber, Ghose, and Egan assist in fast candidate filtering. The approach emphasizes reproducibility and comparability across libraries, enabling objective ranking of compounds before synthesis.

Conceptually, the tool applies established chemoinformatics calculations: MW from atomic weights; logP and logS from fragment-based models; TPSA from polar fragments; and simple counts for donors, acceptors, and rotatable bonds. Outputs include numeric values with standard units and categorical flags indicating rule compliance. Optional features add consensus solubility predictions, PAINS screening, and a basic synthetic accessibility estimate. These outputs support decision-making in library design and lead optimization, not clinical forecasting.

Who benefits include medicinal chemists, CROs, and academic researchers performing early screening and lead prioritization. The tool differentiates itself with open, transparent calculations, straightforward data exports, and alignment to common medicinal chemistry conventions, enabling rapid comparisons across compounds. It serves as a guideline for go/no-go decisions and risk assessment during preclinical planning.

Hvordan bruke

  1. Provide inputs: enter a SMILES string (and optional InChI) for a single molecule.
  2. Choose calculation scope: keep default rule sets (Lipinski/Veber) or enable advanced checks.
  3. Run calculations: initiate the analysis to generate property values and flags.
  4. Review outputs: examine MW, logP, logS, TPSA, HBD/HBA, and rule-compliance results.
  5. Export results: download CSV/JSON or copy the property bundle for downstream workflows.
How to use swissadme web tool

Frequently Asked Questions

Finn raske svar

What inputs are accepted?
The primary input is a SMILES string for a single molecule. InChI or InChIKey can be provided as optional identifiers. The tool performs internal normalization (salt removal and tautomer normalization) before calculation.
What properties are computed?
Key properties include molecular weight (Da), logP, logS, topological polar surface area (TPSA), hydrogen bond donors (HBD) and acceptors (HBA), rotatable bonds, and aromatic ring count. Rule-compliance flags for Lipinski, Veber, Ghose, and Egan are reported.
How reliable are the predictions?
Predictions are in silico estimates derived from established chemoinformatics models. They provide relative rankings and screening guidance rather than definitive experimental values. Accuracy varies by chemical space; use results for prioritization and risk assessment, not clinical forecasting.

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