NaPLeS - Natural Product Likeness Score calculator


Natural product-likeness of a molecule, i.e. similarity of this molecule to the structure space covered by natural products, is a useful criterion in screening compound libraries and in designing new lead compounds. This NP-likeness scorer has been trained on 315 916 natural products (NP) from various public databases, on a manually curated NP dataset used for the publication of the previous standalone NP-likeness scorer [1] and on 488 642 randomly selected synthetic molecules (SM) from the ZINC database.

Sugar moieties are removed from the molecules for the training and for the computation of the NP-likeness score as in [2]
The stereochemistry is removed from the training set and from the user-submitted molecules.

Four ways to use the NP-likeness scorer:

Upload a file

Molecular file to upload :
Accepted formats: SDF, MOL, SMILES.
Max number of molecules: 1000 (can be long)

Draw a molecule

The molecules are kept confidential and can be deleted after processing.
Cite us: Sorokina, M., Steinbeck, C. NaPLeS: a natural products likeness scorer—web application and database. J Cheminform 11, 55 (2019).

Paste SMILES string

All SMILES types accepted but stereochemistry and isotopes will be ignored

Distribution of NP-likeness score across databases, taxonomy and molecular size

[1] Jayaseelan et al., Natural product-likeness score revisited: an open-source, open-data implementation. In: BMC Bioinformatics, 13 (1), pp. 106, 2012.

[2] Peter Ertl et al., Natural Product-likeness Score and Its Application for Prioritization of Compound Libraries. In: Journal of Chemical Information and Modeling 48 (1), 68-74, 2008