Motivation

Peptidic natural products (PNPs) are considered a promising compound class that has many applications in medicine. Recently developed mass spectrometry-based pipelines are transforming PNP discovery into a high-throughput technology. However, the current computational methods for PNP identification via database search of mass spectra are still in their infancy and could be substantially improved.

Results

Here we present NPS, a statistical learning-based approach for scoring PNP–spectrum matches. We incorporated NPS into two leading PNP discovery tools and benchmarked them on millions of natural product mass spectra. The results demonstrate more than 45% increase in the number of identified spectra and 20% more found PNPs at a false discovery rate of 1%.

Availability and implementation

NPS is available as a command line tool and as a web application at http://cab.spbu.ru/software/NPS.

Supplementary information

Supplementary data are available at Bioinformatics online.

© The Author(s) 2019. Published by Oxford University Press.
2019
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