PS²MS

Repository for NYCU JHHLab NPS detection project.

The repository for the paper "PS²MS": A Deep Learning-Based Prediction System for Detecting Novel New Psychoactive Substances Using Mass Spectrometry.

Informations

PS²MS is designed specifically to address the limitations of identifying the emergence of unidentified novel illicit drugs. PS²MS builds a synthetic NPS database by enumerating possible derivatives based on the core structure of a preselected illicit drug. The system leverages two deep learning tools, NEIMS and DeepEI, to generate mass spectra and chemical fingerprints, respectively. Finally, PS²MS calculates the integrated similarity scores(SMSF) between the unknown analyte and the derivatives from synthetic database and yields a list of potential NPS identities for the analyte.

Requirement

• GNU g++-10 or higher
• CMake 3.16.0 or higher to build the enumeration step and the detection step
• python 3.6.9 or higher to the run deep learing tools
• rdkit
  • build the c++ code from the source and install python package from conda

Enumeration

• PS²MS will generate a synthetic database by substituting hydrogen atoms in the core structure of a given drug with functional groups.
• The synthetic database will conduct matching calculations with suspicious analytes using mass spectrometry and chemical fingerprints.
• See how to build and run the enumeration here

NEIMS

• PS²MS employs NEIMS to predict the mass spectrum of the compounds in synthetic database
• The system uses NEIMS to predict the spectrum of compounds of synthetic database.
• See how to train the NEIMS here

DeepEI

• PS²MS employs DeepEI to predict the fingerprint of the unknown analyte.
• The system also use the function of DeepEI to calculate the fingerprint of compounds of synthetic database.
• The system merges the fingerprint into the msp file.
• See how to predict fingerprint here

Drug detection

• The final step of PS²MS is to compare the analyte and the synthetic database.
• The system will compare the spectrum and chemical fingerprint between compounds and generate a list of the hundred most similar compounds which are ranked by similarity score.
• See how to build and run drug detection here