Welcome to motifDB

Create a new motifset

Once MS2LDA experiments have been created and annotated, you could use them to create your own motifset on MotifDB. The patterns of fragments and neutral losses from these motifsets could be selected for unsupervised substructural discovery on new data when running LDA experiments on this website and on GNPS-MS2LDA workflow.

Create your own motifset on MotifDB from one of your own MS2LDA experiments

The following motif sets have been contributed by the community
Motifset Name Feature Set Description No. motifs
Urine derived Mass2Motifs 0.005 Da Mass2Motifs annotated from positive ionisation mode mass spectra generated from extracts of urine samples. 134 motifs
GNPS library derived Mass2Motifs 0.005 Da MS/MS spectra obtained from reference compounds and isolated molecules from diverse sources with a focus on bacterial and plant related molecules - positive ionisation mode mass spectrometry on various instruments. 78 motifs
Massbank library derived Mass2Motifs 0.005 Da MS/MS spectra obtained from reference compounds and isolated molecules from diverse sources with a slight focus on plant related molecules - positive ionisation mode mass spectrometry on various instruments 46 motifs
Rhamnaceae Plant Mass2Motifs 0.005 Da Annotated Mass2Motifs from data set comprising 71 Rhamnaceae plant extracts 31 motifs
Euphorbia Plant Mass2Motifs 0.005 Da Annotated Mass2Motifs from data set comprising 43 Euphorbia plant extracts 66 motifs
LDB_NEG_MotifDB_02 0.01 Da Motif DB applicable to lichen samples, produced with 816 spectra from with 250 lichen molecules. The spectra were produced by three different machines (Agilent 6530 qToF, Waters Xevo G2-XS qToF, Thermo Orbitrap q-Exactive). The chemical classification of lichen compounds as described in Identification of lichen substances (Huneck & Yoshimura, 1996) was used to annotate the motifs produced. MS2LDA experiment used : 200421_LDB_NEG_07. 100 motifs
MIADB_pos_indole 0.005 Da Motif DB applicable to MIA-containing plants, produced with 200 spectra from the MIADB - one annotated motif related to decorated indole substructures. 1 motifs
MIADB_pos_60 0.005 Da Motif DB applicable to MIA-containing plants, produced with 200 spectra from the MIADB (60 mass 2 motifs) 7 motifs
MIADB_pos_100 0.005 Da Motif DB applicable to MIA-containing plants, produced with 200 spectra from the MIADB (100 mass 2 motifs) 10 motifs
Streptomyces S29 0.005 Da Mass2Motifs annotated from positive ionisation mode mass spectra generated from extracts of Streptomyces sp. S29 (Atacama Desert rhizosphere derived strain) 13 motifs
fragment_253.1925 0.005 Da Common fragment from cholestane-like structures. Phytochem Anal. 2019 Mar;30(2):132-138. doi: 10.1002/pca.2798. Extending Compound Identification for Molecular Network Using the LipidXplorer Database Independent Method: A Proof of Concept Using Glycoalkaloids From Solanum Pseudoquina A. St.-Hil 0 motifs
Tps6_motifs 0.005 Da Diatoms grown under phosphate-replete and phosphte-deplete conditions 1 motifs
LDB_NEG_MotifDB_01 0.005 Da Motif DB applicable to lichen samples, produced with 1500 spectra from with 250 lichen molecules. The spectra were produced by three different machines (Agilent 6530 qToF, Waters Xevo G2-XS qToF, Thermo Orbitrap q-Exactive). The chemical classification of lichen compounds as described in Identification of lichen substances (Huneck & Yoshimura, 1996) was used to annotate the motifs produced. MS2LDA experiment used : 200326_LDB_NEG_02. 300 motifs
MIADB_pos 0.005 Da Annotated Mass2Motifs from 200 monoterpene indole alkaloids from the MIADB (pos) Qtof 0 motifs
Streptomyces and Salinispora Mass2Motifs 0.1 Da Annotated Mass2Motif set from Streptomyces and Salinispora extracts with 0.1 Da binned features 40 motifs
Photorhabdus and Xenorhabdus Mass2Motifs 0.005 Da Mass2Motifs discovered in Molecular Networking clustered positive ionisation mode mass spectra generated from bacterial extracts of nematode symbionts of the Photorhabdus and Xenorhabdus genera. 46 motifs
LDB MotifDB POS 0.01 Da MotifDB produced by the positive mode spectra of the LDB (250+ compounds with 745 spectra including different adducts and acquisition from three LC-MS instruments: Agilent 6530, Thermo Q-Exactive Focus, Waters Xevo G2-XS). Spectra were annotated with SMILES for MAGMa and substructure annotation. The chemical classes are from Huneck&Yoshimura (1996), and were used to annotate each motif. Parameters: 100 free motifs - binning of 0.01 Da. 100 motifs
Planomonospora-associated Mass2Motifs 0.005 Da Annotated Mass2Motif set from Planomonospora extracts with 0.01 Da binned features. 30 motifs
Human Urine ESI_POS 0.005 Da Mass2Motifs annotated from positive ESI ionization generated from urine samples. 0 motifs
20210810_16HT 0.005 Da GNPS Analysis 0 motifs
cholestane_glicoalkaloids 0.005 Da Common fragment from cholestane-like structures in glycoalkaloids. This is meant to include the key-fragments: 396.32 and 253.19 ([M+H]+. . Phytochem Anal. 2019 Mar;30(2):132-138. DOI: 10.1002/pca.2798. Extending Compound Identification for Molecular Network Using the LipidXplorer Database Independent Method: A Proof of Concept Using Glycoalkaloids From Solanum Pseudoquina A. St.-Hil 0 motifs
Test25 0.005 Da Df 0 motifs
Aporphinic_alkaloids 0.005 Da Test for motifset annotation including Mass2Motif: motif_137 Mass2Motif: motif_366 Mass2Motif: motif_228 for aporphinic alkaloids obtained from the alkaloidic fraction of Peumus boldus. 4 motifs
Urine derived Mass2Motifs 2 0.005 Da Mass2Motifs annotated from positive ionisation mode mass spectra generated from extracts of urine samples. 14 motifs
NP_rings 0.005 Da Natural Products Rings based on: Chen, Y., Rosenkranz, C., Hirte, S., & Kirchmair, J. (2022). Ring systems in natural products: Structural diversity, physicochemical properties, and coverage by synthetic compounds. Natural Product Reports, 39(8), 1544–1556. https://doi.org/10.1039/d2np00001f 300 motifs
Test_FA 0.005 Da Test 0 motifs
Test_FA2 0.005 Da some_oxFA 9 motifs
DHA_motif 0.005 Da Some FAox_motif 14 motifs
test 0.005 Da test 367 motifs
dlc 0.005 Da no 300 motifs
Smka 0.005 Da Jskwk 1 motifs
Luke 0.005 Da Untargeted LC-MS data from coral extracts 0 motifs
API Access

MotifDB provides a RESTful API that allows programmatic access to motif sets and their metadata. This enables integration with other tools and workflows for mass spectrometry data analysis.

Available Endpoints
Endpoint Method Description
http://ms2lda.org/motifdb/list_motifsets GET Returns a JSON dictionary of available motif sets and their IDs
http://ms2lda.org/motifdb/get_motifset/{ID} GET Returns a JSON object with all motifs in the specified motifset
http://ms2lda.org/motifdb/get_motifset_metadata/{ID} GET Returns metadata for motifs in the specified motifset
http://ms2lda.org/motifdb/get_motifset POST Returns motifs and metadata for multiple motifsets
http://ms2lda.org/motifdb/initialise_api GET Returns a CSRF token required for POST requests
Usage Instructions

Single Motifset Access: To access a single motifset, send a GET request to http://ms2lda.org/motifdb/get_motifset/{ID}, where {ID} is the ID obtained from the motifset list. This returns all motifs in that motifset.

Multiple Motifsets: To retrieve motifs and metadata for multiple motifsets, send a POST request to http://ms2lda.org/motifdb/get_motifset with a payload containing:

  • motifset_id_list: A list of motifset IDs you want to retrieve
  • csrfmiddlewaretoken: A valid CSRF token (obtained from /motifdb/initialise_api)
  • filter: Set to "True" to filter duplicate motifs (optional)
  • filter_threshold: Cosine score threshold for filtering (default: 0.95, optional)
Python Example
import requests

server_url = "http://ms2lda.org"

# Get the list of available motif sets
output = requests.get(server_url + '/motifdb/list_motifsets')
motifset_list = output.json()

# Get a CSRF token for POST requests
url = server_url + '/motifdb/initialise_api'
client = requests.session()
token = client.get(url).json()['token']

# Prepare data for POST request
url = server_url + '/motifdb/get_motifset/'
data = {'csrfmiddlewaretoken': token}

# Specify motifsets of interest
massbank_motifset = 'Massbank library derived Mass2Motifs'
gnps_motifset = 'GNPS library derived Mass2Motifs'

massbank_id = motifset_list[massbank_motifset]
gnps_id = motifset_list[gnps_motifset]

# Example 1: Get multiple motifsets with filtering
data['motifset_id_list'] = [massbank_id, gnps_id]
data['filter'] = "True"
data['filter_threshold'] = 0.95  # Default value - not required
output = client.post(url, data=data).json()
print('Retrieved {} motifs and {} metadata entries'.format(
    len(output['motifs']), len(output['metadata'])))

# Example 2: Get metadata for a single motifset
url = server_url + '/motifdb/get_motifset_metadata/{}/'.format(massbank_id)
output = requests.get(url)
motif_metadata = output.json()
print('First 5 metadata entries:')
for k in list(motif_metadata.keys())[:5]:
    print(k)
    print(motif_metadata[k])