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
| 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 |
| 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 |
MotifDB is accessible via an API.
The following instructions demonstrate how to interact with the API
http://m2slda.org/motifdb/list_motifsets will return a json dictionary that gives the names of available motif sets and their IDs.
To access a particular motifset, there are two options. Send a get request to http://ms2lda.org/motifdb/get_motifset/ID, where ID is the ID obtained from the motifset list will return a json object including all of the motifs in that motifset. Replacing get_motifset with get_metadata will return the metadata for those motifs.
Alternatively, if you want to get the motifs and metadata together for multiple motifsets, you can send a POST request to http://ms2lda.org/motifdb/get_motifset. Within the payload dictionary you should include a field motifset_id_list which holds a list of the IDs of the motifsets you'd like.
In addition, you will need to include a field called csrfmiddlewaretoken which holds a valid token. You can get one by sending a GET request to http://ms2lda.org/motifdb/initialise_api.
This way of getting motifs also allows you to filter duplicates. Simply add the field filter with the value "True" to your payload. The default filter threshold (cosine score) is 0.95. To change this, add a field "filter_threshold" to your payload.
Example
import requests
server_url = "http://ms2lda.org"
# Get the list of motif sets
output = requests.get(server_url + '/motifdb/list_motifsets')
motifset_list = output.json()
# Get a token
url = server_url + '/motifdb/initialise_api'
client = requests.session()
token = client.get(url).json()['token']
url = server_url + '/motifdb/get_motifset/'
data = {'csrfmiddlewaretoken': token}
# specify the name of motifsets of interest in motifset_list
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 - get the massbank and gnps motifsets
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', len(output['motifs']), 'motifs', len(output['metadata'])
# example - get the massbank metadata only
url = server_url + '/motifdb/get_motifset_metadata/{}/'.format(massbank_id)
output = requests.get(url)
motif_metadata = output.json()
for k in motif_metadata.keys()[:5]:
print k
print motif_metadata[k]