API
GNPS2¶
TODO
ChemicalStructureWebService¶
Web Server for Chemical Structure pictures as well as other chemical structure things
Web API Endpoints¶
Full resolution of all structural information conversion
https://structure.gnps2.org/convert?smiles=CCO
InChI Conversion
https://structure.gnps2.org/inchi?smiles=CN1C=NC2=C1C(=O)N(C(=O)N2C)C
InChIKey Conversion
https://structure.gnps2.org/inchikey?smiles=CN1C=NC2=C1C(=O)N(C(=O)N2C)C
Smiles Conversion
https://structure.gnps2.org/inchikey?smiles=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Mol Conversion
https://structure.gnps2.org/mol?smiles=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
ClassyFire
https://structure.gnps2.org/classyfire?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Formula
https://structure.gnps2.org/formula?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Structure Mass
https://structure.gnps2.org/structuremass?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
https://structure.gnps2.org/structuremass?formula=C8H10N4O2
Adduct Masses
https://structure.gnps2.org/adductcalc?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Structure Fingerprint
https://structure.gnps2.org/structurefingerprint?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Structure Drawing
https://structure.gnps2.org/structureimg?inchi=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3
Structure Similarity
https://structure.gnps2.org/structuresimilarity?inchi1=InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3&smiles2=CN1C=NC2=C1C(=O)N(C(=O)N2C)C
Structure Natural Product Classifier (NP Classifier)¶
If you have Smiles
https://npclassifier.gnps2.org/classify?smiles=<smiles string>
Example JSON Output
{
class_results: [
"Purine alkaloids"
],
superclass_results: [
"Pseudoalkaloids"
],
pathway_results: [
"Alkaloids"
],
isglycoside: false,
fp1: [
0,
0
...
],
fp2: [
0,
0,
...
]
}
NPClassifier
NPClassifier is A Deep Neural Network-Based Structural Classification Tool for Natural Products - check it out here. For citation: Kim, Hyun Woo, Mingxun Wang, Christopher A. Leber, Louis-FĂ©lix Nothias, Raphael Reher, Kyo Bin Kang, Justin JJ van der Hooft, Pieter C. Dorrestein, William H. Gerwick, and Garrison W. Cottrell. "NPClassifier: A deep neural network-based structural classification tool for natural products." Journal of Natural Products (2020). https://doi.org/10.1021/acs.jnatprod.1c00399. Checkout the tool index for a large scale workflow for batch classification.
ReDU Metadata¶
Getting files for a given metadata category
https://redu.gnps2.org/attribute/<attribute>/attributeterm/<term>/files?filters=%5B%5D
Getting all terms per attribute
https://redu.gnps2.org/attribute/<attribute>/attributeterms?filters=%5B%5D
Fast Search¶
Rapidly search pre-made libraries GNPS and MassIVE spectral data.
Search by peaks in json format using query_spectrum:
https://fasst.gnps2.org/search?usi=None&precursor_mz=981.54&charge=1&library=gnpslibrary&query_spectrum={%22n_peaks%22:15,%22peaks%22:[[165.06979370117188,0.38009798526763916],[167.072998046875,1.7413330078125],[179.07260131835938,0.2999509871006012],[180.08079528808594,100.0],[181.08859252929688,2.8455820083618164],[182.09649658203125,23.914995193481445],[192.08079528808594,0.6896359920501709],[193.0886993408203,0.2419929951429367],[208.07569885253906,3.9236950874328613],[210.09129333496094,51.83255386352539],[236.0706024169922,4.025279998779297],[253.09719848632812,21.652437210083008],[254.08120727539062,46.069068908691406],[255.0872039794922,0.3038550019264221],[271.1077880859375,0.7285820245742798]],%22precursor_charge%22:0,%22precursor_mz%22:271.1077}
Search by USI:
https://fasst.gnps2.org/search?library=gnpslibrary&usi=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000001547
Parameters: * usi (mutually exclusive with query spectrum) * library: The pre-built library index, options are listed on the Fast Search GUI * analog: [Yes/No], Defaults to "No" * cache: [Yes/No], Defaults to "No" * lower_delta: defaults to 130 * upper_delta: defaults to 200 * pm_tolerance (Da): The tolerance for precursor mass matching in daltons, defaults to 0.05 * fragment_tolerance (Da): The tolerance for matching individual peaks in daltons, defaults to 0.05 * cosine_threshold: The minimum cosine threshold to be included in the results, defaults to 0.7 * query_spectrum (mututally exclusive with USI): A json formatted peak list
Public Dataset Files¶
Access spectral data by USI or SpectrumID Getting all files per dataset
https://explorer.gnps2.org/api/datasets/{accession}/files
Getting file path per USI
https://dashboard.gnps2.org/downloadlink?usi={file usi}
Getting spectrum data from Spectrum ID
https://external.gnps2.org/gnpsspectrum?SpectrumID={Spectrum ID}
JSON Peak List from USI
https://fasst.gnps2.org/search?library=gnpslibrary&usi={file usi}
https://fasst.gnps2.org/search?library=gnpslibrary&usi=mzspec:GNPS:GNPS-LIBRARY:accession:CCMSLIB00000001547
ModiFinder¶
Some functions of the ModiFinder visualizer module are accessible via APIs. For details on the parameters you can pass to these functions, refer to the GitHub repository or the documentation.
Draw Molecule¶
https://modifinder.gnps2.org/api/visualizer/draw_molecule?{function argument1}={argument1}&{function argument2}={value2}...{function argumentn}={argumentn}.{type}
Exampes: * https://modifinder.gnps2.org/api/visualizer/draw_molecule?mol=CCO.svg * https://modifinder.gnps2.org/api/visualizer/draw_molecule?mol=CCMSLIB00010102097&size=400,400&highlightAtoms=0,1,5.png
Draw Modification¶
You can also draw the modification between two molecules
https://modifinder.gnps2.org/api/visualizer/draw_modifications?{function argument1}={argument1}&{function argument2}={value2}...{function argumentn}={argumentn}.{type}
Draw Spectrum¶
https://modifinder.gnps2.org/api/visualizer/draw_spectrum?{function argument1}={argument1}&{function argument2}={value2}...{function argumentn}={argumentn}.{type}
Draw Alignment¶
https://modifinder.gnps2.org/api/visualizer/draw_alignment?{function argument1}={argument1}&{function argument2}={value2}...{function argumentn}={argumentn}.{type}
Example: