IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0252486.html
   My bibliography  Save this article

Smell compounds classification using UMAP to increase knowledge of odors and molecular structures linkages

Author

Listed:
  • Marylène Rugard
  • Thomas Jaylet
  • Olivier Taboureau
  • Anne Tromelin
  • Karine Audouze

Abstract

This study aims to highlight the relationships between the structure of smell compounds and their odors. For this purpose, heterogeneous data sources were screened, and 6038 odorant compounds and their known associated odors (162 odor notes) were compiled, each individual molecule being represented with a set of 1024 structural fingerprint. Several dimensional reduction techniques (PCA, MDS, t-SNE and UMAP) with two clustering methods (k-means and agglomerative hierarchical clustering AHC) were assessed based on the calculated fingerprints. The combination of UMAP with k-means and AHC methods allowed to obtain a good representativeness of odors by clusters, as well as the best visualization of the proximity of odorants on the basis of their molecular structures. The presence or absence of molecular substructures has been calculated on odorant in order to link chemical groups to odors. The results of this analysis bring out some associations for both the odor notes and the chemical structures of the molecules such as “woody” and “spicy” notes with allylic and bicyclic structures, “balsamic” notes with unsaturated rings, both “sulfurous” and “citrus” with aldehydes, alcohols, carboxylic acids, amines and sulfur compounds, and “oily”, “fatty” and “fruity” characterized by esters and with long carbon chains. Overall, the use of UMAP associated to clustering is a promising method to suggest hypotheses on the odorant structure-odor relationships.

Suggested Citation

  • Marylène Rugard & Thomas Jaylet & Olivier Taboureau & Anne Tromelin & Karine Audouze, 2021. "Smell compounds classification using UMAP to increase knowledge of odors and molecular structures linkages," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-17, May.
  • Handle: RePEc:plo:pone00:0252486
    DOI: 10.1371/journal.pone.0252486
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0252486
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0252486&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0252486?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Carmen C Licon & Guillaume Bosc & Mohammed Sabri & Marylou Mantel & Arnaud Fournel & Caroline Bushdid & Jerome Golebiowski & Celine Robardet & Marc Plantevit & Mehdi Kaytoue & Moustafa Bensafi, 2019. "Chemical features mining provides new descriptive structure-odor relationships," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-21, April.
    2. Erwan Poivet & Zita Peterlin & Narmin Tahirova & Lu Xu & Clara Altomare & Anne Paria & Dong-Jing Zou & Stuart Firestein, 2016. "Applying medicinal chemistry strategies to understand odorant discrimination," Nature Communications, Nature, vol. 7(1), pages 1-9, September.
    3. Stuart Firestein, 2001. "How the olfactory system makes sense of scents," Nature, Nature, vol. 413(6852), pages 211-218, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hao-Ching Jiang & Sung Jin Park & I-Hao Wang & Daniel M. Bear & Alexandra Nowlan & Paul L. Greer, 2024. "CD20/MS4A1 is a mammalian olfactory receptor expressed in a subset of olfactory sensory neurons that mediates innate avoidance of predators," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Agnes, Everton J. & Erichsen, Rubem & Brunnet, Leonardo G., 2012. "Model architecture for associative memory in a neural network of spiking neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 843-848.
    3. Anastasiia Gusach & Yang Lee & Armin Nikpour Khoshgrudi & Elizaveta Mukhaleva & Ning Ma & Eline J. Koers & Qingchao Chen & Patricia C. Edwards & Fanglu Huang & Jonathan Kim & Filippo Mancia & Dmitry B, 2024. "Molecular recognition of an odorant by the murine trace amine-associated receptor TAAR7f," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. Jane S. Huang & Tenzin Kunkhyen & Alexander N. Rangel & Taryn R. Brechbill & Jordan D. Gregory & Emily D. Winson-Bushby & Beichen Liu & Jonathan T. Avon & Ryan J. Muggleton & Claire E. J. Cheetham, 2022. "Immature olfactory sensory neurons provide behaviourally relevant sensory input to the olfactory bulb," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    5. Silva, Joaquim & Sá, Elisabete Sampaio & Escadas, Marco & Carvalho, Joana, 2021. "The influence of ambient scent on the passengers’ experience, emotions and behavioral intentions: An experimental study in a Public Bus service," Transport Policy, Elsevier, vol. 106(C), pages 88-98.
    6. Chulwon Choi & Jungnam Bae & Seonghan Kim & Seho Lee & Hyunook Kang & Jinuk Kim & Injin Bang & Kiheon Kim & Won-Ki Huh & Chaok Seok & Hahnbeom Park & Wonpil Im & Hee-Jung Choi, 2023. "Understanding the molecular mechanisms of odorant binding and activation of the human OR52 family," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0252486. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.