Clustering of small molecules: new perspectives and their impact on natural product lead discovery
The clustering of small molecules is of considerable importance for computer-aided drug discovery and virtual screening applications. The structure of chemical data in appropriate subspaces of the chemical space is relevant to sample datasets in a representative manner, to generate small libraries w...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-03-01
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| Series: | Frontiers in Natural Products |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fntpr.2024.1367537/full |
| _version_ | 1827161075453263872 |
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| author | Alan Talevi Alan Talevi Carolina L. Bellera Carolina L. Bellera |
| author_facet | Alan Talevi Alan Talevi Carolina L. Bellera Carolina L. Bellera |
| author_sort | Alan Talevi |
| collection | DOAJ |
| description | The clustering of small molecules is of considerable importance for computer-aided drug discovery and virtual screening applications. The structure of chemical data in appropriate subspaces of the chemical space is relevant to sample datasets in a representative manner, to generate small libraries with wide or narrow chemical coverage (depending on the specific goals), and to guide the selection of subsets of in silico hits that are submitted for experimental confirmation. In the field of natural products, identifying regions of the chemical space where bioactive compounds congregate and understanding the relationship between biosynthetic gene clusters and the molecular structure of secondary metabolites may have a direct impact on natural product discovery and engineering. Here, we briefly discuss general approximations and available resources for the clustering of small molecules, and how the clustering of small molecules can be boosted by the application of novel clustering approximations, namely subspace clustering and multi-view clustering, which represent opposite philosophies of the clustering paradigm. We present some specific applications of small molecule clustering in the field of natural products, and analyze how a chemogenomic perspective may be particularly embodied in the field of natural products. |
| first_indexed | 2024-04-24T23:48:15Z |
| format | Article |
| id | doaj.art-f91ce1e356394c37a05c2dbfc32e9553 |
| institution | Directory Open Access Journal |
| issn | 2813-2602 |
| language | English |
| last_indexed | 2025-03-21T00:23:09Z |
| publishDate | 2024-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Natural Products |
| spelling | doaj.art-f91ce1e356394c37a05c2dbfc32e95532024-08-03T07:54:35ZengFrontiers Media S.A.Frontiers in Natural Products2813-26022024-03-01310.3389/fntpr.2024.13675371367537Clustering of small molecules: new perspectives and their impact on natural product lead discoveryAlan Talevi0Alan Talevi1Carolina L. Bellera2Carolina L. Bellera3Laboratory of Bioactive Compound Research and Development (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), Buenos Aires, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CCT La Plata, Buenos Aires, ArgentinaLaboratory of Bioactive Compound Research and Development (LIDeB), Faculty of Exact Sciences, National University of La Plata (UNLP), Buenos Aires, ArgentinaConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CCT La Plata, Buenos Aires, ArgentinaThe clustering of small molecules is of considerable importance for computer-aided drug discovery and virtual screening applications. The structure of chemical data in appropriate subspaces of the chemical space is relevant to sample datasets in a representative manner, to generate small libraries with wide or narrow chemical coverage (depending on the specific goals), and to guide the selection of subsets of in silico hits that are submitted for experimental confirmation. In the field of natural products, identifying regions of the chemical space where bioactive compounds congregate and understanding the relationship between biosynthetic gene clusters and the molecular structure of secondary metabolites may have a direct impact on natural product discovery and engineering. Here, we briefly discuss general approximations and available resources for the clustering of small molecules, and how the clustering of small molecules can be boosted by the application of novel clustering approximations, namely subspace clustering and multi-view clustering, which represent opposite philosophies of the clustering paradigm. We present some specific applications of small molecule clustering in the field of natural products, and analyze how a chemogenomic perspective may be particularly embodied in the field of natural products.https://www.frontiersin.org/articles/10.3389/fntpr.2024.1367537/fullbiosynthetic gene cluster (BGC)secondary metabolitesclusteringsmall moleculesvirtual screeningsubspace clustering |
| spellingShingle | Alan Talevi Alan Talevi Carolina L. Bellera Carolina L. Bellera Clustering of small molecules: new perspectives and their impact on natural product lead discovery Frontiers in Natural Products biosynthetic gene cluster (BGC) secondary metabolites clustering small molecules virtual screening subspace clustering |
| title | Clustering of small molecules: new perspectives and their impact on natural product lead discovery |
| title_full | Clustering of small molecules: new perspectives and their impact on natural product lead discovery |
| title_fullStr | Clustering of small molecules: new perspectives and their impact on natural product lead discovery |
| title_full_unstemmed | Clustering of small molecules: new perspectives and their impact on natural product lead discovery |
| title_short | Clustering of small molecules: new perspectives and their impact on natural product lead discovery |
| title_sort | clustering of small molecules new perspectives and their impact on natural product lead discovery |
| topic | biosynthetic gene cluster (BGC) secondary metabolites clustering small molecules virtual screening subspace clustering |
| url | https://www.frontiersin.org/articles/10.3389/fntpr.2024.1367537/full |
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