DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products
While natural products and derivatives have been crucial in drug discovery, the current databases are limited to known compounds. There is a need for tools that can automatically generate and assess novel derivatives of natural products to enhance early-stage drug discovery. We present DerivaPredict...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/30/8/1683 |
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| author | Yu Song Meng Zhang Sihao Chang Ganghui Chu Hongchao Ji |
| author_facet | Yu Song Meng Zhang Sihao Chang Ganghui Chu Hongchao Ji |
| author_sort | Yu Song |
| collection | DOAJ |
| description | While natural products and derivatives have been crucial in drug discovery, the current databases are limited to known compounds. There is a need for tools that can automatically generate and assess novel derivatives of natural products to enhance early-stage drug discovery. We present DerivaPredict (v1.0), a user-friendly tool that generates novel natural product derivatives through chemical and metabolic transformations. It predicts binding affinities using pretrained deep learning models and assesses drug-likeness via ADMET profiling. DerivaPredict is freely accessible with a source code on GitHub. |
| format | Article |
| id | doaj-art-73c33a1e2e564e918b8ef69cd4dff0d5 |
| institution | OA Journals |
| issn | 1420-3049 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj-art-73c33a1e2e564e918b8ef69cd4dff0d52025-08-20T02:18:20ZengMDPI AGMolecules1420-30492025-04-01308168310.3390/molecules30081683DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural ProductsYu Song0Meng Zhang1Sihao Chang2Ganghui Chu3Hongchao Ji4Laboratory of Xinjiang Native Medicinal and Edible Plant Resource Chemistry, College of Chemistry and Environmental Science, Kashi University, Kashi 844006, ChinaShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, ChinaShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, ChinaLaboratory of Xinjiang Native Medicinal and Edible Plant Resource Chemistry, College of Chemistry and Environmental Science, Kashi University, Kashi 844006, ChinaShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, ChinaWhile natural products and derivatives have been crucial in drug discovery, the current databases are limited to known compounds. There is a need for tools that can automatically generate and assess novel derivatives of natural products to enhance early-stage drug discovery. We present DerivaPredict (v1.0), a user-friendly tool that generates novel natural product derivatives through chemical and metabolic transformations. It predicts binding affinities using pretrained deep learning models and assesses drug-likeness via ADMET profiling. DerivaPredict is freely accessible with a source code on GitHub.https://www.mdpi.com/1420-3049/30/8/1683natural product derivativesin silico molecular designsoftware engineering |
| spellingShingle | Yu Song Meng Zhang Sihao Chang Ganghui Chu Hongchao Ji DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products Molecules natural product derivatives in silico molecular design software engineering |
| title | DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products |
| title_full | DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products |
| title_fullStr | DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products |
| title_full_unstemmed | DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products |
| title_short | DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products |
| title_sort | derivapredict a user friendly tool for predicting and evaluating active derivatives of natural products |
| topic | natural product derivatives in silico molecular design software engineering |
| url | https://www.mdpi.com/1420-3049/30/8/1683 |
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