Computational-aided understanding of metabolic mechanism: A case study Article Swipe
Zixuan Wang
,
Ming‐Yu Bai
,
Xing-Feng Ni
,
Qian Liu
,
Q. L. Niu
,
Mengyuan Zhang
,
Jin Yang
,
Qingqing Li
,
Ning Huang
,
Meng Sun
,
Z Zhao
,
Ning Ding
,
Yan-Cheng Yu
,
Xiaolong Wang
,
Shan‐Liang Sun
,
Chenxiao Shan
,
Nian‐Guang Li
,
Zhi‐Hao Shi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rechem.2025.102453
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rechem.2025.102453
This study presents an innovative computational method, combined with experimental validation, to predict and elucidate the metabolic pathways of SILA-123, a novel FLT3 inhibitor. Using UFLC/Q-TOF MS, we identified 21 metabolites generated through key reactions (oxidation, reduction, hydrolysis, cleavage, deamination, and glucuronidation). Advanced computational techniques were applied to identify key metabolic enzymes, with results confirmed experimentally. Our findings represent a significant advancement in the field of metabolic prediction. By integrating computational methods with experimental data, we have established a robust framework that can be applied to other therapeutic compounds. This approach not only enhances our understanding of SILA-123's metabolic pathways but also provides a novel strategy for guiding metabolic prediction.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.rechem.2025.102453
- OA Status
- gold
- References
- 21
- Related Works
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- OpenAlex ID
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- DOI
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https://doi.org/10.1016/j.rechem.2025.102453Digital Object Identifier
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Computational-aided understanding of metabolic mechanism: A case studyWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
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2025-06-16Full publication date if available
- Authors
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Zixuan Wang, Ming‐Yu Bai, Xing-Feng Ni, Qian Liu, Q. L. Niu, Mengyuan Zhang, Jin Yang, Qingqing Li, Ning Huang, Meng Sun, Z Zhao, Ning Ding, Yan-Cheng Yu, Xiaolong Wang, Shan‐Liang Sun, Chenxiao Shan, Nian‐Guang Li, Zhi‐Hao ShiList of authors in order
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https://doi.org/10.1016/j.rechem.2025.102453Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.rechem.2025.102453Direct OA link when available
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Mechanism (biology), Computer science, Computational biology, Cognitive science, Psychology, Biology, Epistemology, PhilosophyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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21Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Using | 24 |
| abstract_inverted_index.data, | 74 |
| abstract_inverted_index.field | 64 |
| abstract_inverted_index.novel | 21, 104 |
| abstract_inverted_index.other | 86 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.robust | 79 |
| abstract_inverted_index.applied | 46, 84 |
| abstract_inverted_index.guiding | 107 |
| abstract_inverted_index.method, | 6 |
| abstract_inverted_index.methods | 71 |
| abstract_inverted_index.predict | 12 |
| abstract_inverted_index.results | 53 |
| abstract_inverted_index.through | 32 |
| abstract_inverted_index.Advanced | 42 |
| abstract_inverted_index.approach | 90 |
| abstract_inverted_index.combined | 7 |
| abstract_inverted_index.enhances | 93 |
| abstract_inverted_index.enzymes, | 51 |
| abstract_inverted_index.findings | 57 |
| abstract_inverted_index.identify | 48 |
| abstract_inverted_index.pathways | 17, 99 |
| abstract_inverted_index.presents | 2 |
| abstract_inverted_index.provides | 102 |
| abstract_inverted_index.strategy | 105 |
| abstract_inverted_index.SILA-123, | 19 |
| abstract_inverted_index.cleavage, | 38 |
| abstract_inverted_index.confirmed | 54 |
| abstract_inverted_index.elucidate | 14 |
| abstract_inverted_index.framework | 80 |
| abstract_inverted_index.generated | 31 |
| abstract_inverted_index.metabolic | 16, 50, 66, 98, 108 |
| abstract_inverted_index.reactions | 34 |
| abstract_inverted_index.represent | 58 |
| abstract_inverted_index.SILA-123's | 97 |
| abstract_inverted_index.UFLC/Q-TOF | 25 |
| abstract_inverted_index.compounds. | 88 |
| abstract_inverted_index.identified | 28 |
| abstract_inverted_index.inhibitor. | 23 |
| abstract_inverted_index.innovative | 4 |
| abstract_inverted_index.reduction, | 36 |
| abstract_inverted_index.techniques | 44 |
| abstract_inverted_index.(oxidation, | 35 |
| abstract_inverted_index.advancement | 61 |
| abstract_inverted_index.established | 77 |
| abstract_inverted_index.hydrolysis, | 37 |
| abstract_inverted_index.integrating | 69 |
| abstract_inverted_index.metabolites | 30 |
| abstract_inverted_index.prediction. | 67, 109 |
| abstract_inverted_index.significant | 60 |
| abstract_inverted_index.therapeutic | 87 |
| abstract_inverted_index.validation, | 10 |
| abstract_inverted_index.deamination, | 39 |
| abstract_inverted_index.experimental | 9, 73 |
| abstract_inverted_index.computational | 5, 43, 70 |
| abstract_inverted_index.understanding | 95 |
| abstract_inverted_index.experimentally. | 55 |
| abstract_inverted_index.glucuronidation). | 41 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 18 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.21922951 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |