The development and application of in silico models for drug induced liver injury. Issue 15 (20th February 2018)
- Record Type:
- Journal Article
- Title:
- The development and application of in silico models for drug induced liver injury. Issue 15 (20th February 2018)
- Main Title:
- The development and application of in silico models for drug induced liver injury
- Authors:
- Li, Xiao
Chen, Yaojie
Song, Xinrui
Zhang, Yuan
Li, Huanhuan
Zhao, Yong - Abstract:
- Abstract : Drug-induced liver injury (DILI), caused by drugs, herbal agents or nutritional supplements, is a major issue for patients and the pharmaceutical industry. Abstract : Drug-induced liver injury (DILI), caused by drugs, herbal agents or nutritional supplements, is a major issue for patients and the pharmaceutical industry. It has been a leading cause of clinical trials failure and withdrawal of FDA approval. In this research, we focused on in silico estimation of chemical DILI potential on humans based on structurally diverse organic chemicals. We developed a series of binary classification models using five different machine learning methods and eight different feature reduction methods. The model, developed with the support vector machine (SVM) and the MACCS fingerprint, performed best both on the test set and external validation. It achieved a prediction accuracy of 80.39% on the test set and 82.78% on external validation. We made this model available at ; Web:http://opensource.vslead.com/ . The user can freely predict the DILI potential of molecules. Furthermore, we analyzed the difference of distributions of 12 key physical–chemical properties between DILI-positive and DILI-negative compounds and 20 privileged substructures responsible for DILI were identified from the Klekota–Roth fingerprint. Moreover, since traditional Chinese medicine (TCM)-induced liver injury is also one of the major concerns among the toxic effects, we evaluated the DILI potential of TCMAbstract : Drug-induced liver injury (DILI), caused by drugs, herbal agents or nutritional supplements, is a major issue for patients and the pharmaceutical industry. Abstract : Drug-induced liver injury (DILI), caused by drugs, herbal agents or nutritional supplements, is a major issue for patients and the pharmaceutical industry. It has been a leading cause of clinical trials failure and withdrawal of FDA approval. In this research, we focused on in silico estimation of chemical DILI potential on humans based on structurally diverse organic chemicals. We developed a series of binary classification models using five different machine learning methods and eight different feature reduction methods. The model, developed with the support vector machine (SVM) and the MACCS fingerprint, performed best both on the test set and external validation. It achieved a prediction accuracy of 80.39% on the test set and 82.78% on external validation. We made this model available at ; Web:http://opensource.vslead.com/ . The user can freely predict the DILI potential of molecules. Furthermore, we analyzed the difference of distributions of 12 key physical–chemical properties between DILI-positive and DILI-negative compounds and 20 privileged substructures responsible for DILI were identified from the Klekota–Roth fingerprint. Moreover, since traditional Chinese medicine (TCM)-induced liver injury is also one of the major concerns among the toxic effects, we evaluated the DILI potential of TCM ingredients using the MACCS_SVM model developed in this study. We hope the model and privileged substructures could be useful complementary tools for chemical DILI evaluation. … (more)
- Is Part Of:
- RSC advances. Volume 8:Issue 15(2018)
- Journal:
- RSC advances
- Issue:
- Volume 8:Issue 15(2018)
- Issue Display:
- Volume 8, Issue 15 (2018)
- Year:
- 2018
- Volume:
- 8
- Issue:
- 15
- Issue Sort Value:
- 2018-0008-0015-0000
- Page Start:
- 8101
- Page End:
- 8111
- Publication Date:
- 2018-02-20
- Subjects:
- Chemistry -- Periodicals
540.5 - Journal URLs:
- http://pubs.rsc.org/en/Journals/JournalIssues/RA ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c7ra12957b ↗
- Languages:
- English
- ISSNs:
- 2046-2069
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8036.750300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 6178.xml