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Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease

Authors :
Jiayi Yin
Xiaoxu Li
Fengcheng Li
Yinjing Lu
Su Zeng
Feng Zhu
Source :
Computational and Structural Biotechnology Journal, Vol 19, Iss , Pp 2318-2328 (2021)
Publication Year :
2021
Publisher :
Elsevier, 2021.

Abstract

An appropriate therapeutic index is crucial for drug discovery and development since narrow therapeutic index (NTI) drugs with slight dosage variation may induce severe adverse drug reactions or potential treatment failure. To date, the shared characteristics underlying the targets of NTI drugs have been explored by several studies, which have been applied to identify potential drug targets. However, the association between the drug therapeutic index and the related disease has not been dissected, which is important for revealing the NTI drug mechanism and optimizing drug design. Therefore, in this study, two classes of disease (cancers and cardiovascular disorders) with the largest number of NTI drugs were selected, and the target property of the corresponding NTI drugs was analyzed. By calculating the biological system profiles and human protein–protein interaction (PPI) network properties of drug targets and adopting an AI-based algorithm, differentiated features between two diseases were discovered to reveal the distinct underlying mechanisms of NTI drugs in different diseases. Consequently, ten shared features and four unique features were identified for both diseases to distinguish NTI from NNTI drug targets. These computational discoveries, as well as the newly found features, suggest that in the clinical study of avoiding narrow therapeutic index in those diseases, the ability of target to be a hub and the efficiency of target signaling in the human PPI network should be considered, and it could thus provide novel guidance in the drug discovery and clinical research process and help to estimate the drug safety of cancer and cardiovascular disease.

Details

Language :
English
ISSN :
20010370
Volume :
19
Issue :
2318-2328
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.5c0bbc9b09c44cd29fca6183f362304c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2021.04.035