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Front Pharmacol. 2018 Oct 31;9:1245. doi: 10.3389/fphar.2018.01245. eCollection 2018.

Determining the Balance Between Drug Efficacy and Safety by the Network and Biological System Profile of Its Therapeutic Target.

Li XX1,2, Yin J1, Tang J1,2, Li Y1,2, Yang Q1,2, Xiao Z1, Zhang R1, Wang Y1, Hong J1, Tao L3, Xue W2, Zhu F1,2.

Author information

1
College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
2
School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China.
3
Key Laboratory of Elemene Class Anti-cancer Chinese Medicine of Zhejiang Province, School of Medicine, Hangzhou Normal University, Hangzhou, China.

Abstract

One of the most challenging puzzles in drug discovery is the identification and characterization of candidate drug of well-balanced profile between efficacy and safety. So far, extensive efforts have been made to evaluate this balance by estimating the quantitative structure-therapeutic relationship and exploring target profile of adverse drug reaction. Particularly, the therapeutic index (TI) has emerged as a key indicator illustrating this delicate balance, and a clinically successful agent requires a sufficient TI suitable for it corresponding indication. However, the TI information are largely unknown for most drugs, and the mechanism underlying the drugs with narrow TI (NTI drugs) is still elusive. In this study, the collective effects of human protein-protein interaction (PPI) network and biological system profile on the drugs' efficacy-safety balance were systematically evaluated. First, a comprehensive literature review of the FDA approved drugs confirmed their NTI status. Second, a popular feature selection algorithm based on artificial intelligence (AI) was adopted to identify key factors differencing the target mechanism between NTI and non-NTI drugs. Finally, this work revealed that the targets of NTI drugs were highly centralized and connected in human PPI network, and the number of similarity proteins and affiliated signaling pathways of the corresponding targets was much higher than those of non-NTI drugs. These findings together with the newly discovered features or feature groups clarified the key factors indicating drug's narrow TI, and could thus provide a novel direction for determining the delicate drug efficacy-safety balance.

KEYWORDS:

artificial intelligence; biological system profile; drug efficacy-safety balance; protein-protein interaction network; therapeutic index

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