Wei H, Guan YD, Zhang LX, Liu S, Lu AP, Cheng Y, Cao DS. A combinatorial target screening strategy for deorphaning macromolecular targets of natural product.
Eur J Med Chem 2020;
204:112644. [PMID:
32738412 DOI:
10.1016/j.ejmech.2020.112644]
[Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/02/2020] [Accepted: 07/02/2020] [Indexed: 11/24/2022]
Abstract
Natural products, as an ideal starting point for molecular design, play a pivotal role in drug discovery; however, ambiguous targets and mechanisms have limited their in-depth research and applications in a global dimension. In-silico target prediction methods have become an alternative to target identification experiments due to the high accuracy and speed, but most studies only use a single prediction method, which may reduce the accuracy and reliability of the prediction. Here, we firstly presented a combinatorial target screening strategy to facilitate multi-target screening of natural products considering the characteristics of diverse in-silico target prediction methods, which consists of ligand-based online approaches, consensus SAR modelling and target-specific re-scoring function modelling. To validate the practicability of the strategy, natural product neferine, a bisbenzylisoquinoline alkaloid isolated from the lotus seed, was taken as an example to illustrate the screening process and a series of corresponding experiments were implemented to explore the pharmacological mechanisms of neferine. The proposed computational method could be used for a complementary hypothesis generation and rapid analysis of potential targets of natural products.
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