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  3. Utilizing artificial intelligence for precision exploration of N protein targeting phenanthridine sars-cov-2 inhibitors: A novel approach

Utilizing artificial intelligence for precision exploration of N protein targeting phenanthridine sars-cov-2 inhibitors: A novel approach

  • Eur J Med Chem. 2024 Sep 18:279:116885. doi: 10.1016/j.ejmech.2024.116885.
Zheng-Rui Xiang 1,  Shi-Rui Fan 1,  Juan Ren 2,  Ting Ruan 1,  Yuan Chen 1,  Yun-Wu Zhang 3,  Yi-Ting Wang 1,  Ze-Zhou Yu 1,  Chao-Fan Wang 1,  Xiao-Long Sun 4,  Xiao-Jiang Hao 5,  Duo-Zhi Chen 6
Affiliations

Affiliations

  • 1 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China; Research Unit of Chemical Biology of Natural Anti-Virus Products, Chinese Academy of Medical Sciences, Beijing, 100730, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, 650204, China.
  • 2 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China; School of Life Sciences, Yunnan University, Kunming, Yunnan, 650091, China; Research Unit of Chemical Biology of Natural Anti-Virus Products, Chinese Academy of Medical Sciences, Beijing, 100730, China.
  • 3 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China; School of Life Sciences, Yunnan University, Kunming, Yunnan, 650091, China.
  • 4 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China; School of Life Sciences, Yunnan University, Kunming, Yunnan, 650091, China; Institute of International Rivers and Eco-Security, Yunnan University, Kunming, Yunnan, 650091, China.
  • 5 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China. Electronic address: haoxj@mail.kib.ac.cn.
  • 6 State Key Laboratory of Phytochemistry and Plant Resources in West China, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, 650201, China. Electronic address: chenduozhi@mail.kib.ac.cn.
PMID: 39307103 DOI: 10.1016/j.ejmech.2024.116885
Abstract

The persistent mutation of the novel coronavirus presents a continual threat of infections and associated illnesses. While considerable research efforts have concentrated on the functional proteins of SARS-CoV-2 in the development of anti-COVID-19 therapeutics, the structural proteins, particularly the N protein, have received comparatively less attention. This study focuses on the N protein, a critical structural component of the virus, and employs advanced deep learning models, including EMPIRE and DeepFrag, to optimize the structures of phenanthridine-based compounds. More than 10,000 small molecules, derived through deep learning, underwent high-throughput virtual screening, resulting in the synthesis of 44 compounds. Compound 38 showed a binding potential energy of -8.2 kcal/mol in molecular docking. Surface Plasmon Resonance (SPR) and Microscale Thermophoresis (MST) validation yielded dissociation constants of 353 nM and 726 nM, confirming strong binding to the N protein. Compound 38 demonstrated Antiviral activity in vitro and exhibited anti-COVID-19 effects by interfering with the binding of N proteins to RNA. This research underscores the potential of targeting the SARS-CoV-2 N protein for therapeutic intervention and illustrates the efficacy of deep learning model in the design of lead compounds. The application of these deep learning models represents a promising approach for accelerating the discovery and development of Antiviral agents.

Keywords

Deep learning; Nucleocapsid protein; Phenanthridine; SARS-CoV-2.

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