Artificial intelligence for drug repurposing against infectious diseases

Anuradha Singh
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Abstract

Traditional drug discovery struggles to keep pace with the ever-evolving threat of infectious diseases. New viruses and antibiotic-resistant bacteria, all demand rapid solutions. Artificial Intelligence (AI) offers a promising path forward through accelerated drug repurposing. AI allows researchers to analyze massive datasets, revealing hidden connections between existing drugs, disease targets, and potential treatments. This approach boasts several advantages. First, repurposing existing drugs leverages established safety data and reduces development time and costs. Second, AI can broaden the search for effective therapies by identifying unexpected connections between drugs and potential new targets. Finally, AI can help mitigate limitations by predicting and minimizing side effects, optimizing drugs for repurposing, and navigating intellectual property hurdles. The article explores specific AI strategies like virtual screening, target identification, structure base drug design and natural language processing. Real-world examples highlight the potential of AI-driven drug repurposing in discovering new treatments for infectious diseases.

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人工智能为防治传染病重新设计药物用途
传统的药物研发难以跟上不断发展的传染病威胁的步伐。新型病毒和抗生素耐药细菌都需要快速的解决方案。人工智能(AI)通过加速药物再利用,提供了一条充满希望的前进之路。人工智能使研究人员能够分析海量数据集,揭示现有药物、疾病靶点和潜在治疗方法之间隐藏的联系。这种方法有几个优势。首先,对现有药物进行再利用可以利用已有的安全性数据,并减少开发时间和成本。其次,人工智能可以发现药物与潜在新靶点之间意想不到的联系,从而扩大有效疗法的搜索范围。最后,人工智能可以通过预测和尽量减少副作用、优化药物的再利用以及克服知识产权障碍来帮助减少局限性。文章探讨了虚拟筛选、靶点识别、结构基础药物设计和自然语言处理等具体的人工智能策略。真实世界的例子突出了人工智能驱动的药物再利用在发现传染病新疗法方面的潜力。
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来源期刊
Artificial intelligence chemistry
Artificial intelligence chemistry Chemistry (General)
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审稿时长
21 days
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