Harnessing network pharmacology in drug discovery: an integrated approach.

IF 3.1 4区 医学 Q2 PHARMACOLOGY & PHARMACY
Chandra Prakash Joshi, Ashish Baldi, Neeraj Kumar, Joohee Pradhan
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引用次数: 0

Abstract

Traditional drug discovery approach is based on one drug-one target, that is associated with very lengthy timelines, high costs and very low success rates. Network pharmacology (NP) is a novel method of drug designing, that is based on a multiple-target approach. NP integrates systems such as biology, pharmacology and computational techniques to address the limitations of traditional methods of drug discovery. With help of mapping biological networks, it provides deep insights into biological molecules' interactions and enhances our understanding to the mechanism of drugs, polypharmacology and disease etiology. This review explores the theoretical framework of network pharmacology, discussing the principles and methodologies that enable the construction of drug-target and disease-gene networks. It highlights how data mining, bioinformatics tools and computational models are utilised to predict drug behaviour, repurpose existing drugs and identify novel therapeutic targets. Applications of network pharmacology in the treatment of complex diseases-such as cancer, neurodegenerative disorders, cardiovascular diseases and infectious diseases-are extensively covered, demonstrating its potential to identify multi-target drugs for multifaceted disease mechanisms. Despite the promising results, NP faces challenges due to incomplete and quality of biological data, computational complexities and biological system redundancy. It also faces regulatory challenges in drug approval, demanding revision in regulatory guidelines towards multi-target therapies. Advancements in AI and machine learning, dynamic network modelling and global collaboration can further enhance the efficacy of network pharmacology. This integrative approach has the potential to revolutionise drug discovery, offering new solutions for personalised medicine, drug repurposing and tackling the complexities of modern diseases.

在药物发现中利用网络药理学:一种综合方法。
传统的药物发现方法是基于一种药物-一种靶点,这与非常漫长的时间、高成本和非常低的成功率有关。网络药理学(Network pharmacology, NP)是一种基于多靶点的药物设计新方法。NP集成了生物学、药理学和计算技术等系统,以解决传统药物发现方法的局限性。借助绘制生物网络,它可以深入了解生物分子的相互作用,增强我们对药物机制、多药理学和疾病病因学的理解。本文综述了网络药理学的理论框架,讨论了构建药物靶点和疾病基因网络的原理和方法。它强调了如何利用数据挖掘、生物信息学工具和计算模型来预测药物行为、重新利用现有药物和确定新的治疗靶点。网络药理学在治疗复杂疾病(如癌症、神经退行性疾病、心血管疾病和传染病)中的应用被广泛覆盖,展示了其在识别多层面疾病机制的多靶点药物方面的潜力。尽管取得了令人鼓舞的成果,但由于生物数据的不完整和质量,计算复杂性和生物系统冗余,NP面临着挑战。它还面临着药物审批方面的监管挑战,要求修订针对多靶点治疗的监管指南。人工智能和机器学习、动态网络建模和全球协作的进步可以进一步增强网络药理学的功效。这种综合方法有可能彻底改变药物发现,为个性化医疗、药物再利用和解决现代疾病的复杂性提供新的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.20
自引率
5.60%
发文量
142
审稿时长
4-8 weeks
期刊介绍: Naunyn-Schmiedeberg''s Archives of Pharmacology was founded in 1873 by B. Naunyn, O. Schmiedeberg and E. Klebs as Archiv für experimentelle Pathologie und Pharmakologie, is the offical journal of the German Society of Experimental and Clinical Pharmacology and Toxicology (Deutsche Gesellschaft für experimentelle und klinische Pharmakologie und Toxikologie, DGPT) and the Sphingolipid Club. The journal publishes invited reviews, original articles, short communications and meeting reports and appears monthly. Naunyn-Schmiedeberg''s Archives of Pharmacology welcomes manuscripts for consideration of publication that report new and significant information on drug action and toxicity of chemical compounds. Thus, its scope covers all fields of experimental and clinical pharmacology as well as toxicology and includes studies in the fields of neuropharmacology and cardiovascular pharmacology as well as those describing drug actions at the cellular, biochemical and molecular levels. Moreover, submission of clinical trials with healthy volunteers or patients is encouraged. Short communications provide a means for rapid publication of significant findings of current interest that represent a conceptual advance in the field.
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