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新冠疫情中计算设计药物递送系统的进展:当前进展与未来相互影响——重要更新

Advancement of Computational Design Drug Delivery System in COVID-19: Current Updates and Future Crosstalk- A Critical update.

作者信息

Mohiuddin Abu, Mondal Sumanta

机构信息

GITAM University, Pharmaceutics, India.

出版信息

Infect Disord Drug Targets. 2023 Aug 16;23(8). doi: 10.2174/1871526523666230816151614.

DOI:10.2174/1871526523666230816151614
PMID:37584349
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11348471/
Abstract

Positive strides have been achieved in developing vaccines to combat the coronavirus-2019 infection (COVID-19) pandemic. Still, the outline of variations, particularly the most current delta divergent, has posed significant health encounters for people. Therefore, developing strong treatment strategies, such as an anti-COVID-19 medicine plan, may help deal with the pandemic more effectively. During the COVID-19 pandemic, some drug design techniques were effectively used to develop and substantiate relevant critical medications. Extensive research, both experimental and computational, has been dedicated to comprehending and characterizing the devastating COVID-19 disease. The urgency of the situation has led to the publication of over 130,000 COVID-19-related research papers in peer-reviewed journals and preprint servers. A significant focus of these efforts has been the identification of novel drug candidates and the repurposing of existing drugs to combat the virus. Many projects have utilized computational or computer-aided approaches to facilitate their studies. In this overview, we will explore the key computational methods and their applications in the discovery of small-molecule therapeutics for COVID-19, as reported in the research literature. We believe that the true effectiveness of computational tools lies in their ability to provide actionable and experimentally testable hypotheses, which in turn facilitate the discovery of new drugs and combinations thereof. Additionally, we recognize that open science and the rapid sharing of research findings are vital in expediting the development of much-needed therapeutics for COVID-19.

摘要

在开发抗击2019冠状病毒感染(COVID-19)大流行的疫苗方面已经取得了积极进展。然而,变异毒株的情况,尤其是最新的德尔塔变种,给人们带来了重大的健康挑战。因此,制定强有力的治疗策略,如抗COVID-19药物计划,可能有助于更有效地应对这一流行病。在COVID-19大流行期间,一些药物设计技术被有效地用于开发和验证相关的关键药物。广泛的实验和计算研究致力于理解和表征具有破坏性的COVID-19疾病。形势的紧迫性导致在同行评审期刊和预印本服务器上发表了超过13万篇与COVID-19相关的研究论文。这些努力的一个重要重点是识别新型候选药物以及将现有药物重新用于对抗该病毒。许多项目利用了计算或计算机辅助方法来促进其研究。在本综述中,我们将探讨研究文献中报道的关键计算方法及其在发现COVID-19小分子疗法中的应用。我们认为,计算工具的真正有效性在于它们能够提供可操作且可通过实验验证的假设,这反过来又有助于发现新药物及其组合。此外,我们认识到开放科学和研究结果的快速共享对于加速开发急需的COVID-19疗法至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/b8f2e9085c88/IDDT-23-E160823219858_F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/5d5f9788c5fb/IDDT-23-E160823219858_F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/b818536b66aa/IDDT-23-E160823219858_F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/b8f2e9085c88/IDDT-23-E160823219858_F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/5d5f9788c5fb/IDDT-23-E160823219858_F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/b818536b66aa/IDDT-23-E160823219858_F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8f6/11348471/b8f2e9085c88/IDDT-23-E160823219858_F3.jpg

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