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通过超大型文库筛选靶向离子通道以发现活性分子。

Targeting ion channels with ultra-large library screening for hit discovery.

作者信息

Melancon Kortney, Pliushcheuskaya Palina, Meiler Jens, Künze Georg

机构信息

Department of Chemistry, Vanderbilt University, Nashville, TN, United States.

Center for Structural Biology, Vanderbilt University, Nashville, TN, United States.

出版信息

Front Mol Neurosci. 2024 Jan 5;16:1336004. doi: 10.3389/fnmol.2023.1336004. eCollection 2023.

Abstract

Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.

摘要

离子通道在多种生理和病理过程中发挥着关键作用,这使得它们成为糖尿病、癫痫、高血压、癌症和慢性疼痛等疾病药物研发的有吸引力的靶点。尽管离子通道在药物发现中很重要,但化学空间的广阔性和离子通道的复杂性给识别候选药物带来了重大挑战。药物发现中方法的使用极大地减少了药物开发的时间和成本,并有可能彻底改变医学领域。计算机硬件和软件的最新进展使得筛选超大化合物库成为可能。在不同规模和维度上整合不同方法正成为药物开发中不可避免的趋势。在这篇综述中,我们概述了用于超大化合物库筛选的当前最先进的计算化学方法及其在离子通道药物发现研究中的应用。我们讨论了各种技术的优点和局限性,包括虚拟筛选、分子力学/动力学模拟和基于机器学习的方法。我们还强调了计算化学方法在离子通道药物发现中的几个成功应用,并对该领域的未来方向和挑战提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dbf9/10796734/af6858499fef/fnmol-16-1336004-g0001.jpg

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