Abstract：
Nucleoside analogs have been widely used as antiviral, antitumor, and antiparasitic agents due to their ability to inhibit nucleic acid synthesis. Adenosine, cytidine, guanosine, thymidine and uridine analogs such as didanosine, vidarabine, remdesivir, gemcitabine, lamivudine, acyclovir, abacavir, zidovusine, stavudine, and idoxuridine showed remarkable anticancer and antiviral activities. In our previously published articles, our main intention was to develop newer generation nucleoside analogs with acylation-induced modification of the hydroxyl group and showcase their biological potencies. In the process of developing nucleoside analogs, in silico studies play an important role and provide a scientific background for biological data. Molecular interactions between drugs and receptors followed by assessment of their stability in physiological environments, help to optimize the drug development process and minimize the burden of unwanted synthesis. Computational approaches, such as DFT, FMO, MEP, ADMET prediction, PASS prediction, POM analysis, molecular docking, and molecular dynamics simulation, are the most popular tools to culminate all preclinical study data and deliver a molecule with maximum bioactivity and minimum toxicity. Although clinical drug trials are crucial for providing dosage recommendations, they can only indirectly provide mechanistic information through researchers for pathological, physiological, and pharmacological determinants. As a result, in silico approaches are increasingly used in drug discovery and development to provide mechanistic information of clinical value. This article portrays the current status of these methods and highlights some remarkable contributions to the development of nucleoside analogs with optimized bioactivity.
摘要：
核苷类似物已被广泛用作抗病毒，抗肿瘤，和抗寄生虫剂，因为它们能够抑制核酸合成。腺苷,胞苷,鸟苷,胸苷和尿苷类似物如去羟肌苷，阿糖腺苷,remdesivir,吉西他滨,拉米夫定,阿昔洛韦,阿巴卡韦,齐多夫素,司他夫定,并显示出显著的抗癌和抗病毒活性。在我们之前发表的文章中，我们的主要目的是开发具有酰化诱导的羟基修饰的新一代核苷类似物，并展示其生物学功效。在开发核苷类似物的过程中，计算机模拟研究起着重要作用，并为生物学数据提供了科学背景。药物和受体之间的分子相互作用，然后评估它们在生理环境中的稳定性，有助于优化药物开发过程，最大限度地减少不必要的合成负担。计算方法，如DFT，FMO,MEP,ADMET预测，通过预测,POM分析,分子对接,和分子动力学模拟，是最流行的工具，以结束所有临床前研究数据，并提供具有最大生物活性和最小毒性的分子。尽管临床药物试验对于提供剂量建议至关重要，他们只能通过研究人员间接提供病理机制信息，生理,和药理学决定因素。因此,计算机模拟方法越来越多地用于药物发现和开发，以提供具有临床价值的机械信息。本文描述了这些方法的现状，并强调了对开发具有优化生物活性的核苷类似物的一些杰出贡献。
