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.