Anti-human immunodeficiency virus activities of nucleosides and nucleotides: correlation with molecular electrostatic potential data

In Silico Pharmacokinetics, Molecular Docking and Molecular Dynamics Simulation Studies of Nucleoside Analogs for Drug Discovery- A Mini Review

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.

Anti-HIV activity of HEPT, TIBO, and cyclic urea derivatives: structure-property studies, focused combinatorial library generation, and hits selection using substructural molecular fragments method

Substructural molecular fragments (SMF) method [Solov'ev, V. P.; Varnek, A.; Wipff, G. J. Chem. Inf. Comput. Sci. 2000, 40, 847-858] was applied to assess anti-HIV activity for large data sets for three families of compounds: 1-[2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT) derivatives, tetrahydroimidazobenzodiazepinone (TIBO) derivatives, and cyclic urea (CU) derivatives. The SMF method uses 49 types of topological descriptors (atom/bond sequences and "augmented atoms") which, being coupled with 3 linear and nonlinear fitting equations, allows the user to generate up to 147 structure-property models. For each family of compounds, the modeling was performed on several training sets followed by the validation calculations where three best fit models were applied. Calculated activities well reproduce available experimental data. On the basis of the "optimal" molecular fragments, the focused combinatorial library containing 252 virtual HEPT derivatives has been generated. Its filtering led to several hits potentially possessing anti-HIV activity.

Theoretical investigation of the triphosphate forms of azidothymidine and thymidine

In this paper we investigate (using AM1 semi-empirical as well as HF methods at the STO-3G, 3-21G, 6-31G, 6-31G* and 6-31+G** level) the conformations, geometrical parameters, Mulliken charges, and solvation effects of the triphosphate form of AZT (AZTTP), as well as the thymidine nucleotide (dTTP) structure. Our calculated geometrical parameters and Mulliken charges, with and without solvation effects, are correlated with recent experimental results.