Identification of Selective JAK3/STAT1 and CYP34A from
Pyrazolopyrimidine Derivatives: A Search for Potential Drug Targets for
Rheumatoid Arthritis using In-silico Drug Discovery Techniques

Abdelmoujoud      Faris; Ibrahim   M.   Ibrahim; Souvik      Chakraborty; Omkulthom      Al Kamaly; Samar   Zuhair   Alshawwa; Menana      Elhallaoui

doi:10.2174/1570180820666230821102836

Abstract

Objective: This study aimed to discover a novel active compound capable of effectively inhibiting JAK3/STAT1 and CYP3A4 using molecular modelling techniques, with the goal of treating autoimmune diseases such as cancer and specifically rheumatoid arthritis. The study involved modelling compounds derived from pyrazolopyrimidine, followed by screening methods to identify the most promising compounds. Moreover, this study seeks to identify potential compounds that can inhibit JAK3/STAT through molecular modelling techniques and validate the stability and affinity of the predicted molecule.

Methods: Various molecular modelling techniques were employed to identify potential compounds and assess the stability and affinity of the predicted molecule. A pharmacophore hypothesis was developed to obtain crucial information about the experimental series of pyrazolopyrimidine studied, which served as the basis for designing new molecules. Additionally, ADMET was utilized to predict and evaluate the pharmacokinetic properties and potential toxicity of the compound prior to synthesis or utilization. To determine the essential residues involved in the interaction between the molecule and the target JAK3 protein, the covalent docking method was applied. We further validated the binding stability of the JAK3 protein with the ligands ZINC62162141 and Tofacitinib, both of which have been approved by the FDA for JAK3/STAT inhibition., using DFT/B3LYP/6-31G molecular dynamics simulations lasting 1000 ns and MM/GBSA.

Results: During the study, we identified compounds that displayed notable activity against JAK3/STAT, specifically those containing thiadiazol, oxadiazol, and chlorophenyl groups. Additionally, the pharmacophore model, ADRRR_1, exhibited promising potential for predicting new molecules. The predicted compound, ZINC62162141, demonstrated favourable ADMET properties, including inhibition of CYP3A4. Furthermore, we assessed its binding stability to the target protein and determined its affinity for the protein-ligand complex using MMGBSA.

Conclusion: The results of this study suggest that the compounds identified have the potential to be promising candidates for inhibiting JAK3/STAT and CYP3A4, offering potential therapeutic benefits for the treatment of rheumatoid arthritis. These findings provide a foundation for subsequent experimental validation and the development of novel drugs in this field.

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DOI https://dx.doi.org/10.2174/1570180820666230821102836	Print ISSN 1570-1808
Publisher Name Bentham Science Publisher	Online ISSN 1875-628X

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