article · Scientific Reports
New pyridine derivatives were designed and synthesised to investigate their potential medicinal effects against SARS-CoV-2. A combination of computational methods and laboratory evaluations characterised the new molecules. Molecular docking and molecular dynamics simulations against viral proteins showed that compounds 5, 11, and 12 were the strongest binders to the SARS-CoV-2 main protease, forming stable complexes over simulation periods. Computational pharmacokinetics and drug-likeness analyses revealed that all seven newly prepared compounds complied with Lipinski rules and exhibited high gastrointestinal absorption. Laboratory testing using cytotoxicity and inhibitory concentration assays evaluated the safety and antiviral activity of the compounds. Among the tested candidates, compound 5 demonstrated the highest antiviral potential alongside a safer profile in cell-based assays. Overall, the findings indicate that these pyridine derivatives, particularly compound 5, represent promising candidates for COVID-19 treatment development.
The ongoing challenge of COVID-19 requires new therapeutic options to inhibit the virus effectively. Identifying novel chemical structures that bind to essential viral proteins while meeting drug-likeness criteria helps streamline the early stages of drug discovery. Demonstrating computational binding stability alongside low cellular toxicity provides an empirical foundation for selecting specific lead molecules for further antiviral research.
The research presents early-stage pharmaceutical drug candidates for treating COVID-19. Pharmaceutical developers and medicinal chemistry teams could use compound 5, along with compounds 11 and 12, as starting points for lead optimisation and preclinical evaluation. Because the work is at the stage of computational modelling and initial in vitro cell testing, it remains distant from real-world clinical use, requiring extensive in vivo validation, safety profiling, and clinical trials.
AI-generated from the published abstract. Always read the original work before citing.
Computer-aided drug design has been employed to get the medicinal effects against Corona virus from different pyridine derivatives after synthesizing the new compounds. Additionally, various computational studies are also employed between the newly prepared pyridine derivatives and three controls against three proteins (6Y2E, 6M71 and 6M3M). Different methods were employed to synthesize new pyridine derivatives according to the literature using different reaction mediums. MTT was performed for cytotoxicity study and IC<sub>50</sub> for inhibitory concentration. Additionally, in-silico studies including DFT, molecular docking, molecular dynamics, MMPBSA, ADME, pharmacokinetics and Lipinski rules were evaluated. The chemical structures of all new compounds were elucidated based on spectroscopic investigation. A molecular docking study demonstrated that compounds 5, 11, and 12 have the best binders of the SARS-CoV-2 main protease enzyme, with energy scores of - 7.5 kcal/mol, - 7.2 kcal/mol, and - 7.9 kcal/mol, respectively. The net binding energy values of the 11-Mpro, 12-Mpro, and 5-Mpro complexes revealed their highly stable nature in terms of both intermolecular interactions and docked conformation across the simulation time. ADME properties, besides the pharmacokinetics and Lipinski rules, showed that all seven newly synthesized compounds follow Lipinski rules with high GI absorption. The In Vitro antiviral study against SARS-CoV-2 using MTT methods confirms that compound 5 has more potential and is safer than other tested compounds. The study shows that the newly synthesized pyridine derivatives have medicinal properties against SARS-CoV-2 without violating Lipinski rules. Compounds 5, 11, and 12, particularly compound 5, may serve as promising potential candidate for COVID-19.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1038/s41598-024-51443-7
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
