Computational Engineering of Malonate and Tetrazole Derivatives Targeting SARS-CoV-2 Main Protease: Pharmacokinetics, Docking, and Molecular Dynamics Insights to Support the Sustainable Development Goals (SDGs), with a Bibliometric Analysis

Abstract

This research applies computational engineering to explore malonate and tetrazole derivatives as potential inhibitors of the SARS-CoV-2 Main Protease. A comprehensive in silico approach, including pharmacokinetics prediction, molecular docking, and molecular dynamics simulations, was utilized to evaluate the drug-likeness, binding affinity, and stability of the designed compounds. The malonate derivatives demonstrated strong interaction stability with the target protease and exhibited favorable pharmacokinetic profiles with minimal predicted toxicity, supporting their potential as therapeutic candidates. A bibliometric analysis was also performed to position this study within the broader scientific landscape, showing increasing global interest in SARS-CoV-2 protease inhibitors and antiviral drug development. This work aligns with the Sustainable Development Goals by contributing to global health improvement and fostering innovation in pharmaceutical engineering. The promising computational outcomes underscore the need for further experimental validation to confirm therapeutic efficacy and safety, potentially contributing to future antiviral treatment strategies.