Computational Screening of Nicotine and Bacterial Degradation Derivatives as Inhibitors of Key SARS-CoV-2 Proteins

Abstract

The emergence of SARS-CoV-2 has prompted extensive research into repurposed compounds as potential inhibitors. While nicotine's interactions with viral proteins have been explored, its bacterial degradation derivatives remain largely uninvestigated. This computational study evaluates nicotine and 11 bacterial nicotine metabolites as inhibitors of key SARS-CoV-2 targets: wild-type and Omicron-type spike-ACE2 complexes, main protease (MPRO), RNA-dependent RNA polymerase (RdRp), and TMPRSS2. Molecular docking identified moderate binding affinities (-8.1 to -4.6 kcal/mol), with Nic Blue showing the strongest docking scores. However, 100 ns molecular dynamics MD simulations and MM/GBSA binding free energy calculations provided more reliable insights, revealing stable binding for select derivatives: 6H3SP with wild-type spike-ACE2 (-10.67 kcal/mol), nicotine with Omicron spike-ACE2 (-28.66 kcal/mol), 3SAP and Nic Blue with MPRO, NMM and 6HMM with RdRp (-23.57 and -21.87 kcal/mol), and 6H3SAP/6H3SP with TMPRSS2 (-25.08 and -24.48 kcal/mol). These molecules are valuable for their high affinities relative to their size, in comparison with larger literature candidates. This work highlights bacterial nicotine metabolites as novel leads for SARS-CoV-2 inhibition, warranting further in silico/in vitro/in vivo validation.

Keywords

• Computational drug design
• COVID-19
• Nicotine
• Nicotine derivatives
• Molecular dynamics

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