The Nedd4-1 E3 Ubiquitin ligase has been implicated in multiple disease conditions due its overexpression. Although the enzyme may be targeted both covalently and non-covalently, minimal studies provide effective inhibitors against it. Recently, research has focused on covalent inhibitors based on their characteristic, highly-selective warheads and ability to prevent drug resistance. This prompted us to screen for new covalent inhibitors of Nedd4-1 using a combination of computational approaches. However, this task proved challenging due to the limited number of electrophilic moieties available in virtual libraries. Therefore, we opted to divide an existing covalent Nedd4-1 inhibitor into two parts: a non-covalent binding group and a pre-selected α, β-unsaturated ester that forms the covalent linkage with the protein. A non-covalent pharmacophore model was built based on molecular interactions at the binding site. The pharmacophore was then subjected to virtual screening to identify structurally similar hit compounds. Multiple filtrations were implemented prior to selecting four hits, which were validated with a covalent conjugation and later assessed by molecular dynamic simulations. The results showed that, of the four hit molecules, Zinc00937975 exhibited advantageous molecular groups, allowing for favourable interactions with one of the characteristic cysteine residues. Predictive pharmacokinetic analysis further justified the compound as a potential lead molecule, prompting its recommendation for confirmatory biological evaluation. Our inhouse, refined, pharmacophore model approach serves as a robust method that will encourage screening for novel covalent inhibitors in drug discovery.
Keywords: NEDD4-1 E3 ligase; covalent inhibition; molecular dynamic simulations; molecular modeling; pharmacophore modeling.