Exploring the viral protease inhibitor space driven by consensus scoring-based virtual screening

Area of Science:

• Virology
• Drug Discovery
• Computational Chemistry

Background:

• Dengue fever is a significant global health issue with no effective vaccine or treatment.
• Inhibiting the NS2B-NS3 protease complex is a promising strategy against dengue virus.
• Identifying safe-by-design drug targets is crucial for novel therapeutic development.

Purpose of the Study:

• To computationally model and identify inhibitors of the dengue virus NS2B-NS3 protease complex.
• To explore physicochemical features essential for blocking the NS2B-NS3 interaction.
• To discover novel small molecules as potential scaffolds for dengue antiviral drugs.

Main Methods:

• Alanine scanning to identify critical hot spot residues for NS2B-NS3 association.
• Consensus score-based virtual screening of chemical datasets.
• Molecular docking, molecular dynamics simulations, and binding free energy calculations.

Main Results:

• Identified key residues (Tyr23, Lys26, Phe46, Leu58) crucial for NS2B-NS3 interaction.
• Screened over 1,500 small molecules, with 233 progressing to docking.
• Selected top five molecules exhibiting enhanced stability and binding affinity to the target protein.

Conclusions:

• The study successfully identified potential protein-protein interaction blockers against the dengue virus NS2B-NS3 protease.
• The discovered compounds show promise as novel scaffolds for developing dengue antiviral therapies.
• Further research will focus on atomistic details for structure-based drug design against DENV-2.