Identification of Binding Peptides for Dengue Virus: New Horizons for Diagnostic and Therapeutic Strategies

The Dengue virus (DENV) is an arbovirus responsible for more than 390 million infections and more than 9,000 deaths annually worldwide. Despite the accumulated knowledge on dengue immunopathogenesis, the determinants of severe disease manifestations still pose significant challenges. A favorable prognosis depends mainly on early and appropriate clinical management, given the absence of a specific therapy. Among antiviral discovery strategies, the identification of biomolecules capable of binding to key proteins involved in DENV infection ‒ such as the envelope (E) protein and the nonstructural protein 1 (NS1) ‒ stands out, as it can directly impact viral infection and/or replication processes. Alternatively, these biomolecules may indicate compounds with potential antiviral activity. To identify binding peptides with high avidity for DENV, a library containing one trillion random peptides was used in phage display assays, using the E and NS1 proteins as targets. The proteins were incubated with bacteriophages expressing 12–amino acid peptides on their surface. Peptides selected after cycles of biopanning were identified by sequencing the corresponding plasmid. In the NS1 screening, a progressive reduction in the number of affinity phages was observed: from more than 10,000 colonies in the first cycle, to around 100 in the second, and 15 in the third. Forty colonies from the first two cycles and all 15 from the third were sequenced. One sequence recurred in cycles two and three, suggesting selective enrichment. For the E protein, phage titers dropped from 10,000 to 150 between the first two cycles. Forty colonies from the first cycle and 23 from the second cycle were sequenced, and data analysis is ongoing. These findings demonstrate the feasibility of selecting peptides with specific affinity for DENV proteins. The selected peptides will undergo molecular docking analyses, surface plasmon resonance, and artificial intelligence tools to identify hits, optimize interactions, and predict new binders. Developing panels with anti-DENV peptides represents an innovative strategy with the potential to fill scientific gaps and address public health demands.