PROPHET: Phylogenetically Robust Antiviral Peptide Design Against Heterogeneous Evolutionary Trajectories

Antiviral therapeutics often lose efficacy as viral proteins accumulate escape mutations, yet existing peptide binder design methods optimize against a single observed target sequence and do not account for future evolutionary variation. We introduce a method for Phylogenetically Robust antiviral Peptide design against Heterogeneous Evolutionary Trajectories, termed PROPHET, a framework for evolutionary robustness-aware peptide generation. PROPHET estimates a phylogenetic energy landscape from FastTree phylogenies using site-specific mutation rates, substitution preferences, and direct coupling analysis of coevolving residues, defining a structured distribution over evolutionarily plausible future variants. We then leverage multi-objective discrete flow matching to guide against this distribution using a CVaR robustness objective computed over Gibbs-sampled variants from the phylogenetic energy landscape. The resulting peptides jointly optimize wild-type affinity and robustness across plausible escape trajectories implied by observed viral evolution. On HIV-1 protease, PROPHET achieves substantially stronger mean and worst-case binding across held-out escape variants than methods optimized against the wild-type alone, uniformly weighted observed sequences, or randomly generated variants, while preserving high affinity to the current target. Overall, our results demonstrate that the phylogenetic history of a virus can directly guide the generative design of antiviral peptide therapeutics robust to future evolutionary escape.