A computer simulated gp100 Peptide mimic designed pharmacophore as a Vaccine-like and Interleukin-2 in silico generated superagonist with potential clinical effect in Patients with Advanced Melanoma using an Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design.

Stimulating an immune response against cancer with the use of vaccines remainsa challenge. We hypothesized that combining a melanoma vaccine with interleukin-2, an immuneactivating agent, could improve outcomes. In a previous phase 2 Research Scientific Project, patients with metastaticmelanoma receiving high-dose interleukin-2 plus the gp100:209–217(210M) peptide vaccine hada higher rate of response than the rate that is expected among patients who are treated withinterleukin-2 alone. We here, present an evolutionary algorithm that works in conjunction with existing open-source software to automatically optimize candidate ligands for predicted binding affinity and other druglike properties. We used the rules of click chemistry to guide optimization, greatly enhancing synthesizability. Here, we have for the first time disxovered a computer simulated gp100 Peptide mimic designed pharmacophore as a Vaccine-like and Interleukin-2 superagonist in Patients withAdvanced Melanoma using an Improved Algorithm for Chemically Tractable, Semi-Automated Protein Inhibitor Design.