Human Leukocyte Antigen (HLA) receptors play a key role in cellular immunity, binding intracellular peptides and displaying them for recognition by T-cell lymphocytes. T-cell activation is partially driven by structural features of these peptide-HLA complexes, making structural modeling and analysis of these complexes a desired goal for cancer immunotherapy projects. Unfortunately, these analyses are limited by their computational cost, and the small number of experimentally-determined structures of peptide-HLA complexes. Here we describe HLA-Arena, a computational environment designed to overcome the challenges associated with structural modeling, visualization, and analysis of peptide-HLA complexes. To illustrate the capabilities of HLA-Arena, we conducted a large-scale virtual screening of peptides for multiple HLA alleles. Our dataset included experimentally-determined binders, as well as decoys, and our results demonstrate the enrichment of true binders among top scoring peptides. HLA-Arena can be integrated within larger computational pipelines, and could be used to conduct structural analyses for personalized cancer immunotherapy, neoantigen discovery or vaccine development.