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SurfGraphPro, an AI tool, transforms complex protein structures into an easy-to-analyze format that helps researchers quickly identify binding sites, predict molecular interactions and understand protein behavior with greater speed and scalability than traditional approaches. By combining 3D surface graph representations with advanced machine learning, this technology from Los Alamos National Laboratory reduces the computational burden of protein analysis while preserving the structural detail needed for high-value applications in drug discovery, antibody design, pathogen detection and custom protein engineering. The Challenge: Protein surfaces are extremely complex, three-dimensional structures, and that complexity makes them difficult to analyze using traditional computational approaches. In practice, many existing methods rely on hand-selected biochemical features, expensive calculations or narrow task-specific models that do not generalize well to new questions. As a result, researchers can face slow runtimes, limited scalability and incomplete insight when trying to identify binding sites, predict molecular interactions or understand broader protein behavior across large sets of proteins. These limitations can make it difficult to move quickly from protein structure data to useful predictions in areas such as drug discovery, antibody design, pathogen detection and protein engineering. Problems Solved: SurfGraphPro solves these problems by converting protein surfaces into

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