MAAD: Multidimensional Antiviral Antibody Database

Abstract Antibodies have emerged as central components of therapeutic strategies against viral infectious diseases, functioning as key effectors in both prevention and treatment. While traditional antibody discovery has relied heavily on high-throughput screening, the field is now shifting toward rational antibody design, which requires integrative insights into sequence-structure-function relationships. However, the absence of a standardized and well-annotated antibody database integrating these multidimensional features hampers systematic exploration, cross-pathogen comparison, and rational antibody design. Here, we introduce a “Multidimensional Antiviral Antibody Database” (MAAD; http://www.xxx), a curated platform dedicated to antibody nanobody and single-chain variable fragment targeting three high-impact RNA virus families, Coronaviridae (SARS-CoV-1, SARS-CoV-2, MERS-CoV), Orthomyxoviridae (influenza virus), and Pneumoviridae (respiratory syncytial virus, human metapneumovirus), due to the large, high-quality datasets accumulated in recent years. MAAD further incorporates a suite of interactive analysis modules, including CDR annotation, similarity-based CDR3 sequence analysis, V/J gene usage profiling, sequence-based clustering and structure-based antigen-antibody interfaces residues with per-site entropy and mutation rate profiling. These features enable in-depth exploration of antibody sequence characteristics, thereby facilitating functional and structural insights for rational antibody design. Together, by bridging antibody sequence, structure and function, MAAD offers an open and standardized platform that advances comparative antiviral research and supports therapeutic antibody discovery.