COMPUTATIONAL IDENTIFICATION OF A NOVEL ANTIBODY TARGETING NIPAH VIRUS GLYCOPROTEIN G

The Nipah virus (NiV) is a highly pathogenic zoonotic virus that causes severe respiratory disease and encephalitis in humans, with case fatality rates ranging from 40% to 75%. It is primarily transmitted to humans through the ingestion of food contaminated with secretions from fruit bats of the Pteropodidae family. The World Health Organization has designated NiV as a high-priority pathogen, underscoring the need for medical countermeasures. Antibody repurposing is an approach that explores the potential cross-reactivity of antibodies with novel targets, providing a rational basis for the rapid identification of candidate biopharmaceuticals.  To propose the structural repositioning of an existing antibody to recognize a key epitope of the NiV glycoprotein G. The structure was retrieved from the PDB (entry: 8XPY). A conserved epitope was identified through solvent accessibility variation analysis and characterized using three-dimensional (3D) Zernike descriptors. The Euclidean distance was then employed to measure structural similarity, enabling the identification of antibodies predicted to recognize epitopes with comparable geometries. The selected antibodies were subjected to molecular docking against glycoprotein G using HADDOCK2.4 to assess their binding orientations. Finally, the highest-ranked complexes were subjected to triplicate-heating molecular dynamics simulations. Complexes with RMSD values below 5 Å were retained as stable binding modes, whereas the remaining complexes were discarded as false positives. Structural similarity analysis identified three epitopes resembling the NiV glycoprotein G epitope: two recognized by anti-dengue antibodies (5N09 and 4UTB) and one associated with a SARS-CoV-2 antibody (7YVM). Docking of the selected antibodies against the NiV target revealed that the three most populated clusters consistently occupied the selected epitopes, supporting a compatible structural recognition pattern. Among the evaluated candidates, the antibodies originally directed against the SARS-CoV-2 epitope exhibited stable binding during molecular dynamics simulations, maintaining RMSD values below the established 5 Å threshold throughout the simulations. We identified a candidate antiviral antibody with the potential to recognize NiV glycoprotein G and establish stable interactions with its target epitope. These findings highlight its potential as a promising scaffold for biopharmaceutical development, supporting further computational investigations followed by experimental validation to confirm its therapeutic applicability.