Integrated In Silico, In Vitro, and Clinical Analysis of Antibody Binding to the SARS-CoV-2 Spike SD2 Disulfide Loop

Study Overview This dataset supports the research titled “Computational and Experimental Quantification of Antibody Affinity for the SARS-CoV-2 Spike Subdomain 2 Major Disulfide Loop (SD2MDL)”. The investigation combines in silico and in vitro approaches to examine antibody–epitope interactions within a highly conserved region of the SARS-CoV-2 Spike (S) protein. Objectives The primary goal of this study is to integrate computational prediction and laboratory validation to characterize antibody binding affinity toward the SD2MDL region. Specifically, the project was designed to accomplish the following: 1. Design and generate synthetic peptide analogs corresponding to the SARS-CoV-2 Spike Subdomain 2 Major Disulfide Loop (SD2MDL), ensuring high immunogenicity, sequence conservation, and structural fidelity. 2. Quantitatively determine antibody–peptide affinity using experimental immunoassays with antipeptide antibodies, applying absorbance-based binding curve fitting and dissociation constant (Kd) estimation methods. 3. Demonstrate specific antibody recognition of the designed peptide analogs in clinical serum samples, confirming the immunological relevance of the SD2MDL region. Significance The work provides a comparative framework linking computational affinity prediction and experimental antibody binding assays to support epitope validation in emerging viral pathogens. These results contribute to ongoing efforts in rational peptide vaccine design, serological assay development, and structure-guided immunodiagnostics.