Computational design and molecular dynamics for developing a multistage serodiagnostic biomarker for tuberculosis

Tuberculosis (TB) remains a leading cause of global morbidity and mortality, with approximately 25% of the population harboring latent infection. Despite being preventable and curable, TB remains a significant global health burden due to a lack of affordable, reliable diagnostic tools for low-income populations. This study presents the computational design and in silico evaluation of TetraFuSD2, a novel multi-stage fusion antigen diagnostic biomarker. The construct comprises four stage-specific antigens, including HspX (latency-associated), ESAT-6 and CFP-10 (early-stage), and CFP-21 (active-stage). The constituent antigens were fused in an N- to C-terminal orientation using glycine-serine linkers. A comprehensive in silico characterization, including physicochemical profiling, structural modeling, and validation via ProSA-web and Ramachandran plot analysis, revealed a stable and physiologically favorable conformation of TetraFuSD2. Antigen–antibody docking simulations using HDOCK and PRODIGY revealed high-affinity interactions with human IgG-Fab fragments, with a predicted static binding energy (Δ G bind ) of − 13.4 kcal/mol. Furthermore, 100 ns molecular dynamics simulations with stable RMSF and RMSD plots and MM/GBSA binding free-energy calculations demonstrated sustained stability of the antigen–antibody complex with ΔG = − 68.54 kcal/mol. Given these computational insights, TetraFuSD2 warrants further evaluation to establish its clinical diagnostic potential for TB, which will be the primary focus of our upcoming experimental studies.