Tian_2026_Int.J.Biol.Macromol__151681

Computational protein design faces challenges in simultaneously optimizing stability and catalytic activity. We integrated sequence-generative design (ProteinMPNN) with structure-based preorganization strategies to engineer thermostable yet active Bacillus subtilis Lipase A (BSLA) variants. Three preorganization approaches-active-site residues (ASP), conserved residues (CRP), and network neighborhood nodes (NNP)-plus an unconstrained control (NPC), were exploratorily evaluated using eight experimentally characterized variants. Variant NNP-6 showed a 16.95 degreesC increase in melting temperature with partial activity retention (44.41% of wild-type), in contrast to the complete activity loss in NPC variants and destabilization in ASP variants. Molecular dynamics and residue interaction network analysis retrospectively identified two dynamic network signatures: edge weight variance exhibited a negative correlation with melting temperature (r = -0.87), reflecting global rigidity, while dynamic conflicting contacts in the vicinity of the active site showed a positive correlation with retained activity (r = 0.88), indicating localized dynamic frustration. These exploratory correlations establish a preliminary dual-parameter framework for understanding stability and activity as distinct dimensions in BSLA, illustrating how dynamic network analysis can rationalize experimental outcomes.