In silico mining and identification of a novel lipase from Paenibacillus larvae: Rational protein design for improving catalytic performance.

Lipases play a vital role in various biological processes, from lipid metabolism to industrial applications. However, the ever-evolving challenges and diverse substrates necessitate the continual exploration of novel high-performance lipases. In this study, we employed an in silico mining approach to search for lipases with potential high sn-1,3 selectivity and catalytic activity. The identified novel lipase, PLL, from Paenibacillus larvae subsp. larvae B-3650 exhibited a specific activity of 111.2 ± 5.5 U/mg towards the substrate p-nitrophenyl palmitate (pNPP) and 6.9 ± 0.8 U/mg towards the substrate olive oil when expressed in Escherichia coli (E. coli). Computational design of cysteine mutations was employed to enhance the catalytic performance of PLL. Superior stability was achieved with the mutant K7C/A386C/H159C/K108C (2M3/2M4), showing an increase in melting temperature (T) by 1.9°C, a 2.05-fold prolonged half-life at 45°C, and no decrease in enzyme activity. Another mutant, K7C/A386C/A174C/A243C (2M1/2M3), showed a 4.9-fold enhancement in specific activity without compromising stability. Molecular dynamics simulations were conducted to explore the mechanisms of these two mutants. Mutant 2M3/2M4 forms putative disulfide bonds in the loop region, connecting the N- and C-termini of PLL, thus enhancing overall structural rigidity without impacting catalytic activity. The cysteines introduced in mutant 2M1/2M3 not only form new intramolecular hydrogen bonds but also alter the polarity and volume of the substrate-binding pocket, facilitating the entry of large substrate pNPP. These results highlight an efficient in silico exploration approach for novel lipases, offering a rapid and efficient method for enhancing catalytic performance through rational protein design.