Biochemical and structural insights into dehairing proteases for efficient leather processing

Abstract

Dehairing proteases are eco-friendly alternatives to chemical dehairing process. Yet, their widespread industrial adoption requires focused research on key factors influencing their efficacy. Earlier research on two microbial proteases, SP01 (from Bacillus cereus VITSP01) and SP02 (from Brevibacterium luteolum VITSP02), revealed a correlation between substrate specificity for proteoglycans and dehairing efficacy. Herein, a comprehensive comparative analysis of their biochemical, thermodynamic, and molecular characteristics was performed to elucidate the determinants of their performance. In comparison to SP01, SP02 could cleave skin proteoglycans and dehair goat skins efficiently at lower temperatures (15 °C and 37 °C). Additionally, it exhibited thermolability, lower activation energy (Ea = 27.003 kJ mol⁻¹) and tolerance to 10% SDS, non-ionic detergents, and 20% NaCl, while Ca²⁺ had a stabilizing effect on its structure. The protease genes of SP01 and SP02 were identified to be trypsin-like peptidase domain-containing protein and S8 family peptidase, respectively. The docking and molecular dynamics simulation revealed stabler interactions between proteoglycans and SP02 compared to SP01. The penetration of SP02 was faster than that of SP01 through skin matrix, probably due to its lower molecular weight (around 30 kDa), pI (about 4.6), proteoglycan degrading property, and smaller Rg and Rh. In silico structural analyses suggested some salient structural features responsible for the cold tolerance of SP02, and the resultant structural flexibility along with a larger catalytic pocket and longer multiple substrate-interacting tunnels could enable better substrate accommodation. In conclusion, SP02 was demonstrated as a potential dehairing enzyme with cold tolerant structural features. This study revealed some key determinants influencing its efficacy and stability, thereby implying improvements for process optimization.

Graphical Abstract

The alternative text for this image may have been generated using AI.