Enhancing thermal stability of pectinase using thermal titration molecular dynamics and density functional theory approach

Pectinase, an enzyme primarily produced from Aspergillus niger, is essential in various industrial applications. However, the enzyme's functionality at high temperatures is challenging, restricting its effectiveness and potential uses. Therefore, the present study investigated the potential of peptide binding to enhance the thermal stability of pectinase. Thermal titration molecular dynamics (MD) simulations were performed at 300, 320, 340 and 360 K to identify regions susceptible to thermal fluctuations. Based on these results, 235,200 peptide sequences were screened to target the detected unstable regions. Machine learning models predicted the peptide activity and 12 promising peptide-protein complexes were identified using docking. Binding free energy calculations showed pep-10 (-19.4 kcal/mol), pep-8 (-17.97 kcal/mol), pep-12 (-15.25 kcal/mol) and pep-6 (-9.86 kcal/mol) as the most promising candidates to improve the thermal stability. Density functional theory calculations showed that pep-12 had the lowest energy of -2365. MD simulations at 360 K for 100 ns demonstrated that pep-12 maintained the most stable conformation with root mean square deviation (0.2-0.25 nm) compared to other peptides. Quantum mechanics/molecular mechanics hybrid approach to examine the mechanism of the pep-12 complex with Pectinase. The outcomes of this study suggested that pep-12 is the most potential candidate for enhancing pectinase thermal stability.