Accurate prediction for adsorption rate of peptides with high ACE-inhibitory activity from sericin hydrolysate on thiophene hypercross-linked polymer using CoMSIA in 3D-QSAR model

摘要

Efficient screening of angiotensin converting enzyme inhibitory (ACE-I) peptides from agricultural or edible sources attract increasing attention. However, their purification process from the complex natural system is still semi-empirical or even uncontrollable, which has seriously reduced their screening efficiency. Herein, inspired by the prediction of ACE-I activity, 3D-QSAR was proposed to predict the adsorption performance of peptides from sericin hydrolysate (SH) having high ACE-I activity on porous hypercross-linked polymers according to their molecular structures. Thiophene hypercross-linked polymer (T-HCP) possessing better screening capacity for ACE-I peptides was chosen as our research object in this work. The sequence and relative adsorption rate of 101 peptides in SH were analyzed by LC-MS and was used as a database to construct the relationship of peptide's chemical structure and adsorption performance on T-HCP by Comparative molecular similarity indices analysis (CoMSIA) from 3D-QSAR. Optimum CoMSIA revealed that enhanced interaction of hydrophobicity and H-bond between T-HCP and the peptide was conducive to increase the adsorption performance of dito hexapeptides. Based on these relationships, the adsorption capability of 24 designed peptides with distinguished hydrophobic and H-bond fields was predicted on T-HCP by using optimum CoMSIA and the results of half of these were verified, which showed high consistency with their predicted adsorption rate. Interestingly, these peptides having higher adsorption capacities on T-HCP also possessed higher ACE-I activity. This can be attributed to the high concentration of aromatic surface with 7C-7C interaction and weak-polar C-S-C group with H-bond interaction on T-HCP material, which is ideal for the selective adsorption of peptides with higher ACE-I activity from SH. This study provides important theoretical guidance for the industrial screening of bio-functional peptides from complex protein mixtures.