2026-04-17T18:39:50Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/470252025-12-18T01:08:43Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Cavaco, Marco author Valle, Javier author Flores, Isabel author Andreu Martínez, David author Castanho, Miguel A.R.B. author 2021-04-07T05:51:28Z 2021-04-07T05:51:28Z 2021 Proteolytic instability is a critical limitation for peptide-based products. Although significant efforts are devoted to stabilize sequences against proteases/peptidases in plasma/serum, such approaches tend to be rather empirical, unspecific, time-consuming, and frequently not cost-effective. A more rational and potentially rewarding alternative is to identify the chemical grounds of susceptibility to enzymatic degradation of peptides so that proteolytic resistance can be tuned by manipulation of key chemical properties. In this regard, we conducted a meta-analysis of literature published over the last decade reporting experimental data on the lifetimes of peptides exposed to proteolytic conditions. Our initial database contained 579 entries and was curated with regard to amino acid sequence, chemical modification, terminal half-life (t1/2 ) or other stability readouts, type of stability assay, and biological application of the study. Although the majority of entries in the database corresponded to (slightly or substantially) modified peptides, we chose to focus on unmodified ones, as we aimed to decipher intrinsic characteristics of peptide proteolytic susceptibility. Specifically, we developed a multivariable regression model to unravel those peptide properties with most impact on proteolytic stability and thus potential t1/2 predicting ability. Model validation was done by two different approaches. First, a library of peptides spanning a large interval of properties that modulate stability was synthesized and their t1/2 in human serum were experimentally determined. Second, the t1/2 of 21 selected peptides approved for clinical use or in clinical trials were recorded and matched with the model-estimated values. With both approaches, good correlation between experimental and predicted t1/2 data was observed. This research was supported by the Portuguese Fundação para a Ciência e a Tecnologia (FCT; grants PD/BD/128281/2017, PTDC/BBB‐NAN/1578/2014, PTDC/BIA‐VIR/29495/2017, UID/Multi/04349/2019, and PTDC/QUI‐NUC/30147/2017), the Spanish Ministry of Economy and Innovation (MINECO, grants AGL2014‐52395‐C2‐2‐R and AGL2017‐84097‐C2‐2‐R, and Maria de Maeztu Program for Centers of Excellence); the European Union H2020‐MSCA‐RISE‐2014 program (grant no. 828774), and the “La Caixa” Banking Foundation (grant HR17‐00409). Estimating peptide half‐life in serum from tunable, sequence‐related physicochemical properties