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Control of Surface-Localized, Enzyme-Assisted Self-Assembly of Peptides through Catalyzed Oligomerization.

Cécile Vigier-CarrièreDéborah WagnerAlain ChaumontBaptiste DurrPaolo LupattelliChristophe LambourMarc SchmutzJoseph HemmerléBernard SengerPierre SchaafFouzia BoulmedaisLoïc Jierry
Published in: Langmuir : the ACS journal of surfaces and colloids (2017)
Localized self-assembly allowing both spatial and temporal control over the assembly process is essential in many biological systems. This can be achieved through localized enzyme-assisted self-assembly (LEASA), also called enzyme-instructed self-assembly, where enzymes present on a substrate catalyze a reaction that transforms noninteracting species into self-assembling ones. Very few LEASA systems have been reported so far, and the control of the self-assembly process through the surface properties represents one essential step toward their use, for example, in artificial cell mimicry. Here, we describe a new type of LEASA system based on α-chymotrypsin adsorbed on a surface, which catalyzes the production of (KL)nOEt oligopeptides from a KLOEt (K: lysine; L: leucine; OEt ethyl ester) solution. When a critical concentration of the formed oligopeptides is reached near the surface, they self-assemble into β-sheets resulting in a fibrillar network localized at the interface that can extend over several micrometers. One significant feature of this process is the existence of a lag time before the self-assembly process starts. We investigate, in particular, the effect of the α-chymotrypsin surface density and KLOEt concentration on the self-assembly kinetics. We find that the lag time can be finely tuned through the surface density in α-chymotrypsin and KLOEt concentration. For a given surface enzyme concentration, a critical KLOEt concentration exists below which no self-assembly takes place. This concentration increases when the surface density in enzyme decreases.
Keyphrases
  • stem cells
  • machine learning
  • deep learning
  • cell therapy
  • ionic liquid
  • neural network