Structure and function of SPP/SPPL proteases: insights from biochemical evidence and predictive modeling

Publikation: Beitrag in FachzeitschriftÜbersichtsartikel (Review)BeigetragenBegutachtung

Beitragende

  • Sabine Höppner - , Universität Augsburg (Autor:in)
  • Bernd Schröder - , Institut für Physiologische Chemie, Institute for Physiological Chemistry (Autor:in)
  • Regina Fluhrer - , Universität Augsburg (Autor:in)

Abstract

More than 20 years ago, signal peptide peptidase (SPP) and its homologues, the signal peptide peptidase-like (SPPL) proteases have been identified based on their sequence similarity to presenilins, a related family of intramembrane aspartyl proteases. Other than those for the presenilins, no high-resolution structures for the SPP/SPPL proteases are available. Despite this limitation, over the years bioinformatical and biochemical data have accumulated, which altogether have provided a picture of the overall structure and topology of these proteases, their localization in the cell, the process of substrate recognition, their cleavage mechanism, and their function. Recently, the artificial intelligence-based structure prediction tool AlphaFold has added high-confidence models of the expected fold of SPP/SPPL proteases. In this review, we summarize known structural aspects of the SPP/SPPL family as well as their substrates. Of particular interest are the emerging substrate recognition and catalytic mechanisms that might lead to the prediction and identification of more potential substrates and deeper insight into physiological and pathophysiological roles of proteolysis.

Details

OriginalspracheEnglisch
Seiten (von - bis)5456-5474
Seitenumfang19
FachzeitschriftThe FEBS journal
Jahrgang290
Ausgabenummer23
PublikationsstatusVeröffentlicht - 8 Dez. 2023
Peer-Review-StatusJa

Externe IDs

Scopus 85173989737

Schlagworte

Schlagwörter

  • Peptide Hydrolases/genetics, Membrane Proteins, Artificial Intelligence, Aspartic Acid Endopeptidases/chemistry, Presenilins