Harnessing Machine Learning To Unravel Protein Degradation in Escherichia coli
Natan Nagar, Noa Ecker, Gil Loewenthal, Oren Avram, Daniella Ben‐Meir, Dvora Biran, Eliora Z. Ron, Tal Pupko
Abstract
is composed of three protein populations that are distinct in terms of stability and functionality, and we show that fast-degrading proteins can be identified using a combination of various protein properties. Our findings expand the understanding of protein degradation in bacteria and have implications for protein engineering. Moreover, as rapidly degraded proteins may play an important role in pathogenesis, our findings may help to identify new potential antibacterial drug targets.
Topics & Concepts
Degradation (telecommunications)Dispose patternEscherichia coliProtein degradationBacteriaChemistryComputational biologyCell biologyComputer scienceBiochemistryBiologyGeneticsGeneProgramming languageTelecommunicationsBacterial Genetics and BiotechnologyProtein Structure and DynamicsMicrobial Metabolic Engineering and Bioproduction