Le complexe ternaire de la procarboxypeptidase A du pancréas de bœuf

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Modification of pancreatic lipase properties by directed molecular evolution

International audienceCystic fibrosis is associated with pancreatic insufficiency and acidic intraluminal conditions that limit the action of pancreatic enzyme replacement therapy, especially that of lipase. Directed evolution combined with rational design was used in the aim of improving the performances of the human pancreatic lipase at acidic pH. We set up a method for screening thousands of lipase variants for activity at low pH. A single round of random mutagenesis yielded one lipase variant with an activity at acidic pH enhanced by ∼50% on medium- and long-chain triglycerides. Sequence analysis revealed two substitutions (E179G/N406S) located in specific regions, the hydrophobic groove accommodating the sn-1 chain of the triglyceride (E179G) and the surface loop that is likely to mediate lipase/colipase interaction in the presence of lipids (N406S). Interestingly, these two substitutions shifted the chain-length specificity of lipase toward medium- and long-chain triglycerides. Combination of those two mutations with a promising one at the entrance of the catalytic cavity (K80E) negatively affected the lipase activity at neutral pH but not that at acidic pH. Our results provide a basis for the design of improved lipase at acidic pH and identify for the first time key residues associated with chain-length specificit

Single-Domain Antibody-Based and Linker-Free Bispecific Antibodies Targeting Fc RIII Induce Potent Antitumor Activity without Recruiting Regulatory T Cells

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From sequence to enzyme mechanism using multi-label machine learning

Background: In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling. Results: In this study, we evaluate whether sequence identity, InterPro or Catalytic Site Atlas sequence signatures provide enough information for bulk prediction of enzyme mechanism. By splitting MACiE (Mechanism, Annotation and Classification in Enzymes database) mechanism labels to a finer granularity, which includes the role of the protein chain in the overall enzyme complex, the method can predict at 96% accuracy (and 96% micro-averaged precision, 99.9% macro-averaged recall) the MACiE mechanism definitions of 248 proteins available in the MACiE, EzCatDb (Database of Enzyme Catalytic Mechanisms) and SFLD (Structure Function Linkage Database) databases using an off-theshelf K-Nearest Neighbours multi-label algorithm. Conclusion: We find that InterPro signatures are critical for accurate prediction of enzyme mechanism. We also find that incorporating Catalytic Site Atlas attributes does not seem to provide additional accuracy. The software code (ml2db), data and results are available online at http://sourceforge.net/projects/ml2db/ and as supplementary files.Publisher PDFPeer reviewe