Magdalena Wysocka

Serine proteases are extensively known to play key roles in many physiological processes. However, their dysregulation is often associated to several diseases including inflammatory bowel diseases (IBD). Here, we used specific substrates to monitor fecal protease activities in a large cohort of healthy and IBD patients. Of interest, serine protease activity was 10-fold higher in IBD fecal samples compared to healthy controls. Moreover, functional analysis of these fecal proteolytic activities revealed that the most increased activities are trypsin-like, elastase-like and cathepsin G-like. We also show for the first time, an increase of proteinase 3-like activity in these samples compared to controls. Results presented here will guide further investigations to better understand the relevance of these peptidases in IBD.

BACKGROUND: There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will deliver models with limited transparency and explainability, which constrain their deployment in biomedical settings. METHODS: This systematic review discusses DL models used to support inference in cancer biology with a particular emphasis on multi-omics analysis. It focuses on how existing models address the need for better dialogue with prior knowledge, biological plausibility and interpretability, fundamental properties in the biomedical domain. For this, we retrieved and analyzed 42 studies focusing on emerging architectural and methodological advances, the encoding of biological domain knowledge and the integration of explainability methods. RESULTS: We discuss the recent evolutionary arch of DL models in the direction of integrating prior biological relational and network knowledge to support better generalisation (e.g. pathways or Protein-Protein-Interaction networks) and interpretability. This represents a fundamental functional shift towards models which can integrate mechanistic and statistical inference aspects. We introduce a concept of bio-centric interpretability and according to its taxonomy, we discuss representational methodologies for the integration of domain prior knowledge in such models. CONCLUSIONS: The paper provides a critical outlook into contemporary methods for explainability and interpretability used in DL for cancer. The analysis points in the direction of a convergence between encoding prior knowledge and improved interpretability. We introduce bio-centric interpretability which is an important step towards formalisation of biological interpretability of DL models and developing methods that are less problem- or application-specific.

This work is focused on SFTI-1, a member of the Bowman-Birk family of inhibitors. This 14 amino acid cyclic peptide exhibits several features i.e. compact rigidity, well-defined structure and small size that could result in a wide range of potential applications. Some examples of engineering of the specificity of this inhibitor along with structure - activity relationships will be discussed herein. Additionally, potential uses of STFI-1 and its analogs as pharmaceutical agents will be described. Keywords: SFTI-1, inhibitor, serine proteinases, peptidomimetics, peptomers, analogs, pharmaceutical agents, cytotoxicity, trypsin, chymotrypsin

Zika virus ( ZIKV ), isolated from macaques in Uganda in 1947, was not considered to be a dangerous human pathogen. However, this view has recently changed as ZIKV infections are now associated with serious pathological disorders including microcephaly and Guillain–Barré syndrome. Similar to other viruses in the Flaviviridae family, ZIKV expresses the serine protease NS 3 which is responsible for viral protein processing and replication. Herein, we report the expression of an active NS 3 pro domain fused with the NS 2B cofactor ( NS 2 B LN NS 3 pro ) in a prokaryotic expression system and profile its specificity for synthesized FRET ‐type substrate libraries. Our findings pave way for screening potential intracellular substrates of NS 3 and for developing specific inhibitors of this ZIKV protease.