Postharvest valorization and upgrading of algal constituents are promising strategies in the development of a sustainable bioeconomy based on algal biomass. In this respect, alginate epimerases and lyases are valuable enzymes for tailoring the functional properties of alginate, a polysaccharide extracted from brown seaweed with numerous applications in food, medicine, and material industries.

Osteosarcoma (OS) is a mesenchymally derived, aggressive bone cancer. OS cells produce an aberrant nonmineralized or partly mineralized extracellular matrix (ECM) whose components participate in signaling pathways connected to specific pathogenic phenotypes of this bone cancer. The expression of biglycan (BGN), a secreted small leucine-rich proteoglycan (SLRP), is correlated to aggressive OS phenotype and resistance to chemotherapy. A constitutive signaling of IGF-IR signaling input in sarcoma progression has been established. Here, we show that biglycan activates the IGF-IR signaling pathway to promote MG63 biglycan-secreting OS cell growth by forming a complex with the receptor. Computational models of IGF-IR and biglycan docking suggest that biglycan binds IGF-IR dimer via its concave surface. Our binding free energy calculations indicate the formation of a stable complex. Biglycan binding results in prolonged IGF-IR activation leading to protracted IGF-IR-dependent cell growth response of the poorly-differentiated MG63 cells. Moreover, biglycan facilitates the internalization (p ≤ 0.01, p ≤ 0.001) and sumoylation-enhanced nuclear translocation of IGF-IR (p ≤ 0.05) and its DNA binding in MG63 cells (p ≤ 0.001). The tyrosine kinase activity of the receptor mediates this mechanism. Furthermore, biglycan downregulates the expression of the tumor-suppressor gene, PTEN (p ≤ 0.01), and increases the expression of endothelial–mesenchymal transition (EMT) and aggressiveness markers vimentin (p ≤ 0.01) and fibronectin (p ≤ 0.01) in MG63 cells. Interestingly, this mechanism is not valid in moderately and well-differentiated, biglycan non-expressing U-2OS and Saos-2 OS cells. Furthermore, biglycan exhibits protective effects against the chemotherapeutic drug, doxorubicin, in MG63 OS cells (p ≤ 0.01). In conclusion, these data indicate a potential direct and adjunct therapeutical role of biglycan in osteosarcoma.

The functional properties of alginates are dictated by the monomer composition and molecular weight distribution. Mannuronan C-5 epimerases determine the former by epimerizing β-D-mannuronic acid residues (M) into α-L-guluronic acid residues (G). The molecular weight is affected by alginate lyases, which cleave alginate chains through β-elimination. The reaction mechanisms for the epimerization and cleavage are similar and some enzymes can perform both. These dualistic enzymes share high sequence identity with mannuronan C-5 epimerases without lyase activity, and the mechanism behind their activity as well as the amino acids responsible for it are still unknown. In this study, we investigate mechanistic determinants of the bifunctional epimerase and lyase activity of AlgE7 from Azotobacter vinelandii . Based on sequence analyses, a range of AlgE7 variants were constructed and subjected to activity assays and product characterization by NMR. Our results show that the lyase activity of AlgE7 is regulated by the type of ion present: Calcium promotes it, whereas NaCl reduces it. By using defined poly-M and poly-MG substrates, the preferred cleavage sites of AlgE7 were found to be M↓XM and G↓XM, where X can be either M or G. By studying AlgE7 mutants, R148 was identified as an important residue for the lyase activity, and the point mutant R148G resulted in an enzyme with only epimerase activity. Based on the results obtained in the present study we suggest a unified catalytic reaction mechanism for both epimerase and lyase activities where H154 functions as the catalytic base and Y149 as the catalytic acid. Importance: Post-harvest valorisation and upgrading of algal constituents is a promising strategy in the development of a sustainable bioeconomy based on algal biomass. In this respect, alginate epimerases and lyases are valuable enzymes for tailoring of the functional properties of alginate, a polysaccharide extracted from brown seaweed with numerous applications in food, medicine and material industries. By providing a better understanding of the reaction mechanism and of how the two enzyme reactions can be altered by changes in reaction conditions, this study opens for further applications of bacterial epimerases and lyases in enzymatic tailoring of alginate polymers.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homo-dimers, 3 homo-trimers, 13 hetero-dimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their 5 best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% for the targets compared to 8% two years earlier, a remarkable improvement resulting from the wide use of the AlphaFold2 and AlphaFold-Multimer software. Creative use was made of the deep learning inference engines affording the sampling of a much larger number of models and enriching the multiple sequence alignments with sequences from various sources. Wide use was also made of the AlphaFold confidence metrics to rank models, permitting top performing groups to exceed the results of the public AlphaFold-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.