C1r serine proteinase of human complement: A case of intramolecular autolytic activation

1985 ◽  
Vol 5 (10-11) ◽  
pp. 831-837 ◽  
Author(s):  
Gérard J. Arlaud ◽  
Maurice G. Colomb ◽  
Christian L. Villiers

This paper presents a short review of our contribution to the knowledge of the structure and function of human Clr, the activation unit of C1, the first component of the classical pathway of complement. On the basis of the domain structure of Clr, a model accounting for its autolytic activation mechanism is proposed. We suggest that this represents the basic mechanism of C1 function.

2019 ◽  
Vol 5 (1) ◽  
pp. eaau9739 ◽  
Author(s):  
Sandip De ◽  
Yuzhong Cheng ◽  
Ming-an Sun ◽  
Natalie D. Gehred ◽  
Judith A. Kassis

Polycomb group proteins (PcGs) drive target gene repression and form large chromatin domains. InDrosophila, DNA elements known as Polycomb group response elements (PREs) recruit PcGs to the DNA. We have shown that, within theinvected-engrailed(inv-en) Polycomb domain, strong, constitutive PREs are dispensable for Polycomb domain structure and function. We suggest that the endogenous chromosomal location imparts stability to this Polycomb domain. To test this possibility, a 79-kbentransgene was inserted into other chromosomal locations. This transgene is functional and forms a Polycomb domain. The spreading of the H3K27me3 repressive mark, characteristic of PcG domains, varies depending on the chromatin context of the transgene. Unlike at the endogenous locus, deletion of the strong, constitutive PREs from the transgene leads to both loss- and gain-of function phenotypes, demonstrating the important role of these regulatory elements. Our data show that chromatin context plays an important role in Polycomb domain structure and function.


1985 ◽  
Vol 225 (1) ◽  
pp. 135-142 ◽  
Author(s):  
J Gagnon ◽  
G J Arlaud

Activated human complement-classical-pathway enzyme C1r has previously been shown to undergo autolytic cleavages occurring in the A chain [Arlaud, Villiers, Chesne & Colomb (1980) Biochim. Biophys. Acta 616, 116-129]. Chemical analysis of the autolytic products confirms that the A chain undergoes two major cleavages, generating three fragments, which have now been isolated and characterized. The N-terminal alpha fragment (approx. 210 residues long) has a blocked N-terminus, as does the whole A chain, whereas N-terminal sequences of fragments beta and gamma (approx. 66 and 176 residues long respectively) do not, and their N-terminal sequences were determined. Fragments alpha, beta and gamma, which are not interconnected by disulphide bridges, are located in this order within C1r A chain. Fragment gamma is disulphide-linked to the B chain of C1r, which is C-terminal in the single polypeptide chain of precursor C1r. CNBr cleavage of C1r A chain yields seven major peptides, CN1b, CN4a, CN2a, CN1a, CN3, CN4b and CN2b, which were positioned in that order, on the basis of N-terminal sequences of the methionine-containing peptides generated from tryptic cleavage of the succinylated (3-carboxypropionylated) C1r A chain. About 60% of the sequence of C1r A chain (440-460 residues long) was determined, including the complete sequence of the C-terminal 95 residues. This region shows homology with the corresponding parts of plasminogen and chymotrypsinogen and, more surprisingly, with the alpha 1 chain of human haptoglobin 1-1, a serine proteinase homologue.


2020 ◽  
Author(s):  
R Christian McDonald ◽  
Matthew J Schott ◽  
Temitope A Idowu ◽  
Peter J Lyons

Abstract Background. Like most major enzyme families, the M14 family of metallocarboxypeptidases (MCPs) contains a number of pseudoenzymes predicted to lack enzyme activity and with poorly characterized molecular function. The genome of the yeast Saccharomyces cerevisiae encodes one member of the M14 MCP family, a pseudoenzyme named Ecm14 proposed to function in the extracellular matrix. In order to better understand the function of such pseudoenzymes, we studied the structure and function of Ecm14 in S. cerevisiae. Results. A phylogenetic analysis of Ecm14 in fungi found it to be conserved throughout the ascomycete phylum, with a group of related pseudoenzymes found in basidiomycetes. To investigate the structure and function of this conserved protein, His6-tagged Ecm14 was overexpressed in Sf9 cells and purified. The prodomain of Ecm14 was cleaved in vivo and in vitro by endopeptidases, suggesting an activation mechanism; however, no activity was detectable using standard carboxypeptidase substrates. In order to determine the function of Ecm14 using an unbiased screen, we undertook a synthetic lethal assay. Upon screening approximately 27,000 yeast colonies, twenty-two putative synthetic lethal clones were identified. Further analysis showed many to be synthetic lethal with auxotrophic marker genes and requiring multiple mutations, suggesting that there are few, if any, single S. cerevisiae genes that present synthetic lethal interactions with ecm14Δ. Conclusions. We show in this study that Ecm14, although lacking detectable enzyme activity, is a conserved carboxypeptidase-like protein that is secreted from cells and is processed to a mature form by the action of an endopeptidase. Our study and datasets from other recent large-scale screens suggest a role for Ecm14 in processes such as vesicle-mediated transport and aggregate invasion, a fungal process that has been selected against in modern laboratory strains of S. cerevisiae.


2020 ◽  
Author(s):  
Damianos P. Melidis ◽  
Brandon Malone ◽  
Wolfgang Nejdl

Abstract Background: Word embedding approaches have revolutionized natural language processing (NLP) research. These approaches aim to map words to a low-dimensional vector space, in which words with similar linguistic features cluster together. Embedding-based methods have also been developed for proteins, where words are amino acids and sentences are proteins. The learned embeddings have been evaluated qualitatively, via visual inspection of the embedding space and extrinsically, via performance comparison on downstream protein prediction tasks. However, these sequence embeddings have the caveat that biological metadata do not exist for each amino acid, in order to measure the quality of each unique learned embedding vector. Results: Here, we present dom2vec, an approach for learning protein domain embeddings using word2vec on InterPro annotations. In contrast to sequence embeddings, biological metadata do exist for protein domains, related to each domain separately. Therefore, we present four intrinsic evaluation strategies to quantitatively assess the quality of the learned embedding space. To perform a reliable evaluation in terms of biology knowledge, we selected the metadata related to the most distinctive biological characteristics of domains. These are the structure, enzymatic and molecular function of a given domain. Notably, dom2vec obtains adequate level of performance in the intrinsic assessment, therefore we can draw an analogy between the local linguistic features in natural languages and the domain structure and function information in domain architectures. Moreover, we demonstrate the dom2vec applicability on protein prediction tasks, by comparing it with state-of-the-art sequence embeddings in three downstream tasks. We show that dom2vec outperform sequence embeddings for toxin and enzymatic function prediction and is comparable with sequence embeddings in cellular location prediction. Conclusions: We report that the application of word2vec on InterPro annotations produces domain embeddings with two significant advantages over sequence embeddings. First, each unique dom2vec vector can be quantitatively evaluated towards its available structure and function metadata. Second, the produced embeddings can outperform the sequence embeddings for a subset of downstream tasks. Overall, dom2vec embeddings are able to capture the most important biological properties of domains and surpass sequence embeddings for a subset of prediction tasks.


2011 ◽  
Vol 28 (3) ◽  
pp. 407-422 ◽  
Author(s):  
Alok K. Sharma ◽  
Alan C. Rigby ◽  
Seth L. Alper

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