Unveiling the peptidases of parasites from the office chair - The endothelin-converting enzyme case study
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, přehledy
PubMed
39448189
DOI
10.1016/bs.apar.2024.05.003
PII: S0065-308X(24)00032-0
Knihovny.cz E-zdroje
- Klíčová slova
- Bioinformatic tools, Biological databases, Computational analysis, Endothelin converting enzyme, High-throughput methodologies, Next-generation sequencing, Omics, Parasite, Parasitic peptidases, Peptidase, Schistosoma mansoni, ECE, metallopeptidase,
- MeSH
- endotelin konvertující enzymy genetika MeSH
- lidé MeSH
- proteasy genetika metabolismus MeSH
- proteomika MeSH
- Schistosoma mansoni enzymologie genetika MeSH
- výpočetní biologie * MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Názvy látek
- endotelin konvertující enzymy MeSH
- proteasy MeSH
The emergence of high-throughput methodologies such as next-generation sequencing and proteomics has necessitated significant advancements in biological databases and bioinformatic tools, therefore reshaping the landscape of research into parasitic peptidases. In this review we outline the development of these resources along the -omics technologies and their transformative impact on the field. Apart from extensive summary of general and specific databases and tools, we provide a general pipeline on how to use these resources effectively to identify candidate peptidases from these large datasets and how to gain as much information about them as possible without leaving the office chair. This pipeline is then applied in an illustrative case study on the endothelin-converting enzyme 1 homologue from Schistosoma mansoni and attempts to highlight the contemporary capabilities of bioinformatics. The case study demonstrate how such approach can aid to hypothesize enzyme functions and interactions through computational analysis alone effectively and emphasizes how such virtual investigations can guide and optimize subsequent wet lab experiments therefore potentially saving precious time and resources. Finally, by showing what can be achieved without traditional wet laboratory methods, this review provides a compelling narrative on the use of bioinformatics to bridge the gap between big data and practical research applications, highlighting the key role of these technologies in furthering our understanding of parasitic diseases.
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