Diverse actinomycetes produce a family of structurally and biosynthetically related non-ribosomal peptide compounds which belong to the chromodepsipeptide family. These compounds act as bisintercalators into the DNA helix. They give rise to antitumor, antiparasitic, antibacterial and antiviral bioactivities. These compounds show a high degree of conserved modularity (chromophores, number and type of amino acids). This modularity and their high sequence similarities at the genetic level imply a common biosynthetic origin for these pathways. Here, we describe insights about rules governing this modular biosynthesis, taking advantage of the fact that nowadays five of these gene clusters have been made public (thiocoraline, triostin, SW-163 and echinomycin/quinomycin). This modularity has potential application for designing and producing novel genetic engineered derivatives, as well as for developing new chemical synthesis strategies. These would facilitate their clinical development.
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http://dx.doi.org/10.3390/md12052668 | DOI Listing |
Arch Microbiol
January 2025
Department of Botany, CMS College Kottayam, Kottayam, Kerala, 686001, India.
Among all photosynthetic life forms, cyanobacteria exclusively possess a water-soluble, light-sensitive carotenoprotein complex known as orange carotenoid proteins (OCPs), crucial for their photoprotective mechanisms. These protein complexes exhibit both structural and functional modularity, with distinct C-terminal (CTD) and N-terminal domains (NTD) serving as light-responsive sensor and effector regions, respectively. The majority of cyanobacterial genomes contain genes for OCP homologs and related proteins, highlighting their essential role in survival of the organism over time.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, PR China.
The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturbation engineering (iCASE) strategy to construct hierarchical modular networks for enzymes of varying complexity. Molecular mechanism analysis elucidates that the peak of adaptive evolution is reached through a structural response mechanism among variants.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Bioengineering, California Institute of Technology, Pasadena, CA 91125.
The diversity and heterogeneity of biomarkers has made the development of general methods for single-step quantification of analytes difficult. For individual biomarkers, electrochemical methods that detect a conformational change in an affinity binder upon analyte binding have shown promise. However, because the conformational change must operate within a nanometer-scale working distance, an entirely new sensor, with a unique conformational change, must be developed for each analyte.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified.
View Article and Find Full Text PDFAnal Chim Acta
January 2025
Christian Doppler Laboratory for Innovative Gut Health Concepts of Livestock, Austria; BOKU University, Vienna, Dept. IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, Tulln, Austria.
Background: Untargeted metabolomics requires robust and reliable strategies for data processing to extract relevant information form the underlying raw data. Multiple platforms for data processing are available, but the choice of software tool can have an impact on the analysis. This study provides a comprehensive evaluation of four workflows based on commonly used metabolomics software tools: XCMS, Compound Discoverer, MS-DIAL, and MZmine.
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