Chaperones are a diverse class of ubiquitous proteins that assist other cellular proteins in folding correctly and maintaining their native structure. Many different chaperones cooperate to constitute the 'proteostasis' machinery in the cells. It has been proposed earlier that archaeal organisms could be ideal model systems for deciphering the basic functioning of the 'protein folding machinery' in higher eukaryotes. Several chaperone families have been characterized in archaea over the years but mostly one protein at a time, making it difficult to decipher the composition and mechanistics of the protein folding system as a whole. In order to deal with these lacunae, we have developed a database of all archaeal chaperone proteins, CrAgDb (Chaperone repertoire in Archaeal genomes). The data have been presented in a systematic way with intuitive browse and search facilities for easy retrieval of information. Access to these curated datasets should expedite large-scale analysis of archaeal chaperone networks and significantly advance our understanding of operation and regulation of the protein folding machinery in archaea. Researchers could then translate this knowledge to comprehend the more complex protein folding pathways in eukaryotic systems. The database is freely available at http://14.139.227.92/mkumar/cragdb/.
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http://dx.doi.org/10.1093/femsle/fnw030 | DOI Listing |
Mol Ther
January 2025
Department CIBIO, University of Trento, Via delle Regole 101, 38123 Trento, Italy. Electronic address:
Cystic Fibrosis (CF) is a life-shortening autosomal recessive disease caused by mutations in the CFTR gene, resulting in functional impairment of the encoded ion channel. F508del mutation, a trinucleotide deletion, is the most frequent cause of CF affecting approximately 80% of persons with cystic fibrosis (pwCFs). Even though current pharmacological treatments alleviate the F508del-CF disease symptoms there is no definitive cure.
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January 2025
A.N. Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, 119991 Moscow, Russia.
Apurinic/apyrimidinic (AP) sites are endogenous DNA lesions widespread in human cells. Having no nucleobases, they are noncoding and promutagenic. AP site repair is generally initiated through strand incision by AP endonuclease 1 (APE1).
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Anatomy, Animal Physiology and Biophysics, Faculty of Biology, University of Bucharest, 91-95 Splaiul Independenței Str., 050095 Bucharest, Romania.
Glycosylation is a critical post-translational modification that influences protein folding, stability and function. While extensively studied in extracellular and intracellular regions, glycosylation within transmembrane (TM) regions and at membrane interfaces remains poorly understood. This study aimed to map O- and N-glycosylation sites in these regions using a comprehensive database search and structural validation where possible.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Department of Biomedical Sciences, College of Medicine, Korea University, Seoul 02841, Republic of Korea.
The protein therapeutics market, including antibody and fusion proteins, has experienced steady growth over the past decade, underscoring the importance of optimizing amino acid sequences. In our previous study, we developed a fusion protein, R31, which combines retinol-binding protein (RBP) with albumin domains IIIA and IB, linked by a sequence (AAAA), and includes an additional disulfide bond (N227C-V254C) in IIIA. This fusion protein effectively inhibited hepatic stellate cell activation.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
School of Computer Science, University College Dublin (UCD), D04 V1W8 Dublin, Ireland.
Accurately predicting protein secondary structure (PSSP) is crucial for understanding protein function, which is foundational to advancements in drug development, disease treatment, and biotechnology. Researchers gain critical insights into protein folding and function within cells by predicting protein secondary structures. The advent of deep learning models, capable of processing complex sequence data and identifying meaningful patterns, offer substantial potential to enhance the accuracy and efficiency of protein structure predictions.
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