Despite years of effort to clarify the structural basis of insulin receptor binding no clear consensus has emerged. It is generally believed that insulin receptor binding is accompanied by some degree of conformational change in the carboxy-terminal of the insulin B-chain. In particular, while most substitutions for PheB24 lead to inactive species, glycine or D-amino acids are well tolerated in this position. Here we assess the conformation change by solving the solution structure of the biologically active (GluB16, GlyB24, desB30)-insulin mutant. The structure in aqueous solution at pH 8 reveals a subtle, albeit well-defined rearrangement of the C-terminal decapeptide involving a perturbation of the B20-23 turn, which allows the PheB25 residue to occupy the position normally taken up by PheB24 in native insulin. The new protein surface exposed rationalizes the receptor binding properties of a series of insulin analogs. We suggest that the structural switch is forced by the structure of the underlying core of species invariant residues and that an analogous rearrangement of the C-terminal of the B-chain occurs in native insulin on binding to its receptor.
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http://dx.doi.org/10.1006/jmbi.1998.1801 | DOI Listing |
Proc Natl Acad Sci U S A
February 2025
Department of Biological Sciences, College of Liberal Arts and Sciences, Wayne State University, Detroit, MI 48202.
The mammalian Hippo kinases, MST1 and MST2, regulate organ development and suppress tumor formation by balancing cell proliferation and death. In macrophages, inflammasomes detect molecular patterns from invading pathogens or damaged host cells and trigger programmed cell death. In addition to lytic pyroptosis, the signatures associated with apoptosis are induced by inflammasome activation, but how the inflammasomes coordinate different cell death processes remains unclear.
View Article and Find Full Text PDFPLoS Pathog
January 2025
Department of Clinical Microbiology, Umeå University, Umeå, Sweden.
Human adenovirus type 36 (HAdV-D36) has been putatively linked to obesity in animals and has been associated with obesity in humans in some but not all studies. Despite extensive epidemiological research there is limited information about its receptor profile. We investigated the receptor portfolio of HAdV-D36 using a combined structural biology and virology approach.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Pathology, 906 Hospital of Joint Logistic Support Force of PLA, Ningbo, Zhejiang, China.
Objective: To investigate the effects and mechanisms of miRNA 221 on myocardial ischemia/reperfusion injury (MIRI) in mice through the regulation of phospholamban (PLB) expression.
Methods: The MIRI mouse model was created and mice were divided into sham, MIRI, MIRI+ 221, and MIRI+ scr groups, with miRNA 221 overexpression induced in the myocardium of MIRI mice by targeted myocardial injection. Quantitative RT-PCR analysis was performed to observe the variation in miRNA 221, PLB, SERCA2, RYR2, NCX1, Cyt C and caspase 3 mRNA levels in myocardium, while Western blot assessed the levels of PLB, p-PLB (Ser16), p-PLB (Thr17), SERCA2, RYR2, NCX1, Cyt C and caspase 3 proteins.
Brief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
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