Journal of proteins and proteomics最新文献

Cytochrome P450 1B1 (CYP1B1) plays a critical role in the pathogenesis of primary congenital glaucoma (PCG), a severe eye disorder that can lead to pediatric blindness if untreated. Increasing evidence suggests that intrinsically disordered proteins and regions (IDPs/IDPRs), which lack a stable three-dimensional structure, are significant in disease pathology due to their flexible nature, impacting protein interactions and function. This study explores the intrinsic disorder within CYP1B1 and its implications in the molecular mechanisms underlying PCG. We employed a comprehensive bioinformatics approach to assess the structural and functional properties of CYP1B1 using tools such as AlphaMissense, a tool crafted to evaluate the functional impact of missense mutations in proteins. Our structural analysis qualitatively demonstrated that CYP1B1 contains intrinsically disordered protein regions (i.e., spaghetti-like entities) that are structureless and flexible. Correlation analysis showed that disorder decreases exponentially relative to AlphaMissense predicted pathogenicity, with an exponential decay fit (R ² = 0.62), suggesting that highly disordered regions tend to harbor benign mutations. This study identifies critical intrinsically disordered regions within CYP1B1 and elucidates its complex interaction network, highlighting the potential role of these regions in PCG pathogenesis. The observed correlation between intrinsic disorder and reduced pathogenicity of mutations suggests that IDPRs may buffer against deleterious effects, providing a possible explanation for the variability in clinical outcomes associated with CYP1B1 mutations. These insights enhance our understanding of the molecular basis of PCG and offer potential targets for novel therapeutic interventions to combat this blinding childhood disorder.

Understanding protein-protein interactions (PPIs) is pivotal for deciphering the intricacies of biological processes. Dysregulation of PPIs underlies a spectrum of diseases, including cancer, neurodegenerative disorders, and autoimmune conditions, highlighting the imperative of investigating these interactions for therapeutic advancements. This review delves into the realm of mass spectrometry-based techniques for elucidating PPIs and their profound implications in biological research. Mass spectrometry in the PPI research field not only facilitates the evaluation of protein-protein interaction modulators but also discovers unclear molecular mechanisms and sheds light on both on- and off-target effects, thus aiding in drug development. Our discussion navigates through six pivotal techniques: affinity purification mass spectrometry (AP-MS), proximity labeling mass spectrometry (PL-MS), cross-linking mass spectrometry (XL-MS), size exclusion chromatography coupled with mass spectrometry (SEC-MS), limited proteolysis-coupled mass spectrometry (LiP-MS), and thermal proteome profiling (TPP).

Data-Independent Acquisition (DIA) LC-MS/MS is an attractive partner for co-immunoprecipitation (co-IP) and affinity proteomics in general. Reducing the variability of quantitation by DIA could increase the statistical contrast for detecting specific interactors versus what has been achieved in Data-Dependent Acquisition (DDA). By interrogating affinity proteomes featuring both DDA and DIA experiments, we sought to evaluate the spectral libraries, the missingness of protein quantity tables, and the CV of protein quantities in six studies representing three different instrument manufacturers. We examined four contemporary bioinformatics workflows for DIA: FragPipe, DIA-NN, Spectronaut, and MaxQuant. We determined that (1) identifying spectral libraries directly from DIA experiments works well enough that separate DDA experiments do not produce larger spectral libraries when given equivalent instrument time; (2) experiments involving mock pull-downs or IgG controls may feature such indistinct signals that contemporary software will struggle to quantify them; (3) measured CV values were well controlled by Spectronaut and DIA-NN (and FragPipe, which implements DIA-NN for the quantitation step); and (4) when FragPipe builds spectral libraries and quantifies proteins from DIA experiments rather than performing both operations in DDA experiments, the DIA route results in a larger number of proteins quantified without missing values as well as lower CV for measured protein quantities.

Supplementary information: The online version contains supplementary material available at 10.1007/s42485-024-00166-4.