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Top–down proteomics (TDP) identifies, quantifies, and characterises proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analysing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High‐resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterise low abundance intact proteoforms in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis‐based separation approaches have been developed and applied in TDP to analyse complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarised current applications, and discussed the gaps that may be addressed in the future. [ABSTRACT FROM AUTHOR]

BACKGROUND: The traditional screening method for umami peptide, extracted from porcine bone, was labor‐intensive and time‐consuming. In this study, the rapid screening method and molecular mechanism of umami peptide was investigated. RESULTS: This article showed that a more precisely rapid screening method with composite machine learning and molecular docking was used to screen the potential umami peptide from porcine bone. As reference, 24 reported umami peptides were predicated by composite machine learning, with the accuracy of 86.7%. In this study, potential umami peptide sequences from porcine bone were screened by UMPred‐FRL, Umami‐MRNN Demo, and molecular docking was used to provide further screening. Finally, nine peptides were screened and verified as umami peptides by this method: LREY, HEAL, LAKVH, FQKVVA, HVKELE, AEVKKAP, EAVEKPQS, KALSEEL and KKMFETES. The hydrogen bonding was deemed to be the main interaction force with receptor T1R3, and domain binding sites were Ser146, His121 and Glu277. The result demonstrated the feasibility of machine learning assisted T1R1/T1R3 receptor for rapid screening umami peptides. The screening method would not only adapt to screen umami peptides from porcine bone but possibly applied for other sources. It also provided a reference for rapid screening of umami peptides. CONCLUSION: The manuscript lays a rapid screening method in screening umami peptide, and nine umami peptides from porcine bone were screened and identified. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Top‐down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top‐down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front‐end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top‐down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top‐down proteomics. We comprehensively discuss the evolution of front‐end workflows that today facilitate optimal characterization of proteoform‐driven biology, including a brief description of the clinical applications that have motivated these impactful contributions. [ABSTRACT FROM AUTHOR]

A new stability indicating reverse phase HPLC method has been developed and validated as per International Conference on Harmonization guidelines for the determination of sacubitril‐valsartan premix stereoisomers, namely, (2R)‐valsartan, (2S,4S)‐sacubitril, (2R,4S)‐sacubitril, and (2R,4R)‐sacubitril. Primarily, stability indicating separation study was done on reverse phase LC conditions; it was described by peak homogeneity of sacubitril–valsartan and its stereoisomers. Cellulose tris(4‐methylbenzoate) packing column Chiralcel OJ‐RH(150 mm × 4.6 mm), 5 μm provided better resolution than those of amylose based stationary phase's. Resolution between two arbitrary adjacent analyte was found to be more than 2.0 with 0.1% trifluoroacetic acid in water as mobile phase‐A and mobile phase‐B consisting of acetonitrile, methanol, and trifluoroacetic acid (90:10:0.1, v/v/v). Gradient elution was performed at a flow rate of 1.0 ml/min, column temperature 20°C, injection volume 10 μl, UV detection at 254 nm and run time was 52 min. The detector response linearity of stereoisomers found to be linear (R2 ≥ 0.9998), limit of detection (0.290 μg/ml, 0.122 μg/ml, 0.123 μg/ml, and 0.124 μg/ml), and limit of quantification (0.878 μg/ml, 0.370 μg/ml, 0.373 μg/ml, and 0.375 μg/ml), respectively. Percentage recovery was found to be 98–105. Finally, the proposed method is user friendly and can be used in bulk drugs analysis. [ABSTRACT FROM AUTHOR]