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The fates of nanomaterials (NMs) in vivo are greatly dependent on their interactions with human serum proteins. However, the interfacial molecular details of NMs-serum proteins are still difficult to be probed. Herein, the molecular interaction details of human serum albumin (HSA) with Au and SiO

Photosystem II (PSII), as a multiple-subunit chloroplast membrane-associated pigment-protein complex on the thylakoid membrane, is a primary target of light-induced photodamage. However, the overal...

Bacteria swim using a flagellar motor that is powered by stator units. Vibrio spp. are highly motile bacteria responsible for various human diseases, the polar flagella of which are exclusively driven by sodium-dependent stator units (PomAB). However, how ion selectivity is attained, how ion transport triggers the directional rotation of the stator unit, and how the stator unit is incorporated into the motor remain largely unclear. Here we have determined by cryo-electron microscopy the structure of Vibrio PomAB. The electrostatic potential map uncovers sodium binding sites, which together with functional experiments and molecular dynamics simulations, reveal a mechanism for ion translocation and selectivity. Bulky hydrophobic residues from PomA, prime PomA for clockwise rotation. We propose a dynamic helical motif in PomA regulates the distance between PomA subunit cytoplasmic domains, stator unit activation, and torque transmission. Together, our studies provide mechanistic insights for understanding stator unit ion selectivity and motor incorporation.

Qingyi decoction (QYD) has anti-inflammatory pharmacological properties and substantial therapeutic benefits on severe acute pancreatitis (SAP) in clinical practice. However, its protective mechanism against SAP-associated acute lung injury (ALI) remains unclear. In this study, we screened the active ingredients of QYD from the perspective of network pharmacology to identify its core targets and signaling pathways against SAP-associated ALI. Rescue experiments were used to determine the relationship between QYD and ferroptosis. Then, metabolomics and 16s rDNA sequencing were used to identify differential metabolites and microbes in lung tissue. Correlation analysis was utilized to explore the relationship between core targets, signaling pathways, metabolic phenotypes, and microbial flora, sorting out the potential molecular network of QYD against SAP-associated lung ALI. Inflammatory damage was caused by SAP in the rat lung. QYD could effectively alleviate lung injury, improve respiratory function, and significantly reduce serum inflammatory factor levels in SAP rats. Network pharmacology and molecular docking identified three key targets: ALDH2, AnxA1, and ICAM-1. Mechanistically, QYD may inhibit ferroptosis by promoting the ALDH2 expression and suppress neutrophil infiltration by blocking the cleavage of intact AnxA1 and downregulating ICAM-1 expression. Ferroptosis activator counteracts the pulmonary protective effect of QYD in SAP rats. In addition, seven significant differential metabolites were identified in lung tissues. QYD relatively improved the lung microbiome’s abundance in SAP rats. Further correlation analysis determined the correlation between ferroptosis, differential metabolites, and differential microbes. In this work, the network pharmacology, metabolomics, and 16s rDNA sequencing were integrated to uncover the mechanism of QYD against SAP-associated ALI. This novel integrated method may play an important role in future research on traditional Chinese medicine.

Ultraviolet (UV) laser photolysis of hydrogen peroxide (H

Human serum albumin (HSA) is one of the most important serum carrier proteins that deliver small-molecule drugs to their specific targets. Clarifying the molecular mechanism of the interaction between natural HSA and drugs in an aqueous solution has been a hot topic in pharmaceutical chemistry, clinical medicine, and biochemistry in recent years, but it is still challenging. In this paper, the details of molecular interactions of HSA with a variety of therapeutic drugs including ibuprofen, indomethacin, phenylbutazone, and warfarin are systematically investigated using a mass spectrometry (MS)-based lysine reactivity profiling (LRP) strategy. The results reaffirm that the major ligand binding sites (including Sites I and II) of HSA are located in subdomains IIA and IIIA, while several potential drug-binding areas at subdomain IIIB and α helix IIB-IIIA are newly characterized. The MS-LRP strategy may have important application prospects in pharmacodynamics, pharmacokinetics, and safety evaluation of small-molecule drugs.

Bacteria swim using a flagellar motor that is powered by stator units. These stator units are energized by an ionic gradient across the membrane, typically proton or sodium. The presumed monodirectional rotation of the stator units allows the bidirectional rotation of the flagellar motor. However, how ion selectivity is attained, how ion transport triggers the directional rotation of the stator unit, and how the stator unit is incorporated into the motor remain largely unclear. Here we have determined by cryo-electron microscopy the structure of the Na+-driven type stator unit PomAB from the gram-negative bacteriumVibrio alginolyticusin both lipidic and detergent environments, at a resolution up to 2.5 Å. The structure is in a plugged, auto-inhibited state consisting of five PomA subunits surrounding two PomB subunits. The electrostatic potential map uncovers sodium ion binding sites within the transmembrane domain, which together with functional experiments and explicit solvent molecular dynamics simulations, suggest a mechanism for ion translocation and selectivity. Resolved conformational isomers of bulky hydrophobic residues from PomA, in the vicinity of key determinant residues for sodium ion coupling of PomB, prime PomA for clockwise rotation. The rotation is tightly blocked by the trans-mode organization of the PomB plug motifs. The structure also reveals a conformationally dynamic helical motif at the C-terminus of PomA, which we propose regulates the distance between PomA subunit cytoplasmic domains and is involved in stator unit-rotor interaction, concomitant stator unit activation, and torque transmission. Together, our studies provide mechanistic insight for understanding flagellar stator unit ion selectivity and incorporation of the stator units into the motor.

N-Methyl-D-Aspartate (NMDA) receptors are essential for many brain functions. These receptors are heterotetramers typically comprising two GluN1 subunits and two GluN2 subunits. The latter could alternate among four subtypes (N2A-N2D) and determine the functional diversity of NMDA receptors1, 2. For example, receptors containing N2C or N2D exhibit 50-fold lower channel open probability (Po) than those containing N2A (ref.3–5). Structures of N2A- and N2B-containing receptors have been extensively characterized, providing molecular basis for understanding NMDA receptor function6–14. Here we report the cryo-EM structures of N1-N2D and N1-N2C di-heterotetramers (di-receptors), and N1-N2A-N2C tri-heterotetramer (tri-receptor) at a resolution up to 3.0 Å. Structural analysis showed that the bilobate N-terminal domain (NTD) in N2D adopted an intrinsic closed conformation, leading to a compact NTD tetramer in N1-N2D receptor. Functional studies further demonstrated that, in di-receptors containing N2D but not N2A or N2B, crosslinking NTD at the tetrameric interface had no effect on channel activity, while crosslinking ligand-binding domain (LBD) of two N1 protomers significantly elevated Po. Surprisingly, we found that the N1-N2C di-receptors spontaneously oscillated between symmetric and asymmetric conformation. The later one occupied a predominant population, whereby two N2C protomers exhibited distinct conformation. This asymmetry, which was also found to a lesser extent in N1-N2A di-receptor10, was further locked by the binding of an N2C-specific allosteric potentiator PYD-106 to a unique binding pocket between NTD and LBD in only one N2C protomer. Finally, N2A and N2C in the N1-N2A-N2C tri-receptor displayed the conformation close to that found in one protomer of N1-N2A and N1-N2C di-receptors, respectively. These findings provide a comprehensive structural understanding of diverse functional properties of major NMDA receptor subtypes.

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Background Amyotrophic lateral sclerosis (ALS) is an irreversible fatal neurodegenerative disease with progressive paralysis of limbs and bulb in patients, the cause of which remains unclear. Due to the highly heterogeneous and complex pathophysiology of the disease, there is currently no effective treatment to retard the disease progression. Accumulating studies suggest that motor neuron degeneration is associated with systemic metabolic impairment in ALS. However, the metabolic reprogramming and underlying mechanism in the longitudinal progression of the disease remain poorly understood. Methods Here, we applied unbiased LC-MS-based metabolomics to plasma, lumbar spinal cord, and motor cortex tissues from SOD1G93A mice and wildtype (WT) littermates at different stages to explore the metabolic disturbance during disease progression. To elucidate the regulatory network underlying metabolic changes, spinal cords from SOD1G93A and WT mice in the symptomatic stage were further analyzed by proteomics. Results The results show that SOD1G93A mice presented marked dysregulations of lipid and purine metabolism in both plasma and spinal cord from the pre-symptomatic stage. Furthermore, the metabolic abnormalities were much more pronounced in the symptomatic stage. By integrating metabolomics and proteomics data, we demonstrated the importance of metabolic pathways in the tricarboxylic acid (TCA) cycle, arginine and proline metabolism, and fatty acid degradation in the progression of ALS pathophysiology. Conclusions Notably, for the first time, we highlighted that metabolic dysregulation in purine metabolism might be a critical event in the preclinical phase of ALS. The identified differential metabolites and proteins in our study complement existing data on metabolic reprogramming in ALS; the results from the integrative analysis might provide novel perspectives for early diagnosis and therapeutic intervention of the disease.

Identification of the tyrosine phosphorylation (pY)-dependent interactome of immune co-receptors is crucial for understanding signal pathways involved in immunotherapy. However, identifying the motif-specific interactome for each pY commonly found on these multi-phosphorylated membrane proteins remains challenging. Here, we describe a photoaffinity-based chemical proteomic approach to dissect the motif-specific cytoplasmic interactomes of the critical immune co-receptor CD28. Various full-length CD28 cytoplasmic tails (CD28cyto) with defined pY and selectively replaced photo-methionine were synthesized and applied to explore three pY-motif-dependent CD28cyto interactomes. We identified a stand-alone interaction of phospholipase PLCG1 with the Y191 motif with enhanced affinity for the sequence neighboring the transmembrane domain. Importantly, taking advantage of native top-down mass spectrometry with a 193-nm laser, we discovered the direct association of a previously undefined pY218 motif with the kinase PKCθ through its C2 domain. This synthetic CD28cyto-based photoaffinity proteomic approach is generically applicable to the study of other immune co-receptors with multiple pY sites on their linear cytoplasmic tail.

Graphical abstract, Fully inactivating SARS-CoV-2, the virus causing coronavirus disease 2019, is of key importance for interrupting virus transmission but is currently performed by using biologically or environmentally hazardous disinfectants. Herein, we report an eco-friendly and efficient electrochemical strategy for inactivating the SARS-CoV-2 using in-situ formed nickel oxide hydroxide as anode catalyst and sodium carbonate as electrolyte. At a voltage of 5 V, the SARS-CoV-2 viruses can be rapidly inactivated with disinfection efficiency reaching 95% in only 30 s and 99.99% in 5 min. Mass spectrometry analysis and theoretical calculations indicate that the reactive oxygen species generated on the anode can oxidize the peptide chains and induce cleavage of the peptide backbone of the receptor binding domain of the SARS-CoV-2 spike glycoprotein, and thereby disables the virus. This strategy provides a sustainable and highly efficient approach for the disinfection of the SARS-CoV-2 viruliferous aerosols and wastewater.

Probing the conformational and functional hotspot sites within aqueous native protein complexes is still a challenging task. Herein, a mass spectrometry (MS)-based two-step isotope labeling-lysine reactivity profiling (TILLRP) strategy is developed to quantify the reactivities of lysine residues and probe the molecular details of protein–protein interactions as well as evaluate the conformational interventions by small-molecule active compounds. The hotspot lysine sites that are crucial to the SARS-CoV-2 S1–ACE2 combination could be successfully probed, such as S1 Lys417 and Lys444. Significant alteration of the reactivities of lysine residues at the interaction interface of S1-RBD Lys386–Lys462 was observed during the formation of complexes, which might be utilized as indicators for investigating the S1-ACE2 dynamic recognition and intervention at the molecular level in high throughput., A mass spectrometry-based two-step isotope labeling-lysine reactivity profiling strategy is developed to probe the molecular details of protein–protein interactions and evaluate the conformational interventions by small-molecule active compounds.

Micro/nanoplastics (MNPs) are widespread environmental pollutants that cause high health risks. However, high heterogeneity in particle sizes and chemical compositions of MNPs make their accurate characterization extremely challenging. Herein, we established a matrix-assisted laser desorption ionization-Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR MS) strategy for the unambiguous characterization of different types of MNPs with high performance, including polystyrene, polyethylene glycol terephthalate, polyamide, polymethyl methacrylate, acrylonitrile butadiene styrene copolymer, and polycarbonate. The MNP sample preparation and detection conditions were systematically optimized by using response surface methodology, and the MS detection signal-to-noise ratios were improved 1.5 times on average. The ultrahigh mass resolution of FTICR MS is crucial to the unambiguous elucidation of MNP structures. We demonstrate that this MS strategy is highly efficient in the characterization of polymer constitutions of environmental MNPs derived from foam, bottles, cable ties, and compact discs, providing a promising tool for MNP detection and safety evaluation.

Therapeutics targeting virus-host interactions have been considered promising strategies for treating herpesvirus infection. Our previous study on avian infectious laryngotracheitis virus (ILTV), an avian herpesvirus economically important to the poultry industry worldwide, identified the small molecule Pifithrin-α (PFT-α) as a potential therapeutic agent. However, the underlying mechanisms of its antiviral function remain largely unknown. Using the ILTV-permissive chicken cell line LMH as the model, we found that PFT-α effectively suppressed the transcription and genome replication of ILTV and greatly reduced the level of infectious virions. Genome-wide transcriptome analysis revealed extensive repression of the metabolic processes of infected cells by PFT-α administration. Further metabolome assays of ILTV-infected cells using liquid chromatography coupled with mass spectrometry suggest host nucleotide metabolism and ATP synthesis as the key targets of PFT-α treatment during its repression of ILTV replication, which was experimentally supported by the reduced transcription of many key enzymes essential to nucleotide metabolism and ATP synthesis. The present study provides insights into the mechanisms by which PFT-α inhibits ILTV infection, which may increase the probability of successful clinical application of this molecule.

Monitoring the dynamic alterations of protein structures within an aqueous solution remains enormously challenging. In this study, we describe a size-selective VAILase proteolysis (SVP)-mass spectrometry (MS) strategy to probe the protein structure changes without strict control of the proteolysis kinetics. The unique conformation selectivity of SVP depends on the uniform nano-sized entrance pores of the VAILase hexameric cage as well as the six inherent molecular rulers in the VAILase-substrate recognition and cleavage. The dynamic insights into subtle conformation alterations of both myoglobin unfolding transition and Aurora kinase A-inhibitor binding are successfully captured using the SVP strategy, which matches well with the results in the molecular dynamics simulation. Our work provides a new paradigm of size-selective native proteolysis for exploring the aqueous protein structure-function relationships.

Human serum albumin (HSA) is one of the most important serum carrier proteins that deliver small-molecule drugs to their specific targets. Clarifying the molecular mechanism of the interaction between natural HSA and drugs in an aqueous solution has been a hot topic in pharmaceutical chemistry, clinical medicine, and biochemistry in recent years, but it is still challenging. In this paper, the details of molecular interactions of HSA with a variety of therapeutic drugs including ibuprofen, indomethacin, phenylbutazone, and warfarin are systematically investigated using a mass spectrometry (MS)-based lysine reactivity profiling (LRP) strategy. The results reaffirm that the major ligand binding sites (including Sites I and II) of HSA are located in subdomains IIA and IIIA, while several potential drug-binding areas at subdomain IIIB and α helix IIB-IIIA are newly characterized. The MS-LRP strategy may have important application prospects in pharmacodynamics, pharmacokinetics, and safety evaluation of small-molecule drugs.

Reductive methylation is a highly reactive and selective chemical labeling method and plays an important role in proteomic analysis. Various applications of reductive methylation have been developed and have substantially promoted the scope of proteomic analysis to date. Aside from a well-known method for introducing isotopes, this reaction could also be conducted under biological conditions and has little structural perturbations. In this paper, we reviewed the recent developments and applications of reductive methylation in quantitative proteomics and protein N-terminal profiling, along with the emerging applications in structural proteomics for monitoring protein structural/conformational changes under various conditions.

Although thousands of intact proteins have been feasibly identified in recent years, global quantification of intact proteins is still challenging. Herein, we develop a high-throughput strategy for global intact protein quantification based on chemical isotope labeling. The isotope incorporation efficiency is as high as 99.2% for complex intact protein samples extracted from HeLa cells. Further, the pTop 2.0 software is developed for automated quantification of intact proteoforms in a high-throughput manner. The high quantification accuracy and reproducibility of this strategy have been demonstrated for both standard and complex cellular protein samples. A total of 2283 intact proteoforms originated from 660 protein accessions are successfully quantified under anaerobic and aerobic conditions and the differentially expressed proteins are observed to be involved in the important biological processes such as stress response.

Since the control system in a permanent magnet synchronous motor (PMSM) has uncertainties and disturbances, the switching gain is a key factor in effecting chattering in sliding mode control. An ad...

Background Parkinson’s disease (PD) is a prevalent neurological disease in the elderly with increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis of PD is still compromised. Metabolomics defines the final readout of genome-environment interactions through the analysis of the entire metabolic profile in biological matrices. Recently, unbiased metabolic profiling of human sample has been initiated to identify novel PD metabolic biomarkers and dysfunctional metabolic pathways, however, it remains a challenge to define reliable biomarker(s) for clinical use. Methods We presented a comprehensive metabolic evaluation for identifying crucial metabolic disturbances in PD using liquid chromatography-high resolution mass spectrometry-based metabolomics approach. Plasma samples from 3 independent cohorts (n = 460, 223 PD, 169 healthy controls (HCs) and 68 PD-unrelated neurological disease controls) were collected for the characterization of metabolic changes resulted from PD, antiparkinsonian treatment and potential interferences of other diseases. Unbiased multivariate and univariate analyses were performed to determine the most promising metabolic signatures from all metabolomic datasets. Multiple linear regressions were applied to investigate the associations of metabolites with age, duration time and stage of PD. The combinational biomarker model established by binary logistic regression analysis was validated by 3 cohorts. Results A list of metabolites including amino acids, acylcarnitines, organic acids, steroids, amides, and lipids from human plasma of 3 cohorts were identified. Compared with HC, we observed significant reductions of fatty acids (FFAs) and caffeine metabolites, elevations of bile acids and microbiota-derived deleterious metabolites, and alterations in steroid hormones in drug-naïve PD. Additionally, we found that L-dopa treatment could affect plasma metabolome involved in phenylalanine and tyrosine metabolism and alleviate the elevations of bile acids in PD. Finally, a metabolite panel of 4 biomarker candidates, including FFA 10:0, FFA 12:0, indolelactic acid and phenylacetyl-glutamine was identified based on comprehensive discovery and validation workflow. This panel showed favorable discriminating power for PD. Conclusions This study may help improve our understanding of PD etiopathogenesis and facilitate target screening for therapeutic intervention. The metabolite panel identified in this study may provide novel approach for the clinical diagnosis of PD in the future.

Additional file 1: Table S1. Concentrations of the stable isotope labeled internal standards in methanol. Table S2. Statistical results of FFAs in blank and analytical samples. Table S3. Statistical results of differential metabolites between male and female in HC group. Table S4. Differential metabolites accountable for the discrimination between drug-naïve PD patients and controls. Table S5. Associations between the differential metabolites and disease severity. Table S6. Associations between the differential metabolites and duration time. Table S7. Associations between the differential metabolites and age. Table S8. Statistical results of differential metabolites in PD compared with both HC and NDC groups in cohort 3. Table S9. Statistical results of the six selected differential metabolites in treated-epilepsy patients and HC. Table S10. Parameters of the binary logistic regression model in cohort 1. Table S11. Parameters of the binary logistic regression model in cohort 2. Table S12. Parameters of the binary logistic regression model in cohort 3 (PD vs. HC + NDC). Table S13. Parameters of the binary logistic regression model in cohort 3 (PD vs. HC). Figure S1. Robust assessment of the analytical method across three independent cohorts. Figure S2. PCA analysis of the metabolic profiles in male and female of drug-naïve PD and HC. Figure S3. Permutation test (999 times) of the PLS-DA models. Figure S4. Pathway analysis of the differential metabolites in drug-naïve PD compared with HC. Figure S5. The ROC curves of the metabolite panel to discriminate PD from control groups across different cohorts based on the regression equation developed in cohort 1.

Supervised link prediction aims at finding missing links in a network by learning directly from the data suitable criteria for classifying link types into existent or non-existent. Recently, along this line, subgraph-based methods learning a function that maps subgraph patterns to link existence have witnessed great successes. However, these approaches still have drawbacks. First, the construction of the subgraph relies on an arbitrary nodes selection, often ineffective. Second, the inability of such approaches to evaluate adaptively nodes importance reduces flexibility in nodes features aggregation, an important step in subgraph classification. To address these issues, a novel graph-classification based link-prediction model is proposed: Attention and Re-weighting based subgraph Classification for Link prediction (ARCLink). ARCLink first extracts a subgraph around the two nodes whose link should be predicted, by network reweighting, i.e. attributing a weight in the range 0-1 to all links of the original network, and then learns a function to map the subgraph to a continuous vector for classification, thus revealing the nature (non-existence/existence) of the unknown link. For leaning the mapping function, ARCLink generates a vector representation of the extracted subgraph by hierarchically aggregating nodes features according to nodes importance. In contrast to previous studies that either fully ignore or use fixed schemes to compute nodes importance, ARCLink instead learns nodes importance adaptively by employing attention mechanism. Through extensive experiments, ARCLink was validated on a series of real-world networks against state-of-the-art link prediction methods, consistently demonstrating its superior performances.

Thermal processing is the most frequently adopted processing technology for sea cucumbers, which can significantly affect their protein composition. In this paper, three thermal processing methods high pressure steaming (HPS), atmospheric pressure boiling (APB), and atmospheric pressure steaming (APS) were adopted and protein compositions of both body walls and cooking liquors by thermal processing stichopus japonicus were systematically analysis by proteomic strategy. The total proteins loss rates of body walls were 11.6%, 13.0%, and 14.8% for HPS, APS, and APB methods, respectively. However, the main types of protein composition were retained. Similar mechanisms of protein loss may exist even if different thermal processing were applied. The most frequent hydrolysis sites in thermal processing were phenylalanine, leucine, asparagine, and tyrosine at both C and N terminals. This study provides theoretical guidance for optimizing the industry thermal processing of sea cucumbers.

Further improving the proteomic identification coverage and reliability is still challenging in the mass spectrometry (MS)-based proteomics. Herein, we combine VAILase and trypsin digestion with 193-nm ultraviolet photodissociation (UVPD) and higher-energy collision dissociation (HCD) to improve the performance of bottom-up proteomics. As VAILase exhibits high complementarity to trypsin, the proteome sequence coverage is improved obviously whether with HCD or 193-nm UVPD. The high diversity of fragment ion types produced by UVPD contributes to the improvements of identification reliability for both trypsin- and VAILase-digested peptides with an average XCorr score improvement of 10%.

In this study, we construct a 193 nm ultraviolet laser dissociation high-resolution mass spectrometry (HRMS) platform to produce Pt

Acute lung injury (ALI) is the most common remote organ complication induced by severe acute pancreatitis (SAP). Almost 60-70% SAP-induced deaths are caused by ALI. Efficient clinical therapeutic strategy for SAP-induced ALI is still lacking. In this study, we demonstrate that Emodin (EMO) can significantly alleviate SAP-induced ALI. We investigate the therapeutic mechanisms of EMO by proteomic analysis, which indicates that EMO protects lung tissue against SAP-ALI by negative regulation of endopeptidase activity and inhibition of collagen-containing extracellular matrix degradation. Protein-protein interaction analysis showed Lamc2, Serpina1 and Serpinb1 play important roles in the above pathways. This study elucidates the possible mechanism and suggests the candidacy of EMO in the clinical treatment of SAP-ALI. SIGNIFICANCE: ALI is a major leading cause of death in SAP. DEX is the standard of care drug for treatment of SAP-ALI, but often associated with inevitable side effects. In the present study, EMO was demonstrated to greatly alleviate the lung injury induced by SAP. Through proteomic analysis, the recovered protein profiles in response to EMO treatment in SAP-ALI rat models was obtained, among which Lamc2, Serpina1 and Serpinb1 were discovered as crucial regulatory proteins in SAP-ALI disease. Our study provides the underlying mechanisms and novel targets of EMO protective effect against SAP-ALI.

Proteomics emerges from the protein identification to protein functional elucidation, which depends to a large extent on the characterization of protein sequences. However, a large part of proteome sequences remains unannotated due to the limitation in proteolytic digestion by golden standard protease trypsin. Herein, we demonstrated that a cyanobacterial protease VAILase could specifically cleave at the short-chain aliphatic amino acids valine, alanine, leucine, isoleucine and threonine with cleavage specificity about 92% in total for proteomic analysis. The unique features of VAILase cleavage facilitate the characterization of most proteins and exhibit high complementarity to trypsin, and 22% of the covered sequences by VAILase are unique. VAILase can greatly improve the coverages of sequences with abundant aliphatic residues that are usually dark regions in conventional proteomic analysis, such as the transmembrane regions within anion exchanger 1 and photosystem II.