B Cells Are the Dominant Antigen-Presenting Cells that Activate Naive CD4+ T Cells upon Immunization with a Virus-Derived Nanoparticle Antigen.

B cells can present antigens to CD4+ T cells, but it is thought that dendritic cells (DCs) are the primary initiators of naive CD4+ T cell responses. Nanoparticles, including virus-like particles (VLPs), are attractive candidates as carriers for vaccines and drug delivery. Using RNA phage Qß-derived VLP (Qß-VLP) as a model antigen, we found that antigen-specific B cells were the dominant antigen-presenting cells that initiated naive CD4+ T cell activation. B cells were sufficient to induce T follicular helper cell development in the absence of DCs. Qß-specific B cells promoted CD4+ T cell proliferation and differentiation via cognate interactions and through Toll-like receptor signaling-mediated cytokine production. Antigen-specific B cells were also involved in initiating CD4+ T cell responses during immunization with inactivated influenza virus. These findings have implications for the rational design of nanoparticles as vaccine candidates, particularly for therapeutic vaccines that aim to break immune tolerance.

Hepatocyte-specific Wtap deficiency promotes hepatocellular carcinoma by activating GRB2-ERK depending on downregulation of proteasome-related genes.

Wilm's tumor 1-associating protein (WTAP), a regulatory protein of the m6A methyltransferase complex, has been found to play a role in regulating various physiological and pathological processes. However, the in vivo role of WTAP in the pathogenesis of hepatocellular carcinoma (HCC) is unknown. In this study, we have elucidated the crucial role of WTAP in HCC progression and shown that hepatic deletion of Wtap promotes HCC pathogenesis through activation of multiple signaling pathways. A single dose of diethylnitrosamine injection causes more and larger HCCs in hepatocyte-specific Wtap knockout (Wtap-HKO) mice than Wtapflox/flox mice fed with either normal chow diet or a high-fat diet. Elevated CD36, IGFBP1 (insulin-like growth factor-binding protein 1), and chemokine (C-C motif) ligand 2 (CCL2) expression leads to steatosis and inflammation in the Wtap-HKO livers. The hepatocyte proliferation is dramatically increased in Wtap-HKO mice, which is due to higher activation of extracellular signal-regulated kinase (ERK) and signal transducer and activator of transcription-3 signaling pathways. Hepatic deletion of Wtap activates the ERK signaling pathway by increasing the protein stability of GRB2 and ERK1/2, which is due to the decreased expression of proteasome-related genes. Restoring PSMB4 or PSMB6 (two key components of the proteasome) leads to the downregulation of GRB2 and ERK1/2 in Wtap-HKO hepatocytes. Mechanistically, WTAP interacts with RNA polymerase II and H3K9ac to maintain expression of proteasome-related genes. These results demonstrate that hepatic deletion of Wtap promotes HCC progression through activating GRB2-ERK1/2-mediated signaling pathway depending on the downregulation of proteasome-related genes especially Psmb4 and Psmb6.

GCMSFormer: A Fully Automatic Method for the Resolution of Overlapping Peaks in Gas Chromatography-Mass Spectrometry.

Gas chromatography-mass spectrometry (GC-MS) is one of the most important instruments for analyzing volatile organic compounds. However, the complexity of real samples and the limitations of chromatographic separation capabilities lead to coeluting compounds without ideal separation. In this study, a Transformer-based automatic resolution method (GCMSFormer) is proposed to resolve mass spectra from GC-MS peaks in an end-to-end manner, predicting the mass spectra of components directly from the raw overlapping peaks data. Furthermore, orthogonal projection resolution (OPR) was integrated into GCMSFormer to resolve minor components. The GCMSFormer model was trained, validated, and tested using 100,000 augmented data. It achieves 99.88% of the bilingual evaluation understudy (BLEU) value on the test set, significantly higher than the 97.68% BLEU value of the baseline sequence-to-sequence model long short-term memory (LSTM). GCMSFormer was also compared with two nondeep learning resolution tools (MZmine and AMDIS) and two deep learning resolution tools (PARAFAC2 with DL and MSHub/GNPS) on a real plant essential oil GC-MS data set. Their resolution results were compared on evaluation metrics, including the number of compounds resolved, mass spectral match score, correlation coefficient, explained variance, and resolution speed. The results demonstrate that GCMSFormer has better resolution performance, higher automation, and faster resolution speed. In summary, GCMSFormer is an end-to-end, fast, fully automatic, and accurate method for analyzing GC-MS data of complex samples.

Characterization of a novel anti-PVRIG antibody with Fc-competent function that exerts strong antitumor effects via NK activation in preclinical models.

Poliovirus receptor-related immunoglobulin domain-containing protein, or PVRIG, is a newly discovered immune checkpoint that has emerged as a promising target for cancer immunotherapy. It is primarily expressed on activated T and natural killer (NK) cells, and once engaged with its ligand, PVRL2, it induces inhibitory signaling in T cells, thereby promoting the functional exhaustion of tumor-infiltrating lymphocytes (TILs). Here, we characterized IBI352g4a, a novel humanized anti-PVRIG antibody with Fc-competent function, explored the mechanism of its antitumor activity in preclinical models, and systemically evaluated the contribution of FcrR engagement to PVRIG blockade-induced antitumor activity. IBI352g4a binds to the extracellular domain of human PVRIG with high affinity (Kd = 0.53 nM) and specificity, and fully blocks the interaction between PVRIG and its ligand PVRL2. Unlike other immune checkpoints, IBI352g4a significantly induced NK cell activation and degranulation, but had a minimal effect on T-cell activation in in vitro functional assays. IBI352g4a induced strong antitumor effect in several preclinic models, through in vivo mechanism analysis we found that both NK and T cells contribute to the antitumor effect, but NK cells play predominant roles. Specifically, a single dose of IBI352g4a induced significant NK cell activation in TILs, but T-cell activation was observed only after the second dose. Moreover, the Fc effector function is critical for both NK cell activation and treatment efficacy in vitro and in vivo. Our study, for the first time, demonstrates that both NK activation and FcrR engagement are required for antitumor efficacy induced by PVRIG blockade.

A General Strategy toward Self-assembled Nanovaccine Based on Cationic Lentinan to Induce Potent Humoral and Cellular Immune Responses.

Adjuvants play a critical role in the induction of effective immune responses by vaccines. Here, a self-assembling nanovaccine platform that integrates adjuvant functions into the delivery vehicle is prepared. Cationic Lentinan (CLNT) is mixed with ovalbumin (OVA) to obtain a self-assembling nanovaccine (CLNTO nanovaccine), which induces the uptake and maturation of bone marrow dendritic cells (BMDCs) via the toll-like receptors 2/4 (TLR2/4) to produce effective antigen cross-presentation. CLNTO nanovaccines target lymph nodes (LNs) and induce a robust OVA-specific immune response via TLR and tumor necrosis factor (TNF) signaling pathways, retinoic acid-inducible gene I (RIG-I) receptor, and cytokine-cytokine receptor interactions. In addition, CLNTO nanovaccines are found that promote the activation of follicular helper T (Tfh) cells and induce the differentiation of germinal center (GC) B cells into memory B cells and plasma cells, thereby enhancing the immune response. Vaccination with CLNTO nanovaccine significantly inhibits the growth of ovalbumin (OVA)-expressing B16 melanoma cell (B16-OVA) tumors, indicating its great potential for cancer immunotherapy. Therefore, this study presents a simple, safe, and effective self-assembling nanovaccine that induces helper T cell 1 (Th1) and helper T cell (Th2) immune responses, making it an effective vaccine delivery system.

Alterations in leukocyte telomere length and mitochondrial DNA copy number in benzene poisoning patients.

OBJECTIVE: The aim of this study is to examine and evaluate the impact of benzene poisoning on the relative content of the mitochondrial MT-ND1 gene and telomere length in individuals with occupational chronic benzene poisoning (CBP) compared to a control group. The study will analyze and gather data on the mitochondrial gene content and telomere length in cases of benzene poisoning, and investigate the relationship with blood routine parameters in order to contribute scientific experimental data for the prevention and treatment of CBP. METHOD: The case group comprised 30 individuals diagnosed with occupational chronic benzene poisoning, whereas the control group consisted of 60 healthy individuals who underwent physical examinations at our hospital concurrently. Blood routine indicators were detected and analyzed, and the PCR method was employed to measure changes in mitochondrial MT-ND1 content and telomere length. Subsequently, a comparison and analysis of the aforementioned indicators was conducted. RESULT: The case group exhibited a higher mitochondrial gene content (median 366.2, IQR 90.0 rate) compared to the control group (median 101.5, IQR 12.0 rate), with a statistically significant difference between the two groups (P < 0.05). Additionally, the case group demonstrated lower white blood cell levels (3.78 ± 1.387 × 109/L) compared to the control group (5.74 ± 1.41 × 109/L), with a significant difference between the two groups (P < 0.05). Furthermore, the case group displayed lower red blood cell levels (3.86 ± 0.65 × 1012/L) compared to the control group (4.89 ± 0.65 × 1012/L), with a significant difference between the two groups (P < 0.05). The hemoglobin level in the case group (113.33 ± 16.34 g/L) was lower than that in the control group (138.22 ± 13.22 g/L). There was a significant difference between the two groups (P < 0.05). Platelet levels in the case group (153.80 ± 58.31 × 109/L) is smaller than the control group (244.92 ± 51.99 × 109/L), there was a significant difference between the two groups (P < 0.05). The average telomere length of the normal control group was 1.451 ± 0.475 (rate); The mean telomere length of individuals in the case group diagnosed with benzene poisoning was determined to be 1.237 ± 0.457 (rate). No significant correlation was observed between telomere length and three blood routine parameters, namely white blood cells (WBC), hemoglobin (HB), and platelets (PLT). However, a significant correlation was found between telomere length and red blood cell count (RBC). Additionally, a negative correlation was observed between mitochondrial gene content and white blood cell count (r = - 0.314, P = 0.026), as well as between mitochondrial gene content and red blood cell count (r = - 0.226, P = 0.032). Furthermore, a negative correlation was identified between mitochondrial gene content and hemoglobin (r = - 0.314, P = 0.028), and platelets (r = - 0.445, P = 0.001). CONCLUSION: Individuals diagnosed with occupational chronic benzene poisoning exhibit a reduction in telomere length and an elevation in the relative content of the mitochondrial MT-ND1 gene. Moreover, a negative correlation is observed between the content of the mitochondrial MT-ND1 gene and four blood routine parameters, namely white blood cells (WBC), red blood cells (RBC), hemoglobin (HB), and platelets (PLT). Consequently, benzene exposure may potentially contribute to the onset of premature aging.

Structural basis for DNMT3A-mediated de novo DNA methylation.

DNA methylation by de novo DNA methyltransferases 3A (DNMT3A) and 3B (DNMT3B) at cytosines is essential for genome regulation and development. Dysregulation of this process is implicated in various diseases, notably cancer. However, the mechanisms underlying DNMT3 substrate recognition and enzymatic specificity remain elusive. Here we report a 2.65-ångström crystal structure of the DNMT3A-DNMT3L-DNA complex in which two DNMT3A monomers simultaneously attack two cytosine-phosphate-guanine (CpG) dinucleotides, with the target sites separated by 14 base pairs within the same DNA duplex. The DNMT3A-DNA interaction involves a target recognition domain, a catalytic loop, and DNMT3A homodimeric interface. Arg836 of the target recognition domain makes crucial contacts with CpG, ensuring DNMT3A enzymatic preference towards CpG sites in cells. Haematological cancer-associated somatic mutations of the substrate-binding residues decrease DNMT3A activity, induce CpG hypomethylation, and promote transformation of haematopoietic cells. Together, our study reveals the mechanistic basis for DNMT3A-mediated DNA methylation and establishes its aetiological link to human disease.

Nicotinate-curcumin improves NASH by inhibiting the AKR1B10/ACCα-mediated triglyceride synthesis.

BACKGROUND: Nonalcoholic steatohepatitis (NASH) is a prevalent chronic liver condition. However, the potential therapeutic benefits and underlying mechanism of nicotinate-curcumin (NC) in the treatment of NASH remain uncertain. METHODS: A rat model of NASH induced by a high-fat and high-fructose diet was treated with nicotinate-curcumin (NC, 20, 40 mg·kg- 1), curcumin (Cur, 40 mg·kg- 1) and metformin (Met, 50 mg·kg- 1) for a duration of 4 weeks. The interaction between NASH, Cur and Aldo-Keto reductase family 1 member B10 (AKR1B10) was filter and analyzed using network pharmacology. The interaction of Cur, NC and AKR1B10 was analyzed using molecular docking techniques, and the binding energy of Cur and NC with AKR1B10 was compared. HepG2 cells were induced by Ox-LDL (25 µg·ml- 1, 24 h) in high glucose medium. NC (20µM, 40µM), Cur (40µM) Met (150µM) and epalrestat (Epa, 75µM) were administered individually. The activities of ALT, AST, ALP and the levels of LDL, HDL, TG, TC and FFA in serum were quantified using a chemiluminescence assay. Based on the changes in the above indicators, score according to NAS standards. The activities of Acetyl-CoA and Malonyl-CoA were measured using an ELISA assay. And the expression and cellular localization of AKR1B10 and Acetyl-CoA carboxylase (ACCα) in HepG2 cells were detected by Western blotting and immunofluorescence. RESULTS: The results of the animal experiments demonstrated that NASH rat model induced by a high-fat and high-fructose diet exhibited pronounced dysfunction in liver function and lipid metabolism. Additionally, there was a significant increase in serum levels of FFA and TG, as well as elevated expression of AKR1B10 and ACCα, and heightened activity of Acetyl-CoA and Malonyl-CoA in liver tissue. The administration of NC showed to enhance liver function in rats with NASH, leading to reductions in ALT, AST and ALP levels, and decrease in blood lipid and significant inhibition of FFA and TG synthesis in the liver. Network pharmacological analysis identified AKR1B10 and ACCα as potential targets for NASH treatment. Molecular docking studies revealed that both Cur and NC are capable of binding to AKR1B10, with NC exhibiting a stronger binding energy to AKR1B10. Western blot analysis demonstrated an upregulation in the expression of AKR1B10 and ACCα in the liver tissue of NASH rats, accompanied by elevated Acetyl-CoA and Malonyl-CoA activity, and increased levels of FFA and TG. The results of the HepG2 cell experiments induced by Ox-LDL suggest that NC significantly inhibited the expression and co-localization of AKR1B10 and ACCα, while also reduced levels of TC and LDL-C and increased level of HDL-C. These effects are accompanied by a decrease in the activities of ACCα and Malonyl-CoA, and levels of FFA and TG. Furthermore, the impact of NC appears to be more pronounced compared to Cur. CONCLUSION: NC could effectively treat NASH and improve liver function and lipid metabolism disorder. The mechanism of NC is related to the inhibition of AKR1B10/ACCα pathway and FFA/TG synthesis of liver.

Mechanism of Action of "Astragali Radix-Cassia Twig-Poria" in Chronic Heart Failure: A Network Pharmacology Approach.

This study utilizes network pharmacology analysis to investigate the components, targets, and pathways involved in the treatment of chronic heart failure (CHF) with the combination of "Astragali Radix-Cassia Twig-Poria." The TCMSP, GeneCards, OMIM, PharmGkb, TTD, and DrugBank databases were utilized to identify the active ingredients and targets of this combination for CHF. Protein interactions were derived from the STRING database, and Cytoscape was used to construct the "drug-component-target-disease" network and protein interactions network. The GO function and KEGG signaling pathway were enriched, and molecular docking was performed to verify the stability of the core components and their targets. The study identified 41 active ingredients, 101 targets (including 94 related to CHF), 9 core targets, and 26 core ingredients of "Astragali Radix-Cassia Twig-Poria." Additionally, 1444 GO entries and 140 KEGG pathways (including 36 related to CHF) were found. Molecular docking results confirmed the binding ability of the combination to core targets. Overall, this study provides valuable insights into the key components, targets, and pathways involved in the treatment of CHF with "Astragali Radix-Cassia Twig-Poria," contributing to further research on its pharmacological effects.

Plant-Derived Caffeic Acid and Its Derivatives: An Overview of Their NMR Data and Biosynthetic Pathways.

In recent years, caffeic acid and its derivatives have received increasing attention due to their obvious physiological activities and wide distribution in nature. In this paper, to clarify the status of research on plant-derived caffeic acid and its derivatives, nuclear magnetic resonance spectroscopy data and possible biosynthetic pathways of these compounds were collected from scientific databases (SciFinder, PubMed and China Knowledge). According to different types of substituents, 17 caffeic acid and its derivatives can be divided into the following classes: caffeoyl ester derivatives, caffeyltartaric acid, caffeic acid amide derivatives, caffeoyl shikimic acid, caffeoyl quinic acid, caffeoyl danshens and caffeoyl glycoside. Generalization of their 13C-NMR and 1H-NMR data revealed that acylation with caffeic acid to form esters involves acylation shifts, which increase the chemical shift values of the corresponding carbons and decrease the chemical shift values of the corresponding carbons of caffeoyl. Once the hydroxyl group is ester, the hydrogen signal connected to the same carbon shifts to the low field (1.1~1.6). The biosynthetic pathways were summarized, and it was found that caffeic acid and its derivatives are first synthesized in plants through the shikimic acid pathway, in which phenylalanine is deaminated to cinnamic acid and then transformed into caffeic acid and its derivatives. The purpose of this review is to provide a reference for further research on the rapid structural identification and biofabrication of caffeic acid and its derivatives.

Kinase Inhibition via Small Molecule-Induced Intramolecular Protein Cross-Linking.

Remarkable progress has been made in the development of cysteine-targeted covalent inhibitors. In kinase drug discovery, covalent inhibitors capable of targeting other nucleophilic residues (i.e. lysine, or K) have emerged in recent years. Besides a highly conserved catalytic lysine, almost all human protein kinases possess an equally conserved glutamate/aspartate (e.g. E/D) that forms a K-E/D salt bridge within the enzyme's active site. Electrophilic ynamides were previously used as effective peptide coupling reagents and to develop E/D-targeting covalent protein inhibitors/probes. In the present study, we report the first ynamide-based small-molecule inhibitors capable of inducing intramolecular cross-linking of various protein kinases, leading to subsequent irreversible inhibition of kinase activity. Our strategy took advantage of the close distance between the highly conserved catalytic K and E/D residues in a targeted kinase, thus providing a conceptually general approach to achieve irreversible kinase inhibition with high specificity and desirable cellular potency. Finally, this ynamide-facilitated, ligand-induced mechanism leading to intramolecular kinase cross-linking and inhibition was unequivocally established by using recombinant ABL kinase as a representative.

Global Reactivity Profiling of the Catalytic Lysine in Human Kinome for Covalent Inhibitor Development.

Advances in targeted covalent inhibitors (TCIs) have been made by using lysine-reactive chemistries. Few aminophiles possessing balanced reactivity/stability for the development of cell-active TCIs are however available. We report herein lysine-reactive activity-based probes (ABPs; 2-14) based on the chemistry of aryl fluorosulfates (ArOSO2 F) capable of global reactivity profiling of the catalytic lysine in human kinome from mammalian cells. We concurrently developed reversible covalent ABPs (15/16) by installing salicylaldehydes (SA) onto a promiscuous kinase-binding scaffold. The stability and amine reactivity of these probes exhibited a broad range of tunability. X-ray crystallography and mass spectrometry (MS) confirmed the successful covalent engagement between ArOSO2 F on 9 and the catalytic lysine of SRC kinase. Chemoproteomic studies enabled the profiling of >300 endogenous kinases, thus providing a global landscape of ligandable catalytic lysines of the kinome. By further introducing these aminophiles into VX-680 (a noncovalent inhibitor of AURKA kinase), we generated novel lysine-reactive TCIs that exhibited excellent in vitro potency and reasonable cellular activities with prolonged residence time. Our work serves as a general guide for the development of lysine-reactive ArOSO2 F-based TCIs.

BDH1 promotes lung cancer cell proliferation and metastases by PARP1-mediated autophagy.

Lymph node metastases and distant metastases were the important limiting factor for therapy of unresectable locally advanced (IIIB stage) and oligotransduction (IVa stage) lung cancer. This study was undertaken to identify a novel predictive biomarker for predicting lymph node metastases of lung cancer. A total of 364 patients with lung cancer which comprised of 198 patients with transcriptome sequencing data, 110 cases with immunohistochemistry data and 66 patients with serum samples were included to identify and validate the candidate gene. Autophagy was measured by western blots, immunofluorescence and electron microscope. We found that 3-hydroxybutyrate dehydrogenase 1 (BDH1) was associated with proliferation and metastases of lung cancer. BDH1 expression in both tissue and serum samples was associated with lung cancer metastases. Mechanical studies revealed that the AMPK-mTOR signalling pathway mediated by PARP1 played an important role in BDH1-induced autophagy. Activation of mTOR pathway markedly increased the effect of BDH1 in cell proliferation and metastases. These results were verified by the knockdown of PARP1. Furthermore, in vivo administration of BDH1 effectively promoted tumour growth in H460 xenografts mice. Our finding not only suggested that BDH1 might be useful as a novel biomarker and therapeutic target for lung cancer metastases, but also imply that PARP1-mediated AMPK-mTOR signalling pathway might play a critical role in BDH1-induced autophagy and lung cancer proliferation and metastases.

CapsNetYY1: identifying YY1-mediated chromatin loops based on a capsule network architecture.

BACKGROUND: Previous studies have identified that chromosome structure plays a very important role in gene control. The transcription factor Yin Yang 1 (YY1), a multifunctional DNA binding protein, could form a dimer to mediate chromatin loops and active enhancer-promoter interactions. The deletion of YY1 or point mutations at the YY1 binding sites significantly inhibit the enhancer-promoter interactions and affect gene expression. To date, only a few computational methods are available for identifying YY1-mediated chromatin loops. RESULTS: We proposed a novel model named CapsNetYY1, which was based on capsule network architecture to identify whether a pair of YY1 motifs can form a chromatin loop. Firstly, we encode the DNA sequence using one-hot encoding method. Secondly, multi-scale convolution layer is used to extract local features of the sequence, and bidirectional gated recurrent unit is used to learn the features across time steps. Finally, capsule networks (convolution capsule layer and digital capsule layer) used to extract higher level features and recognize YY1-mediated chromatin loops. Compared with DeepYY1, the only prediction for YY1-mediated chromatin loops, our model CapsNetYY1 achieved the better performance on the independent datasets (AUC [Formula: see text]). CONCLUSION: The results indicate that CapsNetYY1 is an excellent method for identifying YY1-mediated chromatin loops. We believe that the CapsNetYY1 method will be used for predictive classification of other DNA sequences.

Iodinene Nanosheet-to-Iodine Molecule Allotropic Transformation for Antibiosis.

Iodine, as a typical haloid element in group VIIA, has been extensively applied as antiseptics clinically, thanks to its effective and wide-spectrum antimicrobial activity against bacteria, fungi, and viruses. Nevertheless, current iodic sterilizing agents are still limited to topical applications such as instrument sterilization and treatments of skin or mucous membrane infection due to its unsatisfactory stability and biocompatibility. Here, we propose an emerging two-dimensional iodine nanomaterial (noted as iodinene) for the treatment of infection diseases in vivo. Iodinene nanosheets were fabricated by a facile and environmentally friendly approach via sonication-assisted liquid exfoliation, which present an intriguing layered structure and negligible toxicity. The as-synthesized iodinene would experience an in situ allotropic transformation spontaneously to release active HIO and I2 molecules by reacting with H2O2 in the infectious microenvironment. By the in situ production of active HIO and I2 molecules via allotropic transformation, iodinene presents enhanced antibacterial efficacy against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. In vivo outcome demonstrates the desirable antibacterial efficacy of iodinene in treating bacterial wound infection and pneumonia. This study thus offers an alternative to conventional sterilizing agents against hard-to-treat bacterial infections.

Simultaneous Covalent Modification of K-Ras(G12D) and K-Ras(G12C) with Tunable Oxirane Electrophiles.

Owing to their remarkable pharmaceutical properties compared to those of noncovalent inhibitors, the development of targeted covalent inhibitors (TCIs) has emerged as a powerful method for cancer treatment. The K-Ras mutant, which is prevalent in multiple cancers, has been confirmed to be a crucial drug target in the treatment of various malignancies. However, although the K-Ras(G12D) mutation is present in up to 33% of K-Ras mutations, no covalent inhibitors targeting K-Ras(G12D) have been developed to date. The relatively weak nucleophilicity of the acquired aspartic acid (12D) residue in K-Ras may be the reason for this. Herein, we present the first compound capable of covalently engaging both K-Ras(G12D) and K-Ras(G12C) mutants. Proteome profiling revealed that this compound effectively conjugates with G12C and G12D residues, modulating the protein functions in situ. These findings offer a unique pathway for the development of novel dual covalent inhibitors.

2-Ethynylbenzaldehyde-Based, Lysine-Targeting Irreversible Covalent Inhibitors for Protein Kinases and Nonkinases.

Lysine-targeting irreversible covalent inhibitors have attracted growing interests in recent years, especially in the fields of kinase research. Despite encouraging progress, few chemistries are available to develop inhibitors that are exclusively lysine-targeting, selective, and cell-active. We report herein a 2-ethynylbenzaldehyde (EBA)-based, lysine-targeting strategy to generate potent and selective small-molecule inhibitors of ABL kinase by selectively targeting the conserved catalytic lysine in the enzyme. We showed the resulting compounds were cell-active, capable of covalently engaging endogenous ABL kinase in K562 cells with long-residence time and few off-targets. We further validated the generality of this strategy by developing EBA-based irreversible inhibitors against EGFR (a kinase) and Mcl-1 (a nonkinase) that covalently reacted with the catalytic and noncatalytic lysine within each target.

A Universal and Accurate Method for Easily Identifying Components in Raman Spectroscopy Based on Deep Learning.

Raman spectroscopy has been widely used to provide the structural fingerprint for molecular identification. Due to interference from coexisting components, noise, baseline, and systematic differences between spectrometers, component identification with Raman spectra is challenging, especially for mixtures. In this study, a method entitled DeepRaman has been proposed to solve those problems by combining the comparison ability of a pseudo-Siamese neural network (pSNN) and the input-shape flexibility of spatial pyramid pooling (SPP). DeepRaman was trained, validated, and tested with 41,564 augmented Raman spectra from two databases (pharmaceutical material and S.T. Japan). It can achieve 96.29% accuracy, 98.40% true positive rate (TPR), and 94.36% true negative rate (TNR) on the test set. Another six data sets measured on different instruments were used to evaluate the performance of the proposed method from different aspects. DeepRaman can provide accurate identification results and significantly outperform the hit quality index (HQI) method and other deep learning models. In addition, it performs well in cases of different spectral complexity and low-content components. Once the model is established, it can be used directly on different data sets without retraining or transfer learning. Furthermore, it also obtains promising results for the analysis of surface-enhanced Raman spectroscopy (SERS) data sets and Raman imaging data sets. In summary, it is an accurate, universal, and ready-to-use method for component identification in various application scenarios.

Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefore, developing effective ROI evaluation algorithms is necessary to eliminate false positives meanwhile keep the false-negative rate as low as possible. In this study, a deep fused filter of ROIs (dffROI) was proposed to improve the accuracy of ROI extraction by combining the handcrafted evaluation metrics with convolutional neural network (CNN)-learned representations. To evaluate the performance of dffROI, dffROI was compared with peakonly (CNN-learned representation) and five handcrafted metrics on three LC-MS datasets and a gas chromatography-mass spectrometry (GC-MS) dataset. Results show that dffROI can achieve higher accuracy, better true-positive rate, and lower false-positive rate. Its accuracy, true-positive rate, and false-positive rate are 0.9841, 0.9869, and 0.0186 on the test set, respectively. The classification error rate of dffROI (1.59%) is significantly reduced compared with peakonly (2.73%). The model-agnostic feature importance demonstrates the necessity of fusing handcrafted evaluation metrics with the convolutional neural network representations. dffROI is an automatic, robust, and universal method for ROI filtering by virtue of information fusion and end-to-end learning. It is implemented in Python programming language and open-sourced at https://github.com/zhanghailiangcsu/dffROI under BSD License. Furthermore, it has been integrated into the KPIC2 framework previously proposed by our group to facilitate real metabolomic LC-MS dataset analysis.

Prediction of drug-likeness using graph convolutional attention network.

MOTIVATION: The drug-likeness has been widely used as a criterion to distinguish drug-like molecules from non-drugs. Developing reliable computational methods to predict the drug-likeness of compounds is crucial to triage unpromising molecules and accelerate the drug discovery process. RESULTS: In this study, a deep learning method was developed to predict the drug-likeness based on the graph convolutional attention network (D-GCAN) directly from molecular structures. Results showed that the D-GCAN model outperformed other state-of-the-art models for drug-likeness prediction. The combination of graph convolution and attention mechanism made an important contribution to the performance of the model. Specifically, the application of the attention mechanism improved accuracy by 4.0%. The utilization of graph convolution improved the accuracy by 6.1%. Results on the dataset beyond Lipinski's rule of five space and the non-US dataset showed that the model had good versatility. Then, the billion-scale GDB-13 database was used as a case study to screen SARS-CoV-2 3C-like protease inhibitors. Sixty-five drug candidates were screened out, most substructures of which are similar to these of existing oral drugs. Candidates screened from S-GDB13 have higher similarity to existing drugs and better molecular docking performance than those from the rest of GDB-13. The screening speed on S-GDB13 is significantly faster than screening directly on GDB-13. In general, D-GCAN is a promising tool to predict the drug-likeness for selecting potential candidates and accelerating drug discovery by excluding unpromising candidates and avoiding unnecessary biological and clinical testing. AVAILABILITY AND IMPLEMENTATION: The source code, model and tutorials are available at https://github.com/JinYSun/D-GCAN. The S-GDB13 database is available at https://doi.org/10.5281/zenodo.7054367. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.