SGNet: Sequence-Based Convolution and Ligand Graph Network for Protein Binding Affinity Prediction.

Protein-ligand binding can play an important role in many fields. It is of great importance to accurately predict the binding affinity between molecules by computational methods. Most computational binding affinity methods require molecular structures. However, there are still a large number of protein molecules with known amino acid sequences whose structures have not yet been solved. To address this issue, this paper proposes a sequence-based convolution and ligand graph network, called SGNet, to fuse the molecular graph information and the amino acid sequence information. This method integrates Conjoint Triad (CT) encoding of amino acid sequence and one-dimensional convolutional neural network module to extract protein molecules, develops graph attention network to extract molecular features of ligand, and then fuses the two feature sets to predict the binding affinity between molecules from the fully connected layer. As a result, SGNet achieves good prediction performance on both KIKD and IC50 data sets, with prediction error RMSEs of 1.287 and 1.58, and correlation Pearson Rs of 0.687 and 0.592, respectively. Comparative experimental results under the same conditions showed that SGNet outperformed Kdeep and GraphDTA in predicting binding affinities between protein-ligand molecules.

Osteocalcin inhibits myocyte aging through promotion of starvation-induced autophagy via IL-6/STAT3 signaling.

This study aimed to investigate the effects and mechanisms of osteocalcin on autophagy in myoblasts, as well as its possible therapeutic effects in aging muscle. Starved murine myoblast C2C12 cells with or without interleukin (IL)-6 siRNA were treated with osteocalcin. Expression of the autophagy protein marker LC3, as well as IL-6 and phosphorylated STAT3 were detected by immunoblotting, immunofluorescence, or immunohistochemistry. Autophagosomes were observed with transmission electron microscopy. Levels of reactive oxygen species (ROS) were detected by flow cytometry. Fasted young mice were injected intraperitoneally with osteocalcin, with or without the JAK inhibitor CP-690550 to inhibit IL-6 signaling. Older mice were treated with osteocalcin and muscle mass, grip strength and muscle structure were assessed. The results revealed that compared to control and serum-starved cells, osteocalcin treatment significantly increased the relative expression of LC3-II/LC3-I protein, the numbers of autophagosomes, and levels of intracellular ROS. Osteocalcin injection in mice also resulted in increased relative LC3-II/LC3-I protein expression and autophagosome numbers. Osteocalcin treatment significantly increased the secretion of IL-6 in muscle cells and tissue, and activated STAT3 signaling. Moreover, knockdown of IL-6 or blocking IL-6 signaling inhibited the phosphorylation of STAT3, and further inhibited autophagy in starved myoblasts and fasting-treated murine muscle tissue. In addition, osteocalcin treatment significantly increased muscle mass and grip strength in both aged mice and aged fasting mice. In conclusion, the inhibition of osteocalcin on muscle cell aging is accompanied by the induction of IL-6-STAT3-dependent autophagy, indicating osteocalcin might be a promising therapeutic candidate for aging-related myopathies.

Pituitary hormone α-MSH promotes tumor-induced myelopoiesis and immunosuppression.

The hypothalamic-pituitary (HP) unit can produce various hormones to regulate immune responses, and some of its downstream hormones or effectors are elevated in cancer patients. We show that the HP unit can promote myelopoiesis and immunosuppression to accelerate tumor growth. Subcutaneous implantation of tumors induced hypothalamus activation and pituitary α-melanocyte-stimulating hormone (α-MSH) production in mice. α-MSH acted on bone marrow progenitors to promote myelopoiesis, myeloid cell accumulation, immunosuppression, and tumor growth through its melanocortin receptor MC5R. MC5R peptide antagonist boosted antitumor immunity and anti-programmed cell death protein 1 (anti-PD-1) immunotherapy. Serum α-MSH concentration was elevated and correlated with circulating myeloid-derived suppressor cells in cancer patients. Our results reveal a neuroendocrine pathway that suppresses tumor immunity and suggest MC5R as a potential target for cancer immunotherapy.

The Co-occurrence of mcr-3 and fosA3 in IncP plasmid in ST131 Escherichia coli: A novel case.

INTRODUCTION: Plasmid-mediated colistin resistance genes, especially mcr-3 combined with the fosfomycin resistance gene fosA3, are a grave health concern. Our study was designed to determine the epidemiological characteristics of the combination of mcr-3 and fosA3 in Anhui province, China. METHODOLOGY: A total of 127 multi-drug-resistant (MDR) E. coli strains were assessed for antibiotic resistance/sensitivity to detect mcr-3 and fosA3 using polymerase chain reaction (PCR) and sequencing. The genes of interest were conjugated using EC600, and replicon and sequence types (STs) were identified by PCR-based replicon typing (PBRT) and multilocus sequence typing (MLST). Cluster similarity and genomic relatedness among the positive isolates were confirmed by Xbal PFGE. RESULTS: The processed E. coli isolates were highly resistant to the tested antibiotics; the prevalence of mcr-3 was 0.78% in the transferable IncP-type plasmid in ST131, whereas fosA3 prevalence was 38.58% among different transferable plasmids, including IncFIIK, IncFII and IncA/C, and in various STs including ST69, ST1193, ST12, ST46, ST57, ST1196, ST38, ST95, ST131, ST7584 and ST10184. Both were successfully transferred to EC600. The Xbal PFGE cluster exposed similarities among the STs. CONCLUSIONS: Our results show that to control the spread of colistin and fosfomycin resistance genes in human pathogens, the ban on colistin must be continued in animal feeding farms not only in China but around the world; additionally, awareness platforms on the use of colistin must be implemented and strict policies in poultry and pig farms must be maintained. Furthermore, fosfomycin misuse by patients and overuse by physicians must be strictly managed to stop the spread of fosfomycin resistance.

Epidemiological Characterization of Colistin and Carbapenem Resistant Enterobacteriaceae in a Tertiary: A Hospital from Anhui Province.

PURPOSE: Antimicrobial resistance, especially carbapenem resistance Enterobacteriaceae and plasmid mediated mobile colistin resistance, is a serious issue worldwide. This study was designed to determine the epidemiological characteristics of plasmid mediated colistin resistance and carbapenem resistant Enterobacteriaceae from tertiary A hospital located in Hefei, China. METHODS: Totally, 158 carbapenems resistant Enterobacteriaceae (CRE) were screened for antibiotic susceptibility, mcr-1, extended spectrum ß-lactamases (ESBLs), metallo-ß-lactamases (MBLs), and fosfomycin resistance genes using PCR and sequencing. The sequence types were identified by multilocus sequence typing (MLST). Plasmid profiles were determined by PCR based replicon typing (PBRT), and the plasmid sizes were confirmed by southern blotting. RESULTS: The isolates showed high MIC50 and MIC90 for all antimicrobials, except tigecycline, meropenem, and colistin. The main Carbapenemase genes were bla KPC-2 (90.5%), bla NDM-1(3.7%), bla OXA-48(5.6%) and fosA3 (14.5%). The bla CTXM-15 found 36.7%, mcr-1 (3.7%) recorded in six isolates. PBRT revealed bla KPC-2 in K. pneumoniae on IncR, IncFII, and IncA/C. bla NDM-1 in E. coli on IncFII, whereas in E. cloacae noticed on IncHI2 plasmid. mcr-1 was recorded among IncFIIK, IncFII, and IncF in E. coli, K. pneumoniae, and E. cloacae. Resistance genes (mcr-1, bla NDM-1, bla KPC-2) harboring plasmids are successfully trans-conjugant to EC-600. A high incidence of ST11 was observed in K. pneumoniae carbapenem resistant isolates. While in E. coli, multiple STs were identified. However, mcr-1 in ST23 was identified for the first time in Anhui Province. Among Enterobacter cloacae, ST270 detected carrying bla NDM-1. Southern-hybridization confirmed the plasmid sizes 35-150kb. CONCLUSION: This study indicates the co-carrying of mcr-1, bla KPC-2, and bla NDM-1 among clinical isolates, the prevalence of different Enterobacteriaceae STs is alarming, especially in E. coli. Holding such a resistance profile is a threat for humans and animals, which may be transferred between the strains through plasmid transfusion. Persistent control actions are immediately necessary to combat this hazard.

Predictive value of circulating cystatin C level in patients with acute coronary syndrome: a meta-analysis.

Circulating cystatin C level has been identified as a predictor of adverse outcomes in patients with coronary artery disease (CAD). This meta-analysis aimed to investigate the value of circulating cystatin C level for predicting adverse outcomes in patients with acute coronary syndrome (ACS). We comprehensively searched articles indexed in Pubmed and Embase databases from their inceptions to 30 November 2019. All available observational studies that investigated the association between circulating cystatin C level and major adverse cardiovascular events [MACE] (including death, heart failure, re-infarction, target vascular revascularization, angina and stroke) or all-cause mortality in patients with ACS were included. The prognostic value was expressed by pooling the multivariable-adjusted hazard risk (HR) with 95% confidence interval (CI) for the highest versus the lowest category of cystatin C level. Eleven eligible studies (12 articles) with 4600 ACS patients were identified. Meta-analysis indicated that the highest versus lowest category of cystatin C level was associated with higher risk of MACE (HR 2.28; 95% CI 1.92-2.71) and all-cause mortality (HR 2.89; 95% CI 1.43-5.83) after adjustment for estimated glomerular filtration rate (eGFR) or creatinine. Subgroup analysis by subtypes of patients, study design, follow-up duration and cutoff level of cystatin C further confirmed the value of cystatin C level for predicting MACE. Elevated circulating cystatin C level at baseline is strongly and independently associated with an increased risk of MACE and all-cause mortality in patients with ACS. Determination of circulating cystatin C level has potential to improve risk stratification of ACS patients.

A Deep Learning-Based Chemical System for QSAR Prediction.

Research on quantitative structure-activity relationships (QSAR) provides an effective approach to determine new hits and promising lead compounds during drug discovery. In the past decades, various works have gained good performance for QSAR with the development of machine learning. The rise of deep learning, along with massive accessible chemical databases, made improvement on the QSAR performance. This article proposes a novel deep-learning-based method to implement QSAR prediction by the concatenation of end-to-end encoder-decoder model and convolutional neural network (CNN) architecture. The encoder-decoder model is mainly used to generate fixed-size latent features to represent chemical molecules; while these features are then input into CNN framework to train a robust and stable model and finally to predict active chemicals. Two models with different schemes are investigated to evaluate the validity of our proposed model on the same data sets. Experimental results showed that our proposed method outperforms other state-of-the-art methods in successful identification of chemical molecule whether it is active.

Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks.

BACKGROUND: Accurate identification of potential interactions between drugs and protein targets is a critical step to accelerate drug discovery. Despite many relative experimental researches have been done in the past decades, detecting drug-target interactions (DTIs) remains to be extremely resource-intensive and time-consuming. Therefore, many computational approaches have been developed for predicting drug-target associations on a large scale. RESULTS: In this paper, we proposed an deep learning-based method to predict DTIs only using the information of drug structures and protein sequences. The final results showed that our method can achieve good performance with the accuracies up to 92.0%, 90.0%, 92.0% and 90.7% for the target families of enzymes, ion channels, GPCRs and nuclear receptors of our created dataset, respectively. Another dataset derived from DrugBank was used to further assess the generalization of the model, which yielded an accuracy of 0.9015 and an AUC value of 0.9557. CONCLUSION: It was elucidated that our model shows improved performance in comparison with other state-of-the-art computational methods on the common benchmark datasets. Experimental results demonstrated that our model successfully extracted more nuanced yet useful features, and therefore can be used as a practical tool to discover new drugs. AVAILABILITY: http://deeplearner.ahu.edu.cn/web/CnnDTI.htm.

Analysis of serum undercarboxylated osteocalcin level in rats with type 2 diabetes mellitus and the correlation with cognitive impairment.

The aim of the study was to investigate the correlation between the serum undercarboxylated osteocalcin (ucOC) level and the blood biochemistry and cognitive impairment in rats with type 2 diabetes mellitus (T2DM). Sprague-Dawley (SD) rats were randomly divided into the normal control group (NC) and type 2 DM group. DM group received the high-fat and high-sugar diet combined with the intraperitoneal injection of low-dose STZ to establish the type 2 DM rat model. After 12 weeks of feeding, a Morris water maze was used to observe the rats' cognitive ability, and the levels of blood lipid, ucOC, insulin and adiponectin in the two groups were measured. The results showed that blood glucose of rats in DM group was increased significantly at 2-12 weeks (p<0.01) and the body weight was significantly increased at 4-12 weeks (p<0.01). The levels of serum triglyceride (TG), total cholesterol, low-density lipoprotein and insulin in rats in DM group were significantly increased compared with those in NC group (p<0.01) and the levels of high-density lipoprotein, adiponectin and ucOC were significantly decreased compared with those in the NC group (p<0.01). The place navigation and spatial exploration capacities of rats in DM group were significantly decreased compared with those in NC group (p<0.01). In the DM group, the place navigation and spatial exploration capacities of rats in the low ucOC group were significantly decreased compared with those in the high ucOC group (p<0.01). Additionally, single-factor correlation analysis revealed that ucOC was negatively correlated with blood glucose, TG and escape latency (p<0.01), but was positively correlated with adiponectin, residence time in target quadrant and traversing times (p<0.05 or p<0.01). In conclusion, the decreased serum ucOC level in rats with type 2 diabetes mellitus has a certain correlation with cognitive impairment.

Relevance of plasma obestatin and early arteriosclerosis in patients with type 2 diabetes mellitus.

We investigated the correlation between obestatin and metabolic parameters and carotid intima-media thickness (IMT) in plasma of patients with type 2 diabetes mellitus (T2DM). We collected 103 patients aged from 60 to 83 years (69.26 ± 5.83 years) form January, 2007 to May, 2009. All patients were divided into normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and T2DM according to the oral glucose tolerance test (OGTT). We found that higher levels of fasting insulin (Fins), fasting blood glucose, 2 h OGTT glucose, homeostasis model assessment of insulin resistance (HOMA-IR), low density lipoprotein cholesterol, glycated haemoglobin, and C-reactive protein (CRP), as well as lower obestatin level and higher intima-media thickness level (IMT), existed in T2DM group compared with NGT group and IGT group (P < 0.01). Also, obestatin level was independently associated with HOMA-IR and CRP, while IMT level was independently associated with HOMA-IR, triglyceride, Fins, and obestatin (P < 0.01), based on stepwise multiple regression analysis. Therefore, we deduced that the low level of plasma obestatin might be related to early arteriosclerosis in patients with T2DM via increasing IMT level, and elevated plasma obestatin levels might protect T2DM patients against carotid atherosclerosis to some extent.