DeepKa Web Server: High-Throughput Protein pKa Prediction.

DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how pKa's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.

Basis for Accurate Protein pKa Prediction with Machine Learning.

pH regulates protein structures and the associated functions in many biological processes via protonation and deprotonation of ionizable side chains where the titration equilibria are determined by pKa's. To accelerate pH-dependent molecular mechanism research in the life sciences or industrial protein and drug designs, fast and accurate pKa prediction is crucial. Here we present a theoretical pKa data set PHMD549, which was successfully applied to four distinct machine learning methods, including DeepKa, which was proposed in our previous work. To reach a valid comparison, EXP67S was selected as the test set. Encouragingly, DeepKa was improved significantly and outperforms other state-of-the-art methods, except for the constant-pH molecular dynamics, which was utilized to create PHMD549. More importantly, DeepKa reproduced experimental pKa orders of acidic dyads in five enzyme catalytic sites. Apart from structural proteins, DeepKa was found applicable to intrinsically disordered peptides. Further, in combination with solvent exposures, it is revealed that DeepKa offers the most accurate prediction under the challenging circumstance that hydrogen bonding or salt bridge interaction is partly compensated by desolvation for a buried side chain. Finally, our benchmark data qualify PHMD549 and EXP67S as the basis for future developments of protein pKa prediction tools driven by artificial intelligence. In addition, DeepKa built on PHMD549 has been proven an efficient protein pKa predictor and thus can be applied immediately to, for example, pKa database construction, protein design, drug discovery, and so on.

Polymorphisms in gene UGT1A1 modify the association of prenatal exposure to polycyclic aromatic hydrocarbons with congenital heart diseases risk.

INTRODUCTION: Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) is a risk factor for the occurrence of congenital heart diseases (CHDs). Genetic susceptibility to PAHs metabolism may modify the exposure-risk relationship. The role of uridine diphosphoglucuronosyl transferase 1A1 (UGT1A1) genetic polymorphisms for modulating the impacts of prenatal PAHs exposure on the risk of CHDs remains to be discovered. OBJECTIVE: The aim of this study was to investigate whether maternal UGT1A1 genetic polymorphisms are associated with fetal susceptibility to CHDs and to assess whether the risk is modified by maternal PAHs exposure. METHODS: Maternal urinary biomarker of PAHs exposure was determined in 357 pregnant women with CHDs fetuses and 270 controls (pregnant women carrying fetuses without major congenital malformations). Urinary 1-hydroxypyrene-glucuronide (1-OHPG) concentration, a sensitive biomarker for PAHs exposure, was measured using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry. Maternal single nucleotide polymorphisms (SNPs) in UGT1A1, including rs3755319, rs887829, rs4148323, rs6742078, and rs6717546, were genotyped using an improved multiplex ligation detection reaction (iMLDR) technique. Unconditional logistic regression was performed to determine the impacts of UGT1A1 polymorphisms on the risks of CHDs and their subtypes. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-gene and gene-PAHs exposure interactions. RESULTS: None of the selected UGT1A1 polymorphisms was independently associated with the risk of CHDs. The interaction between SNP rs4148323 and PAHs exposure was observed to be associated with CHDs (p< .05). Pregnant women with high-level PAHs exposure and rs4148323 had an increased risk of carrying CHDs fetuses (GA-AA vs. GG: aOR = 2.00, 95% CI = 1.06-3.79). Moreover, the joint effect of rs4148323 and PAHs exposure was found to be significantly associated with risks of septal defects, conotruncal heart defects, and right-sided obstructive malformations. CONCLUSIONS: Maternal genetic variations of UGT1A1 rs4148323 may modify the association between prenatal PAHs exposure and CHDs risk. This finding needs to be further confirmed in a larger-scale study.

Investigation of urine metabolome of BALB/c mouse infected with an avirulent strain of Toxoplasma gondii.

BACKGROUND: The protozoan parasite Toxoplasma gondii is a major concern for human and animal health. Although the metabolic understanding of toxoplasmosis has increased in recent years, the analysis of metabolic alterations through noninvasive methodologies in biofluids remains limited. METHODS: Here, we applied liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics and multivariate statistical analysis to analyze BALB/c mouse urine collected from acutely infected, chronically infected and control subjects. RESULTS: In total, we identified 2065 and 1409 metabolites in the positive electrospray ionization (ESI +) mode and ESI - mode, respectively. Metabolomic patterns generated from principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) score plots clearly separated T. gondii-infected from uninfected urine samples. Metabolites with altered levels in urine from T. gondii-infected mice revealed changes in pathways related to amino acid metabolism, fatty acid metabolism, and nicotinate and nicotinamide metabolism. CONCLUSIONS: This is the first study to our knowledge on urine metabolic profiling of BALB/c mouse with T. gondii infection. The urine metabolome of infected mouse is distinctive and has value in the understanding of Toxoplasmosis pathogenesis and improvement of treatment.

Levels, distribution and risk assessment of hexabromocyclododecane (HBCD) in fish in Xiamen, China.

In this study, hexabromocyclododecane (HBCD) was detected in 114 fish samples collected from 6 administrative regions of Xiamen city, China. HBCD amounts ranged between ND (not detected) and 2.216 ng g-1 ww (mean, 0.127 ± 0.318 ng g-1 ww). Besides, α-HBCD was the main diastereoisomer in these fish specimens, followed by ß-HBCD. Meanwhile, γ-HBCD was not detected in any of the samples. Significant differences were recorded among fish species. The results indicated that the levels and detection rates of HBCD were higher in Trachinotus ovatus compared with other aquatic organisms. Therefore, Trachinotus ovatus could be used as a marine biological indicator of HBCD. Within the regions investigated, Siming was significantly different from Jimei, Haicang, and Xiang'an. The spatial distribution of HBCD concentrations indicated higher mean levels in samples collected from Haicang, Jimei, and Xiang'an, respectively, with the highest detection rates in Jimei and Xiang'an, which might be related to geographical location and intense industrial and urban activities. Estimation of daily HBCD intake was performed according to fish consumption in Xiamen residents. The medium bound HBCD amounts in fish were approximately 0.073 and 0.088 ng kg bw-1d-1 for male and female residents of Xiamen, respectively. Exposure doses of HBCD indicated no health concern for Xiamen residents.

Protein pK a Prediction with Machine Learning.

Protein pK a prediction is essential for the investigation of the pH-associated relationship between protein structure and function. In this work, we introduce a deep learning-based protein pK a predictor DeepKa, which is trained and validated with the pK a values derived from continuous constant-pH molecular dynamics (CpHMD) simulations of 279 soluble proteins. Here, the CpHMD implemented in the Amber molecular dynamics package has been employed (Huang Y.J. Chem. Inf. Model.2018, 58, 1372-1383). Notably, to avoid discontinuities at the boundary, grid charges are proposed to represent protein electrostatics. We show that the prediction accuracy by DeepKa is close to that by CpHMD benchmarking simulations, validating DeepKa as an efficient protein pK a predictor. In addition, the training and validation sets created in this study can be applied to the development of machine learning-based protein pK a predictors in the future. Finally, the grid charge representation is general and applicable to other topics, such as the protein-ligand binding affinity prediction.

Intelligent Disease Prediagnosis Only Based on Symptoms.

People often concern the relationships between symptoms and diseases when seeking medical advices. In this paper, medical data are divided into three copies, records related to main disease categories, records related to subclass disease types, and records of specific diseases firstly; then two disease recognition methods only based on symptoms for the main disease category identification, subclass disease type identification, and specific disease identification are given. In the methods, a neural network and a support vector machine (SVM) algorithms are adopted, respectively. In the method validation part, accuracy of the two diagnosis methods is tested and compared. Results show that automatic disease prediction only based on symptoms is possible for intelligent medical triage and common disease diagnosis.

Protein Secondary Structure Prediction With a Reductive Deep Learning Method.

Protein secondary structures have been identified as the links in the physical processes of primary sequences, typically random coils, folding into functional tertiary structures that enable proteins to involve a variety of biological events in life science. Therefore, an efficient protein secondary structure predictor is of importance especially when the structure of an amino acid sequence fragment is not solved by high-resolution experiments, such as X-ray crystallography, cryo-electron microscopy, and nuclear magnetic resonance spectroscopy, which are usually time consuming and expensive. In this paper, a reductive deep learning model MLPRNN has been proposed to predict either 3-state or 8-state protein secondary structures. The prediction accuracy by the MLPRNN on the publicly available benchmark CB513 data set is comparable with those by other state-of-the-art models. More importantly, taking into account the reductive architecture, MLPRNN could be a baseline for future developments.

Scaffold with Micro/Macro-Architecture for Myocardial Alignment Engineering into Complex 3D Cell Patterns.

Tissue structural anisotropy is an important basis for heart function. Attempts to regenerate the complicated heart-tissue alignment has rarely featured macroscale 3D constructs required for myocardial tissue engineering. The feasibility of engineered scaffolds with micro/macro-architecture for guiding spatial cell alignment following complex patterns is reported. The scaffold is composed of stackable dual-structured layers with linear micro-ridge/groove patterns and macro-through-hole arrays, which enable tailorable anisotropy and interconnective free space. When human mesenchymal stem cells are seeded on the scaffold, well-organized spreading alignment showing the precise control in cellular orientation is significantly introduced over nonpatterned controls. Moreover, spatial cell distribution in the scaffold and directional changes of the layered linear patterns that made cell alignment orientations turning accordingly are observed, leading to the complex 3D pattern reconstruction of cellular alignment resembling natural myocardial tissue. This work validates the potential of micro/macro-architecture engineering for spatial cell guidance. Scaffolds with this capability can be potentially used for biomanufacturing of the structural alignment in myocardial tissue engineering.

Indicator polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in seafood from Xiamen (China): levels, distributions, and risk assessment.

Indicator polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) were determined in 289 seafood samples including fishes, crustaceans, and shellfish collected from six administrative regions in Xiamen of China. The residual levels of PCBs, dichlorodiphenyltrichloroethane and its metabolites (DDTs), and hexachlorocyclohexanes (HCHs) ranged

Dual-Microstructured Porous, Anisotropic Film for Biomimicking of Endothelial Basement Membrane.

Human endothelial basement membrane (BM) plays a pivotal role in vascular development and homeostasis. Here, a bioresponsive film with dual-microstructured geometries was engineered to mimic the structural roles of the endothelial BM in developing vessels, for vascular tissue engineering (TE) application. Flexible poly(ε-caprolactone) (PCL) thin film was fabricated with microscale anisotropic ridges/grooves and through-holes using a combination of uniaxial thermal stretching and direct laser perforation, respectively. Through optimizing the interhole distance, human mesenchymal stem cells (MSCs) cultured on the PCL film's ridges/grooves obtained an intact cell alignment efficiency. With prolonged culturing for 8 days, these cells formed aligned cell multilayers as found in native tunica media. By coculturing human umbilical vein endothelial cells (HUVECs) on the opposite side of the film, HUVECs were observed to build up transmural interdigitation cell-cell contact with MSCs via the through-holes, leading to a rapid endothelialization on the PCL film surface. Furthermore, vascular tissue construction based on the PCL film showed enhanced bioactivity with an elevated total nitric oxide level as compared to single MSCs or HUVECs culturing and indirect MSCs/HUVECs coculturing systems. These results suggested that the dual-microstructured porous and anisotropic film could simulate the structural roles of endothelial BM for vascular reconstruction, with aligned stromal cell multilayers, rapid endothelialization, and direct cell-cell interaction between the engineered stromal and endothelial components. This study has implications of recapitulating endothelial BM architecture for the de novo design of vascular TE scaffolds.

Enhancement of pulsed laser ablation in environmentally friendly liquid.

Enhancement of pulsed laser ablation can be achieved in acetic acid as an environmentally friendly liquid. This paper evaluates microholes and textured features induced by a nanosecond pulsed laser under different processing circumstances. The microholes are fabricated by laser drilling in acetic acid and found to be 100% deeper than in air. The textured features achieved in the liquid demonstrate a higher content of Copper and a lower content of Oxygen. The improvement of laser ablation efficiency in the liquid is attributed to the strong confinement of plasma plume accompanying with shockwave and cavitation bubbles. Meanwhile, the laser enhanced chemical etching by the weak acid plays a critical role.

[Effects of trimetazidine therapy on left ventricular function after percutaneous coronary intervention].

OBJECTIVE: To explore the effects of trimetazidine therapy on left ventricular (LV) function after percutaneous coronary intervention (PCI). METHODS: A total of 106 patients with unstable angina pectoris underwent successful elective PCI were randomly assigned to standard therapy group (control, n = 55) or trimetazidine group (n = 51, 60 mg trimetazidine loading dose prior to PCI followed by 20 mg Tid after PCI on top of standard therapy). cTnI level was measured before and at 16-18 hours after PCI. LV function was evaluated by echocardiography and major adverse cardiac events (MACE, including death, re-infarction and target vessel revascularization) at 12 months after PCI was compared between the two groups. RESULTS: Post procedural cTnI level increased from [0.02 (0.01, 0.03)] µg/L at baseline to [0.11 (0.07, 0.13)] µg/L (P < 0.05) at 16-18 hours in the trimetazidine group, while [0.02(0.01, 0.03)] µg/L to [1.31(0.44, 2.31)] µg/L in the control group (P < 0.05). Post procedural cTnI level was significantly reduced in the trimetazidine group compared to the control group (P < 0.05). At 12 months follow-up, left ventricular ejection fraction in the trimetazidine group was significantly higher than in control group [(65.65 ± 3.94)% vs. (62.29 ± 3.06)%, P < 0.01] while incidence of MACE was similar between the two groups. CONCLUSION: Trimetazidine can reduce the post-PCI cTnI release and improve left ventricular function after PCI in patients with unstable angina pectoris.

Femtosecond laser-induced inverted microstructures inside glasses by tuning refractive index of objective's immersion liquid.

We report the formation of inverted microstructures inside glasses after femtosecond laser irradiation by tuning the refractive index contrast between the immersion liquid and the glass sample. By using water as well as 1-bromonaphthalene as immersion liquids, microstructures with similar shape but opposite directions are induced after femtosecond laser irradiation. Interestingly, the elemental distribution in the induced structures is also inverted. The simulation of laser intensity distribution along the laser propagation direction indicates that the interfacial spherical aberration effect is responsible for the inversion of microstructures and elemental distribution.

Space-selective precipitation of Ge crystalline patterns in glasses by femtosecond laser irradiation.

Crystalline Ge was induced space selectively inside a borosilicate glass by 800 nm, 250 kHz femtosecond laser irradiation. Micro-Raman spectra and x-ray diffraction analysis confirmed that the laser-induced crystals were cubic Ge. A periodic structure consisting of Ge crystalline lines was inscribed in the glass sample by continuously moving the focal point of the laser beam. Large third-order nonlinear optical properties and ultrafast response time were observed from the crystallization region owing to highly optical nonlinearity of Ge crystals. These results may find some applications in fabrication of functional optical and photonic devices, such as optical circuits.

Shape- and size-controllable microstructure on glass surface induced by femtosecond laser irradiation.

Controllable microstructures are formed on a glass surface after irradiation of a focused 800 nm, 250 KHz femtosecond laser beam. Field-emission scanning electron microscope and 3D measuring laser microscope images reveal that the induced structures are circular and linear protuberances and can be controlled from 10 microm to hundreds of micrometers in width, and from 1 microm to tens of micrometers in height. The protuberance structure is proposed to be formed as a consequence of the laser-induced high temperature and pressure owing to linear and nonlinear absorption near the laser focal point, and low softening and melting temperature of the glass sample.

Redistribution of elements in glass induced by a high-repetition-rate femtosecond laser.

The redistribution of elements in a multicomponent oxyfluoride glass is induced by a 250 kHz femtosecond laser. Elemental distribution in the cross section of the modified region along the laser propagation axis is analyzed by an electron microprobe analyzer. The results indicate that the relative concentrations of network formers of the glass are higher in the central area of the modified region and lower in the periphery of the modified region compared with the unirradiated areas. However, the relative concentrations of network modifiers are as opposed to that of network formers. Fluorescence spectra confirm that the distribution of fluorescence intensity of Yb(3+) in the modified region is consistent with that of its concentration. The effects of spherical aberration of the incident beam on the elemental redistribution are also discussed.

[Molecular characteristics of DNA-A of tomato leaf curl Guangdong virus isolate G2].

Virus isolate G2 was isolated from tomato plants showing leaf curl symptoms in Guangdong. The complete nucleotide sequence of G2 DNA-A was determined to be 2744 nucleotides encoding six potential ORFs, with two (AV1 and AV2) in virus sense and four (AC1, AC2, AC3 and AC4) in complementary sense. G2 DNA-A has a typical characteristics of Begomovirus genome organization. BLAST results showed that G2 DNA-A belonged to the Begomovirus of Geminiviridae. Pairwise comparisons of G2 DNA-A with those of other 41 begomoviruses indicated that G2 DNA-A was most closely related to that of Papaya leaf curl China virus isolate G10 (PaLCuCNV-[G10]) (82.8% sequence identity). The intergenic region (IR) of G2 differed to great extent with other begomoviruses (30.9%-81.8% nucleotide sequence identity); when individual encoded proteins were compared, the CP of G2 had relatively high amino acid sequence identity (77.6%-99.2%) with other begomoviruses whereas the AC4 of G2 had less amino acid sequence identity (43.5%-78.8%). Phylogenetic analysis based on the DNA-A sequences also showed that G2 was less related to the reported begomoviruses. These results revealed that G2 infecting Guangdong tomato might be a previously unreported species of Begomovirus, for which the name Tomato leaf curl Guangdong Virus (ToLCGDV) is proposed.