Citations

The interaction of death-associated protein kinase 1 (DAPK1) with the 2B subunit (GluN2B) C-terminus of N-methyl-D-aspartate receptor (NMDAR) plays a critical role in the pathophysiology of depression and is considered a potential target for the structure-based discovery of new antidepressants. However, the 3D structures of C-terminus residues 1290–1310 of GluN2B (GluN2B-CT1290-1310) remain elusive and the interaction between GluN2B-CT1290-1310 and DAPK1 is unknown. In this study, the mechanism of interaction between DAPK1 and GluN2B-CT1290-1310 was predicted by computational simulation methods including protein–peptide docking and molecular dynamics (MD) simulation. Based on the equilibrated MD trajectory, the total binding free energy between GluN2B-CT1290-1310 and DAPK1 was computed by the mechanics generalized born surface area (MM/GBSA) approach. The simulation results showed that hydrophobic, van der Waals, and electrostatic interactions are responsible for the binding of GluN2B-CT1290–1310/DAPK1. Moreover, through per-residue free energy decomposition and in silico alanine scanning analysis, hotspot residues between GluN2B-CT1290-1310 and DAPK1 interface were identified. In conclusion, this work predicted the binding mode and quantitatively characterized the protein–peptide interface, which will aid in the discovery of novel drugs targeting the GluN2B-CT1290-1310 and DAPK1 interface.

Background: Due to its ability to provide quantitative and dynamic information on tumor genesis and development by directly profiling protein expression, the proteomics has become intensely popular for characterizing the functional proteins driving the transformation of malignancy, tracing the large-scale protein alterations induced by anticancer drug, and discovering the innovative targets and first-in-class drugs for oncologic disorders. Objective: To quantify cancer proteomics data, the label-free quantification (LFQ) is frequently employed. However, low precision, poor reproducibility and inaccuracy of the LFQ of proteomics data have been recognized as the key “technical challenge” in the discovery of anticancer targets and drugs. In this paper, the recent advances and development in the computational perspective of LFQ in cancer proteomics were therefore systematically reviewed and analyzed. Methods: PubMed and Web of Science database were searched for label-free quantification approaches, cancer proteomics and computational advances. Results: First, a variety of popular acquisition techniques and state-of-the-art quantification tools are systematically discussed and critically assessed. Then, many processing approaches including transformation, normalization, filtering and imputation are subsequently discussed, and their impacts on improving LFQ performance of cancer proteomics are evaluated. Finally, the future direction for enhancing the computation-based quantification technique for cancer proteomics are also proposed. Conclusion: There is a dramatic increase in LFQ approaches in recent year, which significantly enhance the diversity of the possible quantification strategies for studying cancer proteomics.

Background: The human Monoamine Transporters (hMATs), primarily including hSERT, hNET and hDAT, are important targets for the treatment of depression and other behavioral disorders with more than the availability of 30 approved drugs. Objective: This paper is to review the recent progress in the binding mode and inhibitory mechanism of hMATs inhibitors with the central or allosteric binding sites, for the benefit of future hMATs inhibitor design and discovery. The Structure-Activity Relationship (SAR) and the selectivity for hit/lead compounds to hMATs that are evaluated by in vitro and in vivo experiments will be highlighted. Methods: PubMed and Web of Science databases were searched for protein-ligand interaction, novel inhibitors design and synthesis studies related to hMATs. Results: Literature data indicate that since the first crystal structure determinations of the homologous bacterial Leucine Transporter (LeuT) complexed with clomipramine, a sizable database of over 100 experimental structures or computational models has been accumulated that now defines a substantial degree of structural variability hMATs-ligands recognition. In the meanwhile, a number of novel hMATs inhibitors have been discovered by medicinal chemistry with significant help from computational models. Conclusion: The reported new compounds act on hMATs as well as the structures of the transporters complexed with diverse ligands by either experiment or computational modeling have shed light on the poly-pharmacology, multimodal and allosteric regulation of the drugs to transporters. All of the studies will greatly promote the Structure-Based Drug Design (SBDD) of structurally novel scaffolds with high activity and selectivity for hMATs.

Intrahepatic cholangiocarcinoma (iCCA) has over the last 10‐20 years become the focus of increasing concern, largely due to its rising incidence and high mortality rates worldwide. The significant increase in mortality rates from this primary hepatobiliary cancer, particularly over the past decade, has coincided with a rapidly growing interest among clinicians, investigators, and patient advocates to seek greater mechanistic insights and more effective biomarker‐driven targeted approaches for managing and/or preventing this challenging liver cancer. In addition to discussing challenges posed by this aggressive cancer, this review will emphasize recent epidemiological, basic, and translational research findings for iCCA. In particular, we will highlight emerging demographic changes and evolving risk factors, the critical role of the tumor microenvironment, extracellular vesicle biomarkers and therapeutics, intertumoral and intratumoral heterogeneity, and current and emerging targeted therapies regarding iCCA. Specifically, recent evidence linking non–bile duct medical conditions, such as nonalcoholic fatty liver disease and nonspecific cirrhosis, to intrahepatic cholangiocarcinogenesis together with geographic and ethnic variation will be assessed. Recent developments concerning the roles played by transforming growth factor‐β and platelet‐derived growth factor D in driving the recruitment and expansion of cancer‐associated myofibroblasts within cholangiocarcinoma (CCA) stroma as well as their therapeutic implications will also be discussed. In addition, the potential significance of extracellular vesicles as bile and serum biomarkers and therapeutic delivery systems for iCCA will be described. An integrated systems approach to classifying heterogeneous iCCA subtypes will be further highlighted, and recent clinical trials and emerging targeted therapies will be reviewed, along with recommendations for future translational research opportunities. Established international CCA networks are now facilitating collaborations aimed at advancing iCCA translational and clinical research.

BackgroundPreoperative prediction of tumor recurrence is important in the management of patients with hepatocellular carcinoma (HCC).PurposeTo investigate whether tumor stiffness derived by magnetic resonance elastography (MRE) could predict early recurrence of HCC after hepatic resection.Study TypeRetrospective.PopulationIn all, 99 patients with pathologically confirmed HCCs after surgical resection.Field Strength/Sequence3.0T; preoperative MRE with 60‐Hz mechanical vibrations using an active acoustic driver.AssessmentRegions of interest (ROIs) were manually drawn in the tumors to measure mean tumor stiffness. Surgical specimens were reviewed for histological grade, capsule, vascular invasion, and surgical margins. The early recurrence of HCC was defined as that occurring within 2 years after resection.Statistical TestsCox proportional hazard models were used to evaluate risk factors associated with the time to early recurrence.ResultsHCCs with recurrence had higher tumor stiffness, higher rate of advanced T stage, vascular invasion, lower rate of capsule formation, larger tumor size, higher aspartate aminotransferase (AST), and hepatitis B virus (HBV)‐DNA level and aspartate aminotransferase / alanine aminotransferase ratio (P = 0.031, 0.007, 0.01, <0.001, 0.015, 0.034, 0.01, and 0.014, respectively) than HCCs without recurrence. Vascular invasion (hazard ratio [HR] = 2.922; 95% confidence interval [CI]: [1.079, 7.914], P = 0.035) and mean tumor stiffness (HR = 1.163; 95% CI: [1.055, 1.282], P = 0.002) were risk factors associated with early recurrence. Each 1‐kPa increase in tumor stiffness was associated with a 16.3% increase in the risk for tumor recurrence.Data ConclusionThe mean stiffness of HCCs may be a useful, noninvasive, quantitative biomarker for the prediction of early HCC recurrence after hepatic resection.Level of Evidence: 4Technical Efficacy: Stage 5J. Magn. Reson. Imaging 2019;49:719–730.

Abstract Context Previous epidemiological studies had inconsistent results regarding the relationship between blood lead level (BLL) and adiposity. Objective We aimed to investigate the associations of BLL with body mass index (BMI) particularly using Mendelian randomization analyses and examine the interaction between obesity-predisposing genes and BLL on the associations. Design and Setting A total of 3922 participants were enrolled from 16 sites in East China in 2014 from the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (ChiCTR-ECS-14005052, www.chictr.org.cn). We calculated the weighted BMI genetic risk score (GRS) based on 29 variants that were identified and validated in East Asians. BLL was measured by atomic absorption spectrometry. Main Outcome Measure BMI was calculated, and BMI ≥25 kg/m2 was defined as overweight. Results Multivariable logistic regression analysis demonstrated significant associations between BMI with each unit increase in lnBLL (β = 0.24; 95% CI, 0.08 to 0.40; P &lt; 0.001) and each 1-point increase in BMI-GRS (β = 0.08; 95% CI, 0.05 to 0.11; P &lt; 0.001). The causal regression coefficients of genetically determined BMI for lnBLL were −0.003 (95% CI, −0.075 to 0.070), which showed no significance. The GRS modified the association of BLL with BMI and overweight (BMI ≥25 kg/m2; P for interaction = 0.031 and 0.001, respectively). Each unit of lnBLL was associated with 63% higher odds of overweight (OR 1.63; 95% CI, 1.30 to 2.05) in the highest quartile of GRS, but no significant associations were found in the lower three quartiles. Conclusions The associations of BLL with BMI and overweight (BMI ≥25 kg/m2) were significantly modulated by BMI genetic susceptibility.