Metabolism of 4-Aminopiperidine Drugs by Cytochrome P450s: Molecular and Quantum Mechanical Insights into Drug Design

4-Aminopiperidines are a variety of therapeutic agents that are extensively metabolized by cytochrome P450s with CYP3A4 as a major isoform catalyzing their N-dealkylation reaction. However, its catalytic mechanism has not been fully elucidated in a molecular interaction level. Here, we applied theoretical approaches including the molecular mechanics-based docking to study the binding patterns and quantum mechanics-based reactivity calculations. They were supported by the experimental human liver microsomal clearance and P450 isoform phenotyping data. Our results herein suggested that the molecular interactions between substrates and CYP3A4 active site residues are essential for the N-dealkylation of 4-aminopiperidines. We also found that the serine 119 residue of CYP3A4 may serve as a key hydrogen-bonding partner to interact with the 4-amino groups of the studied drugs. The reactivity of the side chain α-carbon hydrogens drives the direction of catalysis as well. As a result, structure-based drug design approaches look promising to guide drug discovery programs into the optimized drug metabolism space

Data_Sheet_1_Causal association between depression and intracranial aneurysms: a bidirectional two-sample Mendelian randomization study.pdf

BackgroundAlthough observational studies have suggested a bidirectional relation between depression and intracranial aneurysms (IAs), their causal relations remain unclear. Thus we aimed to assess the causal association between depression and IAs.MethodsWe conducted a bidirectional two-sample Mendelian randomization (MR) study using summary-level data from publicly available genome-wide association studies of depression (n = 500,199), IAs (n = 79,429), unruptured intracranial aneurysm (uIA) (n = 74,004), and subarachnoid hemorrhage (SAH) (n = 77,074). MR analyses included the inverse-variance weighted (IVW) method as the primary analytic, plus weighted-median, simple mode, weighted mode, MR-Egger, and MR PRESSO.ResultsGenetically predicted depression was strongly positively related to IAs (odds ratio [OR] = 1.69, 95% confidence interval [CI] 1.19–2.39, p = 0.003), uIA (OR = 1.96, 95% CI 1.06–3.64, p = 0.032), and SAH (OR = 1.73, 95% CI 1.14–2.61, p = 0.009). Reverse MR analyses showed that while genetically predicted uIA was positively related to depression (OR = 1.02, 95% CI 1.00–1.05, p = 0.044), no causal relations were observed for either IAs or SAH for depression.ConclusionOur findings provide evidence of a causal effect of depression on IAs, uIA, and SAH. For the reverse MR analyses, we found a causal impact of uIA on depression, but no causal influence of either IAs or SAH for depression.</p

Sebnif: An Integrated Bioinformatics Pipeline for the Identification of Novel Large Intergenic Noncoding RNAs (lincRNAs) - Application in Human Skeletal Muscle Cells

<div><p><i>Ab initio</i> assembly of transcriptome sequencing data has been widely used to identify large intergenic non-coding RNAs (lincRNAs), a novel class of gene regulators involved in many biological processes. To differentiate real lincRNA transcripts from thousands of assembly artifacts, a series of filtering steps such as filters of transcript length, expression level and coding potential, need to be applied. However, an easy-to-use and publicly available bioinformatics pipeline that integrates these filters is not yet available. Hence, we implemented sebnif, an integrative bioinformatics pipeline to facilitate the discovery of <i>bona fide</i> novel lincRNAs that are suitable for further functional characterization. Specifically, sebnif is the only pipeline that implements an algorithm for identifying high-quality single-exonic lincRNAs that were often omitted in many studies. To demonstrate the usage of sebnif, we applied it on a real biological RNA-seq dataset from Human Skeletal Muscle Cells (HSkMC) and built a novel lincRNA catalog containing 917 highly reliable lincRNAs. Sebnif is available at <a href="http://sunlab.lihs.cuhk.edu.hk/sebnif/" target="_blank">http://sunlab.lihs.cuhk.edu.hk/sebnif/</a>.</p></div

Snapshots of sebnif web server.

<p>(A) The data upload page. All the parameters of sebnif could be specified by the users through this page. (B) The result page showing the report of novel lincRNAs identified in Human Skeletal Muscle Cells. The final list of novel lincRNAs in standard GFF format and the iSeeRNA noncoding score for each transcript can be downloaded directly; statistic numbers during the filtering steps and the FRFE Profile and STGE Profile generated by FRFE and STGE algorithms were also provided for users to evaluate the quality of the data.</p

Identification of novel lincRNA catalog in HSkMC.

<p>(A) The raw RNA-seq data was pre-processed, aligned with Tophat and assembled using Cufflinks in <i>ab initio</i> mode. (B) Sebnif filtering on the assembled transcripts. The numbers in parentheses represent the number of transcripts after each filtering step. (C) Annotating and further filtering of the novel lincRNAs with H3K4me3 and CAGE data.</p

Analysis of the novel lincRNAs in HSkMC.

<p>(A) Cumulative curve of the average PhastCons score of the novel lincRNAs (green) compared to randomly selected genome background (blue) and known mRNAs (red). These novel lincRNAs are more conserved than the genome background but less conserved than the mRNAs. (B) Comparison of expression profiles of novel lincRNAs (green), known ncRNAs (blue) and known mRNAs (red). Both novel lincRNAs and the known ncRNAs are expressed at a lower level than known mRNAs. (C) 57% (523 out of 917) of the novel lincRNAs are divergent transcripts generated within 2 kbp upstream of known protein coding genes. (D) Gene Ontology annotation of the above protein coding genes. The y-axis shows the top 10 enriched GO terms and the x-axis shows the enrichment significance P-values.</p

Validation of the novel lincRNAs.

<p>(A) 26 randomly selected novel lincRNAs from the final lincRNA list were subjected to RT-PCR validations, among which 8 were divergent lincRNAs (the transcript id is marked in red color and ends with a ‘*’ suffix). The PCR products were visualized on Agoras gel and the sizes of DNA markers (M) are shown on the right. (B) Comparison of the identified novel lincRNAs with NONCODE v3.0. 299 transcripts (32.6%) were found in common.</p

Self-Catalyzed Carbon Dioxide Adsorption by Metal–Organic Chains on Gold Surfaces

Efficient capture of CO₂ by chemical means requires a microscopic understanding of the interactions of the molecule–substrate bonding and adsorption-induced collective phenomena. By molecule-resolved imaging with scanning tunneling microscopy (STM), we investigate self-catalyzed CO₂ adsorption on one-dimensional (1D) substrates composed of self-assembled metal–organic chains (MOCs) supported on gold surfaces. CO₂ adsorption turns on attractive interchain interactions, which induce pronounced surface structural changes; the initially uniformly dispersed chains gather into close packed bundles, which are held together by highly ordered, single molecule wide CO₂ ranks. CO₂ molecules create more favorable adsorption sites for further CO₂ adsorption by mediating the interchain attraction, thereby self-catalyzing their capture. The release of CO₂ molecules by thermal desorption returns the MOCs to their original structure, indicating that the CO₂ capture and release are reversible processes. The real space microscopic characterization of the self-catalyzed CO₂ adsorption on 1D substrates could be exploited as platform for design of molecular materials for CO₂ capture and reduction

Impact of Continuous Positive Airway Pressure Treatment on Left Ventricular Ejection Fraction in Patients with Obstructive Sleep Apnea: A Meta-Analysis of Randomized Controlled Trials

<div><p>Background</p><p>It has been known for a long time that obstructive sleep apnea (OSA) is associated with a decreased left ventricular ejection fraction (LVEF). Continuous positive airway pressure (CPAP) is the gold standard treatment for OSA; however, it is unknown whether or not CPAP treatment will improve the LVEF. The aim of the current study was to assess whether or not CPAP treatment improves the LVEF. A meta-analysis was conducted to determine the effect of CPAP treatment on the LVEF among patients with OSA.</p><p>Methods</p><p>A literature search of PubMed, the Web of Science, and Cochrane Collaboration’s database were utilized to identify eligible reports for this trial. Ten randomized controlled trails were examined and the meta-analysis was performed using STATA 11.</p><p>Results</p><p>A significant improvement in the LVEF was observed after CPAP treatment (weighted mean difference(WMD) = 3.59, 95% CI = 1.74–5.44; P<0.001). Subgroup analysis revealed that patients with OSA and heart failure had a significant improvement in the LVEF after CPAP treatment (WMD = 5.18, 95% CI = 3.27–7.08; P<0.001); however, the LVEF of patients with OSA only increased 1.11% and there was no statistical significance (WMD = 1.11, 95% CI = −1.13–3.35; P = 0.331). Furthermore, based on univariate meta-regression analysis, only the baseline AHI had a statistically significant correlation with the LVEF.</p><p>Conclusions</p><p>Our meta-analysis supports the notion that CPAP may improve the LVEF among patients with OSA.</p></div

Characteristics of 10 studies included in the meta-analysis.

<p>OSA: obstructive sleep apnea; HF: heart failure; NR: not reported.</p