A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

Mol Ther Nucleic Acids. 2018 Jun 01;11:337-344

Authors: Yi HC, You ZH, Huang DS, Li X, Jiang TH, Li LP

Abstract
The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research.

PMID: 29858068 [PubMed]

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Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

Arch Toxicol. 2018 May 19;:

Authors: Slavov SH, Stoyanova-Slavova I, Mattes W, Beger RD, Brüschweiler BJ

Abstract
A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13C and 15N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.

PMID: 29779177 [PubMed - as supplied by publisher]

Common and unique transcriptional responses to dietary restriction and loss of insulin receptor substrate 1 (IRS1) in mice.

Aging (Albany NY). 2018 May 20;:

Authors: Page MM, Schuster EF, Mudaliar M, Herzyk P, Withers DJ, Selman C

Abstract
Dietary restriction (DR) is the most widely studied non-genetic intervention capable of extending lifespan across multiple taxa. Modulation of genes, primarily within the insulin/insulin-like growth factor signalling (IIS) and the mechanistic target of rapamycin (mTOR) signalling pathways also act to extend lifespan in model organisms. For example, mice lacking insulin receptor substrate-1 (IRS1) are long-lived and protected against several age-associated pathologies. However, it remains unclear how these particular interventions act mechanistically to produce their beneficial effects. Here, we investigated transcriptional responses in wild-type and IRS1 null mice fed an ad libitum diet (WTAL and KOAL) or fed a 30% DR diet (WTDR or KODR). Using an RNAseq approach we noted a high correlation coefficient of differentially expressed genes existed within the same tissue across WTDR and KOAL mice and many metabolic features were shared between these mice. Overall, we report that significant overlap exists in the tissue-specific transcriptional response between long-lived DR mice and IRS1 null mice. However, there was evidence of disconnect between transcriptional signatures and certain phenotypic measures between KOAL and KODR, in that additive effects on body mass were observed but at the transcriptional level DR induced a unique set of genes in these already long-lived mice.

PMID: 29779018 [PubMed - as supplied by publisher]

New N-phenylpyrrolamide DNA gyrase B inhibitors: Optimization of efficacy and antibacterial activity.

Eur J Med Chem. 2018 May 10;154:117-132

Authors: Durcik M, Lovison D, Skok Ž, Durante Cruz C, Tammela P, Tomašič T, Benedetto Tiz D, Draskovits G, Nyerges Á, Pál C, Ilaš J, Peterlin Mašič L, Kikelj D, Zidar N

Abstract
The ATP binding site located on the subunit B of DNA gyrase is an attractive target for the development of new antibacterial agents. In recent decades, several small-molecule inhibitor classes have been discovered but none has so far reached the market. We present here the discovery of a promising new series of N-phenylpyrrolamides with low nanomolar IC50 values against DNA gyrase, and submicromolar IC50 values against topoisomerase IV from Escherichia coli and Staphylococcus aureus. The most potent compound in the series has an IC50 value of 13 nM against E. coli gyrase. Minimum inhibitory concentrations (MICs) against Gram-positive bacteria are in the low micromolar range. The oxadiazolone derivative 11a, with an IC50 value of 85 nM against E. coli DNA gyrase displays the most potent antibacterial activity, with MIC values of 1.56 μM against Enterococcus faecalis, and 3.13 μM against wild type S. aureus, methicillin-resistant S. aureus (MRSA) and vancomycin-resistant Enterococcus (VRE). The activity against wild type E. coli in the presence of efflux pump inhibitor phenylalanine-arginine β-naphthylamide (PAβN) is 4.6 μM.

PMID: 29778894 [PubMed - as supplied by publisher]

Renal Pre-Competitive Consortium (RPC2): discovering therapeutic targets together.

Drug Discov Today. 2018 May 17;:

Authors: Tomilo M, Ascani H, Mirel B, Magnone MC, Quinn CM, Karihaloo A, Duffin K, Patel UD, Kretzler M

Abstract
Despite significant effort, patients with kidney disease have not seen their outcomes improved significantly over the past two decades. This has motivated clinicians and researchers to consider alternative methods to identifying risk factors, disease progression markers, and effective therapies. Genome-scale data sets from patients with renal disease can be used to establish a platform to improve understanding of the molecular basis of disease; however, such studies require expertise and resources. To overcome these challenges, we formed an academic-industry consortium to share molecular target identification efforts and expertise across academia and the pharmaceutical industry. The Renal Pre-Competitive Consortium (RPC2) aims to accelerate novel drug development for kidney diseases through a systems biology approach. Here, we describe the rationale, philosophy, establishment, and initial results of this strategy.

PMID: 29778696 [PubMed - as supplied by publisher]

Noninvasive diagnosis of endometriosis: Review of current peripheral blood and endometrial biomarkers.

Best Pract Res Clin Obstet Gynaecol. 2018 Apr 13;:

Authors: O DF, Flores I, Waelkens E, D'Hooghe T

Abstract
A noninvasive biomarker-based test could help shorten the diagnostic delay for endometriosis. The most investigated biomarker sources are peripheral blood and endometrium. Discovery of endometriosis biomarkers is often hypothesis-driven, i.e. when one or a few biomarkers are investigated based on their role in the disease pathogenesis. Alternatively, a hypothesis-generating approach has been followed using the "omics" technologies. A variety of biomarkers for endometriosis have been investigated, but no biomarker has been validated for clinical use. Many challenges lie ahead in the endometriosis biomarker field. In the future, harmonized collection and reporting methods should allow large-scale international collaboration for highly powered studies.

PMID: 29778458 [PubMed - as supplied by publisher]

Accelerated lipid catabolism and autophagy are cancer survival mechanisms under inhibited glutaminolysis.

Cancer Lett. 2018 May 16;:

Authors: Halama A, Kulinski M, Dib SS, Zaghlool SB, Siveen KS, Iskandarani A, Zierer J, Prabhu KS, Satheesh NJ, Bhagwat AM, Uddin S, Kastenmüller G, Elemento O, Gross SS, Suhre K

Abstract
Suppressing glutaminolysis does not always induce cancer cell death in glutamine dependent tumors because cells may switch to alternative energy sources. To reveal compensatory metabolic pathways, we investigated the metabolome-wide cellular response to inhibited glutaminolysis in cancer cells. Glutaminolysis inhibition with C.968 suppressed cell proliferation but was insufficient to induce cancer cell death. We found that lipid catabolism was activated as a compensation for glutaminolysis inhibition. Accelerated lipid catabolism, together with oxidative stress induced by glutaminolysis inhibition, triggered autophagy. Simultaneously inhibiting glutaminolysis and either beta oxidation with trimetazidine or autophagy with chloroquine both induced cancer cell death. Here we identified metabolic escape mechanisms contributing to cancer cell survival under treatment and we suggest potentially translational strategy for combined cancer therapy, given that chloroquine is an FDA approved drug. Our findings are first to show efficiency of combined inhibition of glutaminolysis and beta oxidation as potential anti-cancer strategy as well as add to the evidence that combined inhibition of glutaminolysis and autophagy may be effective in glutamine-addicted cancers.

PMID: 29777783 [PubMed - as supplied by publisher]