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Keywords = QSER

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18 pages, 10864 KiB  
Article
Presenilin-1-Derived Circular RNAs: Neglected Epigenetic Regulators with Various Functions in Alzheimer’s Disease
by Nima Sanadgol, Javad Amini, Cordian Beyer and Adib Zendedel
Biomolecules 2023, 13(9), 1401; https://doi.org/10.3390/biom13091401 - 17 Sep 2023
Cited by 7 | Viewed by 3042
Abstract
The presenilin-1 (PSEN1) gene is crucial in developing Alzheimer’s disease (AD), a progressive neurodegenerative disorder and the most common cause of dementia. Circular RNAs (circRNAs) are non-coding RNA generated through back-splicing, resulting in a covalently closed circular molecule. This study aimed to investigate [...] Read more.
The presenilin-1 (PSEN1) gene is crucial in developing Alzheimer’s disease (AD), a progressive neurodegenerative disorder and the most common cause of dementia. Circular RNAs (circRNAs) are non-coding RNA generated through back-splicing, resulting in a covalently closed circular molecule. This study aimed to investigate PSEN1-gene-derived circular RNAs (circPSEN1s) and their potential functions in AD. Our in silico analysis indicated that circPSEN1s (hsa_circ_0008521 and chr14:73614502-73614802) act as sponge molecules for eight specific microRNAs. Surprisingly, two of these miRNAs (has-mir-4668-5p and has-mir-5584-5p) exclusively interact with circPSEN1s rather than mRNA-PSEN1. Furthermore, the analysis of pathways revealed that these two miRNAs predominantly target mRNAs associated with the PI3K-Akt signaling pathway. With sponging these microRNAs, circPSEN1s were found to protect mRNAs commonly targeted by these miRNAs, including QSER1, BACE2, RNF157, PTMA, and GJD3. Furthermore, the miRNAs sequestered by circPSEN1s have a notable preference for targeting the TGF-β and Hippo signaling pathways. We also demonstrated that circPSEN1s potentially interact with FOXA1, ESR1, HNF1B, BRD4, GATA4, EP300, CBX3, PRDM9, and PPARG proteins. These proteins have a prominent preference for targeting the TGF-β and Notch signaling pathways, where EP300 and FOXA1 have the highest number of protein interactions. Molecular docking analysis also confirms the interaction of these hub proteins and Aβ42 with circPSEN1s. Interestingly, circPSEN1s-targeted molecules (miRNAs and proteins) impacted TGF-β, which served as a shared signaling pathway. Finally, the analysis of microarray data unveiled distinct expression patterns of genes influenced by circPSEN1s (WTIP, TGIF, SMAD4, PPP1CB, and BMPR1A) in the brains of AD patients. In summary, our findings suggested that the interaction of circPSEN1s with microRNAs and proteins could affect the fate of specific mRNAs, interrupt the function of unique proteins, and influence cell signaling pathways, generally TGF-β. Further research is necessary to validate these findings and gain a deeper understanding of the precise mechanisms and significance of circPSEN1s in the context of AD. Full article
(This article belongs to the Special Issue Circular RNAs: Functions, Applications and Prospects)
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13 pages, 2114 KiB  
Article
Quantitative Structure–Electrochemistry Relationship (QSER) Studies on Metal–Amino–Porphyrins for the Rational Design of CO2 Reduction Catalysts
by Furong Chen, Amphawan Wiriyarattanakul, Wanting Xie, Liyi Shi, Thanyada Rungrotmongkol, Rongrong Jia and Phornphimon Maitarad
Molecules 2023, 28(7), 3105; https://doi.org/10.3390/molecules28073105 - 30 Mar 2023
Cited by 1 | Viewed by 2160
Abstract
The quantitative structure–electrochemistry relationship (QSER) method was applied to a series of transition-metal-coordinated porphyrins to relate their structural properties to their electrochemical CO2 reduction activity. Since the reactions mainly occur within the core of the metalloporphyrin catalysts, the cluster model was used [...] Read more.
The quantitative structure–electrochemistry relationship (QSER) method was applied to a series of transition-metal-coordinated porphyrins to relate their structural properties to their electrochemical CO2 reduction activity. Since the reactions mainly occur within the core of the metalloporphyrin catalysts, the cluster model was used to calculate their structural and electronic properties using density functional theory with the M06L exchange–correlation functional. Three dependent variables were employed in this work: the Gibbs free energies of H*, C*OOH, and O*CHO. QSER, with the genetic algorithm combined with multiple linear regression (GA–MLR), was used to manipulate the mathematical models of all three Gibbs free energies. The obtained statistical values resulted in a good predictive ability (R2 value) greater than 0.945. Based on our QSER models, both the electronic properties (charges of the metal and porphyrin) and the structural properties (bond lengths between the metal center and the nitrogen atoms of the porphyrin) play a significant role in the three Gibbs free energies. This finding was further applied to estimate the CO2 reduction activities of the metal–monoamino–porphyrins, which will prove beneficial in further experimental developments. Full article
(This article belongs to the Special Issue Design, Synthesis and Applications of Supported Metal Catalysts)
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14 pages, 698 KiB  
Article
Identification of Novel Candidate Markers of Type 2 Diabetes and Obesity in Russia by Exome Sequencing with a Limited Sample Size
by Yury A. Barbitoff, Elena A. Serebryakova, Yulia A. Nasykhova, Alexander V. Predeus, Dmitrii E. Polev, Anna R. Shuvalova, Evgenii V. Vasiliev, Stanislav P. Urazov, Andrey M. Sarana, Sergey G. Scherbak, Dmitrii V. Gladyshev, Maria S. Pokrovskaya, Oksana V. Sivakova, Aleksey N. Meshkov, Oxana M. Drapkina, Oleg S. Glotov and Andrey S. Glotov
Genes 2018, 9(8), 415; https://doi.org/10.3390/genes9080415 - 17 Aug 2018
Cited by 25 | Viewed by 6940
Abstract
Type 2 diabetes (T2D) and obesity are common chronic disorders with multifactorial etiology. In our study, we performed an exome sequencing analysis of 110 patients of Russian ethnicity together with a multi-perspective approach based on biologically meaningful filtering criteria to detect novel candidate [...] Read more.
Type 2 diabetes (T2D) and obesity are common chronic disorders with multifactorial etiology. In our study, we performed an exome sequencing analysis of 110 patients of Russian ethnicity together with a multi-perspective approach based on biologically meaningful filtering criteria to detect novel candidate variants and loci for T2D and obesity. We have identified several known single nucleotide polymorphisms (SNPs) as markers for obesity (rs11960429), T2D (rs9379084, rs1126930), and body mass index (BMI) (rs11553746, rs1956549 and rs7195386) (p < 0.05). We show that a method based on scoring of case-specific variants together with selection of protein-altering variants can allow for the interrogation of novel and known candidate markers of T2D and obesity in small samples. Using this method, we identified rs328 in LPL (p = 0.023), rs11863726 in HBQ1 (p = 8 × 10−5), rs112984085 in VAV3 (p = 4.8 × 10−4) for T2D and obesity, rs6271 in DBH (p = 0.043), rs62618693 in QSER1 (p = 0.021), rs61758785 in RAD51B (p = 1.7 × 10−4), rs34042554 in PCDHA1 (p = 1 × 10−4), and rs144183813 in PLEKHA5 (p = 1.7 × 10−4) for obesity; and rs9379084 in RREB1 (p = 0.042), rs2233984 in C6orf15 (p = 0.030), rs61737764 in ITGB6 (p = 0.035), rs17801742 in COL2A1 (p = 8.5 × 10−5), and rs685523 in ADAMTS13 (p = 1 × 10−6) for T2D as important susceptibility loci in Russian population. Our results demonstrate the effectiveness of whole exome sequencing (WES) technologies for searching for novel markers of multifactorial diseases in cohorts of limited size in poorly studied populations. Full article
(This article belongs to the Special Issue Computational Approaches for Disease Gene Identification)
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