8 results on '"Cai, Chao"'
Search Results
2. Determinants of DNMT2/TRDMT1 preference for substrates tRNA and DNA during the evolution.
- Author
-
Li, Huari, Zhu, Daiyun, Yang, Yapeng, Ma, Yunfei, Chen, Yong, Xue, Pingfang, Chen, Juan, Qin, Mian, Xu, Dandan, Cai, Chao, and Cheng, Hongjing
- Subjects
TRANSFER RNA ,DNA ,GENE expression ,RNA ,CYTOSINE ,METHYLTRANSFERASES - Abstract
RNA methyltransferase DNMT2/TRDMT1 is the most conserved member of the DNMT family from bacteria to plants and mammals. In previous studies, we found some determinants for tRNA recognition of DNMT2/TRDMT1, but the preference mechanism of this enzyme for substrates tRNA and DNA remains to be explored. In the present study, CFT-containing target recognition domain (TRD) and target recognition extension domain (TRED) in DNMT2/TRDMT1 play a crucial role in the substrate DNA and RNA selection during the evolution. Moreover, the classical substrate tRNA for DNMT2/TRDMT1 had a characteristic sequence CUXXCAC in the anticodon loop. Position 35 was occupied by U, making cytosine-38 (C38) twist into the loop, whereas C, G or A was located at position 35, keeping the C38-flipping state. Hence, the substrate preference could be modulated by the easily flipped state of target cytosine in tRNA, as well as TRD and TRED. Additionally, DNMT2/TRDMT1 cancer mutant activity was collectively mediated by five enzymatic characteristics, which might impact gene expressions. Importantly, G155C, G155V and G155S mutations reduced enzymatic activities and showed significant associations with diseases using seven prediction methods. Altogether, these findings will assist in illustrating the substrate preference mechanism of DNMT2/TRDMT1 and provide a promising therapeutic strategy for cancer. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
3. New substrates and determinants for tRNA recognition of RNA methyltransferase DNMT2/TRDMT1.
- Author
-
Li, Huari, Zhu, Daiyun, Wu, Jian, Ma, Yunfei, Cai, Chao, Chen, Yong, Qin, Mian, and Dai, Hanchuan
- Subjects
TRANSFER RNA ,RNA ,TERTIARY structure ,METHYLATION kinetics ,CYTOSINE ,METHYLATION - Abstract
Methylation is a common post-transcriptional modification of tRNAs, particularly in the anticodon loop region. The cytosine 38 (C38) in tRNAs, such as tRNA
Asp-GUC , tRNAGly-GCC , tRNAVal-AAC , and tRNAGlu-CUC , can be methylated by human DNMT2/TRDMT1 and some homologs found in bacteria, plants, and animals. However, the substrate properties and recognition mechanism of DNMT2/TRDMT1 remain to be explored. Here, taking into consideration common features of the four known substrate tRNAs, we investigated methylation activities of DNMT2/TRDMT1 on the tRNAGly-GCC truncation and point mutants, and conformational changes of mutants. The results demonstrated that human DNMT2/TRDMT1 preferred substrate tRNAGly-GCC in vitro. L-shaped conformation of classical tRNA could be favourable for DNMT2/TRDMT1 activity. The complete sequence and structure of tRNA were dispensable for DNMT2/TRDMT1 activity, whereas T-arm was indispensable to this activity. G19, U20, and A21 in D-loop were identified as the important bases for DNMT2/TRDMT1 activity, while G53, C56, A58, and C61 in T-loop were found as the critical bases. The conserved CUXXCAC sequence in the anticodon loop was confirmed to be the most critical determinant, and it could stabilize C38-flipping to promote C38 methylation. Based on these tRNA properties, new substrates, tRNAVal-CAC and tRNAGln-CUG , were discovered in vitro. Moreover, a single nucleotide substitute, U32C, could convert non-substrate tRNAAla-AGC into a substrate for DNMT2/TRDMT1. Altogether, our findings imply that DNMT2/TRDMT1 relies on a delicate network involving both the primary sequence and tertiary structure of tRNA for substrate recognition. [ABSTRACT FROM AUTHOR]- Published
- 2021
- Full Text
- View/download PDF
4. Sampling Lasso quantile regression for large-scale data.
- Author
-
Xu, Qifa, Cai, Chao, Jiang, Cuixia, Sun, Fang, and Huang, Xue
- Subjects
- *
QUANTILE regression , *REGRESSION analysis , *LOGISTIC regression analysis , *MULTIPLE regression analysis , *PROBABILITY theory - Abstract
With the quantile regression methods successfully applied in various applications, we often need to tackle with the big dataset with thousands of variables and millions of observations. In this article, we focus on the variable selection aspect of penalized quantile regression, and propose a new method Sampling Lasso Quantile Regression (SLQR), which allows selecting a small amount but informative data for fitting quantile regression models. Different from the ordinary regularization methods, this SLQR method performs a sampling technique to reduce the number of observations before applying Lasso. Through numerical simulation studies and real application in Greenhouse Gas Observing Network, we illustrate the efficacy of the SLQR method. The numerical results show that the SLQR method is able to achieve a high-precision quantile regression on large-scale data for both prediction and interpretation. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
5. Structural Study of Sulfated Fuco-Oligosaccharide Branched Glucuronomannan from Kjellmaniella crassifolia by ESI-CID-MS/MS.
- Author
-
Wu, Jiandong, Lv, Youjing, Liu, Xiaoxiao, Zhao, Xiaoliang, Jiao, Guangling, Tai, Wenjing, Wang, Peipei, Zhao, Xia, Cai, Chao, and Yu, Guangli
- Subjects
OLIGOSACCHARIDES ,BROWN algae ,HYDROLYSIS ,ELECTROSPRAY ionization mass spectrometry ,SUBSTITUENTS (Chemistry) - Abstract
A polysaccharide was purified from brown algaKjellmaniella crassifolia, and its precise structure was deduced on the basis of sequence analysis of oligosaccharide fragments obtained from mildly and strongly acidic hydrolysis of the polysaccharide. Electrospray ionization collision-induced dissociation tandem mass spectrometry (ESI-CID-MS/MS) was used to identify the structural features of the resultant oligosaccharides. The side chain oligosaccharides were composed of α-1,3-linked 4-O-sulfated fucose and α-1,3-linked 2,4-O-disulfated fucose, while the backbone oligosaccharides consisted of the disaccharide repeating unit of β-1,4-linked glucuronic acid and α-1,2-linked mannose. Thus, the fucoidan was determined to be a sulfated fuco-oligosaccharide branched glucuronomannan. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
6. Strain Energy Calculations of Caged Silanes.
- Author
-
Ye, Cai-Chao, Zhao, Feng-Qi, and Ju, Xue-Hai
- Subjects
- *
SILANE compounds , *STRAINS & stresses (Mechanics) , *FORCE & energy , *CHEMICAL reactions , *DENSITY functionals , *ELECTRIC charge , *COMPARATIVE studies - Abstract
Strain energies (SE) of typical caged silanes were evaluated at the B3LYP/6-31+G** and B3LYP/aug-cc-pVDZ levels, in combination with the isodesmic and homodesmotic reactions. The SE values of Si4H4 and Si8H8 are 512 kJ/mol and 336–338 kJ/mol, respectively, at the B3LYP/6-31+G** level, whereas the SE values of the caged silanes with five-number or larger rings are very small. In comparison, the SE value of Si8H8 is much smaller than 656–707 kJ/mol of cubane (C8H8), since the Si‒Si bond length (2.274 Å) of Si8H8 is much larger than the corresponding C‒C bond length of cubane. The large electron charge density at body-center of Si4H4 causes strong repulsion between the cage center and Si‒Si bond, which leads to the Si‒Si bond bending. The electron charge density at the face center of Si4H4 is more than two times of that of Si8H8, which also contributes significantly to the large SE difference between Si4H4 and Si8H8. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
- View/download PDF
7. Theoretical Study on Thermodynamic Properties and Stabilities of n-Silanes.
- Author
-
Ye, Cai-Chao, Xie, Li-Feng, and Ju, Xue-Hai
- Subjects
- *
THERMODYNAMICS , *SILANE compounds , *DISSOCIATION (Chemistry) , *CHEMICAL bonds , *ATOMIZATION , *CHEMICAL reactions , *STABILITY (Mechanics) , *HEAT of formation - Abstract
First-principle computations were performed on the n-silane series (SinH2n+2, n = 1-10). The heat of formation (ΔfH), Gibbs free energy of formation (ΔfG), bond length, and bond dissociation energy (BDE) for both the Si-Si and Si-H bonds were predicted. The values of ΔfH and ΔfG from the accurate high level G3 method for lower silanes (n ≤ 5) were compared with experimental values and used as benchmarks. Thermodynamic properties derived from the G3 method in combination with the permutation reaction are in better agreement with experiments than those with the atomization reaction. The increments of the ΔfH and ΔfG values with an increasing SiH2-unit for n-silanes are 40.39 and 58.93 kJ/mol on average, respectively. The length of Si-Si bond increases slightly on average as the series number increases and then tends to be a constant for higher silanes. The BDEs for both the Si-Si and Si-H bonds initially decrease for lower silanes, and then approach a constant for higher silanes. The BDEs of the Si-Si bonds are smaller than those of Si-H bonds. The higher silanes are more unstable than the lower silanes. The average BDE of Si-Si bond at the MP2 level is ca. 302 kJ/mol, which is only half the experimental BDE value of the C-C bond (618 kJ/mol). GRAPHICAL ABSTRACT [image omitted] [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
8. The complete mitochondrial genome of Hemigrammus bleberi.
- Author
-
Li, Chunyan, Sun, Zhijing, Feng, Shouming, Jiang, Jufeng, Wu, Huimin, Zhang, Zhenguo, Cai, Chao, and Wang, Yongchen
- Subjects
HEMIGRAMMUS ,FISH phylogeny ,FISHES ,MITOCHONDRIAL DNA ,FISH genomes ,TRANSFER RNA ,RIBOSOMAL RNA - Abstract
The complete mitochondrial genome ofHemigrammus bleberiwas obtained by the traditional polymerase chain reaction (PCR)-based sequencing approach. The mitogenome ofH. bleberiwas determined as 17 021bp in length, including 13 protein-coding genes, 22 transfer RNA genes and 2 ribosomal RNA genes. Phylogenetic tree was constructed based on the complete mitogenomes of the species and closely related 21 teleost species to assess their phylogenetic relationship and evolution. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.