The novel targets of DL-3-n-butylphthalide predicted by similarity ensemble approach in combination with molecular docking study

Wang, Yan; Qi, Wei; Zhang, Li; Ying, Zhenguang; Sha, Ou; Li, Chunman; Lü, Lei; Chen, Xiangyan; Li, Zhenzhong; Niu, Feng; Xue, Fang; Wang, Dong; Ng, Tat Fong; Zhang, Lihong

doi:10.21037/qims.2017.10.08

Cited by 13 publications

(15 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A large number of experiments at home and abroad have revealed that NBP can regulate brain energy metabolism (Yan, Wang, Yao, Liu, & Xiao, ), protect the mitochondria (Min et al, ), promote normal blood flow in the ischemic area (Xu et al, ), inhibit oxidative stress and platelet aggregation (Li et al, ; Zhao, Li, Zhang, Chen, & Li, ), and prevent the vigorous apoptosis of cells (Min et al, ). In addition, Chinese scholars found that NBP plays a neuroprotective role by acting on multiple active targets (Wang et al, ; Zhao et al, ). Furthermore, some scholars considered that the effective rate of NBP in treating ACI can reach 76%–93% (Offner et al, ).…”

Section: Discussionmentioning

confidence: 99%

Effects of dl‐3‐n‐butylphthalide on serum lipoprotein‐associated phospholipase A2 and hypersensitive C‐reactive protein levels in acute cerebral infarction

Zhang¹,

Dong²,

Liu³

et al. 2019

Brain and Behavior

View full text Add to dashboard Cite

ObjectiveThis study aims to explore the curative effect of dl‐3‐n‐butylphthalide (NBP) on patients with acute cerebral infarction (ACI) and its effects on serum lipoprotein‐associated phospholipase A2 (Lp‐PLA2) and hypersensitive C‐reactive protein (hs‐CRP) levels.MethodsA total of 136 ACI patients treated in our hospital, who met the criteria, were selected and randomly divided into two groups: control group (n = 60, including 28 males and 32 females) and treatment group (n = 76, including 32 males and 44 females). Patients in the control group were treated with routine drug therapy, while patients in the treatment group were treated with NBP on this basis. A dose of 100 ml was administered by intravenous injection for 2 times/day, for 14 days. The curative effect was evaluated using the National Institute of Health Stroke Scale (NIHSS) and Barthel index (BI) self‐care ability. The levels of the two factors in serum were measured using enzyme‐linked immunosorbent assay, and the changes in levels of these two factors in serum at different time points before and after treatment were compared between the two groups.Results(a) Lp‐PLA2 and hs‐CRP levels in the treatment group after treatment were significantly lower than those before treatment and those in the control group after treatment (p < .05). (b) The NIHSS and BI scores in the treatment group were significantly lower after treatment than before treatment and those in the control group after treatment (p < .05).ConclusionDl‐3‐n‐butylphthalide can improve the expression of Lp‐PLA2 and hs‐CRP in serum in ACI patients. Furthermore, NBP has significant efficacy in inhibiting inflammation and improving neurological symptoms.

show abstract

Section: Discussionmentioning

confidence: 99%

Effects of dl‐3‐n‐butylphthalide on serum lipoprotein‐associated phospholipase A2 and hypersensitive C‐reactive protein levels in acute cerebral infarction

Zhang¹,

Dong²,

Liu³

et al. 2019

Brain and Behavior

View full text Add to dashboard Cite

show abstract

“…Nie et al [60], Bai et al [61], Cai et al [62,63] adopted graph Laplacian matrix to keep the graph’s local structure. Moreover, the Studies [34,64–67] revealed that the combination of multiple similarities helps to improve performances. Inspired by pioneer work, we define a novel ensemble graph Laplacian regularization: where D i is a diagonal matrix whose diagonal elements are corresponding row sums of W i , and θ = [ θ 1 , θ 2 ,⋯, θ i ,⋯, θ m ] is a weight vector which is introduced to control the contribution of different graph Laplacian regularizations, and tr (∙) is the trace of a matrix.…”

Section: Methodsmentioning

confidence: 99%

SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions

et al. 2018

View full text Add to dashboard Cite

LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational methods utilize multiple lncRNA features or multiple protein features to predict lncRNA-protein interactions, but features are not available for all lncRNAs or proteins; most of existing methods are not capable of predicting interacting proteins (or lncRNAs) for new lncRNAs (or proteins), which don’t have known interactions. In this paper, we propose the sequence-based feature projection ensemble learning method, “SFPEL-LPI”, to predict lncRNA-protein interactions. First, SFPEL-LPI extracts lncRNA sequence-based features and protein sequence-based features. Second, SFPEL-LPI calculates multiple lncRNA-lncRNA similarities and protein-protein similarities by using lncRNA sequences, protein sequences and known lncRNA-protein interactions. Then, SFPEL-LPI combines multiple similarities and multiple features with a feature projection ensemble learning frame. In computational experiments, SFPEL-LPI accurately predicts lncRNA-protein associations and outperforms other state-of-the-art methods. More importantly, SFPEL-LPI can be applied to new lncRNAs (or proteins). The case studies demonstrate that our method can find out novel lncRNA-protein interactions, which are confirmed by literature. Finally, we construct a user-friendly web server, available at http://www.bioinfotech.cn/SFPEL-LPI/.

show abstract

“…Focusing proteins in drug discovery direct the way to finding the best lead compound, with high efficacy at the lowest micromolar concentrations. Numerous software tools for protein-ligand dockings, such as Autodock, DOCK 4.0, GOLD, Flex-X, ICM, SLIDE, GLIDE, and DeepBindRG, were developed based on various scoring functions, including empirical, knowledge-based, and machine learning, and are summarized in Table 2 [50,[115][116][117][118][119][120][121][122][123][124][125][126][127][128][129][130]. The field of drug designing has been rapidly advancing in recent decades, and many new state-of-the-art technologies and methods have been discovered [20,[104][105][106][107][108][109][110][111][112][113][114].…”

Section: Challenges and Opportunities In Targeting Ctdsp1mentioning

confidence: 99%

Targeting the C-Terminal Domain Small Phosphatase 1

Rallabandi

Ganesan

Kim

2020

Life

View full text Add to dashboard Cite

The human C-terminal domain small phosphatase 1 (CTDSP1/SCP1) is a protein phosphatase with a conserved catalytic site of DXDXT/V. CTDSP1’s major activity has been identified as dephosphorylation of the 5th Ser residue of the tandem heptad repeat of the RNA polymerase II C-terminal domain (RNAP II CTD). It is also implicated in various pivotal biological activities, such as acting as a driving factor in repressor element 1 (RE-1)-silencing transcription factor (REST) complex, which silences the neuronal genes in non-neuronal cells, G1/S phase transition, and osteoblast differentiation. Recent findings have denoted that negative regulation of CTDSP1 results in suppression of cancer invasion in neuroglioma cells. Several researchers have focused on the development of regulating materials of CTDSP1, due to the significant roles it has in various biological activities. In this review, we focused on this emerging target and explored the biological significance, challenges, and opportunities in targeting CTDSP1 from a drug designing perspective.

show abstract

The novel targets of DL-3-n-butylphthalide predicted by similarity ensemble approach in combination with molecular docking study

Cited by 13 publications

References 17 publications

Effects of dl‐3‐n‐butylphthalide on serum lipoprotein‐associated phospholipase A2 and hypersensitive C‐reactive protein levels in acute cerebral infarction

Effects of dl‐3‐n‐butylphthalide on serum lipoprotein‐associated phospholipase A2 and hypersensitive C‐reactive protein levels in acute cerebral infarction

SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions

Targeting the C-Terminal Domain Small Phosphatase 1

Contact Info

Product

Resources

About