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A Transcriptomic Analysis and shRNA Screen for Intracellular Ion Channels and Transporters Regulating Pigmentation
Published in Bruno Gasnier, Michael X. Zhu, Ion and Molecule Transport in Lysosomes, 2020
Donald C. Koroma, Salwa Y. Hafez, Elena Oancea
An inherent characteristic of transcripts encoding melanosomal transporters, ion channels, and receptors is the presence of transmembrane domains. From the two sets of differentially expressed transcripts, we selected only those predicted to have >1 transmembrane domain based on UniProtKB database (www.uniprot.org). The Human Protein Atlas and GeneCards were then used to further select transcripts encoding proteins with predicted intracellular localization based on Compartments (compartments.jensenlab.org). We obtained 218 such transcripts common to both data sets, RR and H&O. We further selected these transcripts by calculating their fractional representation in HEMs compared to KERs, as shown in Figure 10.2A and setting the threshold to >10% enrichment in HEMs. The enrichment scores allowed for comparison of individual transcripts across both H&O and RR datasets and the scores for all the identified transcripts were positively correlated. In total, we obtained 182 transcripts that fulfilled all our selection criteria, not including known genes encoding melanosomal proteins. As expected, transcripts encoding known melanosomal proteins with a role in pigmentation, like OCA2, TPCN2, and SLC45A2 (the gene mutated in OCA4), fulfilled all the selection criteria, exhibiting a >80% enrichment in melanocytes (Figure 10.2B). A large majority of the 182 selected transcripts encode proteins with unknown function, in addition to other transcripts for which a function in melanocytes has not been characterized.
PI3K/AKT/SERBP-1 pathway regulates Alisma orientalis beverage treatment of atherosclerosis in APOE−/− high-fat diet mice
Published in Pharmaceutical Biology, 2023
Ruiyi Liu, Yan Sun, Dong Di, Xiyuan Zhang, Boran Zhu, Haoxin Wu
GeneCards is a searchable comprehensive database that automatically integrates gene-centric data from approximately 150 web sources, including genomics, transcriptomics, proteomics, genetics, clinical and functional information (Rebhan et al. 1997). With ‘Atherosclerosis’ as the keyword, relevant gene target information was searched in the GeneCards database (https://www.genecards.org) (Rebhan et al. 1997), and potential genes were supplemented using the TTD database (http://db.idrblab.net/ttd/) (Hamosh et al. 2005). When the number of targets is too large, the Score value in the Genecards database can be used for screening. The larger the score value, the closer the relationship between the target and the disease. The median of the Score value is used as the screening value. When there is too much data, multiple screening can be performed to obtain AS-related targets. The intersection of drug component-related targets and AS targets was operated by Venny2.1 (https://bioinfogp.cnb.csic.es/tools/venny/).
Study on mechanism of matrine in treatment of COVID-19 combined with liver injury by network pharmacology and molecular docking technology
Published in Drug Delivery, 2021
Fangzhou Liu, Yuanbai Li, Yang Yang, Meng Li, Yu Du, Yiying Zhang, Jing Wang, Yujing Shi
The targets related to COVID-19 were acquired from GeneCards (https://www.genecards.org/) and PubChem (https://pubchem.ncbi.nlm.nih.gov/). These two databases illuminate the relationship between targets and disease from different perspectives. GeneCards is a comprehensive, freely available database, which provides information about targets related to disease, gene expression, gene function, protein-protein interactions, pathways, and so on (Fishilevich et al., 2016). The search conditions were set to ‘gene’ and ‘Homo sapiens,’ and the authenticity of the related genes was determined by the literature search. On the other hand, in response to the COVID-19 epidemic, PubChem has set up a special exhibition project. The project is an international, community-driven effort. It aims to establish a knowledge repository on virus-host interaction mechanisms specific to the COVID-19 virus. We can click ‘browse COVID-19 data available in PubChem’ on the PubChem search page to obtain COVID-19 related targets.
Network pharmacology and molecular docking analysis on molecular targets and mechanisms of Huashi Baidu formula in the treatment of COVID-19
Published in Drug Development and Industrial Pharmacy, 2020
Quyuan Tao, Jiaxin Du, Xiantao Li, Jingyan Zeng, Bo Tan, Jianhua Xu, Wenjia Lin, Xin-lin Chen
GeneCards database (https://www.genecards.org/) and Therapeutic Target Database (TTD, https://db.idrblab.org/ttd/) were used to gather the information on COVID-19-associated target genes [28]. GeneCards is a comprehensive database of functions involving proteomics, genomics, and transcriptomics [29]. The keywords ‘novel coronavirus pneumonia,’ ‘cough,’ and ‘fever’ were utilized to screen the COVID-19-associated targets. The names of targets were collected from TTD, which provided information about the therapeutic protein targets, the corresponding ID of each targets and the targeted disease. The common targets of HSBDF and COVID-19 were then gathered as the core targets of HSBDF for COVID-19.