scholarly journals Identification of a new lipolytic enzyme family and several novel nitrilases in metagenomic libraries

2009 ◽  
Vol 25 ◽  
pp. S72-S73
Author(s):  
S. Bayer ◽  
M. Ballschmiter ◽  
T. Greiner-Stoeffele
2016 ◽  
Vol 93 ◽  
pp. 655-664 ◽  
Author(s):  
Yian Hang ◽  
Shi Ran ◽  
Xiangyu Wang ◽  
Jingwen Jiao ◽  
Shunyao Wang ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (4) ◽  
pp. e60645 ◽  
Author(s):  
Lang Rao ◽  
Yanfen Xue ◽  
Yingying Zheng ◽  
Jian R. Lu ◽  
Yanhe Ma

Extremophiles ◽  
2008 ◽  
Vol 12 (3) ◽  
pp. 311-323 ◽  
Author(s):  
Donatella de Pascale ◽  
Angela M. Cusano ◽  
Flavia Autore ◽  
Ermenegilda Parrilli ◽  
Guido di Prisco ◽  
...  

2019 ◽  
Vol 20 (5) ◽  
pp. 540-550 ◽  
Author(s):  
Jiu-Xin Tan ◽  
Hao Lv ◽  
Fang Wang ◽  
Fu-Ying Dao ◽  
Wei Chen ◽  
...  

Enzymes are proteins that act as biological catalysts to speed up cellular biochemical processes. According to their main Enzyme Commission (EC) numbers, enzymes are divided into six categories: EC-1: oxidoreductase; EC-2: transferase; EC-3: hydrolase; EC-4: lyase; EC-5: isomerase and EC-6: synthetase. Different enzymes have different biological functions and acting objects. Therefore, knowing which family an enzyme belongs to can help infer its catalytic mechanism and provide information about the relevant biological function. With the large amount of protein sequences influxing into databanks in the post-genomics age, the annotation of the family for an enzyme is very important. Since the experimental methods are cost ineffective, bioinformatics tool will be a great help for accurately classifying the family of the enzymes. In this review, we summarized the application of machine learning methods in the prediction of enzyme family from different aspects. We hope that this review will provide insights and inspirations for the researches on enzyme family classification.


2021 ◽  
Vol 22 (14) ◽  
pp. 7560
Author(s):  
Julie A. Tucker ◽  
Mathew P. Martin

This special issue on Advances in Kinase Drug Discovery provides a selection of research articles and topical reviews covering all aspects of drug discovery targeting the phosphotransferase enzyme family [...]


Cancers ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 2042 ◽  
Author(s):  
Máté A. Demény ◽  
László Virág

The 17-member poly (ADP-ribose) polymerase enzyme family, also known as the ADP-ribosyl transferase diphtheria toxin-like (ARTD) enzyme family, contains DNA damage-responsive and nonresponsive members. Only PARP1, 2, 5a, and 5b are capable of modifying their targets with poly ADP-ribose (PAR) polymers; the other PARP family members function as mono-ADP-ribosyl transferases. In the last decade, PARP1 has taken center stage in oncology treatments. New PARP inhibitors (PARPi) have been introduced for the targeted treatment of breast cancer 1 or 2 (BRCA1/2)-deficient ovarian and breast cancers, and this novel therapy represents the prototype of the synthetic lethality paradigm. Much less attention has been paid to other PARPs and their potential roles in cancer biology. In this review, we summarize the roles played by all PARP enzyme family members in six intrinsic hallmarks of cancer: uncontrolled proliferation, evasion of growth suppressors, cell death resistance, genome instability, reprogrammed energy metabolism, and escape from replicative senescence. In a companion paper, we will discuss the roles of PARP enzymes in cancer hallmarks related to cancer-host interactions, including angiogenesis, invasion and metastasis, evasion of the anticancer immune response, and tumor-promoting inflammation. While PARP1 is clearly involved in all ten cancer hallmarks, an increasing body of evidence supports the role of other PARPs in modifying these cancer hallmarks (e.g., PARP5a and 5b in replicative immortality and PARP2 in cancer metabolism). We also highlight controversies, open questions, and discuss prospects of recent developments related to the wide range of roles played by PARPs in cancer biology. Some of the summarized findings may explain resistance to PARPi therapy or highlight novel biological roles of PARPs that can be therapeutically exploited in novel anticancer treatment paradigms.


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