2010
DOI: 10.1016/j.chembiol.2010.04.012
|View full text |Cite
|
Sign up to set email alerts
|

DNA Topoisomerases and Their Poisoning by Anticancer and Antibacterial Drugs

Abstract: DNA topoisomerases are the targets of important anticancer and antibacterial drugs. Camptothecins and novel noncamptothecins in clinical development (indenoisoquinolines and ARC-111) target eukaryotic type IB topoisomerases (Top1), whereas human type IIA topoisomerases (Top2alpha and Top2beta) are the targets of the widely used anticancer agents etoposide, anthracyclines (doxorubicin, daunorubicin), and mitoxantrone. Bacterial type II topoisomerases (gyrase and Topo IV) are the targets of quinolones and aminoc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

18
1,487
0
8

Year Published

2012
2012
2020
2020

Publication Types

Select...
10

Relationship

0
10

Authors

Journals

citations
Cited by 1,599 publications
(1,556 citation statements)
references
References 104 publications
(138 reference statements)
18
1,487
0
8
Order By: Relevance
“…Both these stabilize the covalent ternary complexes of the topoisomerases with DNA. DSBs can be formed when these complexes are encountered by the replication forks [Pommier et al, 2010].…”
Section: Degradation Of P12 and The Conversion Of Pol D4 To Pol D3 Inmentioning
confidence: 99%
“…Both these stabilize the covalent ternary complexes of the topoisomerases with DNA. DSBs can be formed when these complexes are encountered by the replication forks [Pommier et al, 2010].…”
Section: Degradation Of P12 and The Conversion Of Pol D4 To Pol D3 Inmentioning
confidence: 99%
“…18 Etoposide (Eto) is an anticancer drug that functions as a topoisomerase inhibitor. 19 Eto causes errors in DNA synthesis and promotes apoptosis in cancer cells. 20 Remarkably, when we treated cells with Eto, we found that NLK-deficient HCT116 cells showed increased resistance to DNA damage when compared with wild-type HCT116 cells (Figure 1a).…”
Section: Resultsmentioning
confidence: 99%
“…These layers are capable of extracting features from previous layers with ease. Stacking many of these layers together, we can form a convolutional neural network to automatically extract features from input single‐cell image and then perform classification 16, 17, 18…”
Section: Introductionmentioning
confidence: 99%