Efficacy of Base-Modification on Target Binding of Small Molecule DNA Aptamers

2013 ◽  
Vol 135 (25) ◽  
pp. 9412-9419 ◽  
Author(s):  
Yuri Imaizumi ◽  
Yuuya Kasahara ◽  
Hiroto Fujita ◽  
Shunsuke Kitadume ◽  
Hiroaki Ozaki ◽  
...  
2017 ◽  
Vol 9 (4) ◽  
pp. 233-268 ◽  
Author(s):  
Annamaria Ruscito ◽  
Erin M. McConnell ◽  
Anna Koudrina ◽  
Ranganathan Velu ◽  
Christopher Mattice ◽  
...  

2019 ◽  
Vol 87 (7-8) ◽  
pp. 231-239 ◽  
Author(s):  
Wenjing Li ◽  
Yu Luo ◽  
Tian Gao ◽  
Luyan Yang ◽  
Jine Wang ◽  
...  

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kelvin F. Cho ◽  
Taylur P. Ma ◽  
Christopher M. Rose ◽  
Donald S. Kirkpatrick ◽  
Kebing Yu ◽  
...  

2020 ◽  
Author(s):  
Ricardo J. Ferreira ◽  
Peter M. Kasson

AbstractThe Gram-negative bacterial outer membrane poses a major obstacle to the development of much-needed antibiotics against drug-resistant infections. Its chemical composition and porin proteins differ from Gram-positive bacteria and mammalian cells, and heuristics developed for mammalian cell uptake apply poorly. Recently, machine-learning methods have predicted small-molecule uptake into Gram-negative bacteria, offering the possibility to rationally optimize this aspect of antibiotic lead development. Here, we report physics-based methods to prospectively predict Gram-negative bacterial uptake, select, and synthesize promising chemical derivatives targeting E. coli DNA gyrase B. Our methods do not require empirical parameterization and are readily adaptable to new chemical scaffolds. These physics-based predictions well capture experimentally measured uptake (r > 0.95) and are indeed predictive of antimicrobial activity (r > 0.92). These methods can be used prospectively in combination with target-binding simulations to optimize both bacterial uptake and target binding, overcoming important barriers to antibiotic lead generation before small-molecule synthesis.


2021 ◽  
Vol 93 (6) ◽  
pp. 3172-3180
Author(s):  
Haixiang Yu ◽  
Yingping Luo ◽  
Obtin Alkhamis ◽  
Juan Canoura ◽  
Boyang Yu ◽  
...  
Keyword(s):  

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Delia J. Scoville ◽  
Tae Kyu Brian Uhm ◽  
Jamie A. Shallcross ◽  
Rebecca J. Whelan

CA125 is a mucin glycoprotein whose concentration in serum correlates with a woman’s risk of developing ovarian cancer and also indicates response to therapy in diagnosed patients. Accurate detection of this large, complex protein in patient samples is of great clinical relevance. We suggest that powerful new diagnostic tools may be enabled by the development of nucleic acid aptamers with affinity for CA125. Here, we report on our use of One-Pot SELEX to isolate single-stranded DNA aptamers with affinity for CA125, followed by high-throughput sequencing of the selected oligonucleotides. This data-rich approach, combined with bioinformatics tools, enabled the entire selection process to be characterized. Using fluorescence anisotropy and affinity probe capillary electrophoresis, the binding affinities of four aptamer candidates were evaluated. Two aptamers, CA125_1 and CA125_12, both without primers, were found to bind to clinically relevant concentrations of the protein target. Binding was differently influenced by the presence of Mg2+ions, being required for binding of CA125_1 and abrogating binding of CA125_12. In conclusion, One-Pot SELEX was found to be a promising selection method that yielded DNA aptamers to a clinically important protein target.


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