Open Access. Powered by Scholars. Published by Universities.®
- Publication Type
Articles 1 - 2 of 2
Full-Text Articles in Molecular Biology
Inhibition Of Apobec3g Activity Impedes Double-Stranded Dna Repair, Ponnandy Prabhu, Shivender Shandilya, Elena Britan-Rosich, Adi Nagler, Celia Schiffer, Moshe Kotler
Inhibition Of Apobec3g Activity Impedes Double-Stranded Dna Repair, Ponnandy Prabhu, Shivender Shandilya, Elena Britan-Rosich, Adi Nagler, Celia Schiffer, Moshe Kotler
Celia A. Schiffer
The cellular cytidine deaminase APOBEC3G (A3G) was first described as an anti-HIV-1 restriction factor, acting by directly deaminating reverse transcripts of the viral genome. HIV-1 Vif neutralizes the activity of A3G, primarily by mediating degradation of A3G to establish effective infection in host target cells. Lymphoma cells, which express high amounts of A3G, can restrict Vif-deficient HIV-1. Interestingly, these cells are more stable in the face of treatments that result in double-stranded DNA damage, such as ionizing radiation and chemotherapies. Previously, we showed that the Vif-derived peptide (Vif25-39) efficiently inhibits A3G deamination, and increases the sensitivity of lymphoma cells to …
Achieving High Accuracy Prediction Of Minimotifs, Tian Mi, Sanguthevar Rajasekaran, Jerlin Camilus Merlin, Michael R. Gryk, Martin Schiller
Achieving High Accuracy Prediction Of Minimotifs, Tian Mi, Sanguthevar Rajasekaran, Jerlin Camilus Merlin, Michael R. Gryk, Martin Schiller
Life Sciences Faculty Research
The low complexity of minimotif patterns results in a high false-positive prediction rate, hampering protein function prediction. A multi-filter algorithm, trained and tested on a linear regression model, support vector machine model, and neural network model, using a large dataset of verified minimotifs, vastly improves minimotif prediction accuracy while generating few false positives. An optimal threshold for the best accuracy reaches an overall accuracy above 90%, while a stringent threshold for the best specificity generates less than 1% false positives or even no false positives and still produces more than 90% true positives for the linear regression and neural network …