scholarly journals DNA-histone complexes as ligands amplify cell penetration and nuclear targeting of anti-DNA antibodies via energy-independent mechanisms

Immunology ◽  
2015 ◽  
Vol 147 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Markella Zannikou ◽  
Sofia Bellou ◽  
Petros Eliades ◽  
Aikaterini Hatzioannou ◽  
Michael D. Mantzaris ◽  
...  
Keyword(s):  
Cell Penetration ◽  
Nuclear Targeting ◽  
Dna Antibodies

Facile Preparation of Cationic Gold Nanoparticle-Bioconjugates for Cell Penetration and Nuclear Targeting

ACS Nano ◽  
2012 ◽  
Vol 6 (9) ◽  
pp. 7692-7702 ◽  
Author(s):  
Isaac Ojea-Jiménez ◽  
Lorena García-Fernández ◽  
Julia Lorenzo ◽  
Victor F. Puntes
Keyword(s):  
Gold Nanoparticle ◽  
Cell Penetration ◽  
Nuclear Targeting ◽  
Facile Preparation ◽  
Cationic Gold

scholarly journals Calreticulin, a Potential Cell Surface Receptor Involved in Cell Penetration of Anti-DNA Antibodies

2001 ◽  
Vol 166 (10) ◽  
pp. 6423-6429 ◽  
Author(s):  
Nabila Seddiki ◽  
Farida Nato ◽  
Pierre Lafaye ◽  
Zahir Amoura ◽  
Jean Charles Piette ◽  
...  
Keyword(s):  
Cell Surface ◽  
Cell Surface Receptor ◽  
Cell Penetration ◽  
Surface Receptor ◽  
Dna Antibodies

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

Nuclear Targeting: The first 60 years

2003 ◽  
Vol 59 (3) ◽  
pp. 60-65
Author(s):  
Arjun Makhijani
Keyword(s):  
Nuclear Targeting

A Novel Amino Acid Sequence-based Computational Approach to Predicting Cell-penetrating Peptides

2019 ◽  
Vol 15 (3) ◽  
pp. 206-211 ◽  
Author(s):  
Jihui Tang ◽  
Jie Ning ◽  
Xiaoyan Liu ◽  
Baoming Wu ◽  
Rongfeng Hu
Keyword(s):  
Machine Learning ◽  
Amino Acid ◽  
Amino Acid Position ◽  
Cell Penetrating Peptides ◽  
Support Vector ◽  
Cell Penetration ◽  
Drug Candidates ◽  
Machine Learning Model ◽  
Cell Penetrating ◽  
Novel Method

<P>Introduction: Machine Learning is a useful tool for the prediction of cell-penetration compounds as drug candidates. </P><P> Materials and Methods: In this study, we developed a novel method for predicting Cell-Penetrating Peptides (CPPs) membrane penetrating capability. For this, we used orthogonal encoding to encode amino acid and each amino acid position as one variable. Then a software of IBM spss modeler and a dataset including 533 CPPs, were used for model screening. </P><P> Results: The results indicated that the machine learning model of Support Vector Machine (SVM) was suitable for predicting membrane penetrating capability. For improvement, the three CPPs with the most longer lengths were used to predict CPPs. The penetration capability can be predicted with an accuracy of close to 95%. </P><P> Conclusion: All the results indicated that by using amino acid position as a variable can be a perspective method for predicting CPPs membrane penetrating capability.</P>

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