2- and 8-Azido photoaffinity probes. 1. Enzymic synthesis, characterization and biological properties of 2- and 8-azido photoprobes of 2-5A and photolabeling of 2-5A binding proteins

Biochemistry ◽  
1988 ◽  
Vol 27 (24) ◽  
pp. 8840-8846 ◽  
Author(s):  
Robert J. Suhadolnik ◽  
Katalin Kariko ◽  
Robert W. Sobol ◽  
Shi Wu Li ◽  
Nancy L. Reichenbach ◽  
...  
1993 ◽  
Vol 293 (3) ◽  
pp. 713-719 ◽  
Author(s):  
G L Francis ◽  
S E Aplin ◽  
S J Milner ◽  
K A McNeil ◽  
F J Ballard ◽  
...  

Recombinant insulin-like growth factor-II (IGF-II) and two structural analogues, des(1-6)IGF-II and [Arg6]-IGF-II, were produced to investigate the role of N-terminal residues in binding to IGF-binding proteins (IGFBPs) and hence the biological properties of the modified peptides. The growth factors were modelled on two previously characterized variants of IGF-I, des(1-3)IGF-I and [Arg3]-IGF-I, which both show substantially decreased binding to IGFBPs and were expressed as fusion proteins in Escherichia coli. The biological activities of the corresponding analogues of IGF-I and IGF-II were compared in rat L6 myoblasts and H35B hepatoma cells. In the L6-myoblast protein-synthesis assay, the IGF-II analogues, des(1-6)IGF-II and [Arg6]-IGF-II, were slightly more potent than IGF-II but about 10-fold less potent than IGF-I and 100-fold less potent than the respective IGF-I analogues, des(1-3)IGF-I and [Arg3]IGF-I. In H35 hepatoma cells the anabolic response measured was the inhibition of protein breakdown, and the potency order was insulin >>> [Arg3]-IGF-I > des(1-3)IGF-I > [Arg6]-IGF-II > des(1-6)IGF-II > IGF-I > IGF-II. Binding of the IGFs and their analogues to the type 1 IGF receptor in L6 myoblasts and to the insulin receptor in H35 hepatoma cells did not fully explain the observed anabolic potency differences. Moreover, binding of all four analogues to the IGFBPs secreted by L6 myoblasts and H35B hepatoma cells was greatly decreased compared with the parent IGF. We conclude that the observed anabolic response to each IGF was determined by their relative binding to the competing cell receptor and IGFBP binding sites present.


2017 ◽  
Vol 129 (10) ◽  
pp. 2788-2792 ◽  
Author(s):  
Jun Liang ◽  
Lin Zhang ◽  
Xiang-Long Tan ◽  
Yun-Kun Qi ◽  
Shan Feng ◽  
...  

2022 ◽  
Vol 3 (1) ◽  
pp. 101076
Author(s):  
Yingjie Hou ◽  
Heng Lu ◽  
Le Sun ◽  
Yaoyang Zhang ◽  
Hong Jiang

2016 ◽  
Author(s):  
Malvika Sharan ◽  
Konrad U. Förstner ◽  
Ana Eulalio ◽  
Jörg Vogel

ABSTRACTRNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs), and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches.We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using Position Specific Scoring Matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot


1992 ◽  
Vol 31 (5) ◽  
pp. 1459-1464 ◽  
Author(s):  
Michael H. Beale ◽  
Richard Hooley ◽  
Sally J. Smith ◽  
Robert P. Walker

2017 ◽  
Vol 56 (10) ◽  
pp. 2744-2748 ◽  
Author(s):  
Jun Liang ◽  
Lin Zhang ◽  
Xiang-Long Tan ◽  
Yun-Kun Qi ◽  
Shan Feng ◽  
...  

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