protein gb1
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2021 ◽  
Vol 118 (16) ◽  
pp. e2010057118
Author(s):  
R. Charlotte Eccleston ◽  
David D. Pollock ◽  
Richard A. Goldstein

Epistasis and cooperativity of folding both result from networks of energetic interactions in proteins. Epistasis results from energetic interactions among mutants, whereas cooperativity results from energetic interactions during folding that reduce the presence of intermediate states. The two concepts seem intuitively related, but it is unknown how they are related, particularly in terms of selection. To investigate their relationship, we simulated protein evolution under selection for cooperativity and separately under selection for epistasis. Strong selection for cooperativity created strong epistasis between contacts in the native structure but weakened epistasis between nonnative contacts. In contrast, selection for epistasis increased epistasis in both native and nonnative contacts and reduced cooperativity. Because epistasis can be used to predict protein structure only if it preferentially occurs in native contacts, this result indicates that selection for cooperativity may be key for predicting structure using epistasis. To evaluate this inference, we simulated the evolution of guanine nucleotide-binding protein (GB1) with and without cooperativity. With cooperativity, strong epistatic interactions clearly map out the native GB1 structure, while allowing the presence of intermediate states (low cooperativity) obscured the structure. This indicates that using epistasis measurements to reconstruct protein structure may be inappropriate for proteins with stable intermediates.



2020 ◽  
Vol 29 (7) ◽  
pp. 078701
Author(s):  
Xiaofeng Zhang ◽  
Zilong Guo ◽  
Ping Yu ◽  
Qiushi Li ◽  
Xin Zhou ◽  
...  


2019 ◽  
Vol 10 (40) ◽  
pp. 9277-9284 ◽  
Author(s):  
Ruidi Wang ◽  
Jiayu Li ◽  
Xiumei Li ◽  
Jin Guo ◽  
Junqiu Liu ◽  
...  

Utilizing protein fragment reconstitution of a small protein GB1, we developed an efficient, supramolecular polymerization strategy to engineer protein polymers with ultrahigh molecular weight that mimic the giant muscle protein titin.



2018 ◽  
Author(s):  
Alberto Perez ◽  
Kari Gaalswyk ◽  
Christopher P. Jaroniec ◽  
Justin L. MacCallum

AbstractThere is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid-state NMR restraints with physics-based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi-quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid-state NMR data for the model protein GB1 labeled with Cu2+-EDTA at six different sites. We are able to determine the structure to ca. 1 Å accuracy within a single day of computation on a modest GPU cluster. We further show that in 4 of 6 cases, the data from only a single paramagnetic tag are sufficient to fold the protein to high accuracy.



Author(s):  
HuiFang Xiao ◽  
Bin Huang ◽  
Ge Yao ◽  
WenBin Kang ◽  
Sheng Gong ◽  
...  


2012 ◽  
Vol 103 (11) ◽  
pp. 2361-2368 ◽  
Author(s):  
Yongnan Devin Li ◽  
Guillaume Lamour ◽  
Jörg Gsponer ◽  
Peng Zheng ◽  
Hongbin Li




2012 ◽  
Vol 131 (5) ◽  
Author(s):  
Xiaomin Wu ◽  
Gang Yang ◽  
Lijun Zhou
Keyword(s):  


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