High-Throughput Electron Cryo-tomography of Protein Complexes and Their Assembly

2018 ◽  
pp. 29-44 ◽  
Author(s):  
Louie D. Henderson ◽  
Morgan Beeby
Keyword(s):  
High Throughput ◽  
Protein Complexes

scholarly journals High-throughput Isolation and Characterization of Untagged Membrane Protein Complexes: Outer Membrane Complexes ofDesulfovibrio vulgaris

2012 ◽  
Vol 11 (12) ◽  
pp. 5720-5735 ◽  
Author(s):  
Peter J. Walian ◽  
Simon Allen ◽  
Maxim Shatsky ◽  
Lucy Zeng ◽  
Evelin D. Szakal ◽  
...  
Keyword(s):  
Membrane Protein ◽  
Outer Membrane ◽  
High Throughput ◽  
Protein Complexes ◽  
Isolation And Characterization ◽  
Membrane Protein Complexes

scholarly journals Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS)

Methods ◽  
2017 ◽  
Vol 118-119 ◽  
pp. 171-181 ◽  
Author(s):  
Tzu-Fang Lou ◽  
Chase A. Weidmann ◽  
Jordan Killingsworth ◽  
Traci M. Tanaka Hall ◽  
Aaron C. Goldstrohm ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
In Vitro Selection ◽  
Rna Binding ◽  
Protein Complexes ◽  
Binding Protein ◽  
Rna Binding Protein ◽  
Integrated Analysis ◽  
Sequence Specificity

Seeing through protein complexes by high-throughput FRET

2008 ◽  
Vol 73A (5) ◽  
pp. 388-389 ◽  
Author(s):  
Peter Nagy ◽  
János Szöllősi
Keyword(s):  
High Throughput ◽  
Protein Complexes

scholarly journals The RNA polymerase factory: a robotic in vitro assembly platform for high-throughput production of recombinant protein complexes

2007 ◽  
Vol 36 (1) ◽  
pp. 245-252 ◽  
Author(s):  
Sven Nottebaum ◽  
Lin Tan ◽  
Dominika Trzaska ◽  
Hannah C. Carney ◽  
Robert O. J. Weinzierl
Keyword(s):  
Recombinant Protein ◽  
Rna Polymerase ◽  
High Throughput ◽  
Protein Complexes ◽  
In Vitro Assembly

scholarly journals Identifying protein complexes directly from high-throughput TAP data with Markov random fields

2007 ◽  
Vol 8 (1) ◽  
Author(s):  
Wasinee Rungsarityotin ◽  
Roland Krause ◽  
Arno Schödl ◽  
Alexander Schliep
Keyword(s):  
High Throughput ◽  
Random Fields ◽  
Markov Random Fields ◽  
Protein Complexes ◽  
Markov Random

scholarly journals A novel high-throughput approach for purification and reconstitution of large multi-protein complexes

2011 ◽  
Vol 67 (a1) ◽  
pp. C813-C813
Author(s):  
M. Calero ◽  
J. Guerrero ◽  
F. Pullara ◽  
Q. Zhang ◽  
H. Stevenson ◽  
...  
Keyword(s):  
High Throughput ◽  
Protein Complexes

scholarly journals MutateX: an automated pipeline for in-silico saturation mutagenesis of protein structures and structural ensembles

2019 ◽  
Author(s):  
Matteo Tiberti ◽  
Thilde Terkelsen ◽  
Tycho Canter Cremers ◽  
Miriam Di Marco ◽  
Isabelle da Piedade ◽  
...  
Keyword(s):  
Free Energy ◽  
High Throughput ◽  
In Silico ◽  
Protein Complexes ◽  
Protein Structures ◽  
Experimental Studies ◽  
Industrial Applications ◽  
Saturation Mutagenesis ◽  
Automated Pipeline ◽  
Protein Ensembles

AbstractMutations resulting in amino acid substitution influence the stability of proteins along with their binding to other biomolecules. A molecular understanding of the effects induced by protein mutations are both of biotechnological and medical relevance. The availability of empirical free energy functions that quickly estimate the free energy change upon mutation (ΔΔG) can be exploited for systematic screenings of proteins and protein complexes. Indeed, in silico saturation mutagenesis can guide the design of new experiments or rationalize the consequences of already-known mutations at the atomic level. Often software such as FoldX, while fast and reliable, lack the necessary automation features to make them useful in high-throughput scenarios. Here we introduce MutateX, a software which aims to automate the prediction of ΔΔGs associated with the systematic mutation of each available residue within a protein or protein complex to all other possible residue types, by employing the FoldX energy function. MutateX also supports ΔΔG calculations over protein ensembles and the estimation of the changes in free energy upon post-translational modifications. At the heart of MutateX lies an automated pipeline engine that handles input preparation, performs parallel runs with FoldX and outputs publication-ready figures. We here illustrate the MutateX protocol applied to the study of the mutational landscape of cancer-related proteins, industrial enzymes and protein-protein interfaces. The results of the high-throughput scan provided by our tools could help in different applications, such as the analysis of disease-associated mutations, or in the design of protein variants for experimental studies or industrial applications. MutateX is a collection of Python tools that relies on Open Source libraries and requires the FoldX software to be installed beforehand. It is available free of charge and under the GNU General Public License from https://github.com/ELELAB/mutatex.

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