Roles of Fe-His Bonds in stability of Hemoglobin: Recognition of Protein Flexibility by Q Sepharose

2021 ◽  
Author(s):  
S. Nagatomo ◽  
T. Kitagawa ◽  
M. Nagai
Keyword(s):  
Protein Flexibility

scholarly journals Patterns in Protein Flexibility: A Comparison of NMR “Ensembles”, MD Trajectories, and Crystallographic B-Factors

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1484
Author(s):  
Christopher Reinknecht ◽  
Anthony Riga ◽  
Jasmin Rivera ◽  
David A. Snyder
Keyword(s):  
Protein Flexibility ◽  
Molecular Machines ◽  
Md Simulations ◽  
Peptide Bond ◽  
Structure Calculation ◽  
Atomic Scale ◽  
Heavy Atoms ◽  
Structural Ensembles ◽  
Atomic Coordinates ◽  
Motional Behavior

Proteins are molecular machines requiring flexibility to function. Crystallographic B-factors and Molecular Dynamics (MD) simulations both provide insights into protein flexibility on an atomic scale. Nuclear Magnetic Resonance (NMR) lacks a universally accepted analog of the B-factor. However, a lack of convergence in atomic coordinates in an NMR-based structure calculation also suggests atomic mobility. This paper describes a pattern in the coordinate uncertainties of backbone heavy atoms in NMR-derived structural “ensembles” first noted in the development of FindCore2 (previously called Expanded FindCore: DA Snyder, J Grullon, YJ Huang, R Tejero, GT Montelione, Proteins: Structure, Function, and Bioinformatics 82 (S2), 219–230) and demonstrates that this pattern exists in coordinate variances across MD trajectories but not in crystallographic B-factors. This either suggests that MD trajectories and NMR “ensembles” capture motional behavior of peptide bond units not captured by B-factors or indicates a deficiency common to force fields used in both NMR and MD calculations.

Gold nanoparticles and tilt pairs to assess protein flexibility by cryo-electron microscopy

2021 ◽  
pp. 113302
Author(s):  
Milind Jagota ◽  
Raphael J.L. Townshend ◽  
Lin-Woo Kang ◽  
David A. Bushnell ◽  
Ron O. Dror ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Gold Nanoparticles ◽  
Protein Flexibility ◽  
Cryo Electron Microscopy

Protein Flexibility and Adaptability Seen in 25 Crystal Forms of T4 Lysozyme

1995 ◽  
Vol 250 (4) ◽  
pp. 527-552 ◽  
Author(s):  
Xue-jun Zhang ◽  
Joan A. Wozniak ◽  
Brian W. Matthews
Keyword(s):  
Protein Flexibility ◽  
T4 Lysozyme ◽  
Crystal Forms

scholarly journals Predictions of protein flexibility: First-order measures

2004 ◽  
Vol 56 (4) ◽  
pp. 661-668 ◽  
Author(s):  
Julio A. Kovacs ◽  
Pablo Chacón ◽  
Ruben Abagyan
Keyword(s):  
Protein Flexibility ◽  
First Order

NMR: prediction of protein flexibility

2006 ◽  
Vol 1 (2) ◽  
pp. 683-688 ◽  
Author(s):  
Mark Berjanskii ◽  
David S Wishart
Keyword(s):  
Protein Flexibility ◽  
Nmr Prediction

scholarly journals B-Cell Epitope Discovery: The First Protein Flexibility-Based Algorithm – Zika Virus Conserved Epitope Demonstration

2020 ◽  
Author(s):  
Daniel W. Biner ◽  
Jason S. Grosch ◽  
Peter J. Ortoleva
Keyword(s):  
B Cell ◽  
Zika Virus ◽  
Clustering Algorithm ◽  
Cell Epitope ◽  
Protein Flexibility ◽  
Accessible Surface Area ◽  
Solvent Accessible Surface Area ◽  
B Cell Epitopes ◽  
Enveloped Virus ◽  
Epitope Discovery

<p></p><p>Antibody-antigen interaction – at antigenic local environments called B-cell epitopes – is a prominent mechanism for neutralization of infection. Effective mimicry, and display, of B-cell epitopes is key to vaccine design. Here, a physical approach is evaluated for the discovery of epitopes which evolve slowly over closely related pathogens (conserved epitopes). The approach is 1) protein flexibility-based and 2) demonstrated with clinically relevant enveloped viruses, simulated via molecular dynamics. The approach is validated against 1) seven structurally characterized enveloped virus epitopes which evolved the least (out of thirty-eight enveloped virus-antibody structures) and 2) eight preexisting epitope and peptide discovery algorithms. Rationale for a new benchmarking scheme is presented. A data-driven epitope clustering algorithm is introduced. The prediction of eleven Zika virus epitopes (for future exploration on recombinant vaccine technologies) is demonstrated. For the first time, protein flexibility is shown to outperform solvent accessible surface area as an epitope discovery metric.</p><p></p>

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