2019
DOI: 10.1002/pro.3578
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Obscurin is a semi‐flexible molecule in solution

Abstract: Obscurin, a giant modular cytoskeletal protein, is comprised mostly of tandem immunoglobulinlike (Ig-like) domains. This architecture allows obscurin to connect distal targets within the cell. The linkers connecting the Ig domains are usually short (3-4 residues). The physical effect arising from these short linkers is not known; such linkers may lead to a stiff elongated molecule or, conversely, may lead to a more compact and dynamic structure. In an effort to better understand how linkers affect obscurin fle… Show more

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Cited by 7 publications
(25 citation statements)
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References 62 publications
(98 reference statements)
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“…There have been strides to incorporate experimental techniques with computation, with efforts spanning back to the 1980s with NMR and X-ray crystallography and more recently EPR, MS, and cryo-EM among others. HDX experiments, originally probed in the 1970s, have been used to map exchange rates onto atomic-resolution structures to assign dynamic properties to otherwise static representations. , In the general case, HDX rates have also been coupled to molecular dynamics simulations to explain variation in different regions of a protein. , Additionally, these data have been incorporated into protein–protein docking of complexes with known tertiary structure to elucidate quaternary structure. However, importantly, HDX rates have not yet been used to predict de novo tertiary structure. Previous implementations for structural characterization rely on either homology modeling or some starting structures such as an alternative conformation of a protein or a designed protein. While there are multiple software packages with impressive results that exist for ab initio structure prediction, such as the co-evolution-dependent neural network AlphaFold, the secondary structure assembling BCL, or iterative threading I-TASSER, none have been coupled to experimental data as frequently or diversely as the Rosetta Modeling Software. ,,,,, Rosetta ab initio structure prediction allows for the generation of models from amino acid sequence alone, assembling fragments generated from short segments with similar sequences using Monte Carlo sampling combined with a hybrid classical physics and probabilistic knowledge-based scoring function in both coarse-grained and full-atom modeling, similar to other multiscale modeling methods. ,…”
Section: Introductionmentioning
confidence: 99%
“…There have been strides to incorporate experimental techniques with computation, with efforts spanning back to the 1980s with NMR and X-ray crystallography and more recently EPR, MS, and cryo-EM among others. HDX experiments, originally probed in the 1970s, have been used to map exchange rates onto atomic-resolution structures to assign dynamic properties to otherwise static representations. , In the general case, HDX rates have also been coupled to molecular dynamics simulations to explain variation in different regions of a protein. , Additionally, these data have been incorporated into protein–protein docking of complexes with known tertiary structure to elucidate quaternary structure. However, importantly, HDX rates have not yet been used to predict de novo tertiary structure. Previous implementations for structural characterization rely on either homology modeling or some starting structures such as an alternative conformation of a protein or a designed protein. While there are multiple software packages with impressive results that exist for ab initio structure prediction, such as the co-evolution-dependent neural network AlphaFold, the secondary structure assembling BCL, or iterative threading I-TASSER, none have been coupled to experimental data as frequently or diversely as the Rosetta Modeling Software. ,,,,, Rosetta ab initio structure prediction allows for the generation of models from amino acid sequence alone, assembling fragments generated from short segments with similar sequences using Monte Carlo sampling combined with a hybrid classical physics and probabilistic knowledge-based scoring function in both coarse-grained and full-atom modeling, similar to other multiscale modeling methods. ,…”
Section: Introductionmentioning
confidence: 99%
“…Models of the sMyBP‐C M‐motif were generated using Phyre2 based on the respective human cMyBP‐C domain (PBD: 2LH4; 80% identical to sMyBP‐C) (Howarth, Ramisetti, Nolan, Sadavappan, & Rosevear, ; Kelley, Mezulis, Yates, Wass, & Sternberg, ). The model was allowed to equilibrate using the computer program YASARA for ~90 ns (Rossi et al, ; Whitley et al, ). Substitutions were introduced to the model via the “swap” command, and the resulting models were allowed to equilibrate for an additional ~100 ns.…”
Section: Methodsmentioning
confidence: 99%
“…The N‐terminus of human obscurin A (accession number CAC44768), spanning residues 1–5470, comprises of over 50 independently‐folded Ig or FnIII‐like domains, arranged in tandem (Figure 1). 37 This large region can be further divided into two sub‐regions, depending on the linker lengths, that connect neighboring Ig domains to each other (Table S1). The area between Ig1 and Ig18 mostly has longer ~7‐residue linkers, while the area between Ig18 and Ig51 usually contains ~5‐residue linkers 37 .…”
Section: Introductionmentioning
confidence: 99%
“… 37 This large region can be further divided into two sub‐regions, depending on the linker lengths, that connect neighboring Ig domains to each other (Table S1). The area between Ig1 and Ig18 mostly has longer ~7‐residue linkers, while the area between Ig18 and Ig51 usually contains ~5‐residue linkers 37 . All obscurin linkers have been defined previously as the sequence between the final lysine (or equivalent residue) at the exiting beta strand G to the first lysine (or equivalent) of the next domain, using obscurin Ig37/38 as a reference dual‐domain system 37 .…”
Section: Introductionmentioning
confidence: 99%
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