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Institution

Randall Division of Cell and Molecular Biophysics

About: Randall Division of Cell and Molecular Biophysics is a based out in . It is known for research contribution in the topics: Actin cytoskeleton & Skeletal muscle. The organization has 576 authors who have published 1229 publications receiving 78279 citations.


Papers
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Journal ArticleDOI
TL;DR: A review looks at recent advances that have been made in understanding of cofactor-independent oxygenases highlighting the power of an inter-disciplinary approach involving structural biology, spectroscopy and theoretical methods.

31 citations

Journal ArticleDOI
TL;DR: A new stepwise hierarchical model for kinesin-1 activation is proposed, whereby tryptophan-acidic cargo is first recognized by KLCs, resulting in destabilization of KHC autoinhibition, and a second SKIP-binding site on the KHC C-terminal tail is made accessible.
Abstract: The molecular interplay between cargo recognition and regulation of the activity of the kinesin-1 microtubule motor is not well understood. Using the lysosome adaptor SKIP (also known as PLEKHM2) as model cargo, we show that the kinesin heavy chains (KHCs), in addition to the kinesin light chains (KLCs), can recognize tryptophan-acidic-binding determinants on the cargo when presented in the context of an extended KHC-interacting domain. Mutational separation of KHC and KLC binding shows that both interactions are important for SKIP-kinesin-1 interaction in vitro and that KHC binding is important for lysosome transport in vivo However, in the absence of KLCs, SKIP can only bind to KHC when autoinhibition is relieved, suggesting that the KLCs gate access to the KHCs. We propose a model whereby tryptophan-acidic cargo is first recognized by KLCs, resulting in destabilization of KHC autoinhibition. This primary event then makes accessible a second SKIP-binding site on the KHC C-terminal tail that is adjacent to the autoinhibitory IAK region. Thus, cargo recognition and concurrent activation of kinesin-1 proceed in hierarchical stepwise fashion driven by a dynamic network of inter- and intra-molecular interactions.

31 citations

Journal ArticleDOI
TL;DR: These techniques demonstrate it is possible to image retrograde flow of filamentous-actin at superresolution and provide flow quantification in the form of velocity histograms and flow vector maps.

31 citations

Journal ArticleDOI
TL;DR: These results demonstrate that GAAPs are ion channels and define residues that contribute to the ion-conducting pore and affect apoptosis, cell adhesion, and migration independently.

31 citations

Journal ArticleDOI
TL;DR: Analysis of the exon distribution of mutations within the EMD gene, suggests a nonrandom distribution, with exon 2 as a hot spot, which may be due to its high GC content, which at 60% is the most GC-rich exon in the E MD gene.
Abstract: Emery-Dreifuss muscular dystrophy (EDMD) is a neuromuscular disorder exhibiting a cardiomyopathy with cardiac conduction defects. X-linked EDMD arises from mutations in the EMD gene, which encodes for a nuclear membrane protein termed emerin. In this study, we describe novel and recurrent EMD mutations identified in 18 probands and three carriers from a cohort of 255 North American patients referred for EDMD genetic mutation analysis. Eight of these mutations are novel including six frameshift mutations (p.D9GfsX24, p.F39SfsX17, p.R45KfsX16, p.F190YfsX19, p.R203PfsX34 and p.R204PfsX7) and two non-sense mutations (p.S143X, p.W200X). Our data augment the number of EMD mutations by 13.8%, equating to an increase of 5.2% in the total known EMD mutations and to an increase of 6.0% in the number of different mutations. Analysis of the exon distribution of mutations within the EMD gene, suggests a nonrandom distribution, with exon 2 as a hot spot. This phenomenon may be due to its high GC content, which at 60% is the most GC-rich exon in the EMD gene.

30 citations


Authors

Showing all 576 results

NameH-indexPapersCitations
Janet M. Thornton130539105144
Graham Dunn10148437152
Anne J. Ridley9625647563
Luigi Cavallo7954625262
Erik Sahai6914324753
Christopher Corrigan6927722451
Mathias Gautel6915916377
Hannah J. Gould6020711436
Enrico Girardi5936812712
Paul Brown5925113251
John G. Parnavelas5816411046
Heinz Jungbluth5721113707
Gareth E. Jones551619816
Linda J. Richards5415410093
Elisabeth Ehler541328503
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202115
202026
201926
201848
201788
2016113