Results 111 to 120 of about 11,920,429 (358)

Protein—protein binding supersites

open access: yesPLOS Computational Biology, 2019
The lack of a deep understanding of how proteins interact remains an important roadblock in advancing efforts to identify binding partners and uncover the corresponding regulatory mechanisms of the functions they mediate. Understanding protein-protein interactions is also essential for designing specific chemical modifications to develop new reagents ...
Raji Viswanathan   +4 more
openaire   +5 more sources

Mechanisms and kinetic assays of aminoacyl‐tRNA synthetases

open access: yes
FEBS Letters, EarlyView.
Igor Zivkovic   +2 more
wiley   +1 more source

Aβ42 promotes the aggregation of α‐synuclein splice isoforms via heterogeneous nucleation

open access: yesFEBS Letters, EarlyView.
The aggregation of amyloid‐β (Aβ) and α‐synuclein (αSyn) is associated with Alzheimer's and Parkinson's diseases. This study reveals that Aβ aggregates serve as potent nucleation sites for the aggregation of αSyn and its splice isoforms, shedding light on the intricate interplay between these two pathogenic proteins.
Alexander Röntgen   +2 more
wiley   +1 more source

ERBIN limits epithelial cell plasticity via suppression of TGF‐β signaling

open access: yesFEBS Letters, EarlyView.
In breast and lung cancer patients, low ERBIN expression correlates with poor clinical outcomes. Here, we show that ERBIN inhibits TGF‐β‐induced epithelial‐to‐mesenchymal transition in NMuMG breast and A549 lung adenocarcinoma cell lines. ERBIN suppresses TGF‐β/SMAD signaling and reduces TGF‐β‐induced ERK phosphorylation.
Chao Li   +3 more
wiley   +1 more source

RosettaBackrub--a web server for flexible backbone protein structure modeling and design. [PDF]

open access: yes, 2010
The RosettaBackrub server (http://kortemmelab.ucsf.edu/backrub) implements the Backrub method, derived from observations of alternative conformations in high-resolution protein crystal structures, for flexible backbone protein modeling.
Friedland, Gregory F   +4 more
core   +2 more sources

Thermostable neutral metalloprotease from Geobacillus sp. EA1 does not share thermolysin's preference for substrates with leucine at the P1′ position

open access: yesFEBS Letters, EarlyView.
Knowing how proteases recognise preferred substrates facilitates matching proteases to applications. The S1′ pocket of protease EA1 directs cleavage to the N‐terminal side of hydrophobic residues, particularly leucine. The S1′ pocket of thermolysin differs from EA's at only one position (leucine in place of phenylalanine), which decreases cleavage ...
Grant R. Broomfield   +3 more
wiley   +1 more source

2D hybrid analysis: Approach for building three-dimensional atomic model by electron microscopy image matching

open access: yesScientific Reports, 2017
In this study, we develop an approach termed “2D hybrid analysis” for building atomic models by image matching from electron microscopy (EM) images of biological molecules.
Atsushi Matsumoto   +3 more
doaj   +1 more source

Negative Cooperativity in the Nitrogenase Fe Protein Electron Delivery Cycle [PDF]

open access: yes, 2016
Nitrogenase catalyzes the ATP-dependent reduction of dinitrogen (N2) to two ammonia (NH3) molecules through the participation of its two protein components, the MoFe and Fe proteins.
Antony, Edwin   +11 more
core   +2 more sources

Redox‐dependent binding and conformational equilibria govern the fluorescence decay of NAD(P)H in living cells

open access: yesFEBS Letters, EarlyView.
In this work, we reveal how different enzyme binding configurations influence the fluorescence decay of NAD(P)H in live cells using time‐resolved anisotropy imaging and fluorescence lifetime imaging microscopy (FLIM). Mathematical modelling shows that the redox states of the NAD and NADP pools govern these configurations, shaping their fluorescence ...
Thomas S. Blacker   +8 more
wiley   +1 more source

Cyclic peptide structure prediction and design using AlphaFold2

open access: yesNature Communications
Small cyclic peptides have gained significant traction as a therapeutic modality; however, the development of deep learning methods for accurately designing such peptides has been slow, mostly due to the lack of sufficiently large training sets. Here, we
Stephen A. Rettie   +16 more
doaj   +1 more source

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