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Nexus between RNA conformational dynamics and functional versatility
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Empowering the molecular ruler techniques with unnatural base pair system to explore conformational dynamics of flaviviral RNAs
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Conformational penalties: New insights into nucleic acid recognition
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Using residue interaction networks to understand protein function and evolution and to engineer new proteins
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Engineering the native ensemble to tune protein function: Diverse mutational strategies and interlinked molecular mechanisms
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Deep learning for intrinsically disordered proteins: From improved predictions to deciphering conformational ensembles
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Biochemistry and genetics are coming together to improve our understanding of genotype to phenotype relationships
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Characterizing heterogeneity in amyloid formation processes
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Non-canonical amino acids for site-directed spin labeling of membrane proteins
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Characterizing protein-protein interactions with thermal proteome profiling
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Retraction notice to “Liquid-EM goes viral – visualizing structure and dynamics” [Curr Opin Struct Biol 75 (August 2022) 102426]
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Editorial overview: Protein networks in health and disease
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On the emergence of machine-learning methods in bottom-up coarse-graining
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Protein-nucleic acid complexes: Docking and binding affinity
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Protein data bank: From two epidemics to the global pandemic to mRNA vaccines and Paxlovid
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Binding mechanisms of intrinsically disordered proteins: Insights from experimental studies and structural predictions
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Editorial overview: 3D Genome Chromatin organization and regulation
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Editorial overview: New perspectives on the structure and dynamics of protein-nucleic acid interactions
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Advances in structure-based allosteric drug design
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Apprehensions and emerging solutions in ML-based protein structure prediction
Apprehensions and emerging solutions in ML-based protein structure prediction
The three-dimensional structure of proteins determines their function in vital biological processes. Thus, when the struct...
Generative artificial intelligence for de novo protein design
Generative artificial intelligence for de novo protein design
Engineering new molecules with desirable functions and properties has the potential to extend our ability to engineer prot...
Recent advances in data collection for Cryo-EM methods
Recent advances in data collection for Cryo-EM methods
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Modern approaches to improving phase contrast electron microscopy
Modern approaches to improving phase contrast electron microscopy
Although defocus can be used to generate partial phase contrast in transmission electron microscope images, cryo-electron ...
Confronting heterogeneity in cryogenic electron microscopy data: Innovative strategies and future perspectives with data-driven methods
Confronting heterogeneity in cryogenic electron microscopy data: Innovative strategies and future perspectives with data-driven methods
The surge in the influx of data from cryogenic electron microscopy (cryo-EM) experiments has intensified the demand for ro...
Graphene in cryo-EM specimen optimization
Graphene in cryo-EM specimen optimization
Specimen preparation is a critical but challenging step in high-resolution cryogenic electron microscopy (cryo-EM) structu...
Metamorphic proteins and how to find them
Metamorphic proteins and how to find them
In the last two decades, our existing notion that most foldable proteins have a unique native state has been challenged by...
Harnessing the 14-3-3 protein–protein interaction network
Harnessing the 14-3-3 protein–protein interaction network
Protein–protein interactions (PPIs) play a critical role in cellular signaling and represent interesting targets for thera...
Structural biology in the age of X-ray free-electron lasers and exascale computing
Structural biology in the age of X-ray free-electron lasers and exascale computing
Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of ...
Conformational changes of ribosomes during translation elongation resolved by molecular dynamics simulations
Conformational changes of ribosomes during translation elongation resolved by molecular dynamics simulations
Exascale computing provides access to unprecedented computational resources and it is worth considering the beneficial con...
How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms
How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms
Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high...
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