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Abstract Transcription factors carry long intrinsically disordered regions often containing multiple activation domains. Despite numerous recent high‐throughput identifications and characterizations of activation domains, the interplay between sequence motifs, activation domains, and regulator binding in intrinsically disordered transcription factor regions remains unresolved. Here, we map sequence motifs and activation domains in anArabidopsis thalianaNAC transcription factor clade, revealing that although sequence motifs and activation domains often coincide, no systematic overlap exists. Biophysical analyses using NMR spectroscopy show that the long intrinsically disordered region of senescence‐associated transcription factor ANAC046 is devoid of residual structure. We identify two activation domain/sequence motif regions, one at each end that both bind a panel of six positive and negative regulator domains from biologically relevant regulators promiscuously. Binding affinities measured using isothermal titration calorimetry reveal a hierarchy for regulator binding of the two ANAC046 activation domain/sequence motif regions defining these as regulatory hotspots. Despite extensive dynamic intramolecular contacts along the disordered chain revealed using paramagnetic relaxation enhancement experiments and simulations, the regions remain uncoupled in binding. Together, the results imply rheostatic regulation by ANAC046 through concentration‐dependent regulator competition, a mechanism likely mirrored in other transcription factors with distantly located activation domains. 

Abstract We provide an atomic-level description of the structure and dynamics of the UUCG RNA stem–loop by combining molecular dynamics simulations with experimental data. The integration of simulations with exact nuclear Overhauser enhancements data allowed us to characterize two distinct states of this molecule. The most stable conformation corresponds to the consensus three-dimensional structure. The second state is characterized by the absence of the peculiar non-Watson–Crick interactions in the loop region. By using machine learning techniques we identify a set of experimental measurements that are most sensitive to the presence of non-native states. We find that although our MD ensemble, as well as the consensus UUCG tetraloop structures, are in good agreement with experiments, there are remaining discrepancies. Together, our results show that (i) the MD simulation overstabilize a non-native loop conformation, (ii) eNOE data support its presence with a population of ≈10% and (iii) the structural interpretation of experimental data for dynamic RNAs is highly complex, even for a simple model system such as the UUCG tetraloop. 

In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm. 

Abstract Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.