A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Erijman, Ariel; Kozłowski, Łukasz P.; Sohrabi-Jahromi, Salma; Fishburn, James; Warfield, Linda; Schreiber, Jacob; Noble, William Stafford; Söding, Johannes; Hahn, Steven

doi:10.1016/j.molcel.2020.08.013

Cited by 27 publications

(59 citation statements)

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“…Nonstoichiometric IDR clustering also exhibits specificity (Chong et al 2018), although it remains unclear what mechanisms apply here. The numbers and positions of acidic, hydrophobic, and aromatic residues all modulate the affinity of IDR interactions (Staller et al 2018;Erijman et al 2020), as do posttranslational modifications (Guo et al 2019). These observations suggest a departure from the dogma of sequence-defining function via a deterministic 3D protein structure.…”

Section: Transcription Factor Dynamicsmentioning

confidence: 96%

Transcription Factor Dynamics

Lionnet

2021

Cold Spring Harb Perspect Biol

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Section: Transcription Factor Dynamicsmentioning

confidence: 96%

Transcription Factor Dynamics

Lionnet

2021

Cold Spring Harb Perspect Biol

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“…Remarkable progress has also been made in predicting the required functional patterning and valences of specific amino acids for phase separation (Martin et al, 2020;Wang et al, 2018). For TF-activation domains, the functional molecular features within these IDRs have been defined by high-throughput screening efforts where large libraries of synthetically designed protein sequences are screened for their ability to activate gene expression (Erijman et al, 2020;Ravarani et al, 2018). An evolutionary perspective to identify conserved features of IDR sequences is also showing promise (Zarin et al, 2019).…”

Section: Probing Interactions Within Condensatesmentioning

confidence: 99%

Biomolecular Condensates and Gene Activation in Development and Disease

Sabari

2020

Developmental Cell

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Activating the right gene at the right time and place is essential for development. Emerging evidence suggests that this process is regulated by the mesoscale compartmentalization of the gene-control machinery, RNA polymerase II and its cofactors, within biomolecular condensates. Coupling gene activity to the reversible and dynamic process of condensate formation is proposed to enable the robust and precise changes in gene-regulatory programs during signaling and development. The macromolecular features that enable condensates and the regulatory pathways that control them are dysregulated in disease, highlighting their importance for normal physiology. In this review, we will discuss the role of condensates in gene activation; the multivalent features of protein, RNA, and DNA that enable reversible condensate formation; and how these processes are utilized in normal and disease biology. Understanding the regulation of condensates promises to provide novel insights into how organization of the gene-control machinery regulates development and disease.

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“…We therefore propose that the FRQ/FRH complex meets the definition of a fuzzy complex, although further investigation of the conformational dynamics of this interaction is warranted (Tompa and Fuxreiter, 2008). This combination of positively charged residues that can work in concert with hydrophobic residues is reminiscent of acidic activation domains, where negatively-charged residues conspire with hydrophobic sidechains to determine specificity and affinity (Erijman et al, 2020; Ravarani et al, 2018; Sanborn et al, 2021; Staller et al, 2021, 2018; Tuttle et al, 2018). Whether or not these modes of interactions differ only in terms of the charge sign, or if additional chemical and structural nuances emerge, remains an area of open investigation.…”

Section: Discussionmentioning

confidence: 99%

The formation of a fuzzy complex in the negative arm regulates the robustness of the circadian clock

Jankowski

Griffith

Shastry

et al. 2022

Preprint

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The circadian clock times cellular processes to the day/night cycle via a Transcription-Translation negative Feedback Loop (TTFL). However, a mechanistic understanding of the negative arm in both the timing of the TTFL and its control of output is lacking. We posited that the formation of negative-arm protein complexes was fundamental to clock regulation stemming from the negative arm. Using a modified peptide microarray approach termed Linear motif discovery using rational design (LOCATE), we characterized the interaction of the disordered negative-arm clock protein FREQUENCY to its partner protein FREQUENCY-Interacting RNA helicase. LOCATE identified a specific Short Linear Motif (SLiM) and interaction hotspot as well as positively charged islands that mediate electrostatic interactions, suggesting a model where negative arm proteins form a fuzzy complex essential for clock timing and robustness. Further analysis revealed that the positively charged islands were an evolutionarily conserved feature in higher eukaryotes and contributed to proper clock function.

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A High-Throughput Screen for Transcription Activation Domains Reveals Their Sequence Features and Permits Prediction by Deep Learning

Cited by 27 publications

References 0 publications

Transcription Factor Dynamics

Transcription Factor Dynamics

Biomolecular Condensates and Gene Activation in Development and Disease

The formation of a fuzzy complex in the negative arm regulates the robustness of the circadian clock

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