scholarly journals The Anchored Flexibility Model in LC8 Motif Recognition: Insights from the Chica Complex

Biochemistry ◽  
2015 ◽  
Vol 55 (1) ◽  
pp. 199-209 ◽  
Author(s):  
Sarah Clark ◽  
Afua Nyarko ◽  
Frank Löhr ◽  
P. Andrew Karplus ◽  
Elisar Barbar
Keyword(s):  
Motif Recognition

Structural Basis of PxxDY Motif Recognition in SH3 Binding

2008 ◽  
Vol 382 (1) ◽  
pp. 167-178 ◽  
Author(s):  
Olli Aitio ◽  
Maarit Hellman ◽  
Tapio Kesti ◽  
Iivari Kleino ◽  
Olga Samuilova ◽  
...  
Keyword(s):  
Structural Basis ◽  
Motif Recognition

scholarly journals β Structure motif recognition by anti-gliadin antibodies in coeliac disease

FEBS Letters ◽  
1998 ◽  
Vol 427 (1) ◽  
pp. 36-40 ◽  
Author(s):  
Patricia Alfonso ◽  
Claudio Soto ◽  
Juan Pablo Albar ◽  
Emilio Camafeita ◽  
Héctor Escobar ◽  
...  
Keyword(s):  
Coeliac Disease ◽  
Gliadin Antibodies ◽  
Motif Recognition

scholarly journals Structure of the SmallDictyostelium discoideumMyosin Light Chain MlcB Provides Insights into MyoB IQ Motif Recognition

2014 ◽  
Vol 289 (24) ◽  
pp. 17030-17042 ◽  
Author(s):  
Janine Liburd ◽  
Seth Chitayat ◽  
Scott W. Crawley ◽  
Kim Munro ◽  
Emily Miller ◽  
...  
Keyword(s):  
Light Chain ◽  
Iq Motif ◽  
Motif Recognition

scholarly journals Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites

2021 ◽  
Vol 25 (1) ◽  
pp. 7-17
Author(s):  
A. V. Tsukanov ◽  
V. G. Levitsky ◽  
T. I. Merkulova
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
De Novo ◽  
Transcription Factor Binding Sites ◽  
Structural Heterogeneity ◽  
Transcription Factor Binding ◽  
Factor Binding ◽  
Model Training ◽  
Motif Recognition ◽  
Positional Weight

The most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models, BaMM and InMoDe, can do as much. However, application of these models was usually limited only to comparing their recognition accuracies with that of PWMs, while none of the analyses of the co-prediction and relative positioning of hits of different models in peaks has yet been performed. To close this gap, we propose the pipeline called MultiDeNA. This pipeline includes stages of model training, assessing their recognition accuracy, scanning ChIP-seq peaks and their classif ication based on scan results. We applied our pipeline to 22 ChIP-seq datasets of TF FOXA2 and considered PWM, dinucleotide PWM (diPWM), BaMM and InMoDe models. The combination of these four models allowed a signif icant increase in the fraction of recognized peaks compared to that for the sole PWM model: the increase was 26.3 %. The BaMM model provided the main contribution to the recognition of sites. Although the major fraction of predicted peaks contained TFBS of different models with coincided positions, the medians of the fraction of peaks containing the predictions of sole models were 1.08, 0.49, 4.15 and 1.73 % for PWM, diPWM, BaMM and InMoDe, respectively. Thus, FOXA2 BSs were not fully described by only a sole model, which indicates theirs heterogeneity. We assume that the BaMM model is the most successful in describing the structure of the FOXA2 BS in ChIP-seq datasets under study.

scholarly journals A crystal structure of a collaborative RNA regulatory complex reveals mechanisms to refine target specificity

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Chen Qiu ◽  
Vandita D Bhat ◽  
Sanjana Rajeev ◽  
Chi Zhang ◽  
Alexa E Lasley ◽  
...  
Keyword(s):  
Crystal Structure ◽  
In Vitro Selection ◽  
Rna Binding ◽  
Sequence Specificity ◽  
Binding Assays ◽  
Regulatory Complex ◽  
Rna Motif ◽  
Rna Complex ◽  
Motif Recognition

In the Caenorhabditis elegans germline, fem-3 Binding Factor (FBF) partners with LST-1 to maintain stem cells. A crystal structure of an FBF-2/LST-1/RNA complex revealed that FBF-2 recognizes a short RNA motif different from the characteristic 9-nt FBF binding element, and compact motif recognition coincided with curvature changes in the FBF-2 scaffold. Previously, we engineered FBF-2 to favor recognition of shorter RNA motifs without curvature change (Bhat et al., 2019). In vitro selection of RNAs bound by FBF-2 suggested sequence specificity in the central region of the compact element. This bias, reflected in the crystal structure, was validated in RNA-binding assays. FBF-2 has the intrinsic ability to bind to this shorter motif. LST-1 weakens FBF-2 binding affinity for short and long motifs, which may increase target selectivity. Our findings highlight the role of FBF scaffold flexibility in RNA recognition and suggest a new mechanism by which protein partners refine target site selection.

scholarly journals Structural insights into the assembly and polyA signal recognition mechanism of the human CPSF complex

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Marcello Clerici ◽  
Marco Faini ◽  
Ruedi Aebersold ◽  
Martin Jinek
Keyword(s):  
Mammalian Cells ◽  
Rna Binding ◽  
Molecular Architecture ◽  
Binding Assays ◽  
Critical Determinant ◽  
Recognition Mechanism ◽  
Cleavage And Polyadenylation ◽  
Specificity Factor ◽  
Motif Recognition ◽  
Mrna Polyadenylation

3’ polyadenylation is a key step in eukaryotic mRNA biogenesis. In mammalian cells, this process is dependent on the recognition of the hexanucleotide AAUAAA motif in the pre-mRNA polyadenylation signal by the cleavage and polyadenylation specificity factor (CPSF) complex. A core CPSF complex comprising CPSF160, WDR33, CPSF30 and Fip1 is sufficient for AAUAAA motif recognition, yet the molecular interactions underpinning its assembly and mechanism of PAS recognition are not understood. Based on cross-linking-coupled mass spectrometry, crystal structure of the CPSF160-WDR33 subcomplex and biochemical assays, we define the molecular architecture of the core human CPSF complex, identifying specific domains involved in inter-subunit interactions. In addition to zinc finger domains in CPSF30, we identify using quantitative RNA-binding assays an N-terminal lysine/arginine-rich motif in WDR33 as a critical determinant of specific AAUAAA motif recognition. Together, these results shed light on the function of CPSF in mediating PAS-dependent RNA cleavage and polyadenylation.

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