In silico analysis on structure and DNA binding mode of AtNAC1, a NAC transcription factor from Arabidopsis thaliana

Zhu, Qiankun; Zou, Jiaxin; Zhu, Minhao; Liu, Zubi; Feng, Ping; Fan, Guihong; Wang, Wanjun; Liao, Hai

doi:10.1007/s00894-014-2117-8

Cited by 13 publications

(5 citation statements)

References 46 publications

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“…The tertiary structure of the NAC domain from Arabidopsis ANAC019 has been determined by X-ray crystallography. The domain forms a β sheet surrounded by α helices [ 81 ] and inserts an outer β strand with a highly conserved amino acid sequence into the major groove of the DNA binding site [ 82 , 83 ] ( Figure 2 a). Several recent studies have addressed binding by this domain to synthetic oligonucleotides and target promoters using different experimental approaches.…”

Section: Nac Proteins and Senescence Associated Interactionsmentioning

confidence: 99%

NAC Transcription Factors in Senescence: From Molecular Structure to Function in Crops

Podzimska-Sroka

O'Shea

Gregersen

et al. 2015

Plants

114

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Within the last decade, NAC transcription factors have been shown to play essential roles in senescence, which is the focus of this review. Transcriptome analyses associate approximately one third of Arabidopsis NAC genes and many crop NAC genes with senescence, thereby implicating NAC genes as important regulators of the senescence process. The consensus DNA binding site of the NAC domain is used to predict NAC target genes, and protein interaction sites can be predicted for the intrinsically disordered transcription regulatory domains of NAC proteins. The molecular characteristics of these domains determine the interactions in gene regulatory networks. Emerging local NAC-centered gene regulatory networks reveal complex molecular mechanisms of stress- and hormone-regulated senescence and basic physiological steps of the senescence process. For example, through molecular interactions involving the hormone abscisic acid, ArabidopsisNAP promotes chlorophyll degradation, a hallmark of senescence. Furthermore, studies of the functional rice ortholog, OsNAP, suggest that NAC genes can be targeted to obtain specific changes in lifespan control and nutrient remobilization in crop plants. This is also exemplified by the wheat NAM1 genes which promote senescence and increase grain zinc, iron, and protein content. Thus, NAC genes are promising targets for fine-tuning senescence for increased yield and quality.

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Section: Nac Proteins and Senescence Associated Interactionsmentioning

confidence: 99%

NAC Transcription Factors in Senescence: From Molecular Structure to Function in Crops

Podzimska-Sroka

O'Shea

Gregersen

et al. 2015

Plants

114

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“…Molecular docking were executed employing pyDock [38], and the obtained results were analyzed through Chimera [39] and PyMOL [40]. Molecular docking has been used analytically in several studies investigating the interaction between TFs and DNA [41–45]. The predicted model structures of the five TFs were docked with the binding sites identified by PTF-Vāc and as well as experimentally identified binding sites for the same TF.…”

Section: Resultsmentioning

confidence: 99%

PTF-Vāc:Ab-initiodiscovery of plant transcription factors binding sites using explainable and generative deep co-learning encoders-decoders

Gupta,

Jyoti,

Bhati

et al. 2024

Preprint

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Discovery of transcription factors (TFs) binding sites (TFBS) and their motifs in plants pose significant challenges due to high cross-species variability. The interaction between TFs and their binding sites is highly specific and context dependent. Most of the existing TFBS finding software tools are not accurate enough to discover these binding sites in plants. They fail to capture the cross-species variability, interdependence between TF structure and its TFBS, and context specificity of binding. Since they are coupled to predefined TF specific model/matrix, they are highly vulnerable towards the volume and quality of data provided to build the motifs. All these software make a presumption or expect that the user input would be specific to any particular TF which renders them of very limited uses. This all makes them hardly of any use for purposes like genomic annotations of newly sequenced species. Here, we report a Deep Encoders-Decoders system, PTF-Vāc, founded on a universal model of deep co-learning on variability in binding sites and TF structure, making it completely free from the bottlenecks mentioned above. It has successfully decoupled the process of TFBS discovery from the prior step of motif finding and requirement of TF specific motif models. Due to a universal model for TF:DNA interactions as its guide, it can discover the binding sites in total independence from data volume, species and TF specific models. It can accurately detect even the binding sites of never seen before TFs families and species and can be used to define credible motifs from its TFBS report.

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“…Computational methods are ideal ways of providing theoretical information about protein-DNA interactions that can later be validated using experimental methods. Several studies on the interaction between transcription factors and DNA have been carried out using docking and molecular simulation analysis (Konda et al, 2018;Mukherjee et al, 2015;Pandey et al, 2016;Pradeepkiran et al, 2015;Zhu et al, 2014).…”

Section: Molecular Modeling and Docking Of Traescs2b02g002700 And Tramentioning

confidence: 99%

Evolution and identification of DREB transcription factors in the wheat genome: modeling, docking and simulation of DREB proteins associated with salt stress

Hassan

Berk

Aronsson

2021

Journal of Biomolecular Structure and Dynamics

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Soil salinity and the resulting salt stress it imposes on crop plants is a major problem for modern agriculture. Understanding how salt tolerance mechanisms in plants are regulated is therefore important. One regulatory mechanism is the APETALA2/Ethylene Responsive Factor (AP2/ERF) transcription factor family, including dehydration responsive element binding (DREB) transcription factors. By binding to DNA, specifically upstream of genes that play roles in salt tolerance pathways, DREB proteins upregulate expression of these genes. DREB in Triticum aestivum (wheat) cluster in subgroups and in this study by scanning the recently extended predicted proteome of wheat for DREB, we increased the number of members of this sub-family. Using the wheat genome, we identified 576 genes coding for the AP2 domain of which 508 were identified to have one AP2 domain, a characteristic of the DREB/ ERF subfamily. We confirmed the existing four subgroups by sequence-based phylogenetic analyses but also identified 32 new DREB subfamily members, not belonging to any known subgroup. Transcription factor profile inference analysis identified two genes, TraesCS2B02G002700 and TraesCS2D02G015200, being homologous to DREB1A of Arabidopsis thaliana. Based on molecular simulation (25 ns) analysis, TraesCS2B02G002700 with a CCGAC motif was observed to interact very stably with DNA. In silico mutational analysis at the 19 th position in the DREB domain of TraesCS2B02G002700-DNA complex indicated this as a stable part for recognizing and forming interaction with DNA. Moreover, six target genes were predicted having an upstream CCGAC motif regulated by TraesCS2B02G002700. Our study provides an overall framework for exploring the transcription factors in plants and identifying e.g. potential salt stress target genes.

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In silico analysis on structure and DNA binding mode of AtNAC1, a NAC transcription factor from Arabidopsis thaliana

Cited by 13 publications

References 46 publications

NAC Transcription Factors in Senescence: From Molecular Structure to Function in Crops

NAC Transcription Factors in Senescence: From Molecular Structure to Function in Crops

PTF-Vāc:Ab-initiodiscovery of plant transcription factors binding sites using explainable and generative deep co-learning encoders-decoders

Evolution and identification of DREB transcription factors in the wheat genome: modeling, docking and simulation of DREB proteins associated with salt stress

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