Nitric oxide-mediated S-nitrosylation of IAA17 protein in intrinsically disordered region represses auxin signaling

Jing, Hongwei; Yang, Xiaolu; Emenecker, Ryan; Feng, Jian; Zhang, Jian; Figueiredo, Marcelo Rodrigues Alves de; Chaisupa, Patarasuda; Wright, R Clay; Holehouse, Alex S.; Strader, Lucia; Zuo, Jianru

doi:10.1016/j.jgg.2023.05.001

Cited by 11 publications

(1 citation statement)

References 74 publications

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“…, secondary structure analysis, sidechain bond vector analysis, etc. ). − As such, while SOURSOP does not officially support the analysis of coarse-grained simulations at this juncture, unofficially, it works relatively well in this capacity.…”

Section: Discussionmentioning

confidence: 98%

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Lalmansingh

Keeley

Ruff

et al. 2023

J. Chem. Theory Comput.

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Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

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Section: Discussionmentioning

confidence: 98%

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Lalmansingh

Keeley

Ruff

et al. 2023

J. Chem. Theory Comput.

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Metabolism of 2,4‐D in plants: comparative analysis of metabolic detoxification pathways in tolerant crops and resistant weeds

Torra,

Alcántara‐de la Cruz,

de Figueiredo

et al. 2024

Pest Management Science

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The commercialization of 2,4‐D (2,4‐dichlorophenoxyacetic acid) latifolicide in 1945 marked the beginning of the selective herbicide market, with this active ingredient playing a pivotal role among commercial herbicides due to the natural tolerance of monocots compared with dicots. Due to its intricate mode of action, involving interactions within endogenous auxin signaling networks, 2,4‐D was initially considered a low‐risk herbicide to evolve weed resistance. However, the intensification of 2,4‐D use has contributed to the emergence of 2,4‐D‐resistant broadleaf weeds, challenging earlier beliefs. This review explores 2,4‐D tolerance in crops and evolved resistance in weeds, emphasizing an in‐depth understanding of 2,4‐D metabolic detoxification. Nine confirmed 2,4‐D‐resistant weed species, driven by rapid metabolism, highlight cytochrome P450 monooxygenases in Phase I and glycosyltransferases in Phase II as key enzymes. Resistance to 2,4‐D may also involve impaired translocation associated with mutations in auxin/indole‐3‐acetic acid (Aux/IAA) co‐receptor genes. Moreover, temperature variations affect 2,4‐D efficacy, with high temperatures increasing herbicide metabolism rates and reducing weed control, while drought stress did not affect 2,4‐D efficacy. Research on 2,4‐D resistance has primarily focused on non‐target‐site resistance (NTSR) mechanisms, including 2,4‐D metabolic detoxification, with limited exploration of the inheritance and genetic basis underlying these traits. Resistance to 2,4‐D in weeds is typically governed by a single gene, either dominant or incompletely dominant, raising questions about gain‐of‐function or loss‐of‐function mutations that confer resistance. Future research should unravel the physiological and molecular‐genetic basis of 2,4‐D NTSR, exploring potential cross‐resistance patterns and assessing fitness costs that may affect future evolution of auxin‐resistant weeds. © 2024 Society of Chemical Industry.

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Role of protein S-nitrosylation in plant growth and development

Liu,

et al. 2024

Plant Cell Rep

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Nitric oxide-mediated S-nitrosylation of IAA17 protein in intrinsically disordered region represses auxin signaling

Cited by 11 publications

References 74 publications

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Metabolism of 2,4‐D in plants: comparative analysis of metabolic detoxification pathways in tolerant crops and resistant weeds

Role of protein S-nitrosylation in plant growth and development

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