RING NMR dynamics: software for analysis of multiple NMR relaxation experiments

Beckwith, Martha A.; Erazo-Colon, Teddy; Johnson, B. V.

doi:10.1007/s10858-020-00350-w

Cited by 16 publications

(20 citation statements)

References 29 publications

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“…For these residues, CEST indicates a significant chemical shift difference between their bound and unbound states. Using the program RING NMR Dynamics ( Beckwith et al, 2020 ), the CEST data were fit to obtain chemical shift difference between free and bound state (Δδ), the exchange rate (k ex ), and the fractional minor population (P b ) (see Table 1 , Appendix 1—table 1a and b ). The weighted average of the 15 N CEST fit parameters resulted in k ex = 200 ± 70 s –1 , consistent with slow to intermediate exchange (k ex < Δω) on an NMR time scale.…”

Section: Resultsmentioning

confidence: 99%

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Coil-to-α-helix transition at the Nup358-BicD2 interface activates BicD2 for dynein recruitment

Gibson

Cui

Ali

et al. 2022

eLife

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Nup358, a protein of the nuclear pore complex, facilitates a nuclear positioning pathway that is essential for many biological processes, including neuromuscular and brain development. Nup358 interacts with the dynein adaptor Bicaudal D2 (BicD2), which in turn recruits the dynein machinery to position the nucleus. However, the molecular mechanisms of the Nup358/BicD2 interaction and the activation of transport remain poorly understood. Here for the first time, we show that a minimal Nup358 domain activates dynein/dynactin/BicD2 for processive motility on microtubules. Using nuclear magnetic resonance (NMR) titration and chemical exchange saturation transfer (CEST), mutagenesis and circular dichroism spectroscopy (CD), a Nup358 a-helix encompassing residues 2162-2184 was identified, which transitioned from a random coil to an a-helical conformation upon BicD2-binding and formed the core of the Nup358-BicD2 interface. Mutations in this region of Nup358 decreased the Nup358/BicD2 interaction, resulting in decreased dynein recruitment and impaired motility. BicD2 thus recognizes Nup358 though a 'cargo recognition a-helix', a structural feature that may stabilize BicD2 in its activated state and promote processive dynein motility.

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Section: Resultsmentioning

confidence: 99%

“…The saturation frequency ranged from 170 to 180 ppm in steps of 0.33 ppm. The CEST data were fitted with the program RING NMR Dynamics ( Beckwith et al, 2020 ) and are presented in Appendix 1—table 1 .…”

Section: Methodsmentioning

confidence: 99%

Coil-to-α-helix transition at the Nup358-BicD2 interface activates BicD2 for dynein recruitment

Gibson

Cui

Ali

et al. 2022

eLife

View full text Add to dashboard Cite

show abstract

“…For these residues, CEST indicates a significant chemical shift difference between their bound and unbound states. Using the program RING NMR Dynamics 59 , the CEST data were fit to obtain chemical shift difference between free and bound state (Δδ), the exchange rate (k ex ) and the fractional minor population (P b )(See Table S1a, b). The weighted average of the 15 N CEST fit parameters resulted in k ex = 200 ± 70 s -1 , consistent with slow to intermediate exchange (k ex << Δω) on an NMR time scale.…”

Section: Cest Revealed a Coil-to-helix Transition At The Bicd2-nup358 Interfacementioning

confidence: 99%

“…The saturation frequency was ranged from 170 to 180 ppm in steps of 0.33 ppm. The CEST data were fitted with the program RING NMR Dynamics 59 and are presented in Tables 1 and S1.…”

Section: Nuclear Magnetic Resonance (Nmr)mentioning

confidence: 99%

Coil-to-Helix Transition at the Nup358-BicD2 Interface Activates BicD2 for Dynein Recruitment

Gibson

Cui

Ali

et al. 2021

Preprint

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Nup358, a nuclear pore protein, facilitates a nuclear positioning pathway that is essential for brain development. Nup358 binds and activates the auto-inhibited dynein adaptor Bicaudal D2 (BicD2), which in turn recruits and activates the dynein machinery to position the nucleus. The molecular details of the Nup358/BicD2 interaction remain poorly understood. Here, we show that a minimal dimerized Nup358 domain activates dynein/dynactin/BicD2 for processive motility on microtubules. Using nuclear magnetic resonance (NMR) titration and chemical exchange saturation transfer (CEST), a Nup358-helix encompassing residues 2162-2184 was identified, which transitioned from random coil to an alpha-helix upon BicD2-binding and formed the core of the Nup358-BicD2 interface. Mutations in this region of Nup358 decreased the Nup358/BicD2 interaction, resulting in decreased dynein recruitment and impaired motility. BicD2 thus recognizes the cargo adaptor Nup358 though a 'cargo recognition alpha-helix', a structural feature that may stabilize BicD2 in its activated state, promoting activation of dynein motility.

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“…It has been used for several years within the field of clinical magnetic resonance imaging (MRI) and some of the tools have already been approved by the FDA 26 for image enhancement and classification. Within biomolecular NMR there has been a surge in applications of DNNs over the last couple of years, and networks are now available 4 for the reconstruction of sparsely sampled spectra [27][28][29][30] , peak picking 31 , estimating initial fitting parameters 32 , and virtual decoupling 33 .…”

Section: Introductionmentioning

confidence: 99%

Towards autonomous analysis of Chemical Exchange Saturation Transfer experiments using Deep Neural Networks

Karunanithy

Yuwen

Kay

et al. 2021

Preprint

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Macromolecules often exchange between functional states on timescales that can be accessed with NMR spectroscopy and many NMR tools have been developed to characterise the kinetics and thermodynamics of the exchange processes, as well as the structure of the conformers that are involved. However, analysis of the NMR data that report on exchanging macromolecules often hinges on complex least-squares fitting procedures as well as human experience and intuition, which, in some cases, limits the widespread use of the methods. The applications of deep neural networks (DNNs) and artificial intelligence have increased significantly in the sciences, and recently, specifically, within the field of biomolecular NMR, where DNNs are now available for tasks such as the reconstruction of sparsely sampled spectra, peak picking, and virtual decoupling. Here we present a DNN for the analysis of chemical exchange saturation transfer (CEST) data reporting on two- or three-site chemical exchange involving sparse state lifetimes of between approximately 3 - 60 ms, the range most frequently observed via experiment. The work presented here focuses on the 1H CEST class of methods that are further complicated, in relation to applications to other nuclei, by anti-phase features. The developed DNNs accurately predict the chemical shifts of nuclei in the exchanging species directly from anti-phase 1HN CEST profiles, along with an uncertainty associated with the predictions. The performance of the DNN was quantitatively assessed using both synthetic and experimental anti-phase CEST profiles. The assessments show that the DNN accurately determines chemical shifts and their associated uncertainties. The DNNs developed here do not contain any parameters for the end-user to adjust and the method therefore allows for autonomous analysis of complex NMR data that report on conformational exchange.

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RING NMR dynamics: software for analysis of multiple NMR relaxation experiments

Cited by 16 publications

References 29 publications

Coil-to-α-helix transition at the Nup358-BicD2 interface activates BicD2 for dynein recruitment

Coil-to-α-helix transition at the Nup358-BicD2 interface activates BicD2 for dynein recruitment

Coil-to-Helix Transition at the Nup358-BicD2 Interface Activates BicD2 for Dynein Recruitment

Towards autonomous analysis of Chemical Exchange Saturation Transfer experiments using Deep Neural Networks

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