Abstract:Glucosinolate transporters (GTRs) are part of the nitrate/peptide transporter (NPF) family, members of which also transport specialized secondary metabolites as substrates. Glucosinolates are defense compounds derived from amino acids. We selected 4-methylthiobutyl (4MTB) and indol-3-ylmethyl (I3M) glucosinolates to study how GTR1 from Arabidopsis thaliana transports these substrates in computational simulation approaches. The designed pipeline reported here includes massive docking of 4MTB and I3M in an ensem… Show more
“…The dockings indicate strong interactions between the selectivity filter and the side chains for glucosinolates being transported and show that the core glucosinolate structure interacts with two conserved residues that are assumed to be involved in general substrate recognition in the POT family. Whereas interactions with the two conserved residues have previously been observed in dockings of I3M, 4MTB, 4MSB and benzyl in NPF2.10 using inward and outward facing conformations (Chung et al 2022, Peña-Varas et al 2022), but the selectivity filter has not been described before.…”
Section: Discussionmentioning
confidence: 88%
“…In order to facilitate a structural interpretation of the eight mutations identified in NPF2.9Δ8#3, we docked I3M and pOHB in NPF2.9, NPF2.9Δ8#3 and NPF2.10 homology models. We have previously performed dockings of 4MTB and I3M in outward and inward facing conformations of NPF2.10 (Jørgensen et al 2017, Peña-Varas et al 2022). In this study, we were interested in performing the dockings in an occluded state, to better study the binding cavity.…”
Section: Resultsmentioning
confidence: 99%
“…The models were relaxed using Molecular Dynamics as previously described (Peña-Varas et al 2022) before docking. Briefly, all the models were optimized at pH 4.5 ± 2.0 with Epik (Shelley et al 2007) and PROPKA (Olsson et al 2011).…”
Section: Methodsmentioning
confidence: 99%
“…The models were created and validated using SWISS-MODEL. After generation of the models, they were relaxed through Molecular Dynamics simulations (MDs) as previously described (Peña-Varas et al 2022).…”
Section: Generation Of Homology Models For Structural Interpretation ...mentioning
Plants depend on transport processes for correct allocation of specialized metabolites. This is important for optimal defense, avoidance of autotoxicity, connecting compartmented biosynthetic modules and more. Transport of a wide variety of specialized metabolites is mediated by transporters from the Nitrate and Peptide transporter Family (NPF), which belongs to the Major Facilitator Superfamily (MFS). However, the mechanism by which NPF members recognize and transport specialized metabolites remains unknown. Here we mutate eight residues to reciprocally swap the substrate-preference of two closely related glucosinolate transporters (GTRs). Seven of these residues assemble in a ring-like structure in all conformations of the transporters. We labeled the ring-like structure a selectivity filter and based on docking studies, we propose that the interaction between the selectivity filter and the glucosinolate side chain determines whether a given glucosinolate is recognized as a substrate. Besides partly explaining the distinct substrate preference of GTR1 (NPF2.10) and GTR3 (NPF2.9), this study proposes fundamental principles of substrate recognition in the NPF and establishes the GTR subclade as a novel model system for studying structure function relationships in the NPF.
“…The dockings indicate strong interactions between the selectivity filter and the side chains for glucosinolates being transported and show that the core glucosinolate structure interacts with two conserved residues that are assumed to be involved in general substrate recognition in the POT family. Whereas interactions with the two conserved residues have previously been observed in dockings of I3M, 4MTB, 4MSB and benzyl in NPF2.10 using inward and outward facing conformations (Chung et al 2022, Peña-Varas et al 2022), but the selectivity filter has not been described before.…”
Section: Discussionmentioning
confidence: 88%
“…In order to facilitate a structural interpretation of the eight mutations identified in NPF2.9Δ8#3, we docked I3M and pOHB in NPF2.9, NPF2.9Δ8#3 and NPF2.10 homology models. We have previously performed dockings of 4MTB and I3M in outward and inward facing conformations of NPF2.10 (Jørgensen et al 2017, Peña-Varas et al 2022). In this study, we were interested in performing the dockings in an occluded state, to better study the binding cavity.…”
Section: Resultsmentioning
confidence: 99%
“…The models were relaxed using Molecular Dynamics as previously described (Peña-Varas et al 2022) before docking. Briefly, all the models were optimized at pH 4.5 ± 2.0 with Epik (Shelley et al 2007) and PROPKA (Olsson et al 2011).…”
Section: Methodsmentioning
confidence: 99%
“…The models were created and validated using SWISS-MODEL. After generation of the models, they were relaxed through Molecular Dynamics simulations (MDs) as previously described (Peña-Varas et al 2022).…”
Section: Generation Of Homology Models For Structural Interpretation ...mentioning
Plants depend on transport processes for correct allocation of specialized metabolites. This is important for optimal defense, avoidance of autotoxicity, connecting compartmented biosynthetic modules and more. Transport of a wide variety of specialized metabolites is mediated by transporters from the Nitrate and Peptide transporter Family (NPF), which belongs to the Major Facilitator Superfamily (MFS). However, the mechanism by which NPF members recognize and transport specialized metabolites remains unknown. Here we mutate eight residues to reciprocally swap the substrate-preference of two closely related glucosinolate transporters (GTRs). Seven of these residues assemble in a ring-like structure in all conformations of the transporters. We labeled the ring-like structure a selectivity filter and based on docking studies, we propose that the interaction between the selectivity filter and the glucosinolate side chain determines whether a given glucosinolate is recognized as a substrate. Besides partly explaining the distinct substrate preference of GTR1 (NPF2.10) and GTR3 (NPF2.9), this study proposes fundamental principles of substrate recognition in the NPF and establishes the GTR subclade as a novel model system for studying structure function relationships in the NPF.
“…With the expected increasing accessibility of plant protein structures, efforts can be intensified to gain detailed knowledge of molecular processes in plants. And here, computational simulations such as docking or Molecular Dynamics simulations will play an increasingly crucial role in the near future (Navarro-Retamal et al, 2016a,b, 2018Khan et al, 2019;Schott-Verdugo et al, 2019;Rasheed et al, 2020;Lehmann et al, 2021;Moe-Lange et al, 2021;Peña-Varas et al, 2022).…”
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