Prediction of the Iron–Sulfur Binding Sites in Proteins Using the Highly Accurate Three-Dimensional Models Calculated by AlphaFold and RoseTTAFold

Golinelli‐Pimpaneau, Béatrice

doi:10.3390/inorganics10010002

Cited by 8 publications

(5 citation statements)

References 52 publications

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“…Interestingly, the prediction by AlphaFold2, which did not contain any information about the cluster, gives a model of the MmLarE monomer with a globular fold, in which the three cysteines expected to coordinate the cluster adopt a geometry compatible with cluster binding. This result was also reported for several other [Fe-S]-binding proteins (Golinelli-Pimpaneau, 2022).…”

Section: The Alphafold2 Model Of Mmlare Exhibits a Globular Architect...supporting

confidence: 88%

Structure‐based insights into the mechanism of [4Fe‐4S]‐dependent sulfur insertase LarE

Zecchin,

Pecqueur,

Oltmanns

et al. 2024

Protein Science

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Several essential cellular metabolites, such as enzyme cofactors, contain sulfur atoms and their biosynthesis requires specific thiolation enzymes. LarE is an ATP‐dependent sulfur insertase, which catalyzes the sequential conversion of the two carboxylate groups of the precursor of the lactate racemase cofactor into thiocarboxylates. Two types of LarE enzymes are known, one that uses a catalytic cysteine as a sacrificial sulfur donor, and the other one that uses a [4Fe‐4S] cluster as a cofactor. Only the crystal structure of LarE from Lactobacillus plantarum (LpLarE) from the first class has been solved. We report here the crystal structure of LarE from Methanococcus maripaludis (MmLarE), belonging to the second class, in the cluster‐free (apo‐) and cluster‐bound (holo‐) forms. The structure of holo‐MmLarE shows that the [4Fe‐4S] cluster is chelated by three cysteines only, leaving an open coordination site on one Fe atom. Moreover, the fourth non‐protein‐bonded iron atom was able to bind an anionic ligand such as a phosphate group or a chloride ion. Together with the spectroscopic analysis of holo‐MmLarE and the previously reported biochemical investigations of holo‐LarE from Thermotoga maritima, these crystal structures support the hypothesis of a reaction mechanism, in which the [4Fe‐4S] cluster binds a hydrogenosulfide ligand in place of the chloride anion, thus generating a [4Fe‐5S] intermediate, and transfers it to the substrate, as in the case of [4Fe‐4S]‐dependent tRNA thiolation enzymes.This article is protected by copyright. All rights reserved.

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Section: The Alphafold2 Model Of Mmlare Exhibits a Globular Architect...supporting

confidence: 88%

Structure‐based insights into the mechanism of [4Fe‐4S]‐dependent sulfur insertase LarE

Zecchin,

Pecqueur,

Oltmanns

et al. 2024

Protein Science

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“…However, while Cys265 and Cys268 from one model overlap well with the same residues in the second model, the positions of the sulfur atom of Cys348, which belongs to a flexible loop, are 3.7 Å apart in the two models. Such a modeling uncertainty was previously noted for other cysteines from flexible loops that coordinate a [4Fe–4S] cluster in other [Fe-S]-binding proteins ( 43 ). The positioning of Cys265, Cys268 and Cys348, in the heart of the active site and close to each other, together with previously reported site-directed mutagenesis experiments that showed the importance of these cysteines for s 4 U formation ( 21 ), is highly in favor with these three cysteines being the ligands of the [4Fe–4S] cluster in holo-MmTtuI.…”

Section: Resultsmentioning

confidence: 60%

A subclass of archaeal U8-tRNA sulfurases requires a [4Fe–4S] cluster for catalysis

Zhou

Bimaï

et al. 2022

Nucleic Acids Research

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Sulfuration of uridine 8, in bacterial and archaeal tRNAs, is catalyzed by enzymes formerly known as ThiI, but renamed here TtuI. Two different classes of TtuI proteins, which possess a PP-loop-containing pyrophosphatase domain that includes a conserved cysteine important for catalysis, have been identified. The first class, as exemplified by the prototypic Escherichia coli enzyme, possesses an additional C-terminal rhodanese domain harboring a second cysteine, which serves to form a catalytic persulfide. Among the second class of TtuI proteins that do not possess the rhodanese domain, some archaeal proteins display a conserved CXXC + C motif. We report here spectroscopic and enzymatic studies showing that TtuI from Methanococcus maripaludis and Pyrococcus furiosus can assemble a [4Fe–4S] cluster that is essential for tRNA sulfuration activity. Moreover, structural modeling studies, together with previously reported mutagenesis experiments of M. maripaludis TtuI, indicate that the [4Fe–4S] cluster is coordinated by the three cysteines of the CXXC + C motif. Altogether, our results raise a novel mechanism for U8-tRNA sulfuration, in which the cluster is proposed to catalyze the transfer of sulfur atoms to the activated tRNA substrate.

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“…The concept is similar to the template-based docking approach depicted in Figure 2 , except that the apo-structure is taken from AlphaFold predictions rather than being solved experimentally. Intriguingly, the above repertoire might be even larger if one takes into account the fact that proteins can populate different conformational states, while AlphaFold predicts only a single state [ 94 ].…”

Section: Ai Methods Applied To Metalloproteinsmentioning

confidence: 99%

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

Andreini

Rosato

2022

IJMS

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All living organisms require metal ions for their energy production and metabolic and biosynthetic processes. Within cells, the metal ions involved in the formation of adducts interact with metabolites and macromolecules (proteins and nucleic acids). The proteins that require binding to one or more metal ions in order to be able to carry out their physiological function are called metalloproteins. About one third of all protein structures in the Protein Data Bank involve metalloproteins. Over the past few years there has been tremendous progress in the number of computational tools and techniques making use of 3D structural information to support the investigation of metalloproteins. This trend has been boosted by the successful applications of neural networks and machine/deep learning approaches in molecular and structural biology at large. In this review, we discuss recent advances in the development and availability of resources dealing with metalloproteins from a structure-based perspective. We start by addressing tools for the prediction of metal-binding sites (MBSs) using structural information on apo-proteins. Then, we provide an overview of the methods for and lessons learned from the structural comparison of MBSs in a fold-independent manner. We then move to describing databases of metalloprotein/MBS structures. Finally, we summarizing recent ML/DL applications enhancing the functional interpretation of metalloprotein structures.

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Prediction of the Iron–Sulfur Binding Sites in Proteins Using the Highly Accurate Three-Dimensional Models Calculated by AlphaFold and RoseTTAFold

Cited by 8 publications

References 52 publications

Structure‐based insights into the mechanism of [4Fe‐4S]‐dependent sulfur insertase LarE

Structure‐based insights into the mechanism of [4Fe‐4S]‐dependent sulfur insertase LarE

A subclass of archaeal U8-tRNA sulfurases requires a [4Fe–4S] cluster for catalysis

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

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