The integration of AlphaFold-predicted and crystal structures of human trans-3-hydroxy-l-proline dehydratase reveals a regulatory catalytic mechanism.
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ABSTRACT:
SUBMITTER: Ferrario E
PROVIDER: S-EPMC9309405 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Hydroxyprolines, such as trans-4-hydroxy-l-proline (T4LHyp), trans-3-hydroxy-l-proline (T3LHyp), and cis-3-hydroxy-l-proline (C3LHyp), are present in some proteins including collagen, plant cell wall, and several peptide antibiotics. In bacteria, genes involved in the degradation of hydroxyproline are often clustered on the genome (l-Hyp gene cluster). We recently reported that an aconitase X (AcnX)-like hypI gene from an l-Hyp gene cluster functions as a monomeric C3LHyp dehydratase (AcnXType I). However, the physiological role of C3LHyp dehydratase remained unclear. We here demonstrate that Azospirillum brasilense NBRC 102289, an aerobic nitrogen-fixing bacterium, robustly grows using not only T4LHyp and T3LHyp but also C3LHyp as the sole carbon source. The small and large subunits of the hypI gene (hypIS and hypIL, respectively) from A. brasilense NBRC 102289 are located separately from the l-Hyp gene cluster and encode a C3LHyp dehydratase with a novel heterodimeric structure (AcnXType IIa). A strain disrupted in the hypIS gene did not grow on C3LHyp, suggesting its involvement in C3LHyp metabolism. Furthermore, C3LHyp induced transcription of not only the hypI genes but also the hypK gene encoding Δ1-pyrroline-2-carboxylate reductase, which is involved in T3LHyp, d-proline, and d-lysine metabolism. On the other hand, the l-Hyp gene cluster of some other bacteria contained not only the AcnXType IIa gene but also two putative proline racemase-like genes (hypA1 and hypA2). Despite having the same active sites (a pair of Cys/Cys) as hydroxyproline 2-epimerase, which is involved in the metabolism of T4LHyp, the dominant reaction by HypA2 was clearly the dehydration of T3LHyp, a novel type of T3LHyp dehydratase that differed from the known enzyme (Cys/Thr).IMPORTANCE More than 50 years after the discovery of trans-4-hydroxy-l-proline (generally called l-hydroxyproline) degradation in aerobic bacteria, its genetic and molecular information has only recently been elucidated. l-Hydroxyproline metabolic genes are often clustered on bacterial genomes. These loci frequently contain a hypothetical gene(s), whose novel enzyme functions are related to the metabolism of trans-3-hydroxyl-proline and/or cis-3-hydroxyl-proline, a relatively rare l-hydroxyproline in nature. Several l-hydroxyproline metabolic enzymes show no sequential similarities, suggesting their emergence by convergent evolution. Furthermore, transcriptional regulation by trans-4-hydroxy-l-proline, trans-3-hydroxy-l-proline, and/or cis-3-hydroxy-l-proline significantly differs between bacteria. The results of the present study show that several l-hydroxyprolines are available for bacteria as carbon and energy sources and may contribute to the discovery of potential metabolic pathways of another hydroxyproline(s).
| S-EPMC5527387 | biostudies-literature
Project description:trans-4-Hydroxy-l-proline (T4LHyp) and trans-3-hydroxy-l-proline (T3LHyp) occur mainly in collagen. A few bacteria can convert T4LHyp to ?-ketoglutarate, and we previously revealed a hypothetical pathway consisting of four enzymes at the molecular level (J Biol Chem (2007) 282, 6685-6695; J Biol Chem (2012) 287, 32674-32688). Here, we first found that Azospirillum brasilense has the ability to grow not only on T4LHyp but also T3LHyp as a sole carbon source. In A. brasilense cells, T3LHyp dehydratase and NAD(P)H-dependent ?(1)-pyrroline-2-carboxylate (Pyr2C) reductase activities were induced by T3LHyp (and d-proline and d-lysine) but not T4LHyp, and no effect of T3LHyp was observed on the expression of T4LHyp metabolizing enzymes: a hypothetical pathway of T3LHyp ? Pyr2C ? l-proline was proposed. Bacterial T3LHyp dehydratase, encoded to LhpH gene, was homologous with the mammalian enzyme. On the other hand, Pyr2C reductase encoded to LhpI gene was a novel member of ornithine cyclodeaminase/?-crystallin superfamily, differing from known bacterial protein. Furthermore, the LhpI enzymes of A. brasilense and another bacterium showed several different properties, including substrate and coenzyme specificities. T3LHyp was converted to proline by the purified LhpH and LhpI proteins. Furthermore, disruption of LhpI gene from A. brasilense led to loss of growth on T3LHyp, d-proline and d-lysine, indicating that this gene has dual metabolic functions as a reductase for Pyr2C and ?(1)-piperidine-2-carboxylate in these pathways, and that the T3LHyp pathway is not linked to T4LHyp and l-proline metabolism.
| S-EPMC3958920 | biostudies-literature
Project description:Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets. To assess our model, we used a dataset of 144 Human G-protein Coupled Receptors (GPCRs) with over 140,000 measured inhibition constants (Ki) values. Results strongly suggest that our approach performs as well as state-of-the-art ligand-based methods. In a second modeling approach that used 129 targets for training and a separate test set of 15 different protein targets, our model correctly predicted interactions for 73% of targets, with explained variances exceeding 0.50 in 22% of cases. Our findings further verified that the usage of experimentally determined protein structures produced models that were statistically indistinct from the Alphafold synthetic structures. This study presents a proteo-chemometric drug screening approach that uses a simple and scalable method for extracting protein structural information for usage in machine learning models capable of predicting protein-molecule interactions even for orphan targets.
| S-EPMC11001998 | biostudies-literature
Project description:A family of eukaryotic proline racemase-like genes has recently been identified. Several members of this family have been well characterized and are known to catalyze the racemization of free proline or trans-4-hydroxyproline. However, the majority of eukaryotic proline racemase-like proteins, including a human protein called C14orf149, lack a specific cysteine residue that is known to be critical for racemase activity. Instead, these proteins invariably contain a threonine residue at this position. The function of these enzymes has remained unresolved until now. In this study, we demonstrate that three enzymes of this type, including human C14orf149, catalyze the dehydration of trans-3-hydroxy-L-proline to ?(1)-pyrroline-2-carboxylate (Pyr2C). These are the first enzymes of this subclass of proline racemase-like genes for which the enzymatic activity has been resolved. C14orf149 is also the first human enzyme that acts on trans-3-hydroxy-L-proline. Interestingly, a mutant enzyme in which the threonine in the active site is mutated back into cysteine regained 3-hydroxyproline epimerase activity. This result suggests that the enzymatic activity of these enzymes is dictated by a single residue. Presumably, human C14orf149 serves to degrade trans-3-hydroxy-L-proline from the diet and originating from the degradation of proteins that contain this amino acid, such as collagen IV, which is an important structural component of basement membrane.
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Project description:AlphaKnot is a server that measures entanglement in AlphaFold-solved protein models while considering pLDDT confidence values. AlphaKnot has two main functions: (i) providing researchers with a webserver for analyzing knotting in their own AlphaFold predictions and (ii) providing a database of knotting in AlphaFold predictions from the 21 proteomes for which models have been published prior to 2022. The knotting is defined in a probabilistic fashion. The knotting complexity of proteins is presented in the form of a matrix diagram which shows users the knot type for the entire polypeptide chain and for each of its subchains. The dominant knot types as well as the computed locations of the knot cores (i.e. minimal portions of protein backbones that form a given knot type) are shown for each protein structure. Based mainly on the pLDDT confidence values, entanglements are classified as Knots, Unsure, and Artifacts. The database portion of the server can be used, for example, to examine protein geometry and entanglement-function correlations, as a reference set for protein modeling, and for facilitating evolutional studies. The AlphaKnot server can be found at https://alphaknot.cent.uw.edu.pl/.
| S-EPMC9252816 | biostudies-literature
Project description:AlphaFold is making great progress in protein structure prediction, not only for single-chain proteins but also for multi-chain protein complexes. When using AlphaFold-Multimer to predict protein‒protein complexes, we observed some unusual structures in which chains are looped around each other to form topologically intertwining links at the interface. Based on physical principles, such topological links should generally not exist in native protein complex structures unless covalent modifications of residues are involved. Although it is well known and has been well studied that protein structures may have topologically complex shapes such as knots and links, existing methods are hampered by the chain closure problem and show poor performance in identifying topologically linked structures in protein‒protein complexes. Therefore, we address the chain closure problem by using sliding windows from a local perspective and propose an algorithm to measure the topological-geometric features that can be used to identify topologically linked structures. An application of the method to AlphaFold-Multimer-predicted protein complex structures finds that approximately 1.72% of the predicted structures contain topological links. The method presented in this work will facilitate the computational study of protein‒protein interactions and help further improve the structural prediction of multi-chain protein complexes.
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Project description:In the aconitase superfamily, which includes the archetypical aconitase, homoaconitase, and isopropylmalate isomerase, only aconitase X is not functionally annotated. The corresponding gene (LhpI) was often located within the bacterial gene cluster involved in L-hydroxyproline metabolism. Screening of a library of (hydroxy)proline analogues revealed that this protein catalyzes the dehydration of cis-3-hydroxy-L-proline to ?1-pyrroline-2-carboxylate. Furthermore, electron paramagnetic resonance and site-directed mutagenic analyses suggests the presence of a mononuclear Fe(III) center, which may be coordinated with one glutamate and two cysteine residues. These properties were significantly different from those of other aconitase members, which catalyze the isomerization of ?- to ?-hydroxy acids, and have a [4Fe-4S] cluster-binding site composed of three cysteine residues. Bacteria with the LhpI gene could degrade cis-3-hydroxy-L-proline as the sole carbon source, and LhpI transcription was up-regulated not only by cis-3-hydroxy-L-proline, but also by several isomeric 3- and 4-hydroxyprolines.
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Project description:Recent spectacular advances by AI programs in 3D structure predictions from protein sequences have revolutionized the field in terms of accuracy and speed. The resulting "folding frenzy" has already produced predicted protein structure databases for the entire human and other organisms' proteomes. However, rapidly ascertaining a predicted structure's reliability based on measured properties in solution should be considered. Shape-sensitive hydrodynamic parameters such as the diffusion and sedimentation coefficients ([Formula: see text], [Formula: see text]) and the intrinsic viscosity ([η]) can provide a rapid assessment of the overall structure likeliness, and SAXS would yield the structure-related pair-wise distance distribution function p(r) vs. r. Using the extensively validated UltraScan SOlution MOdeler (US-SOMO) suite, a database was implemented calculating from AlphaFold structures the corresponding [Formula: see text], [Formula: see text], [η], p(r) vs. r, and other parameters. Circular dichroism spectra were computed using the SESCA program. Some of AlphaFold's drawbacks were mitigated, such as generating whenever possible a protein's mature form. Others, like the AlphaFold direct applicability to single-chain structures only, the absence of prosthetic groups, or flexibility issues, are discussed. Overall, this implementation of the US-SOMO-AF database should already aid in rapidly evaluating the consistency in solution of a relevant portion of AlphaFold predicted protein structures.
| S-EPMC9072687 | biostudies-literature
Project description:The isolation and structural characterization of both aldehyde- and ketone-derived proline enaminones are reported and discussed. Crystal structures of 10 proline enamines provide information on stereochemical aspects, i.e., double bond configuration and syn- vs. anti-positioning of the carboxylate relative to the enamine double bond. Furthermore, the obtained crystal structures are compared with the density functional theory-calculated structures of the ground and transition state and the postulated Seebach-Eschenmoser transition state.
| S-EPMC2996454 | biostudies-literature
Project description:One of the most striking features of KCTD proteins is their involvement in apparently unrelated yet fundamental physio-pathological processes. Unfortunately, comprehensive structure-function relationships for this protein family have been hampered by the scarcity of the structural data available. This scenario is rapidly changing due to the release of the protein three-dimensional models predicted by AlphaFold (AF). Here, we exploited the structural information contained in the AF database to gain insights into the relationships among the members of the KCTD family with the aim of facilitating the definition of the structural and molecular basis of key roles that these proteins play in many biological processes. The most important finding that emerged from this investigation is the discovery that, in addition to the BTB domain, the vast majority of these proteins also share a structurally similar domain in the C-terminal region despite the absence of general sequence similarities detectable in this region. Using this domain as reference, we generated a novel and comprehensive structure-based pseudo-phylogenetic tree that unraveled previously undetected similarities among the protein family. In particular, we generated a new clustering of the KCTD proteins that will represent a solid ground for interpreting their many functions.
| S-EPMC8699099 | biostudies-literature