The structure, catalytic mechanism, and inhibitor identification of phosphatidylinositol remodeling MBOAT7

Wang, Kun; Lee, Chia‐Wei; Sui, Xuewu; Kim, Siyoung; Wang, Shuhui; Higgs, Aidan B.; Baublis, Aaron J.; Voth, Gregory A.; Liao, Maofu; Walther, Tobias C.; Farese, Robert V.

doi:10.1101/2022.09.15.508141

Cited by 3 publications

(3 citation statements)

References 62 publications

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“…Moreover, our understanding of small-molecule inhibition of MBOAT enzymes, in general, is limited. Inhibitors have been developed for other MBOAT enzymes, such as PORCN 26 and HHAT 27 , that acylate the signaling proteins Wnt and Shh, respectively, or MBOAT5 28 and MBOAT7 21 that acylate phospholipids. Some are in clinical trials 26,29 .…”

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confidence: 99%

Mechanism of action for small-molecule inhibitors of triacylglycerol synthesis

et al. 2023

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Inhibitors of triacylglycerol (TG) synthesis have been developed to treat metabolism-related diseases, but we know little about their mechanisms of action. Here, we report cryo-EM structures of the TG-synthesis enzyme acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), a membrane bound O-acyltransferase (MBOAT), in complex with two different inhibitors, T863 and DGAT1IN1. Each inhibitor binds DGAT1’s fatty acyl-CoA substrate binding tunnel that opens to the cytoplasmic side of the ER. T863 blocks access to the tunnel entrance, whereas DGAT1IN1 extends further into the enzyme, with an amide group interacting with more deeply buried catalytic residues. A survey of DGAT1 inhibitors revealed that this amide group may serve as a common pharmacophore for inhibition of MBOATs. The inhibitors were minimally active against the related MBOAT acyl-CoA:cholesterol acyltransferase 1 (ACAT1), yet a single-residue mutation sensitized ACAT1 for inhibition. Collectively, our studies provide a structural foundation for developing DGAT1 and other MBOAT inhibitors.

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confidence: 99%

Mechanism of action for small-molecule inhibitors of triacylglycerol synthesis

et al. 2023

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“…The contributions of ACSL4 and LPCAT3 to ferroptosis have been extensively reviewed elsewhere [82][83][84][85]. ACSL4 may specifically scaffold with MBOAT7, a Lands cycle enzyme that acylates lysophosphatidylinositol with arachidonoyl-CoA to form PI-PUFAs [76,86,87].…”

Section: Phospholipid Remodelingmentioning

confidence: 99%

“…The contributions of ACSL4 and LPCAT3 to ferroptosis have been extensively reviewed elsewhere [82–85]. ACSL4 may specifically scaffold with MBOAT7, a Lands cycle enzyme that acylates lysophosphatidylinositol with arachidonoyl‐CoA to form PI‐PUFAs [76, 86, 87]. CRISPR‐mediated disruption of MBOAT7 in OVCAR‐7 cells reduces their sensitivity to the direct GPX4 inhibitors ML210 and FIN56, indicating that MBOAT7 promotes ferroptosis sensitivity by inserting AA into PI phospholipids [86].…”

Section: Phospholipid Remodelingmentioning

confidence: 99%

A tale of two lipids: Lipid unsaturation commands ferroptosis sensitivity

Rodencal

Dixon

2023

Proteomics

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Membrane lipids play important roles in the regulation of cell fate, including the execution of ferroptosis. Ferroptosis is a non-apoptotic cell death mechanism defined by iron-dependent membrane lipid peroxidation. Phospholipids containing polyunsaturated fatty acids (PUFAs) are highly vulnerable to peroxidation and are essential for ferroptosis execution. By contrast, the incorporation of less oxidizable monounsaturated fatty acids (MUFAs) in membrane phospholipids protects cells from ferroptosis.The enzymes and pathways that govern PUFA and MUFA metabolism therefore play a critical role in determining cellular sensitivity to ferroptosis. Here, we review three lipid metabolic processes-fatty acid biosynthesis, ether lipid biosynthesis, and phospholipid remodeling-that can govern ferroptosis sensitivity by regulating the balance of PUFAs and MUFAs in membrane phospholipids.

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Lipid network and moiety analysis for revealing enzymatic dysregulation and mechanistic alterations from lipidomics data

Rose

Köhler

Falk

et al. 2023

Briefings in Bioinformatics

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Lipidomics is of growing importance for clinical and biomedical research due to many associations between lipid metabolism and diseases. The discovery of these associations is facilitated by improved lipid identification and quantification. Sophisticated computational methods are advantageous for interpreting such large-scale data for understanding metabolic processes and their underlying (patho)mechanisms. To generate hypothesis about these mechanisms, the combination of metabolic networks and graph algorithms is a powerful option to pinpoint molecular disease drivers and their interactions. Here we present lipid network explorer (LINEX$^2$), a lipid network analysis framework that fuels biological interpretation of alterations in lipid compositions. By integrating lipid-metabolic reactions from public databases, we generate dataset-specific lipid interaction networks. To aid interpretation of these networks, we present an enrichment graph algorithm that infers changes in enzymatic activity in the context of their multispecificity from lipidomics data. Our inference method successfully recovered the MBOAT7 enzyme from knock-out data. Furthermore, we mechanistically interpret lipidomic alterations of adipocytes in obesity by leveraging network enrichment and lipid moieties. We address the general lack of lipidomics data mining options to elucidate potential disease mechanisms and make lipidomics more clinically relevant.

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The structure, catalytic mechanism, and inhibitor identification of phosphatidylinositol remodeling MBOAT7

Cited by 3 publications

References 62 publications

Mechanism of action for small-molecule inhibitors of triacylglycerol synthesis

Mechanism of action for small-molecule inhibitors of triacylglycerol synthesis

A tale of two lipids: Lipid unsaturation commands ferroptosis sensitivity

Lipid network and moiety analysis for revealing enzymatic dysregulation and mechanistic alterations from lipidomics data

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