Evidence for a credit-card-swipe mechanism in the human PC floppase ABCB4

Molecular basis of progressive familial intrahepatic cholestasis 3. A proteomics study

Progressive familial intrahepatic cholestasis type 3 (PFIC3) is a severe rare liver disease that affects between 1/50,000 and 1/100,000 children. In physiological conditions, bile is produced by the liver and stored in the gallbladder, and then it flows to the small intestine to play its role in fat digestion. To prevent tissue damage, bile acids (BAs) are kept in phospholipid micelles. Mutations in phosphatidyl choline transporter ABCB4 (MDR3) lead to intrahepatic accumulation of free BAs that result in liver damage. PFIC3 onset usually occurs at early ages, progresses rapidly, and the prognosis is poor. Currently, besides the palliative use of ursodeoxycholate, the only available treatment for this disease is liver transplantation, which is really challenging for short-aged patients. To gain insight into the pathogenesis of PFIC3 we have performed an integrated proteomics and phosphoproteomics study in human liver samples to then validate the emerging functional hypotheses in a PFIC3 murine model. We identified 6246 protein groups, 324 proteins among them showing differential expression between control and PFIC3. The phosphoproteomic analysis allowed the identification of 5090 phosphopeptides, from which 215 corresponding to 157 protein groups, were differentially phosphorylated in PFIC3, including MDR3. Regulation of essential cellular processes and structures, such as inflammation, metabolic reprogramming, cytoskeleton and extracellular matrix remodeling, and cell proliferation, were identified as the main drivers of the disease. Our results provide a strong molecular background that significantly contributes to a better understanding of PFIC3 and provides new concepts that might prove useful in the clinical management of patients.

Reconstitution of ATP-dependent lipid transporters: gaining insight into molecular characteristics, regulation, and mechanisms

Lipid transporters play a crucial role in supporting essential cellular processes such as organelle assembly, vesicular trafficking, and lipid homeostasis by driving lipid transport across membranes. Cryo-electron microscopy has recently resolved the structures of several ATP-dependent lipid transporters, but functional characterization remains a major challenge. Although studies of detergent-purified proteins have advanced our understanding of these transporters, in vitro evidence for lipid transport is still limited to a few ATP-dependent lipid transporters. Reconstitution into model membranes, such as liposomes, is a suitable approach to study lipid transporters in vitro and to investigate their key molecular features. In this review, we discuss the current approaches for reconstituting ATP-driven lipid transporters into large liposomes and common techniques used to study lipid transport in proteoliposomes. We also highlight the existing knowledge on the regulatory mechanisms that modulate the activity of lipid transporters, and finally, we address the limitations of the current approaches and future perspectives in this field.

Lipid flipping in the omega-3 fatty-acid transporter

Mfsd2a is the transporter for docosahexaenoic acid (DHA), an omega-3 fatty acid, across the blood brain barrier (BBB). Defects in Mfsd2a are linked to ailments from behavioral and motor dysfunctions to microcephaly. Mfsd2a transports long-chain unsaturated fatty-acids, including DHA and α-linolenic acid (ALA), that are attached to the zwitterionic lysophosphatidylcholine (LPC) headgroup. Even with the recently determined structures of Mfsd2a, the molecular details of how this transporter performs the energetically unfavorable task of translocating and flipping lysolipids across the lipid bilayer remains unclear. Here, we report five single-particle cryo-EM structures of Danio rerio Mfsd2a (drMfsd2a): in the inward-open conformation in the ligand-free state and displaying lipid-like densities modeled as ALA-LPC at four distinct positions. These Mfsd2a snapshots detail the flipping mechanism for lipid-LPC from outer to inner membrane leaflet and release for membrane integration on the cytoplasmic side. These results also map Mfsd2a mutants that disrupt lipid-LPC transport and are associated with disease.

CHARMM-GUI Membrane Builder: Past, Current, and Future Developments and Applications

Molecular dynamics simulations of membranes and membrane proteins serve as computational microscopes, revealing coordinated events at the membrane interface. As G protein-coupled receptors, ion channels, transporters, and membrane-bound enzymes are important drug targets, understanding their drug binding and action mechanisms in a realistic membrane becomes critical. Advances in materials science and physical chemistry further demand an atomistic understanding of lipid domains and interactions between materials and membranes. Despite a wide range of membrane simulation studies, generating a complex membrane assembly remains challenging. Here, we review the capability of CHARMM-GUI Membrane Builder in the context of emerging research demands, as well as the application examples from the CHARMM-GUI user community, including membrane biophysics, membrane protein drug-binding and dynamics, protein-lipid interactions, and nano-bio interface. We also provide our perspective on future Membrane Builder development.

Vasor: Accurate prediction of variant effects for amino acid substitutions in multidrug resistance protein 3

The phosphatidylcholine floppase multidrug resistance protein 3 (MDR3) is an essential hepatobiliary transport protein. MDR3 dysfunction is associated with various liver diseases, ranging from severe progressive familial intrahepatic cholestasis to transient forms of intrahepatic cholestasis of pregnancy and familial gallstone disease. Single amino acid substitutions are often found as causative of dysfunction, but identifying the substitution effect in in vitro studies is time and cost intensive. We developed variant assessor of MDR3 (Vasor), a machine learning-based model to classify novel MDR3 missense variants into the categories benign or pathogenic. Vasor was trained on the largest data set to date that is specific for benign and pathogenic variants of MDR3 and uses general predictors, namely Evolutionary Models of Variant Effects (EVE), EVmutation, PolyPhen-2, I-Mutant2.0, MUpro, MAESTRO, and PON-P2 along with other variant properties, such as half-sphere exposure and posttranslational modification site, as input. Vasor consistently outperformed the integrated general predictors and the external prediction tool MutPred2, leading to the current best prediction performance for MDR3 single-site missense variants (on an external test set: F1-score, 0.90; Matthew's correlation coefficient, 0.80). Furthermore, Vasor predictions cover the entire sequence space of MDR3. Vasor is accessible as a webserver at https://cpclab.uni-duesseldorf.de/mdr3_predictor/ for users to rapidly obtain prediction results and a visualization of the substitution site within the MDR3 structure. The MDR3-specific prediction tool Vasor can provide reliable predictions of single-site amino acid substitutions, giving users a fast way to initially assess whether a variant is benign or pathogenic.

Comprehensive Collection and Prediction of ABC Transmembrane Protein Structures in the AI Era of Structural Biology

The number of unique transmembrane (TM) protein structures doubled in the last four years, which can be attributed to the revolution of cryo-electron microscopy. In addition, AlphaFold2 (AF2) also provided a large number of predicted structures with high quality. However, if a specific protein family is the subject of a study, collecting the structures of the family members is highly challenging in spite of existing general and protein domain-specific databases. Here, we demonstrate this and assess the applicability and usability of automatic collection and presentation of protein structures via the ABC protein superfamily. Our pipeline identifies and classifies transmembrane ABC protein structures using the PFAM search and also aims to determine their conformational states based on special geometric measures, conftors. Since the AlphaFold database contains structure predictions only for single polypeptide chains, we performed AF2-Multimer predictions for human ABC half transporters functioning as dimers. Our AF2 predictions warn of possibly ambiguous interpretation of some biochemical data regarding interaction partners and call for further experiments and experimental structure determination. We made our predicted ABC protein structures available through a web application, and we joined the 3D-Beacons Network to reach the broader scientific community through platforms such as PDBe-KB.