The Vps13 Family of Lipid Transporters and Its Role at Membrane Contact Sites

The conserved VPS13 proteins constitute a new family of lipid transporters at membrane contact sites. These large proteins are suspected to bridge membranes and form a direct channel for lipid transport between organelles. Mutations in the 4 human homologs (VPS13A–D) are associated with a number of neurological disorders, but little is known about their precise functions or the relevant contact sites affected in disease. In contrast, yeast has a single Vps13 protein which is recruited to multiple organelles and contact sites. The yeast model system has proved useful for studying the function of Vps13 at different organelles and identifying the localization determinants responsible for its membrane targeting. In this review we describe recent advances in our understanding of VPS13 proteins with a focus on yeast research.

Backbone-independent NMR resonance assignments of methyl probes in large proteins

Methyl-specific isotope labeling is a powerful tool to study the structure, dynamics and interactions of large proteins and protein complexes by solution-state NMR. However, widespread applications of this methodology have been limited by challenges in obtaining confident resonance assignments. Here, we present Methyl Assignments Using Satisfiability (MAUS), leveraging Nuclear Overhauser Effect cross-peak data, peak residue type classification and a known 3D structure or structural model to provide robust resonance assignments consistent with all the experimental inputs. Using data recorded for targets with known assignments in the 10–45 kDa size range, MAUS outperforms existing methods by up to 25,000 times in speed while maintaining 100% accuracy. We derive de novo assignments for multiple Cas9 nuclease domains, demonstrating that the methyl resonances of multi-domain proteins can be assigned accurately in a matter of days, while reducing biases introduced by manual pre-processing of the raw NOE data. MAUS is available through an online web-server.

Large Multidomain Protein NMR: HIV-1 Reverse Transcriptase Precursor in Solution

NMR studies of large proteins, over 100 kDa, in solution are technically challenging and, therefore, of considerable interest in the biophysics field. The challenge arises because the molecular tumbling of a protein in solution considerably slows as molecular mass increases, reducing the ability to detect resonances. In fact, the typical 1H-13C or 1H-15N correlation spectrum of a large protein, using a 13C- or 15N-uniformly labeled protein, shows severe line-broadening and signal overlap. Selective isotope labeling of methyl groups is a useful strategy to reduce these issues, however, the reduction in the number of signals that goes hand-in-hand with such a strategy is, in turn, disadvantageous for characterizing the overall features of the protein. When domain motion exists in large proteins, the domain motion differently affects backbone amide signals and methyl groups. Thus, the use of multiple NMR probes, such as 1H, 19F, 13C, and 15N, is ideal to gain overall structural or dynamical information for large proteins. We discuss the utility of observing different NMR nuclei when characterizing a large protein, namely, the 66 kDa multi-domain HIV-1 reverse transcriptase that forms a homodimer in solution. Importantly, we present a biophysical approach, complemented by biochemical assays, to understand not only the homodimer, p66/p66, but also the conformational changes that contribute to its maturation to a heterodimer, p66/p51, upon HIV-1 protease cleavage.

Visualization of Factor Viii with Flow-Cytometry as a tool for Novel Gene Therapy Approach in Hemophilia A

Haemophilia A is a genetic X-linked disorder, characterized by coagulation Factor VIII (FVIII) deficiency and leading to pathological bleedings. The disease occurs at a rate of 1 in 5000 males’ births. The treatment is the administration of plasma-derived or recombinant Factor VIII, which is expensive and leads to the development of inhibitory antibodies in around 40% of patients affected by the severe form of the disease. The disease becomes for these patients as life threatening. In new approaches to treat Haemophilia include gene therapy (GT), cells corrected through genetic modifications are used to produce in Haemophilia A patients FVIII protein in a sustained manner, as long-term treatment for this disorder. The cells of choice should be persistent and equipped with themachinery for large protein assembly and secretion. So far, target cells for Haemophilia gene correction are mostly liver cells, although they are highly immunogenic and exposed to immune-mediated destruction after GT. Based on literature evidences, bone marrow transplantation can correct Haemophilia A in mice, providing evidence that Hematopoietic stem cells (HSC) or their progeny are able to produce FVIII. We chose the approach of correcting HSC with lentiviral vectors carrying the FVIII gene cassette. Whereas classically FVIII protein is visualized on adherent cells through immunohistochemistry staining, flow-cytometry (FC) literature publications are very scarce. FC analysis is an attractive method for analysing hematopoietic cells, and in general, a versatile method for protein visualization. However, large proteins as FVIII are difficult to be carefully analysed, and the method requires several steps of optimization. This joint project with Dr. Muhammad Elnaggar, aims to optimize a method to characterize large proteins as FVIII with a reliable FC staining protocol. To this aim, we used cell lines to evaluate the expression and secretion pathways of FVIII, the intracellular requirements to fold and secrete large proteins, and the toxicities of protein accumulation, in case of GT mediated protein overexpression. For this purpose, the FC experiments were performed to optimise the FC protocol for FVIII visualization, by improving blocking efficacy, antibody-labelling efficacy and to ensure accuracy and validity through qPCR and FC double staining. This FC protocol proved its validity and usefulness in visualizing and studying functionally FVIII.

Normal Mode Analysis: A Tool for Better Understanding Protein Flexibility and Dynamics with Application to Homology Models

Molecular dynamics (MD) and normal mode analysis (NMA) are very useful methods for characterizing various dynamic aspects of biological macromolecules. In comparison to MD, NMA is computationally less expensive which facilitates the quick and systematic investigation of protein flexibility and dynamics even for large proteins and protein complexes, whose structure was obtained experimentally or in silico. In particular, NMA can be used to describe the flexible states adopted by a protein around an equilibrium position. These states have been repeatedly shown to have biological relevance and functional significance. This chapter briefly characterizes NMA and describes the elastic network model, a schematic model of protein shape used to decrease the computational cost of this method. Finally, we will describe the applications of this technique to several large proteins and their complexes as well as its use in enhancing protein homology modeling.

Impact of non-proteinogenic amino acids in the discovery and development of peptide therapeutics

With the development of modern chemistry and biology, non-proteinogenic amino acids (NPAAs) have become a powerful tool for developing peptide-based drug candidates. Drug-like properties of peptidic medicines, due to the smaller size and simpler structure compared to large proteins, can be changed fundamentally by introducing NPAAs in its sequence. While peptides composed of natural amino acids can be used as drug candidates, the majority have shown to be less stable in biological conditions. The impact of NPAA incorporation can be extremely beneficial in improving the stability, potency, permeability, and bioavailability of peptide-based therapies. Conversely, undesired effects such as toxicity or immunogenicity should also be considered. The impact of NPAAs in the development of peptide-based therapeutics is reviewed in this article. Further, numerous examples of peptides containing NPAAs are presented to highlight the ongoing development in peptide-based therapeutics.

Fmr1 translationally activates stress-sensitive mRNAs encoding large proteins in oocytes and neurons

Mutations in Fmr1 are the leading heritable cause of intellectual disability and autism spectrum disorder. We previously found that Fmr1 acts as a ∼2-fold activator of translation of large proteins in Drosophila oocytes, in contrast to its proposed role as a repressor of translation elongation. Here, we show that genes associated with autism spectrum disorders tend to be dosage-sensitive and encode proteins that are larger than average. Reanalysis of Fmr1 KO mouse cortex ribosome profiling data demonstrates that autism-associated mRNAs encoding large proteins exhibit a concordant reduction in ribosome footprints, consistent with a general role for Fmr1 as a translational activator. We find no evidence that differential ribosomal pausing affects translational output in Fmr1-deficient Drosophila oocytes or mouse cortex. Furthermore, long Fmr1 target transcripts are preferentially enriched in stress granules upon acute stress. Our data thus identify a critical role for Fmr1 in promoting the translation of long, stress-sensitive, autism-associated mRNAs.

REDCRAFT: A Computational Platform Using Residual Dipolar Coupling NMR Data for Determining Structures of Perdeuterated Proteins Without NOEs

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two primary experimental means of characterizing macromolecular structures, including protein structures. Structure determination by NMR spectroscopy has traditionally relied heavily on distance restraints derived from nuclear Overhauser effect (NOE) measurements. While structure determination of proteins from NOE-based restraints is well understood and broadly used, structure determination by NOEs imposes increasing quantity of data for analysis, increased cost of structure determination and is less available in the study of perdeuterated proteins. In the recent decade, Residual Dipolar Couplings (RDCs) have been investigated as an alternative source of data for structural elucidation of proteins by NMR. Several methods have been reported that utilize RDCs in addition to NOEs, and a few utilize RDC data alone. While these methods have individually demonstrated some successes, none of these methods have exposed the full potential of protein structure determination from RDCs. To date, structure determination of proteins from RDCs is limited to small proteins (less than 8.5 kDa) using RDC data from many alignment media (>3) that cannot be collected from larger proteins. Here we present the latest version of the REDCRAFT software package designed for structure determination of proteins from RDC data alone. We have demonstrated the success of REDCRAFT in structure determination of proteins ranging in size from 50 to 145 residues using experimentally collected data and large proteins (145 to 573 residues) using simulated RDC data that can be collected from perdeuterated proteins. Finally, we demonstrate the accuracy of structure determination of REDCRAFT from RDCs alone in application to the structurally novel PF.2048 protein. The RDC-based structure of PF.2048 exhibited 1.0 Å of BB-RMSD with respect to the NOE-based structure by only using a small amount of backbone RDCs (∼3 restraints per residue) compared to what is required by other approaches.Author SummaryResidual Dipolar Couplings have the potential to reduce the cost and the time needed to characterize protein structures. In addition, RDC data have been demonstrated to concurrently elucidate structure of proteins, perform assignment of resonances, and be used in characterization of the internal dynamics of proteins. Given all the advantages associated with the study of proteins from RDC data, based on the statistics provided by the Protein Databank (PDB), surprisingly the only 124 proteins (out of nearly 150,000 proteins) have utilized RDCs as part of their structure determination. Even a smaller subset of these proteins (approximately 7) have utilized RDCs as the primary source of data for structure determination. The impeding factor in the use of RDCs is the challenging computational and analytical aspects of this source of data. In this report, we demonstrate the success of the REDCRAFT software package in structure determination of proteins using RDC data that can be collected from small and large proteins in a routine fashion. REDCRAFT accomplishes the challenging task of structure determination from RDCs by introducing a unique search and optimization technique that is both robust and computationally tractable. Structure determination from routinely collectable RDC data using REDCRAFT can lead to faster and cheaper study of larger and more complex proteins by NMR spectroscopy in solution state.