Publications

Many eukaryotic proteins are anchored to the cell surface via the glycolipid glycosylphosphatidylinositol (GPI). Mammalian GPIs have a conserved core but exhibit diverse N-acetylgalactosamine (GalNAc) modifications, which are added via a yet unresolved process. Here we identify the Golgi-resident GPI-GalNAc transferase PGAP4 and show by mass spectrometry that PGAP4 knockout cells lose GPI-GalNAc structures. Furthermore, we demonstrate that PGAP4, in contrast to known Golgi glycosyltransferases, is not a single-pass membrane protein but contains three transmembrane domains, including a tandem transmembrane domain insertion into its glycosyltransferase-A fold as indicated by comparative modeling. Mutational analysis reveals a catalytic site, a DXD-like motif for UDP-GalNAc donor binding, and several residues potentially involved in acceptor binding. We suggest that a juxtamembrane region of PGAP4 accommodates various GPI-anchored proteins, presenting their acceptor residue toward the catalytic center. In summary, we present insights into the structure of PGAP4 and elucidate the initial step of GPI-GalNAc biosynthesis.

Protein-carbohydrate interactions are very often mediated by the stacking CH-π interactions involving the side chains of aromatic amino acids such as tryptophan (Trp), tyrosine (Tyr) or phenylalanine (Phe). Especially suitable for stacking is the Trp residue. Analysis of the PDB database shows Trp stacking for 265 carbohydrate or carbohydrate like ligands in 5 208 Trp containing motives. An appropriate model system to study such an interaction is the AAL lectin family where the stacking interactions play a crucial role and are thought to be a driving force for carbohydrate binding. In this study we present data showing a novel finding in the stacking interaction of the AAL Trp side chain with the carbohydrate. High resolution X-ray structure of the AAL lectin from Aleuria aurantia with α-methyl-l-fucoside ligand shows two possible Trp side chain conformations with the same occupation in electron density. The in silico data shows that the conformation of the Trp side chain does not influence the interaction energy despite the fact that each conformation creates interactions with different carbohydrate CH groups. Moreover, the PDB data search shows that the conformations are almost equally distributed across all Trp-carbohydrate complexes, which would suggest no substantial preference for one conformation over another.

Mannose-binding type Jacalin-related lectins (mJRLs) bind to branched N-glycans via conserved sugar-binding sites. Despite, significant 3D structural similarities, each mJRL is known to have a unique binding preference toward various N-glycans. However, the molecular basis of varying binding preference is substantially unknown. Here, we report a detailed comparison of N-glycan-binding preference for two mJRLs, Orysata and Calsepa using frontal affinity chromatography (FAC), X-ray and molecular modeling. The FAC analysis using a panel of N-glycans shows difference in N-glycan-binding preference between the lectins. Orysata shows broader specificity toward most high-mannose-type glycans as well as biantennary complex-type glycans bearing an extension on the Manα1-6 branch. Whereas, Calsepa shows narrow specificity to complex-type glycans with bisecting GlcNAc. The X-ray crystallographic structure reveals that two Orysata lectins bind to one biantennary N-glycan (2:1 binding) where one lectin binds to mannose of the α1-3 branch, while the other interacts with an N-acetylglucosamine of the α1-6 branch. In contrast, Calsepa shows 1:1 binding where α1-3 branch and core chitobiose region N-glycan interacts with lectin, while α1-6 branch is flipped-back to the chitobiose core. Molecular dynamics study of Orysata bound to N-glycans substantiate possibility of two-binding modes for each N-glycan. Binding free energies calculated separately for α1-3 and α1-6 branches of each N-glycan suggest both branches can bind to Orysata. Overall these results suggest that each branch of N-glycan has a distinct role in binding to mJRLs and the nonbinding branch can contribute significantly to the binding affinity and hence to the specificity.

Adams-Oliver syndrome (AOS, OMIM; 100300) is a rare genetic disease characterized by aplasia cutis congenita, terminal transverse limb defects and cutis marmorata with vascular anomalies such as congenital heart defects. The etiology of this syndrome has remained largely unknown but defective Notch signaling during vascular formation has been suggested. Here we describe a sporadic Japanese newborn case with clinically diagnosed AOS. Trio whole-exome sequencing identified a de novo, novel, heterozygous missense mutation in the Delta-like 4 ligand gene (DLL4 c.572G>A, p.Arg191His) in the patient. DLL4 functions as a requisite ligand for NOTCH1 receptor, which is essential for vascular formation. Amino acid substitution of Arg191 to His was predicted by molecular models to interfere with direct binding between DLL4 and NOTCH1. DLL4 has recently been identified as a causative gene of an autosomal dominant type of AOS with milder symptoms. The case described here showed gradual recovery from skull defects after birth and no psychomotor developmental delay has been observed. This is the second report of an AOS case with DLL4 mutation, and the phenotypic characteristics between the two cases are compared and discussed.

Orchestration of the multiple enzymes engaged in O-mannose glycan synthesis provides a matriglycan on α-dystroglycan (α-DG) which attracts extracellular matrix (ECM) proteins such as laminin. Aberrant O-mannosylation of α-DG leads to severe congenital muscular dystrophies due to detachment of ECM proteins from the basal membrane. Phosphorylation at C6-position of O-mannose catalyzed by protein O-mannosyl kinase (POMK) is a crucial step in the biosynthetic pathway of O-mannose glycan. Several mis-sense mutations of the POMK catalytic domain are known to cause a severe congenital muscular dystrophy, Walker-Warburg syndrome. Due to the low sequence similarity with other typical kinases, structure-activity relationships of this enzyme remain unclear. Here, we report the crystal structures of the POMK catalytic domain in the absence and presence of an ATP analogue and O-mannosylated glycopeptide. The POMK catalytic domain shows a typical protein kinase fold consisting of N- and C-lobes. Mannose residue binds to POMK mainly via the hydroxyl group at C2-position, differentiating from other monosaccharide residues. Intriguingly, the two amino acid residues K92 and D228, interacting with the triphosphate group of ATP, are donated from atypical positions in the primary structure. Mutations in this protein causing muscular dystrophies can now be rationalized.

A series of macrocycles consisting of 9,10-substituted phenanthrenes connected by butadiynylene linkers in positions 3 and 6 has been described as well as their transformation into the corresponding phenanthrylene-thienylene macrocycles. Structure and properties of the macrocycles, such as self-association in solution and optical and electrochemical properties, were studied and reported in a comparative manner with respect to the effects of the different sizes and shapes of the macrocycles and the character and length of their side chains.

Protein-carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein-carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments.

Knowledge of the structure and conformational flexibility of carbohydrates in an aqueous solvent is important to improving our understanding of how carbohydrates function in biological systems. In this study, we extend a variant of the Hamiltonian replica-exchange molecular dynamics (MD) simulation to improve the conformational sampling of saccharides in an explicit solvent. During the simulations, a biasing potential along the glycosidic-dihedral linkage between the saccharide monomer units in an oligomer is applied at various levels along the replica runs to enable effective transitions between various conformations. One reference replica runs under the control of the original force field. The method was tested on disaccharide structures and further validated on biologically relevant blood group B, Lewis X and Lewis A trisaccharides. The biasing potential-based replica-exchange molecular dynamics (BP-REMD) method provided a significantly improved sampling of relevant conformational states compared with standard continuous MD simulations, with modest computational costs. Thus, the proposed BP-REMD approach adds a new dimension to existing carbohydrate conformational sampling approaches by enhancing conformational sampling in the presence of solvent molecules explicitly at relatively low computational cost.

The linear interaction energy (LIE) method to compute binding free energies is applied to lectin-monosaccharide complexes. Here, we calculate the binding free energies of monosaccharides to the Ralstonia solanacearum lectin (RSL) and the Pseudomonas aeruginosa lectin-II (PA-IIL). The standard LIE model performs very well for RSL, whereas the PA-IIL system, where ligand binding involves two calcium ions, presents a major challenge. To overcome this, we explore a new variant of the LIE model, where ligand-metal ion interactions are scaled separately. This model also predicts the saccharide binding preference of PA-IIL on mutation of the receptor, which may be useful for protein engineering of lectins.

Carbohydrate-receptor interactions are an integral part of biological events. They play an important role in many cellular processes, such as cell-cell adhesion, cell differentiation and in-cell signaling. Carbohydrates can interact with a receptor by using several types of intermolecular interactions. One of the most important is the interaction of a carbohydrate's apolar part with aromatic amino acid residues, known as dispersion interaction or CH/π interaction. In the study presented here, we attempted for the first time to quantify how the CH/π interaction contributes to a more general carbohydrate-protein interaction. We used a combined experimental approach, creating single and double point mutants with high level computational methods, and applied both to Ralstonia solanacearum (RSL) lectin complexes with α-L-Me-fucoside. Experimentally measured binding affinities were compared with computed carbohydrate-aromatic amino acid residue interaction energies. Experimental binding affinities for the RSL wild type, phenylalanine and alanine mutants were -8.5, -7.1 and -4.1 kcal x mol(-1), respectively. These affinities agree with the computed dispersion interaction energy between carbohydrate and aromatic amino acid residues for RSL wild type and phenylalanine, with values -8.8, -7.9 kcal x mol(-1), excluding the alanine mutant where the interaction energy was -0.9 kcal x mol(-1). Molecular dynamics simulations show that discrepancy can be caused by creation of a new hydrogen bond between the α-L-Me-fucoside and RSL. Observed results suggest that in this and similar cases the carbohydrate-receptor interaction can be driven mainly by a dispersion interaction.