Identification of common structural features of binding sites in galactose-specific proteins

Evaluation of substrate specificity and catalytic promiscuity of Bacillus albus cellulase: an insight into in silico proteomic study aiming at enhanced production of renewable energy

Cellulases are enzymes that aid in the hydrolysis of cellulosic fibers and have a wide range of industrial uses. In the present in silico study, sequence alignment between cellulases from different Bacillus species revealed that most of the residues are conserved in those aligned enzymes. Three dimensional structures of cellulase enzymes from 23 different Bacillus species have been predicted and based on the alignment between the modeled structures, those enzymes have been categorized into 7 different groups according to the homology in their conformational folds. There are two structural contents in Gr-I cellulase namely β1-α2 and β3-α5 loops which varies greatly according to their static position. Molecular docking study between the B. albus cellulase and its various cellulosic substrates including xylanoglucan oligosaccharides revealed that residues viz. Phe154, Tyr258, Tyr282, Tyr285, and Tyr376 of B. albus cellulase are significantly involved in formation stacking interaction during enzyme-substrate binding. Residue interaction network and binding energy analysis for the B. albus cellulase with different cellulosic substrates depicted the strong affinity of XylGlc3 substrate with the receptor enzyme. Molecular interaction and molecular dynamics simulation studies exhibited structural stability of enzyme-substrate complexes which are greatly influenced by the presence of catalytic promiscuity in their substrate binding sites. Screening of B. albus in carboxymethylcellulose (CMC) and xylan supplemented agar media revealed the capability of the bacterium in degrading both cellulose and xylan. Overall, the study demonstrated B. albus cellulase as an effective biocatalyst candidate with the potential role of catalytic promiscuity for possible applications in biofuel industries.Communicated by Ramaswamy H. Sarma.

Khasianine Affects the Expression of Sugar-Sensitive Proteins in Pancreatic Cancer Cells, Which Are Altered in Data from the Rat Model and Patients

Pancreatic ductal adenocarcinoma (PDAC) is a deadly malignancy with no effective treatment, particularly in the advanced stage. This study explored the antiproliferative activity of khasianine against pancreatic cancer cell lines of human (Suit2-007) and rat (ASML) origin. Khasianine was purified from Solanum incanum fruits by silica gel column chromatography and analyzed by LC-MS and NMR spectroscopy. Its effect in pancreatic cancer cells was evaluated by cell proliferation assay, chip array and mass spectrometry. Proteins showing sensitivity to sugars, i.e. sugar-sensitive lactosyl-Sepharose binding proteins (LSBPs), were isolated from Suit2-007 cells by competitive affinity chromatography. The eluted fractions included galactose-, glucose-, rhamnose- and lactose-sensitive LSBPs. The resulting data were analyzed by Chipster, Ingenuity Pathway Analysis (IPA) and GraphPad Prism. Khasianine inhibited proliferation of Suit2-007 and ASML cells with IC50 values of 50 and 54 μg/mL, respectively. By comparative analysis, khasianine downregulated lactose-sensitive LSBPs the most (126%) and glucose-sensitive LSBPs the least (85%). Rhamnose-sensitive LSBPs overlapped significantly with lactose-sensitive LSBPs and were the most upregulated in data from patients (23%) and a pancreatic cancer rat model (11.5%). From IPA, the Ras homolog family member A (RhoA) emerged as one of the most activated signaling pathways involving rhamnose-sensitive LSBPs. Khasianine altered the mRNA expression of sugar-sensitive LSBPs, some of which were modulated in data from patients and the rat model. The antiproliferative effect of khasianine in pancreatic cancer cells and the downregulation of rhamnose-sensitive proteins underscore the potential of khasianine in treating pancreatic cancer.

Application of machine learning on understanding biomolecule interactions in cellular machinery

Machine learning (ML) applications have become ubiquitous in all fields of research including protein science and engineering. Apart from protein structure and mutation prediction, scientists are focusing on knowledge gaps with respect to the molecular mechanisms involved in protein binding and interactions with other components in the experimental setups or the human body. Researchers are working on several wet-lab techniques and generating data for a better understanding of concepts and mechanics involved. The information like biomolecular structure, binding affinities, structure fluctuations and movements are enormous which can be handled and analyzed by ML. Therefore, this review highlights the significance of ML in understanding the biomolecular interactions while assisting in various fields of research such as drug discovery, nanomedicine, nanotoxicity and material science. Hence, the way ahead would be to force hand-in hand of laboratory work and computational techniques.

To Improve Prediction of Binding Residues With DNA, RNA, Carbohydrate, and Peptide Via Multi-Task Deep Neural Networks

MOTIVATION

The interactions of proteins with DNA, RNA, peptide, and carbohydrate play key roles in various biological processes. The studies of uncharacterized protein-molecules interactions could be aided by accurate predictions of residues that bind with partner molecules. However, the existing methods for predicting binding residues on proteins remain of relatively low accuracies due to the limited number of complex structures in databases. As different types of molecules partially share chemical mechanisms, the predictions for each molecular type should benefit from the binding information with other molecule types.

RESULTS

In this study, we employed a multiple task deep learning strategy to develop a new sequence-based method for simultaneously predicting binding residues/sites with multiple important molecule types named MTDsite. By combining four training sets for DNA, RNA, peptide, and carbohydrate-binding proteins, our method yielded accurate and robust predictions with AUC values of 0.852, 0836, 0.758, and 0.776 on their respective independent test sets, which are 0.52 to 6.6% better than other state-of-the-art methods. To my best knowledge, this is the first method using multi-task framework to predict multiple molecular binding sites simultaneously.

Structural Analysis of Binding Determinants of Salmonella typhimurium Trehalose-6-phosphate Phosphatase Using Ground-State Complexes

Trehalose-6-phosphate phosphatase (T6PP) catalyzes the dephosphorylation of trehalose 6-phosphate (T6P) to the disaccharide trehalose. The enzyme is not present in mammals but is essential to the viability of multiple lower organisms as trehalose is a critical metabolite, and T6P accumulation is toxic. Hence, T6PP is a target for therapeutics of human pathologies caused by bacteria, fungi, and parasitic nematodes. Here, we report the X-ray crystal structures of Salmonella typhimurium T6PP (StT6PP) in its apo form and in complex with the cofactor Mg²⁺ and the substrate analogue trehalose 6-sulfate (T6S), the product trehalose, or the competitive inhibitor 4-n-octylphenyl α-d-glucopyranoside 6-sulfate (OGS). OGS replaces the substrate phosphoryl group with a sulfate group and the glucosyl ring distal to the sulfate group with an octylphenyl moiety. The structures of these substrate-analogue and product complexes with T6PP show that specificity is conferred via hydrogen bonds to the glucosyl group proximal to the phosphoryl moiety through Glu123, Lys125, and Glu167, conserved in T6PPs from multiple species. The structure of the first-generation inhibitor OGS shows that it retains the substrate-binding interactions observed for the sulfate group and the proximal glucosyl ring. The OGS octylphenyl moiety binds in a unique manner, indicating that this subsite can tolerate various chemotypes. Together, these findings show that these conserved interactions at the proximal glucosyl ring binding site could provide the basis for the development of broad-spectrum therapeutics, whereas variable interactions at the divergent distal subsite could present an opportunity for the design of potent organism-specific therapeutics.

Lactosyl-sepharose binding proteins from pancreatic cancer cells show differential expression in primary and metastatic organs

In normal cells, glycan binding proteins mediate various cellular processes upon recognition and binding to respective ligands. In tumor cells, these proteins have been associated with metastasis. Lactosyl-sepharose binding proteins (LSBPs) were isolated and identified in a workflow involving lactosyl affinity chromatography and label-free quantification mass spectrometry (LFQ MS). A binding study with monosaccharides was performed by microscale thermophoresis and nuclear magnetic resonance spectroscopy. Influence of galactose on LSBPs’ binding to the lactosyl resin was investigated by competitive affinity chromatography followed by LFQ MS. An analysis of amino acids with sugar binding motifs was searched using bioinformatics tools. The expression profiles of these proteins at the mRNA level, as determined by a chip array from a pancreatic ductal adenocarcinoma (PDAC) liver metastasis model, were used for evaluating their potential role in cancer progression. Proteomics data and their respective genes were analyzed by MaxQuant and Ingenuity Pathway Analysis. In total, 1295 LSBPs were isolated and identified from Suit2-007 human pancreatic adenocarcinoma cells. Interaction studies revealed that these proteins exhibit low to moderate affinity for monosaccharide sugars. Some of these LSBPs even showed reduced affinity after calcium depletion. Among the isolated proteins were annexins and galectins in addition to other families, with no history of binding lactosyl residues. A subset of LSBPs exhibited differential profiles in the pancreas, liver, and lung environments. These modulations may be related to tumor progression. In conclusion, we show that PDAC cells contain LSBPs, a subset of which binds galactose with calcium dependency. The differential expression of these proteins in a rat model highlights their value for diagnosis and as potential drug targets for PDAC therapy. Future work will be required to validate these findings in patient samples.

Impact statement

Interaction of glycan binding proteins with aberrantly expressed glycans in tumor environment is crucial for metastasis. Here, we established a work flow for investigating the presence of a subset of these proteins in PDAC cells, which bind to a lactosyl-sepharose resin. The resin had been designed to isolate proteins with lectin-like properties. The corresponding lactosyl-sepharose binding proteins (LSBPs) show affinity for galactose and other monosaccharides. A subset of the LSBPs shows also calcium dependency. The importance of these proteins is highlighted by their differential expression profiles in PDAC cells growing in primary (pancreas) and metastatic (liver and lung) organ sites. Based on their affinity for the lactosyl-resin and monosaccharides, LSBPs hold potential for PDAC diagnosis and as drug targets. This work has set the stage for further investigation of the occurrence and the role of LSBPs in patient samples using the newly established workflow.

Conformational Change of Amyloid-β 40 in Association with Binding to GM1-Glycan Cluster

Aggregates of amyloid-β (Aβ) peptide are well known to be the causative substance of Alzheimer's disease (AD). Recent studies showed that monosialotetrahexosylganglioside (GM1) clusters induce the pathological aggregation of Aβ peptide responsible for the onset and development of AD. However, the effect of GM1-glycan cluster on Aβ conformations has yet to be clarified. Interactions between Aβ peptide and GM1-glycan cluster is important for the earliest stage of the toxic aggregation on GM1 cluster. Here, we performed all-atom molecular dynamics (MD) simulations of Aβ40 on a recently developed artificial GM1-glycan cluster. The artificial GM1-glycan cluster facilitates the characterization of interactions between Aβ40 and multiple GM1-glycans. We succeeded in observing the binding of Aβ40 to the GM1-glycan cluster in all of our MD simulations. Results obtained from these MD simulations indicate the importance of HHQ (13-15) segment of Aβ40 for the GM1-glycan cluster recognition. This result is consistent with previous experimental studies regarding the glycan recognition of Aβ peptide. The recognition mechanism of HHQ (13-15) segment is mainly explained by non-specific stacking interactions between side-chains of histidine and rings of sugar residues, in which the HHQ regime forms coil and bend structures. Moreover, we found that Aβ40 exhibits helix structures at C-terminal side on the GM1-glycan cluster. The helix formation is the initial stage of the pathological aggregation at ceramide moieties of GM1 cluster. The binding of Lys28 to Neu triggers the helix formation at C-terminus side because the formation of a salt bridge between Lys28 and Neu leads to change of intrachain interactions of Aβ40. Our findings suggest that the pathological helix formation of Aβ40 is initiated at GM1-glycan moieties rather than lipid ceramide moieties.

Conformational properties of an artificial GM1 glycan cluster based on a metal-ligand complex

An artificial glycan cluster, in which 24 monosialotetrahexosylganglioside (GM1) glycans are transplanted to the interface of a metal-ligand complex, was recently proposed to investigate the interaction between GM1 glycan clusters and amyloidogenic proteins by NMR analysis. In this study, all-atom molecular dynamics simulations were performed to characterize the conformational properties of the artificial GM1 glycan cluster. We found that more than 65% of GM1 glycans are clustered by interchain hydrogen bonds. Interchain hydrogen bonds are mainly formed between Neu5Ac and Gal'. Pentamers were most frequently observed in the metal-ligand complex. GM1 glycans are tilted and hydrophobically interact with ligand moieties. The hydrophobic surface of the metal-ligand complex increases intrachain hydrogen bonds in each conformation of the GM1 glycans. The increase of intrachain hydrogen bonds stabilizes the local minimum conformations of the GM1 glycan in comparison with the monomeric one. Interchain hydrogen bonding between glycans and glycan-ligand hydrophobic interactions also contribute to this conformational stabilization. Our results provide the physicochemical properties of the new artificial GM1 glycan cluster under the thermal fluctuations for understanding its protein recognition and designing the drug material for amyloidogenic proteins.

Computational Prediction of Carbohydrate-Binding Proteins and Binding Sites

Protein-carbohydrate interaction is essential for biological systems, and carbohydrate-binding proteins (CBPs) are important targets when designing antiviral and anticancer drugs. Due to the high cost and difficulty associated with experimental approaches, many computational methods have been developed as complementary approaches to predict CBPs or carbohydrate-binding sites. However, most of these computational methods are not publicly available. Here, we provide a comprehensive review of related studies and demonstrate our two recently developed bioinformatics methods. The method SPOT-CBP is a template-based method for detecting CBPs based on structure through structural homology search combined with a knowledge-based scoring function. This method can yield model complex structure in addition to accurate prediction of CBPs. Furthermore, it has been observed that similarly accurate predictions can be made using structures from homology modeling, which has significantly expanded its applicability. The other method, SPRINT-CBH, is a de novo approach that predicts binding residues directly from protein sequences by using sequence information and predicted structural properties. This approach does not need structurally similar templates and thus is not limited by the current database of known protein-carbohydrate complex structures. These two complementary methods are available at https://sparks-lab.org. © 2018 by John Wiley & Sons, Inc.

Structural biology of solute carrier (SLC) membrane transport proteins

The human solute carriers (SLCs) comprise over 400 different transporters, organized into 65 families ( http://slc.bioparadigms.org/ ) based on their sequence homology and transport function. SLCs are responsible for transporting extraordinarily diverse solutes across biological membranes, including inorganic ions, amino acids, lipids, sugars, neurotransmitters and drugs. Most of these membrane proteins function as coupled symporters (co-transporters) utilizing downhill ion (H⁺ or Na⁺) gradients as the driving force for the transport of substrate against its concentration gradient into cells. Other members work as antiporters (exchangers) that typically contain a single substrate-binding site with an alternating access mode of transport, while a few members exhibit channel-like properties. Dysfunction of SLCs is correlated with numerous human diseases and therefore they are potential therapeutic drug targets. In this review, we identified all of the SLC crystal structures that have been determined, most of which are from prokaryotic species. We further sorted all the SLC structures into four main groups with different protein folds and further discuss the well-characterized MFS (major facilitator superfamily) and LeuT (leucine transporter) folds. This review provides a systematic analysis of the structure, molecular basis of substrate recognition and mechanism of action in different SLC family members.

Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines

Carbohydrate-binding proteins play significant roles in many diseases including cancer. Here, we established a machine-learning-based method (called sequence-based prediction of residue-level interaction sites of carbohydrates, SPRINT-CBH) to predict carbohydrate-binding sites in proteins using support vector machines (SVMs). We found that integrating evolution-derived sequence profiles with additional information on sequence and predicted solvent accessible surface area leads to a reasonably accurate, robust, and predictive method, with area under receiver operating characteristic curve (AUC) of 0.78 and 0.77 and Matthew's correlation coefficient of 0.34 and 0.29, respectively for 10-fold cross validation and independent test without balancing binding and nonbinding residues. The quality of the method is further demonstrated by having statistically significantly more binding residues predicted for carbohydrate-binding proteins than presumptive nonbinding proteins in the human proteome, and by the bias of rare alleles toward predicted carbohydrate-binding sites for nonsynonymous mutations from the 1000 genome project. SPRINT-CBH is available as an online server at http://sparks-lab.org/server/SPRINT-CBH .

Ligand-binding specificity and promiscuity of the main lignocellulolytic enzyme families as revealed by active-site architecture analysis

Biomass can be converted into sugars by a series of lignocellulolytic enzymes, which belong to the glycoside hydrolase (GH) families summarized in CAZy databases. Here, using a structural bioinformatics method, we analyzed the active site architecture of the main lignocellulolytic enzyme families. The aromatic amino acids Trp/Tyr and polar amino acids Glu/Asp/Asn/Gln/Arg occurred at higher frequencies in the active site architecture than in the whole enzyme structure. And the number of potential subsites was significantly different among different families. In the cellulase and xylanase families, the conserved amino acids in the active site architecture were mostly found at the −2 to +1 subsites, while in β-glucosidase they were mainly concentrated at the −1 subsite. Families with more conserved binding amino acid residues displayed strong selectivity for their ligands, while those with fewer conserved binding amino acid residues often exhibited promiscuity when recognizing ligands. Enzymes with different activities also tended to bind different hydroxyl oxygen atoms on the ligand. These results may help us to better understand the common and unique structural bases of enzyme-ligand recognition from different families and provide a theoretical basis for the functional evolution and rational design of major lignocellulolytic enzymes.

Sphingolipid transfer proteins defined by the GLTP-fold

Glycolipid transfer proteins (GLTPs) originally were identified as small (~24 kDa), soluble, amphitropic proteins that specifically accelerate the intermembrane transfer of glycolipids. GLTPs and related homologs now are known to adopt a unique, helically dominated, two-layer 'sandwich' architecture defined as the GLTP-fold that provides the structural underpinning for the eukaryotic GLTP superfamily. Recent advances now provide exquisite insights into structural features responsible for lipid headgroup selectivity as well as the adaptability of the hydrophobic compartment for accommodating hydrocarbon chains of differing length and unsaturation. A new understanding of the structural versatility and evolutionary premium placed on the GLTP motif has emerged. Human GLTP-motifs have evolved to function not only as glucosylceramide binding/transferring domains for phosphoinositol 4-phosphate adaptor protein-2 during glycosphingolipid biosynthesis but also as selective binding/transfer proteins for ceramide-1-phosphate. The latter, known as ceramide-1-phosphate transfer protein, recently has been shown to form GLTP-fold while critically regulating Group-IV cytoplasmic phospholipase A2 activity and pro-inflammatory eicosanoid production.

CH-π hydrogen bonds in biological macromolecules

This is a sequel to the previous Perspective "The CH-π hydrogen bond in chemistry. Conformation, supramolecules, optical resolution and interactions involving carbohydrates", which featured in a PCCP themed issue on "Weak Hydrogen Bonds - Strong Effects?": Phys. Chem. Chem. Phys., 2011, 13, 13873-13900. Evidence that weak hydrogen bonds play an enormously important role in chemistry and biochemistry has now accumulated to an extent that the rigid classical concept of hydrogen bonds formulated by Pauling needs to be seriously revised and extended. The concept of a more generalized hydrogen bond definition is indispensable for understanding the folding mechanisms of proteins. The CH-π hydrogen bond, a weak molecular force occurring between a soft acid CH and a soft base π-electron system, among all is one of the most important and plays a functional role in defining the conformation and stability of 3D structures as well as in many molecular recognition events. This concept is also valuable in structure-based drug design efforts. Despite their frequent occurrence in organic molecules and bio-molecules, the importance of CH-π hydrogen bonds is still largely unknown to many chemists and biochemists. Here we present a review that deals with the evidence, nature, characteristics and consequences of the CH-π hydrogen bond in biological macromolecules (proteins, nucleic acids, lipids and polysaccharides). It is hoped that the present Perspective will show the importance of CH-π hydrogen bonds and stimulate interest in the interactions of biological macromolecules, one of the most fascinating fields in bioorganic chemistry. Implication of this concept is enormous and valuable in the scientific community.

Recent advances toward the development of inhibitors to attenuate tumor metastasis via the interruption of lectin-ligand interactions

Aberrant glycosylation is a well-recognized phenomenon that occurs on the surface of tumor cells, and the overexpression of a number of ligands (such as TF, sialyl Tn, and sialyl Lewis X) has been correlated to a worse prognosis for the patient. These unique carbohydrate structures play an integral role in cell-cell communication and have also been associated with more metastatic cancer phenotypes, which can result from binding to lectins present on cell surfaces. The most well studied metastasis-associated lectins are the galectins and selectins, which have been correlated to adhesion, neoangiogenesis, and immune-cell evasion processes. In order to slow the rate of metastatic lesion formation, a number of approaches have been successfully developed which involve interfering with the tumor lectin-substrate binding event. Through the generation of inhibitors, or by attenuating lectin and/or carbohydrate expression, promising results have been observed both in vitro and in vivo. This article briefly summarizes the involvement of lectins in the metastatic process and also describes different approaches used to prevent these undesirable carbohydrate-lectin binding events, which should ultimately lead to improvement in current cancer therapies.

Short antibacterial peptides with significantly reduced hemolytic activity can be identified by a systematic L-to-D exchange scan of their amino acid residues

High systemic toxicity of antimicrobial peptides (AMPs) limits their clinical application to the treatment of topical infections; in parenteral systemic application of AMPs the problem of hemolysis is one of the first to be tackled. We now show that the selectivity of lipidated short synthetic AMPs can be optimized substantially by reducing their hemolytic activity without affecting their activity against methicillin resistant Staphylococcus aureus (MRSA). In order to identify the optimized peptides, two sets of 32 diastereomeric H-(D)Arg-WRWRW-(L)Lys(C(O)CnH2n+1)-NH2 (n = 7 or 9) peptides were prepared using a split-split procedure to perform a systematic L-to-D exchange scan on the central WRWRW-fragment. Compared to the all-L C8-lipidated lead sequence, diastereomeric peptides had very similar antibacterial properties, but were over 30 times less hemolytic. We show that the observed hemolysis and antibacterial activity is affected by both differences in lipophilicity of the different peptides and specific combinations of L- and D-amino acid residues. This study identified several peptides that can be used as tools to precisely unravel the origin of hemolysis and thus help to design even further optimized nontoxic very active short antibacterial peptides.

Computational screening of the human TF-glycome provides a structural definition for the specificity of anti-tumor antibody JAA-F11

Recombinant antibodies are of profound clinical significance; yet, anti-carbohydrate antibodies are prone to undesirable cross-reactivity with structurally related-glycans. Here we introduce a new technology called Computational Carbohydrate Grafting (CCG), which enables a virtual library of glycans to be assessed for protein binding specificity, and employ it to define the scope and structural origin of the binding specificity of antibody JAA-F11 for glycans containing the Thomsen-Friedenreich (TF) human tumor antigen. A virtual library of the entire human glycome (GLibrary-3D) was constructed, from which 1,182 TF-containing human glycans were identified and assessed for their ability to fit into the antibody combining site. The glycans were categorized into putative binders, or non-binders, on the basis of steric clashes with the antibody surface. The analysis employed a structure of the immune complex, generated by docking the TF-disaccharide (Galβ1-3GalNAcα) into a crystal structure of the JAA-F11 antigen binding fragment, which was shown to be consistent with saturation transfer difference (STD) NMR data. The specificities predicted by CCG were fully consistent with data from experimental glycan array screening, and confirmed that the antibody is selective for the TF-antigen and certain extended core-2 type mucins. Additionally, the CCG analysis identified a limited number of related putative binding motifs, and provided a structural basis for interpreting the specificity. CCG can be utilized to facilitate clinical applications through the determination of the three-dimensional interaction of glycans with proteins, thus augmenting drug and vaccine development techniques that seek to optimize the specificity and affinity of neutralizing proteins, which target glycans associated with diseases including cancer and HIV.

Proper fatty acid composition rather than an ionizable lipid amine is required for full transport function of lactose permease from Escherichia coli

Energy-dependent uphill transport but not energy-independent downhill transport by lactose permease (LacY) is impaired when expressed in Escherichia coli cells or reconstituted in liposomes lacking phosphatidylethanolamine (PE) and containing only anionic phospholipids. The absence of PE results in inversion of the N-terminal half and misfolding of periplasmic domain P7, which are required for uphill transport of substrates. Replacement of PE in vitro by lipids with no net charge (phosphatidylcholine (PC), monoglucosyl diacylglycerol (GlcDAG), or diglucosyl diacylglycerol (GlcGlcDAG)) supported wild type transmembrane topology of the N-terminal half of LacY. The restoration of uphill transport in vitro was dependent on LacY native topology and proper folding of P7. Support of uphill transport by net neutral lipids in vitro (PE > PC ≫ GlcDAG ≠ GlcGlcDAG provided that PE or PC contained one saturated fatty acid) paralleled the results observed previously in vivo (PE = PC > GlcDAG ≠ GlcGlcDAG). Therefore, a free amino group is not required for uphill transport as previously concluded based on the lack of in vitro uphill transport when fully unsaturated PC replaced E. coli-derived PE. A close correlation was observed in vivo and in vitro between the ability of LacY to carry out uphill transport, the native conformation of P7, and the lipid headgroup and fatty acid composition. Therefore, the headgroup and the fatty acid composition of lipids are important for defining LacY topological organization and catalytically important structural features, further illustrating the direct role of lipids, independent of other cellular factors, in defining membrane protein structure/function.

Simulation studies of the mechanism of membrane transporters

Membrane transporters facilitate active transport of their specific substrates, often against their electrochemical gradients across the membrane, through coupling the process to various sources of cellular energy, for example, ATP binding and hydrolysis in primary transporters, and pre-established electrochemical gradient of molecular species other than the substrate in the case of secondary transporters. In order to provide efficient energy-coupling mechanisms, membrane transporters have evolved into molecular machines in which stepwise binding, translocation, and transformation of various molecular species are closely coupled to protein conformational changes that take the transporter from one functional state to another during the transport cycle. Furthermore, in order to prevent the formation of leaky states and to be able to pump the substrate against its electrochemical gradient, all membrane transporters use the widely-accepted "alternating access mechanism," which ensures that the substrate is only accessible from one side of the membrane at a given time, but relies on complex and usually global protein conformational changes that differ for each family of membrane transporters. Describing the protein conformational changes of different natures and magnitudes is therefore at the heart of mechanistic studies of membrane transporters. Here, using a number of membrane transporters from diverse families, we present common protocols used in setting up and performing molecular dynamics simulations of membrane transporters and in analyzing the results, in order to characterize relevant motions of the system. The emphasis will be on highlighting how optimal design of molecular dynamics simulations combined with mechanistically oriented analysis can shed light onto key functionally relevant protein conformational changes in this family of membrane proteins.

Prediction of protein-mannose binding sites using random forest

Mannose is an abundant cell surface monosaccharide and has an important role in many biochemical processes. It binds to a great diversity of receptor proteins. In this study we have employed Random Forest for prediction of mannose binding sites. Mannosebinding site is taken to be a sphere around the centroid of the ligand and the sphere is subdivided into different layers and atom wise and residue wise features were extracted for each layer. The method achieves 95.59 % of accuracy using Random Forest with 10 fold cross validation. Prediction of mannose binding site analysis will be quite useful in drug design.

Evaluation of riproximin binding properties reveals a novel mechanism for cellular targeting

Riproximin is a cytotoxic type II ribosome-inactivating protein showing high selectivity for tumor cell lines. Its binding to cell surface glycans is crucial for subsequent internalization and cytotoxicity. In this paper, we describe a unique mechanism of interaction and discuss its implications for the cellular targeting and cytotoxicity of riproximin. On a carbohydrate microarray, riproximin specifically bound to two types of asialo-glycans, namely to bi- and triantennary complex N-glycan structures (NA2/NA3) and to repetitive N-acetyl-D-galactosamine (GalNAc), the so-called clustered Tn antigen, a cancer-specific O-glycan on mucins. Two glycoproteins showing high riproximin binding, the NA3-presenting asialofetuin and the clustered Tn-rich asialo-bovine submaxillary mucin, were subsequently chosen as model glycoproteins to mimic the binding interactions of riproximin with the two types of glycans. ELISA analyses were used to relate the two binding specificities of riproximin to its two sugar binding sites. The ability of riproximin to cross-link the two model proteins revealed that binding of the two types of glycoconjugates occurs within different binding sites. The biological implications of these binding properties were analyzed in cellular assays. The cytotoxicity of riproximin was found to depend on its specific and concomitant interaction with the two glycoconjugates as well as on dynamic avidity effects typical for lectins binding to multivalent glycoproteins. The presence of definite, cancer-related structures on the cells to be targeted determines the therapeutic potency of riproximin. Due to its cross-linking ability, riproximin is expected to show a high degree of specificity for cells exposing both NA2/NA3 and clustered Tn structures.

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

BACKGROUND

There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions.

RESULTS

The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature.

CONCLUSIONS

In addition to confirming literature results, ProGolem's model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners.

Formation of GM1 ganglioside clusters on the lipid membrane containing sphingomyeline and cholesterol

GM1 gangliosides form a microdomain with sphingomyeline (SM) and cholesterol (Chol) and are deeply involved in the aggregation of amyloid beta (Aβ) peptides on neural membranes. We performed molecular dynamics simulations on two kinds of lipid bilayers containing GM1 ganglioside: GM1/SM/Chol and GM1/POPC. Both 10 and 100 ns simulations and another set of 10 ns simulations with different initial lipid arrangement essentially showed the same computational results. GM1 molecules in the GM1/SM/Chol membrane were condensed, whereas those in GM1/POPC membrane scattered. That is, the formation of GM1 cluster was observed only on the GM1/SM/Chol mixed membrane. There appeared numerous hydrogen bonds among glycan portions of the GM1 clusters due to the condensation. A comparison in distribution of lipid molecules between the two kinds of membranes suggested that cholesterol had important roles to prevent the membrane from interdigitation and to stabilize other lipids for interacting with each other. This property of cholesterol promotes the formation of GM1 clusters.

SLC5 and SLC2 transporters in epithelia-cellular role and molecular mechanisms

Members of the SLC5 and SLC2 family are prominently involved in epithelial sugar transport. SGLT1 (sodium-glucose transporter) and SGLT2, as representatives of the former, mediate sodium-dependent uptake of sugars into intestinal and renal cells. GLUT2 (glucose transporter), as representative of the latter, facilitates the sodium-independent exit of sugars from cells. SGLT has played a major role in the formulation and experimental proof for the existence of sodium cotransport systems. Based on the sequence data and biochemical and biophysical analyses, the role of extramembranous loops in sugar and inhibitor binding can be delineated. Crystal structures and homology modeling of SGLT reveal that the sugar translocation involves operation of two hydrophobic gates and intermediate exofacial and endofacial occluded states of the carrier in an alternating access model. The same basic model is proposed for GLUT1. Studies on GLUT1 have pioneered the isolation of eukaryotic transporters by biochemical methods and the development of transport kinetics and transporter models. For GLUT1, results from extensive mutagenesis, cysteine substitution and accessibility studies can be incorporated into a homology model with a barrel-like structure in which accessibility to the extracellular and intracellular medium is altered by pinching movements of some of the helices. For SGLT1 and GLUT1, the extensive hydrophilic and hydrophobic interactions between sugars and binding sites of the various intramembrane helices occur and lead to different substrate specificities and inhibitor affinities of the two transporters. A complex network of regulatory steps adapts the transport activity to the needs of the body.

A gate-free pathway for substrate release from the inward-facing state of the Na⁺-galactose transporter

Employing molecular dynamics (MD) simulations, the pathway and mechanism of substrate unbinding from the inward-facing state of the Na(+)-coupled galactose transporter, vSGLT, have been investigated. During a 200-ns equilibrium simulation, repeated spontaneous unbinding events of the substrate from its binding site have been observed. In contrast to the previously proposed gating role of a tyrosine residue (Y263), the unbinding mechanism captured in the present equilibrium simulation does not rely on the displacement and/or rotation of this side chain. Rather, the unbinding involves an initial lateral displacement of the substrate out of the binding site which allows the substrate to completely emerge from the region covered by the side chain of Y263 without any noticeable conformational changes of the latter. Starting with the snapshots taken from this equilibrium simulation with the substrate outside the binding site, steered MD (SMD) simulations were then used to probe the translocation of the substrate along the remaining of the release pathway within the protein's lumen and to characterize the nature of protein-substrate interactions involved in the process. Combining the results of the equilibrium and SMD simulations, we provide a description of the full translocation pathway for the substrate release from the binding site into the cytoplasm. Residues E68, N142, T431, and N267 facilitate the initial substrate's displacement out of the binding site, while the translocation of the substrate along the remainder of the exit pathway formed between TM6 and TM8 is facilitated by H-bond interactions between the substrate and a series of conserved, polar residues (Y138, N267, R273, S365, S368, N371, S372, and T375). The observed molecular events indicate that no gating is required for the release of the substrate from the crystallographically captured structure of the inward-facing state of SGLT, suggesting that this conformation might represent an open, rather than occluded, state of the transporter. This article is part of a Special Issue entitled: Membrane protein structure and function.

Substituent effects on non-covalent interactions with aromatic rings: insights from computational chemistry

Non-covalent interactions with aromatic rings pervade modern chemical research. The strength and orientation of these interactions can be tuned and controlled through substituent effects. Computational studies of model complexes have provided a detailed understanding of the origin and nature of these substituent effects, and pinpointed flaws in entrenched models of these interactions in the literature. Here, we provide a brief review of efforts over the last decade to unravel the origin of substituent effects in π-stacking, XH/π, and ion/π interactions through detailed computational studies. We highlight recent progress that has been made, while also uncovering areas where future studies are warranted.

Identification of mannose interacting residues using local composition

Background

Mannose binding proteins (MBPs) play a vital role in several biological functions such as defense mechanisms. These proteins bind to mannose on the surface of a wide range of pathogens and help in eliminating these pathogens from our body. Thus, it is important to identify mannose interacting residues (MIRs) in order to understand mechanism of recognition of pathogens by MBPs.

Results

This paper describes modules developed for predicting MIRs in a protein. Support vector machine (SVM) based models have been developed on 120 mannose binding protein chains, where no two chains have more than 25% sequence similarity. SVM models were developed on two types of datasets: 1) main dataset consists of 1029 mannose interacting and 1029 non-interacting residues, 2) realistic dataset consists of 1029 mannose interacting and 10320 non-interacting residues. In this study, firstly, we developed standard modules using binary and PSSM profile of patterns and got maximum MCC around 0.32. Secondly, we developed SVM modules using composition profile of patterns and achieved maximum MCC around 0.74 with accuracy 86.64% on main dataset. Thirdly, we developed a model on a realistic dataset and achieved maximum MCC of 0.62 with accuracy 93.08%. Based on this study, a standalone program and web server have been developed for predicting mannose interacting residues in proteins (http://www.imtech.res.in/raghava/premier/).

Conclusions

Compositional analysis of mannose interacting and non-interacting residues shows that certain types of residues are preferred in mannose interaction. It was also observed that residues around mannose interacting residues have a preference for certain types of residues. Composition of patterns/peptide/segment has been used for predicting MIRs and achieved reasonable high accuracy. It is possible that this novel strategy may be effective to predict other types of interacting residues. This study will be useful in annotating the function of protein as well as in understanding the role of mannose in the immune system.

The CH/π hydrogen bond in chemistry. Conformation, supramolecules, optical resolution and interactions involving carbohydrates

The CH/π hydrogen bond is an attractive molecular force occurring between a soft acid and a soft base. Contribution from the dispersion energy is important in typical cases where aliphatic or aromatic CH groups are involved. Coulombic energy is of minor importance as compared to the other weak hydrogen bonds. The hydrogen bond nature of this force, however, has been confirmed by AIM analyses. The dual characteristic of the CH/π hydrogen bond is the basis for ubiquitous existence of this force in various fields of chemistry. A salient feature is that the CH/π hydrogen bond works cooperatively. Another significant point is that it works in nonpolar as well as polar, protic solvents such as water. The interaction energy depends on the nature of the molecular fragments, CH as well as π-groups: the stronger the proton donating ability of the CH group, the larger the stabilizing effect. This Perspective focuses on the consequence of this molecular force in the conformation of organic compounds and supramolecular chemistry. Implication of the CH/π hydrogen bond extends to the specificity of molecular recognition or selectivity in organic reactions, polymer science, surface phenomena and interactions involving proteins. Many problems, unsettled to date, will become clearer in the light of the CH/π paradigm.

Crystal structure of lactose permease in complex with an affinity inactivator yields unique insight into sugar recognition

Lactose permease of Escherichia coli (LacY) with a single-Cys residue in place of A122 (helix IV) transports galactopyranosides and is specifically inactivated by methanethiosulfonyl-galactopyranosides (MTS-gal), which behave as unique suicide substrates. In order to study the mechanism of inactivation more precisely, we solved the structure of single-Cys122 LacY in complex with covalently bound MTS-gal. This structure exhibits an inward-facing conformation similar to that observed previously with a slight narrowing of the cytoplasmic cavity. MTS-gal is bound covalently, forming a disulfide bond with C122 and positioned between R144 and W151. E269, a residue essential for binding, coordinates the C-4 hydroxyl of the galactopyranoside moiety. The location of the sugar is in accord with many biochemical studies.

Quantification of binding affinities of essential sugars with a tryptophan analogue and the ubiquitous role of C-H···π interactions

The role of noncovalent interactions in carbohydrate recognition by aromatic amino acids has long been reported. To develop a molecular understanding of noncovalent interactions in the recognition process, we have examined a series of binary complexes between 3-methylindole (3-MeIn) and sugars. In particular, the geometries and binding affinities of 3-MeIn with α/β-D-glucose, β-D-galactose, α-D-mannose and α/β-L-fucose are obtained using the MP2(full)/6-31G(d,p) and the M06/TZV2D//MP2/6-31G(d,p) level of theories. The conventional hydrogen bonding such as N-H···O and C-H···O as well as nonconventional O-H···π and C-H···π type of interactions is, in general, identified as responsible for the moderately strong interaction energies. Large variations in the position-orientations of 3-MeIn with respect to saccharide are noticed, within the same sugar family, as well as across different sugar series. Furthermore, complexes with large differences in their geometries are recognized as capable of exhibiting very similar interaction energies, underscoring the significance of exhaustive conformation sampling, as carried out in the present study. These observations are readily attributed to the differences in the efficiency of the type of interactions enlisted above. The highest and lowest interaction energies, upon inclusion of 50% BSSE correction, are found to be -16.02 and -6.22 kcal mol(-1), respectively, for α-D-glucose (1a) and α-L-fucose (5j). While more number of prominent conventional hydrogen bonding contacts remains as a characteristic feature of the strongly bound complexes, the lower end of the interaction energy spectrum is dominated by multiple C-H···π interactions. The complexes exhibiting as many as four C-H···π contacts are identified in the case of α/β-D-glucose, β-D-galactose, and α/β-L-fucose with an interaction energy hovering around -8 kcal mol(-1). The presence of effective C-H···π interactions is found to be dependent on the saccharide configuration as well as the area of the apolar patch constituted by the C-H groups. The study offers a comprehensive set of binary complexes, across different saccharides, which serves as an illustration of the significance and ubiquitous nature of C-H···π interactions in carbohydrate binding in saccharide-protein complexes.

NMR and MD investigations of human galectin-1/oligosaccharide complexes

The specific recognition of carbohydrates by lectins plays a major role in many cellular processes. Galectin-1 belongs to a family of 15 structurally related beta-galactoside binding proteins that are able to control a variety of cellular events, including cell cycle regulation, adhesion, proliferation, and apoptosis. The three-dimensional structure of galectin-1 has been solved by x-ray crystallography in the free form and in complex with various carbohydrate ligands. In this work, we used a combination of two-dimensional NMR titration experiments and molecular-dynamics simulations with explicit solvent to study the mode of interaction between human galectin-1 and five galactose-containing ligands. Isothermal titration calorimetry measurements were performed to determine their affinities for galectin-1. The contribution of the different hexopyranose units in the protein-carbohydrate interaction was given particular consideration. Although the galactose moiety of each oligosaccharide is necessary for binding, it is not sufficient by itself. The nature of both the reducing sugar in the disaccharide and the interglycosidic linkage play essential roles in the binding to human galectin-1.

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge

Hexoses are simple sugars that play a key role in many cellular pathways, and in the regulation of development and disease mechanisms. Current protein-sugar computational models are based, at least partially, on prior biochemical findings and knowledge. They incorporate different parts of these findings in predictive black-box models. We investigate the empirical support for biochemical findings by comparing Inductive Logic Programming (ILP) induced rules to actual biochemical results. We mine the Protein Data Bank for a representative data set of hexose binding sites, non-hexose binding sites and surface grooves. We build an ILP model of hexose-binding sites and evaluate our results against several baseline machine learning classifiers. Our method achieves an accuracy similar to that of other black-box classifiers while providing insight into the discriminating process. In addition, it confirms wet-lab findings and reveals a previously unreported Trp-Glu amino acids dependency.

Computational studies of human galectin-1: role of conserved tryptophan residue in stacking interaction with carbohydrate ligands

Galectins belong to the family of glycan-binding proteins, defined by at least one conserved carbohydrate-recognition domain with a highly conserved amino acid sequence and affinity for beta galactosides. They all possess a tryptophan residue in the carbohydrate binding site that forms hydrophobic contacts with the carbohydrate ligands. Site directed mutagenesis experiments have shown that this conserved aromatic residue plays a key role in the interaction. We have studied the interaction between the corresponding human Galectin-1 in silico mutants and different carbohydrate ligands using molecular dynamics in explicit solvent. The results confirm the importance of the conserved tryptophan residue in the affinity of the ligand and gives further insights into the mode of interaction between lactose derivatives and human Galectin-1.

Bacterial glycoprofiling by using random sequence peptide microarrays

Current analytical methods have been slow in addressing the growing need for glyco-analysis. A new generation of more empirical high-throughput (HTP) tools is needed to aid the advance of this important field. To this end, we have developed a new HTP screening platform for identification of surface-immobilized peptides that specifically bind O-antigenic glycans of bacterial lipopolysaccharides (LPS). This method involves screening of random sequence peptide libraries in addressable high-density microarray format with the newly developed luminescent LPS-quantum dot micelles. Screening of LPS fractions from O111:B4 and O55:B5 serotypes of E. coli on a microarray consisting of 10,000 20-mer peptide features revealed minor differences, while comparison of LPS from E. coli O111:B4 and P. aeruginosa produced sets of highly specific peptides. Peptides strongly binding to the E. coli LPS were highly enriched in aromatic and cationic amino acids, and most of these inhibited growth of E. coli. Flow cytometry and isothermal titration calorimetry (ITC) experiments showed that some of these peptides bind LPS in-solution with a K(d) of 1.75 microM. Peptide selections against P. aeruginosa were largely composed of hydrogen-bond forming amino acids in accordance with dramatic compositional differences in O-antigenic glycans in E. coli and P. aeruginosa. While the main value of this approach lies in the ability to rapidly differentiate bacterial and possibly other complex glycans, the peptides discovered here can potentially be used off-array as antiendotoxic and antimicrobial lead compounds, and on-array/on-bead as diagnostic and affinity reagents.

Glycolipid acquisition by human glycolipid transfer protein dramatically alters intrinsic tryptophan fluorescence: insights into glycolipid binding affinity

Glycolipid transfer proteins (GLTPs) are small, soluble proteins that selectively accelerate the intermembrane transfer of glycolipids. The GLTP fold is conformationally unique among lipid binding/transfer proteins and serves as the prototype and founding member of the new GLTP superfamily. In the present study, changes in human GLTP tryptophan fluorescence, induced by membrane vesicles containing glycolipid, are shown to reflect glycolipid binding when vesicle concentrations are low. Characterization of the glycolipid-induced "signature response," i.e. approximately 40% decrease in Trp intensity and approximately 12-nm blue shift in emission wavelength maximum, involved various modes of glycolipid presentation, i.e. microinjection/dilution of lipid-ethanol solutions or phosphatidylcholine vesicles, prepared by sonication or extrusion and containing embedded glycolipids. High resolution x-ray structures of apo- and holo-GLTP indicate that major conformational alterations are not responsible for the glycolipid-induced GLTP signature response. Instead, glycolipid binding alters the local environment of Trp-96, which accounts for approximately 70% of total emission intensity of three Trp residues in GLTP and provides a stacking platform that aids formation of a hydrogen bond network with the ceramide-linked sugar of the glycolipid headgroup. The changes in Trp signal were used to quantitatively assess human GLTP binding affinity for various lipids including glycolipids containing different sugar headgroups and homogenous acyl chains. The presence of the glycolipid acyl chain and at least one sugar were essential for achieving a low-to-submicromolar dissociation constant that was only slightly altered by increased sugar headgroup complexity.

Aromatic-carbohydrate interactions: an NMR and computational study of model systems

The interactions of simple carbohydrates with aromatic moieties have been investigated experimentally by NMR spectroscopy. The analysis of the changes in the chemical shifts of the sugar proton signals induced upon addition of aromatic entities has been interpreted in terms of interaction geometries. Phenol and aromatic amino acids (phenylalanine, tyrosine, tryptophan) have been used. The observed sugar-aromatic interactions depend on the chemical nature of the sugar, and thus on the stereochemistries of the different carbon atoms, and also on the solvent. A preliminary study of the solvation state of a model monosaccharide (methyl beta-galactopyranoside) in aqueous solution, both alone and in the presence of benzene and phenol, has also been carried out by monitoring of intermolecular homonuclear solvent-sugar and aromatic-sugar NOEs. These experimental results have been compared with those obtained by density functional theory methods and molecular mechanics calculations.

The crystal structure of a sodium galactose transporter reveals mechanistic insights into Na+/sugar symport

Membrane transporters that use energy stored in sodium gradients to drive nutrients into cells constitute a major class of proteins. We report the crystal structure of a member of the solute sodium symporters (SSS), the Vibrio parahaemolyticus sodium/galactose symporter (vSGLT). The approximately 3.0 angstrom structure contains 14 transmembrane (TM) helices in an inward-facing conformation with a core structure of inverted repeats of 5 TM helices (TM2 to TM6 and TM7 to TM11). Galactose is bound in the center of the core, occluded from the outside solutions by hydrophobic residues. Surprisingly, the architecture of the core is similar to that of the leucine transporter (LeuT) from a different gene family. Modeling the outward-facing conformation based on the LeuT structure, in conjunction with biophysical data, provides insight into structural rearrangements for active transport.

Protein subtype-targeting through ligand epimerization: talose-selectivity of galectin-4 and galectin-8

A series of O2 and O3-derivatized methyl beta-d-talopyranosides were synthesized and evaluated in vitro as inhibitors of the galactose-binding galectin-1, -2, -3, -4 (N- and C-terminal domains), 8 (N-terminal domain), and 9 (N-terminal domain). Galectin-4C and 8N were found to prefer the d-talopyranose configuration to the natural ligand d-galactopyranose configuration. Derivatization at talose O2 and/or O3 provided selective submillimolar inhibitors for these two galectins.