Rescue of secretion of rare-disease-associated misfolded mutant glycoproteins in UGGT1 knock-out mammalian cells.

Endoplasmic reticulum (ER) retention of misfolded glycoproteins is mediated by the ER-localized eukaryotic glycoprotein secretion checkpoint, UDP-glucose glycoprotein glucosyl-transferase (UGGT). The enzyme recognizes a misfolded glycoprotein and flags it for ER retention by re-glucosylating one of its N-linked glycans. In the background of a congenital mutation in a secreted glycoprotein gene, UGGT-mediated ER retention can cause rare disease, even if the mutant glycoprotein retains activity ("responsive mutant"). Using confocal laser scanning microscopy, we investigated here the subcellular localization of the human Trop-2-Q118E, E227K and L186P mutants, which cause gelatinous drop-like corneal dystrophy (GDLD). Compared with the wild-type Trop-2, which is correctly localized at the plasma membrane, these Trop-2 mutants are retained in the ER. We studied fluorescent chimeras of the Trop-2 Q118E, E227K and L186P mutants in mammalian cells harboring CRISPR/Cas9-mediated inhibition of the UGGT1 and/or UGGT2 genes. The membrane localization of the Trop-2 Q118E, E227K and L186P mutants was successfully rescued in UGGT1-/- cells. UGGT1 also efficiently reglucosylated Trop-2-Q118E-EYFP in cellula. The study supports the hypothesis that UGGT1 modulation would constitute a novel therapeutic strategy for the treatment of pathological conditions associated to misfolded membrane glycoproteins (whenever the mutation impairs but does not abrogate function), and it encourages the testing of modulators of ER glycoprotein folding quality control as broad-spectrum rescue-of-secretion drugs in rare diseases caused by responsive secreted glycoprotein mutants.

A Remote Secondary Binding Pocket Promotes Heteromultivalent Targeting of DC-SIGN.

Dendritic cells (DC) are antigen-presenting cells coordinating the interplay of the innate and the adaptive immune response. The endocytic C-type lectin receptors DC-SIGN and Langerin display expression profiles restricted to distinct DC subtypes and have emerged as prime targets for next-generation immunotherapies and anti-infectives. Using heteromultivalent liposomes copresenting mannosides bearing aromatic aglycones with natural glycan ligands, we serendipitously discovered striking cooperativity effects for DC-SIGN+ but not for Langerin+ cell lines. Mechanistic investigations combining NMR spectroscopy with molecular docking and molecular dynamics simulations led to the identification of a secondary binding pocket for the glycomimetics. This pocket, located remotely of DC-SIGN's carbohydrate bindings site, can be leveraged by heteromultivalent avidity enhancement. We further present preliminary evidence that the aglycone allosterically activates glycan recognition and thereby contributes to DC-SIGN-specific cell targeting. Our findings have important implications for both translational and basic glycoscience, showcasing heteromultivalent targeting of DCs to improve specificity and supporting potential allosteric regulation of DC-SIGN and CLRs in general.

AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

SUMMARY: The performance of docking calculations can be improved by tuning parameters for the system of interest, e.g. biasing the results towards the formation of relevant protein-ligand interactions, such as known ligand pharmacophore or interaction sites derived from cosolvent molecular dynamics. AutoDock Bias is a straightforward and easy to use script-based method that allows the introduction of different types of user-defined biases for fine-tuning AutoDock4 docking calculations. AVAILABILITY AND IMPLEMENTATION: AutoDock Bias is distributed with MGLTools (since version 1.5.7), and freely available on the web at http://ccsb.scripps.edu/mgltools/ or http://autodockbias.wordpress.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes.

Unraveling the structure of lectin-carbohydrate complexes is vital for understanding key biological recognition processes and development of glycomimetic drugs. Molecular Docking application to predict them is challenging due to their low affinity, hydrophilic nature and ligand conformational diversity. In the last decade several strategies, such as the inclusion of glycan conformation specific scoring functions or our developed solvent-site biased method, have improved carbohydrate docking performance but significant challenges remain, in particular, those related to receptor conformational diversity. In the present work we have analyzed conventional and solvent-site biased autodock4 performance concerning receptor conformational diversity as derived from different crystal structures (apo and holo), Molecular Dynamics snapshots and Homology-based models, for 14 different lectin-monosaccharide complexes. Our results show that both conventional and biased docking yield accurate lectin-monosaccharide complexes, starting from either apo or homology-based structures, even when only moderate (45%) sequence identity templates are available. An essential element for success is a proper combination of a middle-sized (10-100 structures) conformational ensemble, derived either from Molecular dynamics or multiple homology model building. Consistent with our previous works, results show that solvent-site biased methods improve overall performance, but that results are still highly system dependent. Finally, our results also show that docking can select the correct receptor structure within the ensemble, underscoring the relevance of joint evaluation of both ligand pose and receptor conformation.

Cosolvent-Based Protein Pharmacophore for Ligand Enrichment in Virtual Screening.

Virtual screening of large compound databases, looking for potential ligands of a target protein, is a major tool in computer-aided drug discovery. Throughout the years, different techniques such as similarity searching, pharmacophore matching, or molecular docking have been applied with the aim of finding hit compounds showing appreciable affinity. Molecular dynamics simulations in mixed solvents have been shown to identify hot spots relevant for protein-drug interaction, and implementations based on this knowledge were developed to improve pharmacophore matching of small molecules, binding free-energy estimations, and docking performance in terms of pose prediction. Here, we proved in a retrospective manner that cosolvent-derived pharmacophores from molecular dynamics (solvent sites) improve the performance of docking-based virtual screening campaigns. We applied a biased docking scheme based on solvent sites to nine relevant target proteins that have a set of known ligands or actives and compounds that are, presumably, nonbinders (decoys). Our results show improvement in virtual screening performance compared to traditional docking programs both at a global level, with up to 35% increase in areas under the receiver operating characteristic curve, and in early stages, with up to a 7-fold increase in enrichment factors at 1%. However, the improvement in pose prediction of actives was less profound. The presented application makes use of the AutoDock Bias method and is the only cosolvent-derived pharmacophore technique that employs its knowledge both in the ligand conformational search algorithm and the final affinity scoring for virtual screening purposes.

Exploring lectin-like activity of the S-layer protein of Lactobacillus acidophilus ATCC 4356.

The surface layer (S-layer) protein of Lactobacillus acidophilus is a crystalline array of self-assembling, proteinaceous subunits non-covalently bound to the outmost bacterial cell wall envelope and is involved in the adherence of bacteria to host cells. We have previously described that the S-layer protein of L. acidophilus possesses anti-viral and anti-bacterial properties. In this work, we extracted and purified S-layer proteins from L. acidophilus ATCC 4356 cells to study their interaction with cell wall components from prokaryotic (i.e., peptidoglycan and lipoteichoic acids) and eukaryotic origin (i.e., mucin and chitin), as well as with viruses, bacteria, yeast, and blood cells. Using chimeric S-layer fused to green fluorescent protein (GFP) from different parts of the protein, we analyzed their binding capacity. Our results show that the C-terminal part of the S-layer protein presents lectin-like activity, interacting with different glycoepitopes. We further demonstrate that lipoteichoic acid (LTA) serves as an anchor for the S-layer protein. Finally, a structure for the C-terminal part of S-layer and possible binding sites were predicted by a homology-based model.

Solvents to Fragments to Drugs: MD Applications in Drug Design.

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

LigQ: A Webserver to Select and Prepare Ligands for Virtual Screening.

Virtual screening is a powerful methodology to search for new small molecule inhibitors against a desired molecular target. Usually, it involves evaluating thousands of compounds (derived from large databases) in order to select a set of potential binders that will be tested in the wet-lab. The number of tested compounds is directly proportional to the cost, and thus, the best possible set of ligands is the one with the highest number of true binders, for the smallest possible compound set size. Therefore, methods that are able to trim down large universal data sets enriching them in potential binders are highly appreciated. Here we present LigQ, a free webserver that is able to (i) determine best structure and ligand binding pocket for a desired protein, (ii) find known binders, as well as potential ligands known to bind to similar protein domains, (iii) most importantly, select a small set of commercial compounds enriched in potential binders, and (iv) prepare them for virtual screening. LigQ was tested with several proteins, showing an impressive capacity to retrieve true ligands from large data sets, achieving enrichment factors of over 10%. LigQ is available at http://ligq.qb.fcen.uba.ar/ .

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 µs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

WATCLUST: a tool for improving the design of drugs based on protein-water interactions.

MOTIVATION: Water molecules are key players for protein folding and function. On the protein surface, water is not placed randomly, but display instead a particular structure evidenced by the presence of specific water sites (WS). These WS can be derived and characterized using explicit water Molecular Dynamics simulations, providing useful information for ligand binding prediction and design. Here we present WATCLUST, a WS determination and analysis tool running on the VMD platform. The tool also allows direct transfer of the WS information to Autodock program to perform biased docking. AVAILABILITY AND IMPLEMENTATION: The WATCLUST plugin and documentation are freely available at http://sbg.qb.fcen.uba.ar/watclust/. CONTACT: marcelo@qi.fcen.uba.ar, adrian@qi.fcen.uba.ar.

Solvent structure improves docking prediction in lectin-carbohydrate complexes.

Recognition and complex formation between proteins and carbohydrates is a key issue in many important biological processes. Determination of the three-dimensional structure of such complexes is thus most relevant, but particularly challenging because of their usually low binding affinity. In silico docking methods have a long-standing tradition in predicting protein-ligand complexes, and allow a potentially fast exploration of a number of possible protein-carbohydrate complex structures. However, determining which of these predicted complexes represents the correct structure is not always straightforward. In this work, we present a modification of the scoring function provided by AutoDock4, a widely used docking software, on the basis of analysis of the solvent structure adjacent to the protein surface, as derived from molecular dynamics simulations, that allows the definition and characterization of regions with higher water occupancy than the bulk solvent, called water sites. They mimic the interaction held between the carbohydrate -OH groups and the protein. We used this information for an improved docking method in relation to its capacity to correctly predict the protein-carbohydrate complexes for a number of tested proteins, whose ligands range in size from mono- to tetrasaccharide. Our results show that the presented method significantly improves the docking predictions. The resulting solvent-structure-biased docking protocol, therefore, appears as a powerful tool for the design and optimization of development of glycomimetic drugs, while providing new insights into protein-carbohydrate interactions. Moreover, the achieved improvement also underscores the relevance of the solvent structure to the protein carbohydrate recognition process.

Rescue of secretion of a rare-disease associated mis-folded mutant glycoprotein in UGGT1 knock-out mammalian cells.

Endoplasmic reticulum (ER) retention of mis-folded glycoproteins is mediated by the ERlocalised eukaryotic glycoprotein secretion checkpoint, UDP-glucose glycoprotein glucosyl-transferase (UGGT). The enzyme recognises a mis-folded glycoprotein and flags it for ER retention by reglucosylating one of its N-linked glycans. In the background of a congenital mutation in a secreted glycoprotein gene, UGGT-mediated ER retention can cause rare disease even if the mutant glycoprotein retains activity ("responsive mutant"). Here, we investigated the subcellular localisation of the human Trop-2 Q118E variant, which causes gelatinous droplike corneal dystrophy (GDLD). Compared with the wild type Trop-2, which is correctly localised at the plasma membrane, the Trop-2-Q118E variant is found to be heavily retained in the ER. Using Trop-2-Q118E, we tested UGGT modulation as a rescue-of-secretion therapeutic strategy for congenital rare disease caused by responsive mutations in genes encoding secreted glycoproteins. We investigated secretion of a EYFP-fusion of Trop-2-Q118E by confocal laser scanning microscopy. As a limiting case of UGGT inhibition, mammalian cells harbouring CRISPR/Cas9-mediated inhibition of the UGGT1 and/or UGGT2 gene expressions were used. The membrane localisation of the Trop-2-Q118E-EYFP mutant was successfully rescued in UGGT1-/- and UGGT1/2-/- cells. UGGT1 also efficiently reglucosylated Trop-2-Q118E-EYFP in cellula. The study supports the hypothesis that UGGT1 modulation constitutes a novel therapeutic strategy for the treatment of Trop-2-Q118E associated GDLD, and it encourages the testing of modulators of ER glycoprotein folding Quality Control (ERQC) as broad-spectrum rescueof-secretion drugs in rare diseases caused by responsive secreted glycoprotein mutants.

First-in-class multifunctional TYMS nonclassical antifolate inhibitor with potent in vivo activity that prolongs survival.

Although thymidylate synthase (TYMS) inhibitors have served as components of chemotherapy regimens, the currently available inhibitors induce TYMS overexpression or alter folate transport/metabolism feedback pathways that tumor cells exploit for drug resistance, limiting overall benefit. Here we report a small molecule TYMS inhibitor that i) exhibited enhanced antitumor activity as compared with current fluoropyrimidines and antifolates without inducing TYMS overexpression, ii) is structurally distinct from classical antifolates, iii) extended survival in both pancreatic xenograft tumor models and an hTS/Ink4a/Arf null genetically engineered mouse tumor model, and iv) is well tolerated with equal efficacy using either intraperitoneal or oral administration. Mechanistically, we verify the compound is a multifunctional nonclassical antifolate, and using a series of analogs, we identify structural features allowing direct TYMS inhibition while maintaining the ability to inhibit dihydrofolate reductase. Collectively, this work identifies nonclassical antifolate inhibitors that optimize inhibition of thymidylate biosynthesis with a favorable safety profile, highlighting the potential for enhanced cancer therapy.

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint.

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 "WY" conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 µM binding affinity for CtUGGTGT24in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 µM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors.

MotSASi: Functional short linear motifs (SLiMs) prediction based on genomic single nucleotide variants and structural data.

Short linear motifs (SLiMs) are key to cell physiology mediating reversible protein-protein interactions. Precise identification of SLiMs remains a challenge, being the main drawback of most bioinformatic prediction tools, their low specificity (high number of false positives). An important, usually overlooked, aspect is the relation between SLiMs mutations and disease. The presence of variants in each residue position can be used to assess the relevance of the corresponding residue(s) for protein function, and its (in)tolerance to change. In the present work, we combined sequence variant information and structural analysis of the energetic impact of single amino acid substitution (SAS) in SLiM-Receptor complex structure, and showed that it improves prediction of true functional SLiMs. Our strategy is based on building a SAS tolerance matrix that shows, for each position, whether one of the possible 19 SAS is tolerated or not. Herein we present the MotSASi strategy and analyze in detail 3 SLiMs involved in intracellular protein trafficking (phospho-independent tyrosine-based motif (NPx[Y/F]), type 1 PDZ-binding motif ([S/T]x[V/I/L]COOH) and tryptophan-acidic motif ([L/M]xW[D/E])). Our results show that inclusion of variant and structure information improves both prediction of true SLiMs and rejection of false positives, while also allowing better classification of variants inside SLiMs, a result with a direct impact in clinical genomics.

Identification of the Allosteric Binding Site for Thiazolopyrimidine on the C-Type Lectin Langerin.

Langerin is a mammalian C-type lectin expressed on Langerhans cells in the skin. As an innate immune cell receptor, Langerin is involved in coordinating innate and adaptive immune responses against various incoming threats. We have previously reported a series of thiazolopyrimidines as murine Langerin ligands. Prompted by the observation that its human homologue exhibits different binding specificities for these small molecules, we report here our investigations to define their exact binding site. By using structural comparison and molecular dynamics simulations, we showed that the nonconserved short loops have a high degree of conformational flexibility between the human and murine homologues. Sequence analysis and mutational studies indicated that a pair of residues are essential for the recognition of the thiazolopyrimidines. Taking solvent paramagnetic relaxation enhancement NMR studies together with a series of peptides occupying the same site, we could define the cleft between the short and long loops as the allosteric binding site for these aromatic heterocycles.

From Genome to Drugs: New Approaches in Antimicrobial Discovery.

Decades of successful use of antibiotics is currently challenged by the emergence of increasingly resistant bacterial strains. Novel drugs are urgently required but, in a scenario where private investment in the development of new antimicrobials is declining, efforts to combat drug-resistant infections become a worldwide public health problem. Reasons behind unsuccessful new antimicrobial development projects range from inadequate selection of the molecular targets to a lack of innovation. In this context, increasingly available omics data for multiple pathogens has created new drug discovery and development opportunities to fight infectious diseases. Identification of an appropriate molecular target is currently accepted as a critical step of the drug discovery process. Here, we review how diverse layers of multi-omics data in conjunction with structural/functional analysis and systems biology can be used to prioritize the best candidate proteins. Once the target is selected, virtual screening can be used as a robust methodology to explore molecular scaffolds that could act as inhibitors, guiding the development of new drug lead compounds. This review focuses on how the advent of omics and the development and application of bioinformatics strategies conduct a "big-data era" that improves target selection and lead compound identification in a cost-effective and shortened timeline.

Clamping, bending, and twisting inter-domain motions in the misfold-recognizing portion of UDP-glucose: Glycoprotein glucosyltransferase.

UDP-glucose:glycoprotein glucosyltransferase (UGGT) flags misfolded glycoproteins for ER retention. We report crystal structures of full-length Chaetomium thermophilum UGGT (CtUGGT), two CtUGGT double-cysteine mutants, and its TRXL2 domain truncation (CtUGGT-ΔTRXL2). CtUGGT molecular dynamics (MD) simulations capture extended conformations and reveal clamping, bending, and twisting inter-domain movements. We name "Parodi limit" the maximum distance on the same glycoprotein between a site of misfolding and an N-linked glycan that can be reglucosylated by monomeric UGGT in vitro, in response to recognition of misfold at that site. Based on the MD simulations, we estimate the Parodi limit as around 70-80 Å. Frequency distributions of distances between glycoprotein residues and their closest N-linked glycosylation sites in glycoprotein crystal structures suggests relevance of the Parodi limit to UGGT activity in vivo. Our data support a "one-size-fits-all adjustable spanner" UGGT substrate recognition model, with an essential role for the UGGT TRXL2 domain.

A Novel SLC5A5 Variant Reveals the Crucial Role of Kinesin Light Chain 2 in Thyroid Hormonogenesis.

CONTEXT: Iodide transport defect (ITD) (Online Mendelian Inheritance in Man No. 274400) is an uncommon cause of dyshormonogenic congenital hypothyroidism due to loss-of-function variants in the SLC5A5 gene, which encodes the sodium/iodide symporter (NIS), causing deficient iodide accumulation in thyroid follicular cells. OBJECTIVE: This work aims to determine the molecular basis of a patient's ITD clinical phenotype. METHODS: The propositus was diagnosed with dyshormonogenic congenital hypothyroidism with minimal 99mTc-pertechnetate accumulation in a eutopic thyroid gland. The propositus SLC5A5 gene was sequenced. Functional in vitro characterization of the novel NIS variant was performed. RESULTS: Sanger sequencing revealed a novel homozygous missense p.G561E NIS variant. Mechanistically, the G561E substitution reduces iodide uptake, because targeting of G561E NIS to the plasma membrane is reduced. Biochemical analyses revealed that G561E impairs the recognition of an adjacent tryptophan-acidic motif by the kinesin-1 subunit kinesin light chain 2 (KLC2), interfering with NIS maturation beyond the endoplasmic reticulum, and reducing iodide accumulation. Structural bioinformatic analysis suggests that G561E shifts the equilibrium of the unstructured tryptophan-acidic motif toward a more structured conformation unrecognizable to KLC2. Consistently, knockdown of Klc2 causes defective NIS maturation and consequently decreases iodide accumulation in rat thyroid cells. Morpholino knockdown of klc2 reduces thyroid hormone synthesis in zebrafish larvae leading to a hypothyroid state as revealed by expression profiling of key genes related to the hypothalamic-pituitary-thyroid axis. CONCLUSION: We report a novel NIS pathogenic variant associated with dyshormonogenic congenital hypothyroidism. Detailed molecular characterization of G561E NIS uncovered the significance of KLC2 in thyroid physiology.