CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates.

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. Here, we present a computational tool, Glycan Modeler for in silico N-/O-glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader, a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-µs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler. Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

Stalis: A Computational Method for Template-Based Ab Initio Ligand Design.

Proteins interact with small molecules through specific molecular recognition, which is central to essential biological functions in living systems. Therefore, understanding such interactions is crucial for basic sciences and drug discovery. Here, we present Structure template-based ab initio ligand design solution (Stalis), a knowledge-based approach that uses structure templates from the Protein Data Bank libraries of whole ligands and their fragments and generates a set of molecules (virtual ligands) whose structures represent the pocket shape and chemical features of a given target binding site. Our benchmark performance evaluation shows that ligand structure-based virtual screening using virtual ligands from Stalis outperforms a receptor structure-based virtual screening using AutoDock Vina, demonstrating reliable overall screening performance applicable to computational high-throughput screening. However, virtual ligands from Stalis are worse in recognizing active compounds at the small fraction of a rank-ordered list of screened library compounds than crystal ligands, due to the low resolution of the virtual ligand structures. In conclusion, Stalis can facilitate drug discovery research by designing virtual ligands that can be used for fast ligand structure-based virtual screening. Moreover, Stalis provides actual three-dimensional ligand structures that likely bind to a target protein, enabling to gain structural insight into potential ligands. Stalis can be an efficient computational platform for high-throughput ligand design for fundamental biological study and drug discovery research at the proteomic level. © 2019 Wiley Periodicals, Inc.

Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank.

MOTIVATION: Glycans play a central role in many essential biological processes. Glycan Reader was originally developed to simplify the reading of Protein Data Bank (PDB) files containing glycans through the automatic detection and annotation of sugars and glycosidic linkages between sugar units and to proteins, all based on atomic coordinates and connectivity information. Carbohydrates can have various chemical modifications at different positions, making their chemical space much diverse. Unfortunately, current PDB files do not provide exact annotations for most carbohydrate derivatives and more than 50% of PDB glycan chains have at least one carbohydrate derivative that could not be correctly recognized by the original Glycan Reader. RESULTS: Glycan Reader has been improved and now identifies most sugar types and chemical modifications (including various glycolipids) in the PDB, and both PDB and PDBx/mmCIF formats are supported. CHARMM-GUI Glycan Reader is updated to generate the simulation system and input of various glycoconjugates with most sugar types and chemical modifications. It also offers a new functionality to edit the glycan structures through addition/deletion/modification of glycosylation types, sugar types, chemical modifications, glycosidic linkages, and anomeric states. The simulation system and input files can be used for CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Glycan Fragment Database in GlycanStructure.Org is also updated to provide an intuitive glycan sequence search tool for complex glycan structures with various chemical modifications in the PDB. AVAILABILITY AND IMPLEMENTATION: http://www.charmm-gui.org/input/glycan and http://www.glycanstructure.org. CONTACT: wonpil@lehigh.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transmembrane motions of PglB induced by LLO are coupled with EL5 loop conformational changes necessary for OST activity.

N-linked glycosylation is an enzymatic reaction in which an oligosaccharide is transferred en bloc onto an asparagine residue of an acceptor polypeptide, catalyzed by oligosaccharyltransferase (OST). Despite the available crystal structures, the role of the external loop EL5, which is critical for the catalytic cycle, is enigmatic as EL5 in the crystal structures is partially absent or blocks a pathway of lipid-linked oligosaccharide to the active site. Here we report the molecular origin of EL5 conformational changes through a series of molecular dynamics simulations of a bacterial OST, Campylobacter lari PglB. The simulations reveal that the isoprenoid moiety of lipid-linked oligosaccharide favorably binds to a hydrophobic groove of the PglB transmembrane domain. This binding triggers the conformational changes of the transmembrane domain and subsequently impairs the structural stability of EL5, leading to disordered EL5 with open conformations that are required for correct placement of the oligosaccharide in the active site.

CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules.

Reading ligand structures into any simulation program is often nontrivial and time consuming, especially when the force field parameters and/or structure files of the corresponding molecules are not available. To address this problem, we have developed Ligand Reader & Modeler in CHARMM-GUI. Users can upload ligand structure information in various forms (using PDB ID, ligand ID, SMILES, MOL/MOL2/SDF file, or PDB/mmCIF file), and the uploaded structure is displayed on a sketchpad for verification and further modification. Based on the displayed structure, Ligand Reader & Modeler generates the ligand force field parameters and necessary structure files by searching for the ligand in the CHARMM force field library or using the CHARMM general force field (CGenFF). In addition, users can define chemical substitution sites and draw substituents in each site on the sketchpad to generate a set of combinatorial structure files and corresponding force field parameters for throughput or alchemical free energy simulations. Finally, the output from Ligand Reader & Modeler can be used in other CHARMM-GUI modules to build a protein-ligand simulation system for all supported simulation programs, such as CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Ligand Reader & Modeler is available as a functional module of CHARMM-GUI at http://www.charmm-gui.org/input/ligandrm. © 2017 Wiley Periodicals, Inc.

CHARMM-GUI 10 years for biomolecular modeling and simulation.

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

Potential pharmacological chaperones targeting cancer-associated MCL-1 and Parkinson disease-associated α-synuclein.

Pharmacological chaperones are small molecules that bind to proteins and stabilize them against thermal denaturation or proteolytic degradation, as well as assist or prevent certain protein-protein assemblies. These activities are being exploited for the development of treatments for diseases caused by protein instability and/or aberrant protein-protein interactions, such as those found in certain forms of cancers and neurodegenerative diseases. However, designing or discovering pharmacological chaperones for specific targets is challenging because of the relatively featureless protein target surfaces, the lack of suitable chemical libraries, and the shortage of efficient high-throughput screening methods. In this study, we attempted to address all these challenges by synthesizing a diverse library of small molecules that mimic protein α-helical secondary structures commonly found in protein-protein interaction surfaces. This was accompanied by establishing a facile "on-bead" high-throughput screening method that allows for rapid and efficient discovery of potential pharmacological chaperones and for identifying novel chaperones/inhibitors against a cancer-associated protein, myeloid cell leukemia 1 (MCL-1), and a Parkinson disease-associated protein, α-synuclein. Our data suggest that the compounds and methods described here will be useful tools for the development of pharmaceuticals for complex-disease targets that are traditionally deemed "undruggable."

GS-align for glycan structure alignment and similarity measurement.

MOTIVATION: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner. RESULTS: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the Protein Data Bank (PDB) N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility. AVAILABILITY AND IMPLEMENTATION: http://www.glycanstructure.org/gsalign. CONTACT: wonpil@ku.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Lipid-linked oligosaccharides in membranes sample conformations that facilitate binding to oligosaccharyltransferase.

Lipid-linked oligosaccharides (LLOs) are the substrates of oligosaccharyltransferase (OST), the enzyme that catalyzes the en bloc transfer of the oligosaccharide onto the acceptor asparagine of nascent proteins during the process of N-glycosylation. To explore LLOs' preferred location, orientation, structure, and dynamics in membrane bilayers of three different lipid types (dilauroylphosphatidylcholine, dimyristoylphosphatidylcholine, and dioleoylphosphatidylcholine), we have modeled and simulated both eukaryotic (Glc3-Man9-GlcNAc2-PP-Dolichol) and bacterial (Glc1-GalNAc5-Bac1-PP-Undecaprenol) LLOs, which are composed of an isoprenoid moiety and an oligosaccharide, linked by pyrophosphate. The simulations show no strong impact of different bilayer hydrophobic thicknesses on the overall orientation, structure, and dynamics of the isoprenoid moiety and the oligosaccharide. The pyrophosphate group stays in the bilayer head group region. The isoprenoid moiety shows high flexibility inside the bilayer hydrophobic core, suggesting its potential role as a tentacle to search for OST. The oligosaccharide conformation and dynamics are similar to those in solution, but there are preferred interactions between the oligosaccharide and the bilayer interface, which leads to LLO sugar orientations parallel to the bilayer surface. Molecular docking of the bacterial LLO to a bacterial OST suggests that such orientations can enhance binding of LLOs to OST.

Restricted N-glycan conformational space in the PDB and its implication in glycan structure modeling.

Understanding glycan structure and dynamics is central to understanding protein-carbohydrate recognition and its role in protein-protein interactions. Given the difficulties in obtaining the glycan's crystal structure in glycoconjugates due to its flexibility and heterogeneity, computational modeling could play an important role in providing glycosylated protein structure models. To address if glycan structures available in the PDB can be used as templates or fragments for glycan modeling, we present a survey of the N-glycan structures of 35 different sequences in the PDB. Our statistical analysis shows that the N-glycan structures found on homologous glycoproteins are significantly conserved compared to the random background, suggesting that N-glycan chains can be confidently modeled with template glycan structures whose parent glycoproteins share sequence similarity. On the other hand, N-glycan structures found on non-homologous glycoproteins do not show significant global structural similarity. Nonetheless, the internal substructures of these N-glycans, particularly, the substructures that are closer to the protein, show significantly similar structures, suggesting that such substructures can be used as fragments in glycan modeling. Increased interactions with protein might be responsible for the restricted conformational space of N-glycan chains. Our results suggest that structure prediction/modeling of N-glycans of glycoconjugates using structure database could be effective and different modeling approaches would be needed depending on the availability of template structures.

Ligand binding site detection by local structure alignment and its performance complementarity.

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands' positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a nontemplate geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy.

CHARMM-GUI Ligand Binder for absolute binding free energy calculations and its application.

Advanced free energy perturbation molecular dynamics (FEP/MD) simulation methods are available to accurately calculate absolute binding free energies of protein-ligand complexes. However, these methods rely on several sophisticated command scripts implementing various biasing energy restraints to enhance the convergence of the FEP/MD calculations, which must all be handled properly to yield correct results. Here, we present a user-friendly Web interface, CHARMM-GUI Ligand Binder ( http://www.charmm-gui.org/input/gbinding ), to provide standardized CHARMM input files for calculations of absolute binding free energies using the FEP/MD simulations. A number of features are implemented to conveniently set up the FEP/MD simulations in highly customizable manners, thereby permitting an accelerated throughput of this important class of computations while decreasing the possibility of human errors. The interface and a series of input files generated by the interface are tested with illustrative calculations of absolute binding free energies of three nonpolar aromatic ligands to the L99A mutant of T4 lysozyme and three FK506-related ligands to FKBP12. Statistical errors within individual calculations are found to be small (~1 kcal/mol), and the calculated binding free energies generally agree well with the experimental measurements and the previous computational studies (within ~2 kcal/mol). Therefore, CHARMM-GUI Ligand Binder provides a convenient and reliable way to set up the ligand binding free energy calculations and can be applicable to pharmaceutically important protein-ligand systems.

CHARMM-GUI micelle builder for pure/mixed micelle and protein/micelle complex systems.

Micelle Builder in CHARMM-GUI, http://www.charmm-gui.org/input/micelle , is a web-based graphical user interface to build pure/mixed micelle and protein/micelle complex systems for molecular dynamics (MD) simulation. The robustness of Micelle Builder is tested by simulating four detergent-only homogeneous micelles of DHPC (dihexanoylphosphatidylcholine), DPC (dodecylphosphocholine), TPC (tetradecylphosphocholine), and SDS (sodium dodecyl sulfate) and comparing the calculated micelle properties with experiments and previous simulations. As a representative protein/micelle model, Pf1 coat protein is modeled and simulated in DHPC micelles with three different numbers of DHPC molecules. While the number of DHPC molecules in direct contact with Pf1 protein converges during the simulation, distinct behavior and geometry of micelles lead to different protein conformations in comparison to that in bilayers. It is our hope that CHARMM-GUI Micelle Builder can be used for simulation studies of various protein/micelle systems to better understand the protein structure and dynamics in micelles as well as distribution of detergents and their dynamics around proteins.

BSP-SLIM: a blind low-resolution ligand-protein docking approach using predicted protein structures.

We developed BSP-SLIM, a new method for ligand-protein blind docking using low-resolution protein structures. For a given sequence, protein structures are first predicted by I-TASSER; putative ligand binding sites are transferred from holo-template structures which are analogous to the I-TASSER models; ligand-protein docking conformations are then constructed by shape and chemical match of ligand with the negative image of binding pockets. BSP-SLIM was tested on 71 ligand-protein complexes from the Astex diverse set where the protein structures were predicted by I-TASSER with an average RMSD 2.92 Å on the binding residues. Using I-TASSER models, the median ligand RMSD of BSP-SLIM docking is 3.99 Å which is 5.94 Å lower than that by AutoDock; the median binding-site error by BSP-SLIM is 1.77 Å which is 6.23 Å lower than that by AutoDock and 3.43 Å lower than that by LIGSITE(CSC) . Compared to the models using crystal protein structures, the median ligand RMSD by BSP-SLIM using I-TASSER models increases by 0.87 Å, while that by AutoDock increases by 8.41 Å; the median binding-site error by BSP-SLIM increase by 0.69Å while that by AutoDock and LIGSITE(CSC) increases by 7.31 Å and 1.41 Å, respectively. As case studies, BSP-SLIM was used in virtual screening for six target proteins, which prioritized actives of 25% and 50% in the top 9.2% and 17% of the library on average, respectively. These results demonstrate the usefulness of the template-based coarse-grained algorithms in the low-resolution ligand-protein docking and drug-screening. An on-line BSP-SLIM server is freely available at http://zhanglab.ccmb.med.umich.edu/BSP-SLIM.

Identification of ligand templates using local structure alignment for structure-based drug design.

With a rapid increase in the number of high-resolution protein-ligand structures, the known protein-ligand structures can be used to gain insight into ligand-binding modes in a target protein. On the basis of the fact that the structurally similar binding sites share information about their ligands, we have developed a local structure alignment tool, G-LoSA (graph-based local structure alignment). The known protein-ligand binding-site structure library is searched by G-LoSA to detect binding-site structures with similar geometry and physicochemical properties to a query binding-site structure regardless of sequence continuity and protein fold. Then, the ligands in the identified complexes are used as templates (i.e., template ligands) to predict/design a ligand for the target protein. The performance of G-LoSA is validated against 76 benchmark targets from the Astex diverse set. Using the currently available protein-ligand structure library, G-LoSA is able to identify a single template ligand (from a nonhomologous protein complex) that is highly similar to the target ligand in more than half of the benchmark targets. In addition, our benchmark analyses show that an assembly of structural fragments from multiple template ligands with partial similarity to the target ligand can be used to design novel ligand structures specific to the target protein. This study clearly indicates that a template-based ligand modeling has potential for de novo ligand design and can be a complementary approach to the receptor structure based methods.

Application of binding free energy calculations to prediction of binding modes and affinities of MDM2 and MDMX inhibitors.

Molecular docking is widely used to obtain binding modes and binding affinities of a molecule to a given target protein. Despite considerable efforts, however, prediction of both properties by docking remains challenging mainly due to protein's structural flexibility and inaccuracy of scoring functions. Here, an integrated approach has been developed to improve the accuracy of binding mode and affinity prediction and tested for small molecule MDM2 and MDMX antagonists. In this approach, initial candidate models selected from docking are subjected to equilibration MD simulations to further filter the models. Free energy perturbation molecular dynamics (FEP/MD) simulations are then applied to the filtered ligand models to enhance the ability in predicting the near-native ligand conformation. The calculated binding free energies for MDM2 complexes are overestimated compared to experimental measurements mainly due to the difficulties in sampling highly flexible apo-MDM2. Nonetheless, the FEP/MD binding free energy calculations are more promising for discriminating binders from nonbinders than docking scores. In particular, the comparison between the MDM2 and MDMX results suggests that apo-MDMX has lower flexibility than apo-MDM2. In addition, the FEP/MD calculations provide detailed information on the different energetic contributions to ligand binding, leading to a better understanding of the sensitivity and specificity of protein-ligand interactions.

Maintained activity of glycogen synthase kinase-3beta despite of its phosphorylation at serine-9 in okadaic acid-induced neurodegenerative model.

Glycogen synthase kinase-3beta (GSK3beta) is recognized as one of major kinases to phosphorylate tau in Alzheimer's disease (AD), thus lots of AD drug discoveries target GSK3beta. However, the inactive form of GSK3beta which is phosphorylated at serine-9 is increased in AD brains. This is also inconsistent with phosphorylation status of other GSK3beta substrates, such as beta-catenin and collapsin response mediator protein-2 (CRMP2) since their phosphorylation is all increased in AD brains. Thus, we addressed this paradoxical condition of AD in rat neurons treated with okadaic acid (OA) which inhibits protein phosphatase-2A (PP2A) and induces tau hyperphosphorylation and cell death. Interestingly, OA also induces phosphorylation of GSK3beta at serine-9 and other substrates including tau, beta-catenin and CRMP2 like in AD brains. In this context, we observed that GSK3beta inhibitors such as lithium chloride and 6-bromoindirubin-3'-monoxime (6-BIO) reversed those phosphorylation events and protected neurons. These data suggest that GSK3beta may still have its kinase activity despite increase of its phosphorylation at serine-9 in AD brains at least in PP2A-compromised conditions and that GSK3beta inhibitors could be a valuable drug candidate in AD.

1,3-Diphenyl-1H-pyrazole derivatives as a new series of potent PPARγ partial agonists.

A new series of PPARγ partial agonists, 1,3-diphenyl-1H-pyrazole derivatives, were identified using an improved virtual screening scheme combining ligand-centric and receptor-centric methods. An in vitro assay confirmed the nanomolar binding affinity of 1,3-diphenyl-1H-pyrazole derivatives such as SP3415. We also characterized the competitive antagonism of SP3415 against rosiglitazone at micromolar concentrations. They showed a PPARγ partial agonistic activity similar to that of a known PPARγ drug, pioglitazone, in a cell-based transactivation assay. Furthermore, the structure-activity relationships of the pyrazole derivatives were investigated through comparative molecular field analysis and binding mode analysis, which provided new insight concerning their partial agonistic effect on PPARγ.

A novel program to design siRNAs simultaneously effective to highly variable virus genomes.

A major concern of antiviral therapy using small interfering RNAs (siRNAs) targeting RNA viral genome is high sequence diversity and mutation rate due to genetic instability. To overcome this problem, it is indispensable to design siRNAs targeting highly conserved regions. We thus designed CAPSID (Convenient Application Program for siRNA Design), a novel bioinformatics program to identify siRNAs targeting highly conserved regions within RNA viral genomes. From a set of input RNAs of diverse sequences, CAPSID rapidly searches conserved patterns and suggests highly potent siRNA candidates in a hierarchical manner. To validate the usefulness of this novel program, we investigated the antiviral potency of universal siRNA for various Human enterovirus B (HEB) serotypes. Assessment of antiviral efficacy using Hela cells, clearly demonstrates that HEB-specific siRNAs exhibit protective effects against all HEBs examined. These findings strongly indicate that CAPSID can be applied to select universal antiviral siRNAs against highly divergent viral genomes.