Jumin Lee

CHARMM-GUI Membrane Builder toward realistic biological membrane simulations.

CHARMM‐GUI Membrane Builder, http://www.charmm‐gui.org/input/membrane, is a web‐based user interface designed to interactively build all‐atom protein/membrane or membrane‐only systems for molecular dynamics simulations through an automated optimized process. In this work, we describe the new features and major improvements in Membrane Builder that allow users to robustly build realistic biological membrane systems, including (1) addition of new lipid types, such as phosphoinositides, cardiolipin (CL), sphingolipids, bacterial lipids, and ergosterol, yielding more than 180 lipid types, (2) enhanced building procedure for lipid packing around protein, (3) reliable algorithm to detect lipid tail penetration to ring structures and protein surface, (4) distance‐based algorithm for faster initial ion displacement, (5) CHARMM inputs for P21 image transformation, and (6) NAMD equilibration and production inputs. The robustness of these new features is illustrated by building and simulating a membrane model of the polar and septal regions of E. coli membrane, which contains five lipid types: CL lipids with two types of acyl chains and phosphatidylethanolamine lipids with three types of acyl chains. It is our hope that CHARMM‐GUI Membrane Builder becomes a useful tool for simulation studies to better understand the structure and dynamics of proteins and lipids in realistic biological membrane environments.

CHARMM-GUI Input Generator for NAMD, Gromacs, Amber, Openmm, and CHARMM/OpenMM Simulations using the CHARMM36 Additive Force Field

Proper treatment of nonbonded interactions is essential for the accuracy of molecular dynamics (MD) simulations, especially in studies of lipid bilayers. The use of the CHARMM36 force field (C36 FF) in different MD simulation programs can result in disagreements with published simulations performed with CHARMM due to differences in the protocols used to treat the long-range and 1-4 nonbonded interactions. In this study, we systematically test the use of the C36 lipid FF in NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM. A wide range of Lennard-Jones (LJ) cutoff schemes and integrator algorithms were tested to find the optimal simulation protocol to best match bilayer properties of six lipids with varying acyl chain saturation and head groups. MD simulations of a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer were used to obtain the optimal protocol for each program. MD simulations with all programs were found to reasonably match the DPPC bilayer properties (surface area per lipid, chain order parameters, and area compressibility modulus) obtained using the standard protocol used in CHARMM as well as from experiments. The optimal simulation protocol was then applied to the other five lipid simulations and resulted in excellent agreement between results from most simulation programs as well as with experimental data. AMBER compared least favorably with the expected membrane properties, which appears to be due to its use of the hard-truncation in the LJ potential versus a force-based switching function used to smooth the LJ potential as it approaches the cutoff distance. The optimal simulation protocol for each program has been implemented in CHARMM-GUI. This protocol is expected to be applicable to the remainder of the additive C36 FF including the proteins, nucleic acids, carbohydrates, and small molecules.

CHARMM-GUI Martini Maker for Coarse-Grained Simulations with the Martini Force Field

Coarse-grained simulations are widely used to study large biological systems. Nonetheless, building such simulation systems becomes nontrivial, especially when membranes with various lipid types are involved. Taking advantage of the frameworks in all-atom CHARMM-GUI modules, we have developed CHARMM-GUI Martini Maker for building solution, micelle, bilayer, and vesicle systems as well as systems with randomly distributed lipids using the Martini force field. Martini Maker supports 82 lipid types and different flavors of the Martini force field, including polar and nonpolar Martini, Dry Martini, and ElNeDyn (an elastic network model for proteins). The qualities of the systems generated by Martini Maker are validated by simulations of various examples involving proteins and lipids. We expect Martini Maker to be a useful tool for modeling large, complicated biomolecular systems in a user-friendly way.

CHARMM-GUI HMMM Builder for Membrane Simulations with the Highly Mobile Membrane-Mimetic Model

Slow diffusion of the lipids in conventional all-atom simulations of membrane systems makes it difficult to sample large rearrangements of lipids and protein-lipid interactions. Recently, Tajkhorshid and co-workers developed the highly mobile membrane-mimetic (HMMM) model with accelerated lipid motion by replacing the lipid tails with small organic molecules. The HMMM model provides accelerated lipid diffusion by one to two orders of magnitude, and is particularly useful in studying membrane-protein associations. However, building an HMMM simulation system is not easy, as it requires sophisticated treatment of the lipid tails. In this study, we have developed CHARMM-GUI HMMM Builder (http://www.charmm-gui.org/input/hmmm) to provide users with ready-to-go input files for simulating HMMM membrane systems with/without proteins. Various lipid-only and protein-lipid systems are simulated to validate the qualities of the systems generated by HMMM Builder with focus on the basic properties and advantages of the HMMM model. HMMM Builder supports all lipid types available in CHARMM-GUI and also provides a module to convert back and forth between an HMMM membrane and a full-length membrane. We expect HMMM Builder to be a useful tool in studying membrane systems with enhanced lipid diffusion.

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.

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.

CHARMM-GUI MDFF/xMDFF Utilizer for Molecular Dynamics Flexible Fitting Simulations in Various Environments

X-ray crystallography and cryo-electron microscopy are two popular methods for the structure determination of biological molecules. Atomic structures are derived through the fitting and refinement of an initial model into electron density maps constructed by both experiments. Two computational approaches, MDFF and xMDFF, have been developed to facilitate this process by integrating the experimental data with molecular dynamics simulation. However, the setup of an MDFF/xMDFF simulation requires knowledge of both experimental and computational methods, which is not straightforward for nonexpert users. In addition, sometimes it is desirable to include realistic environments, such as explicit solvent and lipid bilayers during the simulation, which poses another challenge even for expert users. To alleviate these difficulties, we have developed MDFF/xMDFF Utilizer in CHARMM-GUI that helps users to set up an MDFF/xMDFF simulation. The capability of MDFF/xMDFF Utilizer is greatly enhanced by integration with other CHARMM-GUI modules, including protein structure manipulation, a diverse set of lipid types, and all-atom CHARMM and coarse-grained PACE force fields. With this integration, various simulation environments are available for MDFF Utilizer (vacuum, implicit/explicit solvent, and bilayers) and xMDFF Utilizer (vacuum and solution). In this work, three examples are shown to demonstrate the usage of MDFF/xMDFF Utilizer.

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.

Long-ranged Protein-glycan Interactions Stabilize von Willebrand Factor A2 Domain from Mechanical Unfolding

Abstractvon Willebrand Factor (vWF) is a large multimeric protein that binds to platelets and collagen in blood clotting. vWF A2 domain hosts a proteolytic site for ADAMTS13 (A Disintegrin and Metalloprotease with a ThromboSpondin type 1 motif, member 13) to regulate the size of vWF multimers. This regulation process is highly sensitive to force conditions and protein-glycan interactions as the process occurs in flowing blood. There are two sites on A2 domain (N1515 and N1574) bearing various N-linked glycan structures. In this study, we used molecular dynamics (MD) simulation to study the force-induced unfolding of A2 domain with and without a single N-linked glycan type on each site. The sequential pullout of β-strands was used to represent a characteristic unfolding sequence of A2. This unfolding sequence varied due to protein-glycan interactions. The force-extension and total energy-extension profiles also show differences in magnitude but similar characteristic shapes between the systems with and without glycans. Systems with N-linked glycans encountered higher energy barriers for full unfolding and even for unfolding up to the point of ADAMTS13 cleavage site exposure. Interestingly, there is not much difference observed for A2 domain structure itself with and without glycans from standard MD simulations, suggesting roles of N-glycans in A2 unfolding through long-ranged protein-glycan interactions.

Structure of an EIIC sugar transporter trapped in an inward-facing conformation

Significance The phosphoenolpyruvate-dependent phosphotransferase system (PTS) is a multiprotein system unique to bacteria. The PTS transports sugars into bacteria and then phosphorylates the sugars. Phosphorylation prevents sugars from escaping the cell and primes them for metabolic consumption. As a major component of the PTS, Enzyme IIC (EIIC) transports sugar across the membrane and assists the phosphorylation process, but the molecular mechanism of EIIC-mediated sugar transport is unclear. Results from this study allow visualization of conformational changes during sugar transport and establish the mechanism of transport at the atomic level. The knowledge will facilitate development of inhibitors against EIIC and provide a foundation for understanding the phosphorylation process. The phosphoenolpyruvate-dependent phosphotransferase system (PTS) transports sugar into bacteria and phosphorylates the sugar for metabolic consumption. The PTS is important for the survival of bacteria and thus a potential target for antibiotics, but its mechanism of sugar uptake and phosphorylation remains unclear. The PTS is composed of multiple proteins, and the membrane-embedded Enzyme IIC (EIIC) component transports sugars across the membrane. Crystal structures of two members of the glucose superfamily of EIICs, bcChbC and bcMalT, were solved in the inward-facing and outward-facing conformations, and the structures suggest that sugar translocation could be achieved by movement of a structured domain that contains the sugar-binding site. However, different conformations have not been captured on the same transporter to allow precise description of the conformational changes. Here we present a crystal structure of bcMalT trapped in an inward-facing conformation by a mercury ion that bridges two strategically placed cysteine residues. The structure allows direct comparison of the outward- and inward-facing conformations and reveals a large rigid-body motion of the sugar-binding domain and other conformational changes that accompany the rigid-body motion. All-atom molecular dynamics simulations show that the inward-facing structure is stable with or without the cross-linking. The conformational changes were further validated by single-molecule Föster resonance energy transfer (smFRET). Combined, these results establish the elevator-type mechanism of transport in the glucose superfamily of EIIC transporters.