Automated lung tumor segmentation robust to various tumor sizes using a consistency learning-based multi-scale dual-attention network.

BACKGROUND: It is often difficult to automatically segment lung tumors due to the large tumor size variation ranging from less than 1 cm to greater than 7 cm depending on the T-stage. OBJECTIVE: This study aims to accurately segment lung tumors of various sizes using a consistency learning-based multi-scale dual-attention network (CL-MSDA-Net). METHODS: To avoid under- and over-segmentation caused by different ratios of lung tumors and surrounding structures in the input patch according to the size of the lung tumor, a size-invariant patch is generated by normalizing the ratio to the average size of the lung tumors used for the training. Two input patches, a size-invariant patch and size-variant patch are trained on a consistency learning-based network consisting of dual branches that share weights to generate a similar output for each branch with consistency loss. The network of each branch has a multi-scale dual-attention module that learns image features of different scales and uses channel and spatial attention to enhance the scale-attention ability to segment lung tumors of different sizes. RESULTS: In experiments with hospital datasets, CL-MSDA-Net showed an F1-score of 80.49%, recall of 79.06%, and precision of 86.78%. This resulted in 3.91%, 3.38%, and 2.95% higher F1-scores than the results of U-Net, U-Net with a multi-scale module, and U-Net with a multi-scale dual-attention module, respectively. In experiments with the NSCLC-Radiomics datasets, CL-MSDA-Net showed an F1-score of 71.7%, recall of 68.24%, and precision of 79.33%. This resulted in 3.66%, 3.38%, and 3.13% higher F1-scores than the results of U-Net, U-Net with a multi-scale module, and U-Net with a multi-scale dual-attention module, respectively. CONCLUSIONS: CL-MSDA-Net improves the segmentation performance on average for tumors of all sizes with significant improvements especially for small sized tumors.

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field.

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 µs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

Comparative Molecular Dynamics Simulation Studies of Realistic Eukaryotic, Prokaryotic, and Archaeal Membranes.

We present a comparative all-atom molecular dynamics simulation study of 18 biomembrane systems with lipid compositions corresponding to eukaryotic, bacterial, and archaebacterial membranes together with three single-component lipid bilayers. A total of 105 lipid types used in this study include diverse sterols and glycerol-based lipids with acyl chains of various lengths, unsaturation degrees, and branched or cyclic moieties. Our comparative analysis provides deeper insight into the influences of sterols and lipid unsaturation on the structural and mechanical properties of these biomembranes, including water permeation into the membrane hydrocarbon core. For sterol-containing membranes, sterol fraction is correlated with the membrane thickness, the area compressibility modulus, and lipid order but anticorrelated with the area per lipid and sterol tilt angles. Similarly, for all 18 biomembranes, lipid order is correlated with the membrane thickness and area compressibility modulus. Sterols and lipid unsaturation produce opposite effects on membrane thickness, but only sterols influence water permeation into the membrane. All membrane systems are accessible for public use in CHARMM-GUI Archive. They can be used as templates to expedite future modeling of realistic cell membranes with transmembrane and peripheral membrane proteins to study their structure, dynamics, molecular interactions, and function in a nativelike membrane environment.

Structure, Dynamics, and Interactions of GPI-Anchored Human Glypican-1 with Heparan Sulfates in a Membrane.

Glypican-1 and its heparan sulfate (HS) chains play important roles in modulating many biological processes including growth factor signaling. Glypican-1 is bound to a membrane surface via a glycosylphosphatidylinositol (GPI)-anchor. In this study, we used all-atom molecular modeling and simulation to explore the structure, dynamics, and interactions of GPI-anchored glypican-1, three HS chains, membranes, and ions. The folded glypican-1 core structure is stable, but has substantial degrees of freedom in terms of movement and orientation with respect to the membrane due to the long unstructured C-terminal region linking the core to the GPI-anchor. With unique structural features depending on the extent of sulfation, high flexibility of HS chains can promote multi-site interactions with surrounding molecules near and above the membrane. This study is a first step toward all-atom molecular modeling and simulation of the glycocalyx, as well as its modulation of interactions between growth factors and their receptors.

CHARMM-GUI Membrane Builder for Lipid Nanoparticles with Ionizable Cationic Lipids and PEGylated Lipids.

A lipid nanoparticle (LNP) formulation is a state-of-the-art delivery system for genetic drugs such as DNA, messenger RNA, and small interfering RNA, which is successfully applied to COVID-19 vaccines and gains tremendous interest in therapeutic applications. Despite its importance, a molecular-level understanding of the LNP structures and dynamics is still lacking, which makes rational LNP design almost impossible. In this work, we present an extension of CHARMM-GUI Membrane Builder to model and simulate all-atom LNPs with various (ionizable) cationic lipids and PEGylated lipids (PEG-lipids). These new lipid types can be mixed with any existing lipid types with or without a biomolecule of interest, and the generated systems can be simulated using various molecular dynamics engines. As a first illustration, we considered model LNP membranes with DLin-KC2-DMA (KC2) or DLin-MC3-DMA (MC3) without PEG-lipids. The results from these model membranes are consistent with those from the two previous studies, albeit with mild accumulation of neutral MC3 in the bilayer center. To demonstrate Membrane Builder's capability of building a realistic LNP patch, we generated KC2- or MC3-containing LNP membranes with high concentrations of cholesterol and ionizable cationic lipids together with 2 mol % PEG-lipids. We observe that PEG-chains are flexible, which can be more preferentially extended laterally in the presence of cationic lipids due to the attractive interactions between their head groups and PEG oxygen. The presence of PEG-lipids also relaxes the lateral packing in LNP membranes, and the area compressibility modulus (KA) of LNP membranes with cationic lipids fit into typical KA of fluid-phase membranes. Interestingly, the interactions between PEG oxygen and the head group of ionizable cationic lipids induce a negative curvature. We hope that this LNP capability in Membrane Builder can be useful to better characterize various LNPs with or without genetic drugs for rational LNP design.

CHARMM-GUI Free Energy Calculator for Practical Ligand Binding Free Energy Simulations with AMBER.

Alchemical free energy methods, such as free energy perturbation (FEP) and thermodynamic integration (TI), become increasingly popular and crucial for drug design and discovery. However, the system preparation of alchemical free energy simulation is an error-prone, time-consuming, and tedious process for a large number of ligands. To address this issue, we have recently presented CHARMM-GUI Free Energy Calculator that can provide input and postprocessing scripts for NAMD and GENESIS FEP molecular dynamics systems. In this work, we extended three submodules of Free Energy Calculator to work with the full suite of GPU-accelerated alchemical free energy methods and tools in AMBER, including input and postprocessing scripts. The BACE1 (ß-secretase 1) benchmark set was used to validate the AMBER-TI simulation systems and scripts generated by Free Energy Calculator. The overall results of relatively large and diverse systems are almost equivalent with different protocols (unified and split) and with different timesteps (1, 2, and 4 fs), with R2 > 0.9. More importantly, the average free energy differences between two protocols are small and reliable with four independent runs, with a mean unsigned error (MUE) below 0.4 kcal/mol. Running at least four independent runs for each pair with AMBER20 (and FF19SB/GAFF2.1/OPC force fields), we obtained a MUE of 0.99 kcal/mol and root-mean-square error of 1.31 kcal/mol for 58 alchemical transformations in comparison with experimental data. In addition, a set of ligands for T4-lysozyme was used to further validate our free energy calculation protocol whose results are close to experimental data (within 1 kcal/mol). In summary, Free Energy Calculator provides a user-friendly web-based tool to generate the AMBER-TI system and input files for high-throughput binding free energy calculations with access to the full set of GPU-accelerated alchemical free energy, enhanced sampling, and analysis methods in AMBER.

CHARMM-GUI Supports Hydrogen Mass Repartitioning and Different Protonation States of Phosphates in Lipopolysaccharides.

Hydrogen mass repartitioning (HMR) that permits time steps of all-atom molecular dynamics simulation up to 4 fs by increasing the mass of hydrogen atoms has been used in protein and phospholipid bilayers simulations to improve conformational sampling. Molecular simulation input generation via CHARMM-GUI now supports HMR for diverse simulation programs. In addition, considering ambiguous pH at the bacterial outer membrane surface, different protonation states, either -2e or -1e, of phosphate groups in lipopolysaccharides (LPS) are also supported in CHARMM-GUI LPS Modeler. To examine the robustness of HMR and the influence of protonation states of phosphate groups on LPS bilayer properties, eight different LPS-type all-atom systems with two phosphate protonation states are modeled and simulated utilizing both OpenMM 2-fs (standard) and 4-fs (HMR) schemes. Consistency in the conformational space sampled by standard and HMR simulations shows the reliability of HMR even in LPS, one of the most complex biomolecules. For systems with different protonation states, similar conformations are sampled with a PO41- or PO42- group, but different phosphate protonation states make slight impacts on lipid packing and conformational properties of LPS acyl chains. Systems with PO41- have a slightly smaller area per lipid and thus slightly more ordered lipid A acyl chains compared to those with PO42-, due to more electrostatic repulsion between PO42- even with neutralizing Ca2+ ions. HMR and different protonation states of phosphates of LPS available in CHARMM-GUI are expected to be useful for further investigations of biological systems of diverse origin.

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

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.

Preferred conformations of lipooligosaccharides and oligosaccharides of Moraxella catarrhalis.

Moraxella catarrhalis (M. catarrhalis) is a pathogenic gram-negative bacterium that causes otitis media and sinusitis in children. Three major serotypes A, B and C are identified to account for approximately 95% of the clinical isolates. Understanding the conformational properties of different serotypes of M. catarrhalis provides insights into antigenic determinants. In this work, all-atom molecular dynamics simulations were conducted for M. catarrhalis lipooligosaccharide (LOS) bilayer systems and oligosaccharides (OS) in water solution to investigate the conformational similarities and differences of three serotypes. For up to 10 neutral monosaccharides in the core part, the conformational ensembles described by the pair-wise root mean square deviation distributions are similar among the three serotypes of either the LOS or OS. At the central ß-($1\to4$)-linkage, anti-$\psi$ conformation in conjunction with the gauche-gauche (g-) conformation of the central trisubstituted glucosyl residue is observed as the dominant conformation to sustain the structural characteristics of M. catarrhalis three types, which is further supported by calculated transglycosidic ${}^3{J}_{C,H}\Big({\psi}_H\Big)$ of serotype A in comparison to experimental data. Interestingly, the conformational variability of three serotypes is more restricted for the OS in water solution than that in the LOS bilayer systems. The LOS-LOS interactions in the bilayer systems are responsible for the increased conformational diversity despite of tight packing. Solvent-accessible surface area analysis suggests that a trisaccharide attached to the ß-($1\to 6$)-linked sugar in all three serotypes of LOS could be the common epitope and have the possibility to interact with antibodies.

CHARMM-GUI DEER facilitator for spin-pair distance distribution calculations and preparation of restrained-ensemble molecular dynamics simulations.

The double electron-electron resonance (DEER) is a powerful structural biology technique to obtain distance information in the range of 18 to 80 å by measuring the dipolar coupling between two unpaired electron spins. The distance distributions obtained from the experiment provide valuable structural information about the protein in its native environment that can be exploited using restrained ensemble molecular dynamics (reMD) simulations. We present a new tool DEER Facilitator in CHARMM-GUI that consists of two modules Spin-Pair Distributor and reMD Prepper to setup simulations that utilize information from DEER experiments. Spin-Pair Distributor provides a web-based interface to calculate the spin-pair distance distribution of labeled sites in a protein using MD simulations. The calculated distribution can be used to guide the selection of the labeling sites in experiments as well as validate different protein structure models. reMD Prepper facilities the setup of reMD simulations using different types of spin labels in four different environments including vacuum, solution, micelle, and bilayer. The applications of these two modules are demonstrated with several test cases. Spin-Pair Distributor and reMD Prepper are available at http://www.charmm-gui.org/input/deer and http://www.charmm-gui.org/input/deerre. DEER Facilitator is expected to facilitate advanced biomolecular modeling and simulation, thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems based on experimental DEER data. © 2019 Wiley Periodicals, Inc.

CHARMM-GUI supports the Amber force fields.

As part of our ongoing efforts to support diverse force fields and simulation programs in CHARMM-GUI, this work presents the development of FF-Converter to prepare Amber simulation inputs with various Amber force fields within the current CHARMM-GUI workflow. The currently supported Amber force fields are ff14SB/ff19SB (protein), Bsc1 (DNA), OL3 (RNA), GLYCAM06 (carbohydrate), Lipid17 (lipid), GAFF/GAFF2 (small molecule), TIP3P/TIP4P-EW/OPC (water), and 12-6-4 ions, and more will be added if necessary. The robustness and usefulness of this new CHARMM-GUI extension are demonstrated by two exemplary systems: a protein/N-glycan/ligand/membrane system and a protein/DNA/RNA system. Currently, CHARMM-GUI supports the Amber force fields only for the Amber program, but we will expand the FF-Converter functionality to support other simulation programs that support the Amber force fields.

A method to detect triplet exciton transfer from singlet fission materials into silicon solar cells: Comparing different surface treatments.

Singlet fission is one of the most promising routes to overcome the single-junction efficiency limit for solar cells. Singlet fission-enhanced silicon solar cells are the most desirable implementation, but transfer of triplet excitons, the product of singlet fission, into silicon solar cells has proved to be very challenging. Here, we report on an all optical measurement technique for the detection of triplet exciton quenching at semiconductor interfaces, a necessary requirement for triplet exciton or charge transfer. The method relies on the growth of individual, single-crystal islands of the singlet fission material on the silicon surface. The islands have different heights, and we correlate these heights to the quenching efficiency of triplet excitons. The quenching efficiency is measured by spatially resolved delayed fluorescence and compared to a diffusion-quenching model. Using silicon capped with a blocking thermal oxide and aromatic monolayers, we demonstrate that this technique can quickly screen different silicon surface treatments for triplet exciton quenching.

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.

CHARMM-GUI Nanodisc Builder for modeling and simulation of various nanodisc systems.

Nanodiscs are discoidal protein-lipid complexes that have wide applications in membrane protein studies. Modeling and simulation of nanodiscs are challenging due to the absence of structures of many membrane scaffold proteins (MSPs) that wrap around the membrane bilayer. We have developed CHARMM-GUI Nanodisc Builder (http://www.charmm-gui.org/input/nanodisc) to facilitate the setup of nanodisc simulation systems by modeling the MSPs with defined size and known structural features. A total of 11 different nanodiscs with a diameter from 80 to 180 Å are made available in both the all-atom CHARMM and two coarse-grained (PACE and Martini) force fields. The usage of the Nanodisc Builder is demonstrated with various simulation systems. The structures and dynamics of proteins and lipids in these systems were analyzed, showing similar behaviors to those from previous all-atom and coarse-grained nanodisc simulations. We expect the Nanodisc Builder to be a convenient and reliable tool for modeling and simulation of nanodisc systems. © 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.

Molecular Simulation and Biochemical Studies Support an Elevator-type Transport Mechanism in EIIC.

Enzyme IIC (EIIC) is a membrane-embedded sugar transport protein that is part of the phosphoenolpyruvate-dependent phosphotransferases. Crystal structures of two members of the glucose EIIC superfamily, bcChbC in the inward-facing conformation and bcMalT in the outward-facing conformation, were previously solved. Comparing the two structures led us to the hypothesis that sugar translocation could be achieved by an elevator-type transport mechanism in which a transport domain binds to the substrate and, through rigid body motions, transports it across the membrane. To test this hypothesis and to obtain more accurate descriptions of alternate conformations of the two proteins, we first performed collective variable-based steered molecular dynamics (CVSMD) simulations starting with the two crystal structures embedded in model lipid bilayers, and steered their transport domain toward their own alternative conformation. Our simulations show that large rigid-body motions of the transport domain (55° in rotation and 8 Å in translation) lead to access of the substrate binding site to the alternate side of the membrane. H-bonding interactions between the sugar and the protein are intact, although the side chains of the binding-site residues were not restrained in the simulation. Pairs of residues in bcMalT that are far apart in the crystal structure become close to each other in the simulated model. Some of these pairs can be cross-linked by a mercury ion when mutated to cysteines, providing further support for the CVSMD-generated model. In addition, bcMalT binds to maltose with similar affinities before and after the cross-linking, suggesting that the binding site is preserved after the conformational change. In combination, these results support an elevator-type transport mechanism in EIIC.

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 Martini Maker for modeling and simulation of complex bacterial membranes with lipopolysaccharides.

A complex cell envelope, composed of a mixture of lipid types including lipopolysaccharides, protects bacteria from the external environment. Clearly, the proteins embedded within the various components of the cell envelope have an intricate relationship with their local environment. Therefore, to obtain meaningful results, molecular simulations need to mimic as far as possible this chemically heterogeneous system. However, setting up such systems for computational studies is far from trivial, and consequently the vast majority of simulations of outer membrane proteins still rely on oversimplified phospholipid membrane models. This work presents an update of CHARMM-GUI Martini Maker for coarse-grained modeling and simulation of complex bacterial membranes with lipopolysaccharides. The qualities of the outer membrane systems generated by Martini Maker are validated by simulating them in bilayer, vesicle, nanodisc, and micelle environments (with and without outer membrane proteins) using the Martini force field. We expect this new feature in Martini Maker to be a useful tool for modeling large, complicated bacterial outer membrane systems in a user-friendly manner. © 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.

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.