CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecu- lar simulation program. It has been developed over the last three decades with a primary focus on molecules of bio- logical interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estima- tors, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numer- ous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

/pdf/charmm-the-biomolecular-simulation-program-4kexem0xkx.pdf

CHARMM: the biomolecular simulation program.

The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.

/pdf/charmm-general-force-field-a-force-field-for-drug-like-4mhn8ejv47.pdf

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.

A significant modification to the additive all-atom CHARMM lipid force field (FF) is developed and applied to phospholipid bilayers with both choline and ethanolamine containing head groups and with both saturated and unsaturated aliphatic chains. Motivated by the current CHARMM lipid FF (C27 and C27r) systematically yielding values of the surface area per lipid that are smaller than experimental estimates and gel-like structures of bilayers well above the gel transition temperature, selected torsional, Lennard-Jones and partial atomic charge parameters were modified by targeting both quantum mechanical (QM) and experimental data. QM calculations ranging from high-level ab initio calculations on small molecules to semiempirical QM studies on a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer in combination with experimental thermodynamic data were used as target data for parameter optimization. These changes were tested with simulations of pure bilayers at high hydration of the following six lipids: ...

Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types

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 para...

https://dash.harvard.edu/bitstream/handle/1/24983875/4712441.pdf?sequence=1

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

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. © 2014 Wiley Periodicals, Inc.

CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations

We present an all-atom additive empirical force field for the hexopyranose monosaccharide form of glucose and its diastereomers allose, altrose, galactose, gulose, idose, mannose, and talose. The model is developed to be consistent with the CHARMM all-atom biomolecular force fields, and the same parameters are used for all diastereomers, including both the alpha- and beta-anomers of each monosaccharide. The force field is developed in a hierarchical manner and reproduces the gas-phase and condensed-phase properties of small-molecule model compounds corresponding to fragments of pyranose monosaccharides. The resultant parameters are transferred to the full pyranose monosaccharides, and additional parameter development is done to achieve a complete hexopyranose monosaccharide force field. Parametrization target data include vibrational frequencies, crystal geometries, solute-water interaction energies, molecular volumes, heats of vaporization, and conformational energies, including those for over 1800 monosaccharide conformations at the MP2/cc-pVTZ//MP2/6-31G(d) level of theory. Although not targeted during parametrization, free energies of aqueous solvation for the model compounds compare favorably with experimental values. Also well-reproduced are monosaccharide crystal unit cell dimensions and ring pucker, densities of concentrated aqueous glucose systems, and the thermodynamic and dynamic properties of the exocyclic torsion in dilute aqueous systems. The new parameter set expands the CHARMM additive force field to allow for simulation of heterogeneous systems that include hexopyranose monosaccharides in addition to proteins, nucleic acids, and lipids.

/pdf/additive-empirical-force-field-for-hexopyranose-4pg2ef6qh9.pdf

Additive empirical force field for hexopyranose monosaccharides.

Empirical force field parameters consistent with the CHARMM additive and classical Drude based polarizable force fields are presented for linear and cyclic ethers. Initiation of the optimization pr...

Additive and Classical Drude Polarizable Force Fields for Linear and Cyclic Ethers

Toll-like receptor (TLR) signaling is initiated by dimerization of intracellular Toll/IL-1 receptor resistance (TIR) domains. For all TLRs except TLR3, recruitment of the adapter, myeloid differentiation primary response gene 88 (MyD88), to TLR TIR domains results in downstream signaling culminating in proinflammatory cytokine production. Therefore, blocking TLR TIR dimerization may ameliorate TLR2-mediated hyperinflammatory states. The BB loop within the TLR TIR domain is critical for mediating certain protein–protein interactions. Examination of the human TLR2 TIR domain crystal structure revealed a pocket adjacent to the highly conserved P681 and G682 BB loop residues. Using computer-aided drug design (CADD), we sought to identify a small molecule inhibitor(s) that would fit within this pocket and potentially disrupt TLR2 signaling. In silico screening identified 149 compounds and 20 US Food and Drug Administration-approved drugs based on their predicted ability to bind in the BB loop pocket. These compounds were screened in HEK293T-TLR2 transfectants for the ability to inhibit TLR2-mediated IL-8 mRNA. C16H15NO4 (C29) was identified as a potential TLR2 inhibitor. C29, and its derivative, ortho-vanillin (o-vanillin), inhibited TLR2/1 and TLR2/6 signaling induced by synthetic and bacterial TLR2 agonists in human HEK-TLR2 and THP-1 cells, but only TLR2/1 signaling in murine macrophages. C29 failed to inhibit signaling induced by other TLR agonists and TNF-α. Mutagenesis of BB loop pocket residues revealed an indispensable role for TLR2/1, but not TLR2/6, signaling, suggesting divergent roles. Mice treated with o-vanillin exhibited reduced TLR2-induced inflammation. Our data provide proof of principle that targeting the BB loop pocket is an effective approach for identification of TLR2 signaling inhibitors.

https://www.pnas.org/content/pnas/112/17/5455.full.pdf

Shannon Greene

Papers

Additive empirical force field for hexopyranose monosaccharides.

Additive and Classical Drude Polarizable Force Fields for Linear and Cyclic Ethers

Inhibition of TLR2 signaling by small molecule inhibitors targeting a pocket within the TLR2 TIR domain