An improved parameter set for explicit-solvent simulations of carbohydrates (referred to as GROMOS 53A6GLYC) is presented, allowing proper description of the most stable conformation of all 16 possible aldohexopyranose-based monosaccharides. This set includes refinement of torsional potential parameters associated with the determination of hexopyranose rings conformation by fitting to their corresponding quantum-mechanical profiles. Other parameters, as the rules for third and excluded neighbors, are taken directly from the GROMOS 53A6 force field. Comparisons of the herein presented parameter set to our previous version (GROMOS 45A4), the GLYCAM06 force field, and available NMR data are presented in terms of ring puckering free energies, conformational distribution of the hydroxymethyl group, and glycosidic linkage geometries for 16 selected monosaccharides and eight disaccharides. The proposed parameter modifications have shown a significant improvement for the above-mentioned quantities over the two tested force fields, while retaining full compatibility with the GROMOS 53A6 and 54A7 parameter sets for other classes of biomolecules.

Lipopolysaccharides (LPS) are the main constituent of the outer bacterial membrane of Gram-negative bacteria. Lipid-A is the structural region of LPS that interacts with the innate immune system and induces inflammatory responses. It is formed by a phosphorylated β-d-glucosaminyl-(1→6)-α-N-glucosamine disaccharide backbone containing ester-linked and amide-linked long-chain fatty acids, which may vary in length and number depending on the bacterial strains and the environment. Phenotypical variation (i.e., number of acyl chains), cation type, and temperature influence the phase transition, aggregate structure, and endotoxic activity of Lipid-A. We have applied an extension of the GROMOS force field 45a4 carbohydrate parameter set to investigate the behavior of hexa- and pentaacylated Lipid-A of Pseudomonas aeruginosa at two temperatures (300 and 328 K) and in the presence of mono- and divalent cations (represented by Ca(2+) and Na(+), respectively) through molecular dynamics simulations. The distinct phase of Lipid-A aggregates was characterized by structural properties, deuterium order parameters, the molecular shape of the lipid units (conical versus cylindrical), and molecular packing. Our results show that Na(+) ions induce a transition from the lamellar to nonlamellar phase. In contrast, the bilayer integrity is maintained in the presence of Ca(2+) ions. Through these findings, we present microscopic insights on the influence of different cations on the molecular behavior of Lipid-A associated with the lamellar to nonlamellar transition.

During the past half century, the number and accuracy of experimental techniques that can deliver values of observables for biomolecular systems have been steadily increasing. The conversion of a measured value Q of an observable quantity Q into structural information is, however, a task beset with theoretical and practical problems: 1) insufficient or inaccurate values of Q , 2) inaccuracies in the function Q(r→) used to relate the quantity Q to structure r→ , 3) how to account for the averaging inherent in the measurement of Q , 4) how to handle the possible multiple-valuedness of the inverse r→(Q) of the function Q(r→) , to mention a few. These apply to a variety of observable quantities Q and measurement techniques such as X-ray and neutron diffraction, small-angle and wide-angle X-ray scattering, free-electron laser imaging, cryo-electron microscopy, nuclear magnetic resonance, electron paramagnetic resonance, infrared and Raman spectroscopy, circular dichroism, Förster resonance energy transfer, atomic force microscopy and ion-mobility mass spectrometry. The process of deriving structural information from measured data is reviewed with an eye to non-experts and newcomers in the field using examples from the literature of the effect of the various choices and approximations involved in the process. A list of choices to be avoided is provided.

The identification of lead compounds usually includes a step of chemical diversity generation. Its rationale may be supported by both qualitative (SAR) and quantitative (QSAR) approaches, offering models of the putative ligand-receptor interactions. In both scenarios, our understanding of which interactions functional groups can perform is mostly based on their chemical nature (such as electronegativity, volume, melting point, lipophilicity etc.) instead of their dynamics in aqueous, biological solutions (solvent accessibility, lifetime of hydrogen bonds, solvent structure etc.). As a consequence, it is challenging to predict from 2D structures which functional groups will be able to perform interactions with the target receptor, at which intensity and relative abundance in the biological environment, all of which will contribute to ligand potency and intrinsic activity. With this in mind, the aim of this work is to assess properties of aromatic rings, commonly used for drug design, in aqueous solution through molecular dynamics simulations in order to characterize their chemical features and infer their impact in complexation dynamics. For this, common aromatic and heteroaromatic rings were selected and received new atomic charge set based on the direction and module of the dipole moment from MP2/6-31G* calculations, while other topological terms were taken from GROMOS53A6 force field. Afterwards, liquid physicochemical properties were simulated for a calibration set composed by nearly 40 molecules and compared to their respective experimental data, in order to validate each topology. Based on the reliance of the employed strategy, we expanded the dataset to more than 100 aromatic rings. Properties in aqueous solution such as solvent accessible surface area, H-bonds availability, H-bonds residence time, and water structure around heteroatoms were calculated for each ring, creating a database of potential interactions, shedding light on features of drugs in biological solutions, on the structural basis for bioisosterism and on the enthalpic/entropic costs for ligand-receptor complexation dynamics.

A novel four-bead coarse-grained (CG) model for carbohydrates denoted PITOMBA was devised using a bottom-up approach based on the atomistic GROMOS 53A6GLYC force field and on experimental thermodynamical data. The model was developed to be used in conjunction with the SPC CG water model (J. Chem. Phys. 2011, 134, 084110) and the GROMOS force field functional form. Explicit electrostatic interactions are considered by assigning point charges to each CG bead. Validation of the model is presented to a variety of structural and thermodynamic properties for mono- and oligosaccharides in solution. In addition, the model development philosophy allows for prompt extensions to include hexopyranose chains with diverse glycosidic linkages and branches.