Sire: An interoperability engine for prototyping algorithms and exchanging information between molecular simulation programs.

Sire is a Python/C++ library that is used both to prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of many other programs and libraries. This empowers researchers to use sire to write a single script that can, for example, load a molecule from a PDBx/mmCIF file via Gemmi, perform SMARTS searches via RDKit, parameterize molecules using BioSimSpace, run GPU-accelerated molecular dynamics via OpenMM, and then display the resulting dynamics trajectory in a NGLView Jupyter notebook 3D molecular viewer. This functionality is built on by BioSimSpace, which uses sire's molecular information engine to interconvert with programs such as GROMACS, NAMD, Amber, and AmberTools for automated molecular parameterization and the running of molecular dynamics, metadynamics, and alchemical free energy workflows. Sire comes complete with a powerful molecular information search engine, plus trajectory loading and editing, analysis, and energy evaluation engines. This, when combined with an in-built computer algebra system, gives substantial flexibility to researchers to load, search for, edit, and combine molecular information from multiple sources and use that to drive novel algorithms by combining functionality from other programs. Sire is open source (GPL3) and is available via conda and at a free Jupyter notebook server at https://try.openbiosim.org. Sire is supported by the not-for-profit OpenBioSim community interest company.

Infinite Dilution Activity Coefficients as Constraints for Force Field Parametrization and Method Development.

Molecular simulations begin with an underlying energy model or force field and from this can predict diverse physical properties. However, force fields were often developed with relatively limited data sets, yet accuracy for diverse properties across a broad chemical space is desirable; therefore, tests of such accuracy are particularly important. Here, to this end, we calculated 237 infinite dilution activity coefficients (IDACs), comparing with experimental values from NIST's ThermoML database. We found that calculated IDAC values correlate strongly with experiment (Pearson R of 0.92 ± 0.01) and allow us to identify specific functional groups that appear to present challenges to the force field employed. One potentially valuable aspect of IDACs, as compared to solvation free energies, which have been frequently employed as force field tests, is that the same molecules serve both as solutes and solvents in different cases, allowing us to ensure that force fields are not overly tuned to one particular environment or solvent.

Biomolecular Solvation Structure Revealed by Molecular Dynamics Simulations.

To compare ordered water positions from experiment with those from molecular dynamics (MD) simulations, a number of MD models of water structure in crystalline endoglucanase were calculated. The starting MD model was derived from a joint X-ray and neutron diffraction crystal structure, enabling the use of experimentally assigned protonation states. Simulations were performed in the crystalline state, using a periodic 2 × 2 × 2 supercell with explicit solvent. Water X-ray and neutron scattering density maps were computed from MD trajectories using standard macromolecular crystallography methods. In one set of simulations, harmonic restraints were applied to bias the protein structure toward the crystal structure. For these simulations, the recall of crystallographic waters using strong peaks in the MD water electron density was very good, and there also was substantial visual agreement between the boomerang-like wings of the neutron scattering density and the crystalline water hydrogen positions. An unrestrained simulation also was performed. For this simulation, the recall of crystallographic waters was much lower. For both restrained and unrestrained simulations, the strongest water density peaks were associated with crystallographic waters. The results demonstrate that it is now possible to recover crystallographic water structure using restrained MD simulations but that it is not yet reasonable to expect unrestrained MD simulations to do the same. Further development and generalization of MD water models for force-field development, macromolecular crystallography, and medicinal chemistry applications is now warranted. In particular, the combination of room-temperature crystallography, neutron diffraction, and crystalline MD simulations promises to substantially advance modeling of biomolecular solvation.

Calculating Partition Coefficients of Small Molecules in Octanol/Water and Cyclohexane/Water.

Partition coefficients describe how a solute is distributed between two immiscible solvents. They are used in drug design as a measure of a solute's hydrophobicity and a proxy for its membrane permeability. We calculate partition coefficients from transfer free energies using molecular dynamics simulations in explicit solvent. Setup is done by our new Solvation Toolkit which automates the process of creating input files for any combination of solutes and solvents for many popular molecular dynamics software packages. We calculate partition coefficients between octanol/water and cyclohexane/water with the Generalized AMBER Force Field (GAFF) and the Dielectric Corrected GAFF (GAFF-DC). With similar methods in the past we found a root-mean-squared error (RMSE) of 6.3 kJ/mol in hydration free energies which would correspond to an error of around 1.6 log units in partition coefficients if solvation free energies in both solvents were estimated with comparable accuracy. Here we find an overall RMSE of about 1.2 log units with both force fields. Results from GAFF and GAFF-DC seem to exhibit systematic biases in opposite directions for calculated cyclohexane/water partition coefficients.

Elucidation of Nonadditive Effects in Protein-Ligand Binding Energies: Thrombin as a Case Study.

Accurate predictions of free energies of binding of ligands to proteins are challenging partly because of the nonadditivity of protein-ligand interactions; i.e., the free energy of binding is the sum of numerous enthalpic and entropic contributions that cannot be separated into functional group contributions. In principle, molecular simulations methodologies that compute free energies of binding do capture nonadditivity of protein-ligand interactions, but efficient protocols are necessary to compute well-converged free energies of binding that clearly resolve nonadditive effects. To this end, an efficient GPU-accelerated implementation of alchemical free energy calculations has been developed and applied to two congeneric series of ligands of the enzyme thrombin. The results show that accurate binding affinities are computed across the two congeneric series and positive coupling between nonpolar R(1) substituents and a X = NH3(+) substituent is reproduced, albeit with a weaker trend than experimentally observed. By contrast, a docking methodology completely fails to capture nonadditive effects. Further analysis shows that the nonadditive effects are partly due to variations in the strength of a hydrogen-bond between the X = NH3(+) ligands family and thrombin residue Gly216. However, other partially compensating interactions occur across the entire binding site, and no single interaction dictates the magnitude of the nonadditive effects for all the analyzed protein-ligand complexes.

Evaluation of Selected Classical Force Fields for Alchemical Binding Free Energy Calculations of Protein-Carbohydrate Complexes.

Protein-carbohydrate recognition is crucial in many vital biological processes including host-pathogen recognition, cell-signaling, and catalysis. Accordingly, computational prediction of protein-carbohydrate binding free energies is of enormous interest for drug design. However, the accuracy of current force fields (FFs) for predicting binding free energies of protein-carbohydrate complexes is not well understood owing to technical challenges such as the highly polar nature of the complexes, anomerization, and conformational flexibility of carbohydrates. The present study evaluated the performance of alchemical predictions of binding free energies with the GAFF1.7/AM1-BCC and GLYCAM06j force fields for modeling protein-carbohydrate complexes. Mean unsigned errors of 1.1 ± 0.06 (GLYCAM06j) and 2.6 ± 0.08 (GAFF1.7/AM1-BCC) kcal·mol(-1) are achieved for a large data set of monosaccharide ligands for Ralstonia solanacearum lectin (RSL). The level of accuracy provided by GLYCAM06j is sufficient to discriminate potent, moderate, and weak binders, a goal that has been difficult to achieve through other scoring approaches. Accordingly, the protocols presented here could find useful applications in carbohydrate-based drug and vaccine developments.

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors.

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3-4 orders of magnitude.

Prediction of Small Molecule Hydration Thermodynamics with Grid Cell Theory.

An efficient methodology has been developed to quantify water energetics by analysis of explicit solvent molecular simulations of organic and biomolecular systems. The approach, grid cell theory (GCT), relies on a discretization of the cell theory methodology on a three-dimensional grid to spatially resolve the density, enthalpy, and entropy of water molecules in the vicinity of solute(s) of interest. Entropies of hydration are found to converge more efficiently than enthalpies of hydration. GCT predictions of free energies of hydration on a data set of small molecules are strongly correlated with thermodynamic integration predictions. Agreement with the experiment is comparable for both approaches. A key advantage of GCT is its ability to provide from a single simulation insightful graphical analyses of spatially resolved components of the enthalpies and entropies of hydration.

[Substernal goiter: pre-, intra- and postoperative problems]. / Le problematiche pre-, intra- e postoperatorie del gozzo immerso.

The Authors report their experience with problems in treating substernal goiter. They then explain at length the complex haemodynamic or respiratory situations encountered and the therapeutic management of the condition. Also discussed are technical surgical problems, and the prevention and therapy of possible complications. They conclude by stating that thanks to all the technical means currently available complete patient control can be achieved before, during and after the operation, thus significantly contributing to the successful outcome of surgical treatment.

Warthin's tumour of the parotid gland.

The authors, after examining two recent cases, explain a number of basic concepts regarding the diagnosis and therapy of Warthin's tumour of the parotid gland. Despite their low frequency, such tumours are very important because of their aetiopathogenesis, which is still controversial, and the recent increase in their incidence in females. Today, the diagnostic protocol, undertaken after the necessary clinical examination, relies mainly on ultrasonography and CT, but only a postoperative histological examination is capable of yielding a sure diagnosis and establishing the main histomorphological characteristics of the tumour. The therapeutic approach can be limited to conservative treatment, sparing the parotid gland and its vascularization and innervation.