AMBER-ii: New Combining Rules and Force Field for Perfluoroalkanes

Comparison of the United- and All-Atom Representations of (Halo)alkanes Based on Two Condensed-Phase Force Fields Optimized against the Same Experimental Data Set

The level of accuracy that can be achieved by a force field is influenced by choices made in the interaction-function representation and in the relevant simulation parameters. These choices, referred to here as functional-form variants (FFVs), include for example the model resolution, the charge-derivation procedure, the van der Waals combination rules, the cutoff distance, and the treatment of the long-range interactions. Ideally, assessing the effect of a given FFV on the intrinsic accuracy of the force-field representation requires that only the specific FFV is changed and that this change is performed at an optimal level of parametrization, a requirement that may prove extremely challenging to achieve in practice. Here, we present a first attempt at such a comparison for one specific FFV, namely the choice of a united-atom (UA) versus an all-atom (AA) resolution in a force field for saturated acyclic (halo)alkanes. Two force-field versions (UA vs AA) are optimized in an automated way using the CombiFF approach against 961 experimental values for the pure-liquid densities ρ_liq and vaporization enthalpies ΔH_vap of 591 compounds. For the AA force field, the torsional and third-neighbor Lennard-Jones parameters are also refined based on quantum-mechanical rotational-energy profiles. The comparison between the UA and AA resolutions is also extended to properties that have not been included as parameterization targets, namely the surface-tension coefficient γ, the isothermal compressibility κ_T, the isobaric thermal-expansion coefficient α_P, the isobaric heat capacity c_P, the static relative dielectric permittivity ϵ, the self-diffusion coefficient D, the shear viscosity η, the hydration free energy ΔG_wat, and the free energy of solvation ΔG_che in cyclohexane. For the target properties ρ_liq and ΔH_vap, the UA and AA resolutions reach very similar levels of accuracy after optimization. For the nine other properties, the AA representation leads to more accurate results in terms of η; comparably accurate results in terms of γ, κ_T, α_P, ϵ, D, and ΔG_che; and less accurate results in terms of c_P and ΔG_wat. This work also represents a first step toward the calibration of a GROMOS-compatible force field at the AA resolution.

Ligand and Structure-Based Virtual Screening in Combination, to Evaluate Small Organic Molecules as Inhibitors for the XIAP Anti-Apoptotic Protein: The Xanthohumol Hypothesis

Herein, we propose two chalcone molecules, (E)-1-(4-methoxyphenyl)-3-(p-tolyl) prop-2-en-1-one and (E)-3-(4-hydroxyphenyl)-1-(2,4,6-trihydroxyphenyl) prop-2-en-1-one, based on the anticancer bioactive molecule Xanthohumol, which are suitable for further in vitro and in vivo studies. Their ability to create stable complexes with the antiapoptotic X-linked IAP (XIAP) protein makes them promising anticancer agents. The calculations were based on ligand-based and structure-based virtual screening combined with the pharmacophore build. Additionally, the structures passed Lipinski’s rule for drug use, and their reactivity was confirmed using density functional theory studies. ADMET studies were also performed to reveal the pharmacokinetic potential of the compounds. The candidates were chosen from 10,639,400 compounds, and the docking protocols were evaluated using molecular dynamics simulations.

Partial charges for molecular-mechanical models of heterocyclic compounds: pyridine nitrogen

This paper deals with the effect of introducing an additional interaction site onto molecular-mechanical models of nitrogen-containing heterocyclic compounds. The introduction of only one additional site next to nitrogen atoms is shown to result in significant improvement of the quality of the models along with negligible slowdown of calculation speed. Concretely, it was proposed to introduce the site inside the aromatic ring at a distance of 0.4 Å from the nitrogen atom center. All the parametrization can be completely automated. The proposed force field allows predicting heats of evaporation of liquids of the compound under investigation with an accuracy of 1 kcal/mol.

Amino Acid and Oligopeptide Effects on Calcium Carbonate Solutions

Biological organisms display sophisticated control of nucleation and crystallization of minerals. In order to mimic living systems, deciphering the mechanisms by which organic molecules control the formation of mineral phases from solution is a key step. We have used computer simulations to investigate the effects of the amino acids arginine, aspartic acid, and glycine on species that form in solutions of calcium carbonate (CaCO₃) at lower and higher levels of supersaturation. This provides net positive, negative, and neutral additives. In addition, we have prepared simulations containing hexapeptides of the amino acids to consider the effect of additive size on the solution species. We find that additives have limited impact on the formation of extended, liquid-like CaCO₃ networks in supersaturated solutions. Additives control the amount of (bi)carbonate in solution, but more importantly, they are able to stabilize these networks on the time scales of the simulations. This is achieved by coordinating the networks and assembled additive clusters in solutions. The association leads to subtle changes in the coordination of CaCO₃ and reduced mobility of the cations. We find that the number of solute association sites and the size and topology of the additives are more important than their net charge. Our results help to understand why polymer additives are so effective at stabilizing dense liquid CaCO₃ phases.

Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge

The SAMPL Challenges aim to focus the biomolecular and physical modeling community on issues that limit the accuracy of predictive modeling of protein-ligand binding for rational drug design. In the SAMPL5 log D Challenge, designed to benchmark the accuracy of methods for predicting drug-like small molecule transfer free energies from aqueous to nonpolar phases, participants found it difficult to make accurate predictions due to the complexity of protonation state issues. In the SAMPL6 log P Challenge, we asked participants to make blind predictions of the octanol-water partition coefficients of neutral species of 11 compounds and assessed how well these methods performed absent the complication of protonation state effects. This challenge builds on the SAMPL6 p[Formula: see text] Challenge, which asked participants to predict p[Formula: see text] values of a superset of the compounds considered in this log P challenge. Blind prediction sets of 91 prediction methods were collected from 27 research groups, spanning a variety of quantum mechanics (QM) or molecular mechanics (MM)-based physical methods, knowledge-based empirical methods, and mixed approaches. There was a 50% increase in the number of participating groups and a 20% increase in the number of submissions compared to the SAMPL5 log D Challenge. Overall, the accuracy of octanol-water log P predictions in SAMPL6 Challenge was higher than cyclohexane-water log D predictions in SAMPL5, likely because modeling only the neutral species was necessary for log P and several categories of method benefited from the vast amounts of experimental octanol-water log P data. There were many highly accurate methods: 10 diverse methods achieved RMSE less than 0.5 log P units. These included QM-based methods, empirical methods, and mixed methods with physical modeling supported with empirical corrections. A comparison of physical modeling methods showed that QM-based methods outperformed MM-based methods. The average RMSE of the most accurate five MM-based, QM-based, empirical, and mixed approach methods based on RMSE were 0.92 ± 0.13, 0.48 ± 0.06, 0.47 ± 0.05, and 0.50 ± 0.06, respectively.

The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations

Misfolded Cu/Zn superoxide dismutase enzyme (SOD1) shows prion-like propagation in neuronal cells leading to neurotoxic aggregates that are implicated in amyotrophic lateral sclerosis (ALS). Tryptophan-32 (W32) in SOD1 is part of a potential site for templated conversion of wild type SOD1. This W32 binding site is located on a convex, solvent exposed surface of the SOD1 suggesting that hydration effects can play an important role in ligand recognition and binding. A recent X-ray crystal structure has revealed that 5-Fluorouridine (5-FUrd) binds at the W32 binding site and can act as a pharmacophore scaffold for the development of anti-ALS drugs. In this study, a new protocol is developed to account for structural (non-displaceable) water molecules in docking simulations and successfully applied to predict the correct docked conformation binding modes of 5-FUrd at the W32 binding site. The docked configuration is within 0.58 Å (RMSD) of the observed configuration. The docking protocol involved calculating a hydration structure around SOD1 using molecular theory of solvation (3D-RISM-KH, 3D-Reference Interaction Site Model-Kovalenko-Hirata) whereby, non-displaceable water molecules are identified for docking simulations. This protocol was also used to analyze the hydrated structure of the W32 binding site and to explain the role of solvation in ligand recognition and binding to SOD1. Structural water molecules mediate hydrogen bonds between 5-FUrd and the receptor, and create an environment favoring optimal placement of 5-FUrd in the W32 binding site.

Refined Empirical Force Field to Model Protein-Self-Assembled Monolayer Interactions Based on AMBER14 and GAFF

Understanding protein interaction with material surfaces is important for the development of nanotechnological devices. The structures and dynamics of proteins can be studied via molecular dynamics (MD) if the protein-surface interactions can be accurately modeled. To answer this question, we computed the adsorption free energies of peptides (representing eleven different amino acids) on a hydrophobic self-assembled monolayer (CH₃-SAM) and compared them to the benchmark experimental data set. Our result revealed that existing biomolecular force fields, GAFF and AMBER ff14sb, cannot reproduce the experimental peptide adsorption free energies by Wei and Latour (Langmuir, 2009, 25, 5637-5646). To obtain the improved force fields, we systematically tuned the Lennard-Jones parameters of selected amino acid sidechains and the functional group of SAM with repeated metadynamics and umbrella sampling simulations. The final parameter set has yielded a significant improvement in the free energy values with R = 0.83 and MSE = 0.65 kcal/mol. We applied the refined force field to predict the initial adsorption orientation of lysozyme on CH₃-SAM. Two major orientations-face-down and face-up-were predicted. Our analysis on the protein structure, solvent accessible surface area, and binding of native ligand NAG₃ suggested that lysozyme in the face-up orientation can remain active after initial adsorption. However, because of its weaker affinity (ΔΔG = 7.86 kcal/mol) for the ligand, the bioactivity of the protein is expected to reduce. Our work facilitates the use of MD for the study of protein-SAM systems. The refined force field compatible with GROMACS is available at https://cbbio.cis.um.edu.mo/software/SAMFF .

Development of Nonbonded Models for Metal Cations Using the Electronic Continuum Correction

The parametrization of classical nonbonded models of metal ions has been widely addressed in the recent years. Despite the continuous development of novel and more physically inspired functional forms, the 12-6 Lennard-Jones plus Coulomb potential is still the most adopted force field in molecular dynamics (MD) codes, owing to its simple form and easy implementation. However, due to the integer formal charge, unpolarizable force fields of ions may suffer from overestimated interatomic electrostatic interactions, leading to nonphysical clustering or repulsion between such full charges. The electronic continuum correction (ECC) can fix this problem through a simple inclusion of solvent polarization effects via ionic charge rescaling. In this work, the development of novel nonbonded models for mono, divalent, and highly charged metal ions is presented. For each metal species, the ionic charge has been scaled, according to the ECC. Lennard-Jones parameters have been optimized using experimental structural and thermodynamic properties as target quantities. Performances of the proposed models are discussed and compared with the literature data, while transferability attitudes among different and well-known water models are evaluated. © 2019 Wiley Periodicals, Inc.

The good, the bad and the user in soft matter simulations

Molecular dynamics (MD) simulations have become popular in materials science, biochemistry, biophysics and several other fields. Improvements in computational resources, in quality of force field parameters and algorithms have yielded significant improvements in performance and reliability. On the other hand, no method of research is error free. In this review, we discuss a few examples of errors and artifacts due to various sources and discuss how to avoid them. Besides bringing attention to artifacts and proper practices in simulations, we also aim to provide the reader with a starting point to explore these issues further. In particular, we hope that the discussion encourages researchers to check software, parameters, protocols and, most importantly, their own practices in order to minimize the possibility of errors. The focus here is on practical issues. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.