Influence of the Treatment of Nonbonded Interactions on the Thermodynamic and Transport Properties of Pure Liquids Calculated Using the 2016H66 Force Field

Ab Initio Prediction of Vapor Pressure for Diverse Atomic Layer Deposition Precursors

Understanding the saturated vapor pressure (Pvap) is vital for evaluating atomic layer deposition (ALD) precursors, as it directly influences the ALD temperature window and, by extension, the processability of compounds. The early estimation of vapor pressure ranges is crucial during the initial stages of novel precursor design, reducing the reliance on empirical synthesis or experimentation. However, predicting vapor pressure through computer simulations is often impeded by the scarcity of suitable empirical force fields for molecular dynamics simulations. This challenge is further compounded by the diverse chemical substances and the introduction of new elements into modern ALD processes, necessitating robust force fields that can accommodate metals, organics, and halides. In response, this study introduces a novel approach utilizing a quantum mechanically derived force field for the prediction of vapor pressure across a wide spectrum of potential ALD precursors. This approach enables the creation of system-specific force fields through parametrization based on ab initio calculations for a single molecule. We develop a comprehensive workflow to simulate both liquid and gaseous equilibrium phases, allowing the calculation of vapor pressure across a wide temperature range. Our methodology has been validated with a diverse set of ALD precursors, demonstrating its robustness in predicting Pvap at specified temperatures. The approach yields a Pearson's correlation coefficient (R2) greater than 0.9 on a logarithmic scale and a root-mean-squared deviation in self-solvation-free energies as low as 1.3 kcal mol-1. This innovative workflow, which does not require any prior experimental data, marks a significant advancement in the computer-aided design of novel ALD precursors, paving the way for accelerating developments in technology.

Unravelling carbohydrate binding module 21 (CBM21) dynamics of interaction with amylose

The carbohydrate binding module 21 (CBM21) from Rhizopus oryzae is a dual-site CBM proposed to disrupt polysaccharide structures. Additionally, it serves as a purification tag in industry. CBM21 crystal structure features a Glc residue in an unusual 1S3 conformation, whose relevance for the CBM mechanism of action is unclear. In this context, we seek to contribute for the understanding of CBM21 mechanism of action by: i) investigating the role of the 1S3 conformation on carbohydrate recognition, and ii) characterize the protein-carbohydrate binding dynamics using molecular dynamics and metadynamics simulations at MM and QM/MM levels. Results indicate the 1S3 Glc conformation is unlikely to occur under biological conditions, being originated from the crystallographic environment. CBM21 binding to small ligands appears transient and unstable, while protein dimerization and polysaccharide chain size influence complex stability. In interactions with amylose, CBM21 exhibits a repeated unbinding followed by re-binding, while simultaneously alternating between binding sites I and II. These results suggest that CBM21 acts through transient interactions, directing carbohydrates to the catalytic center rather than forming strong and long-lasting bonds with carbohydrates. Accordingly, we expect such atomistic depiction of CBM21 mechanism could aid in CBM design targeting biotechnological applications.

A molecular dynamics simulation study of glycine/serine octapeptides labeled with 2,3-diazabicyclo[2.2.2]oct-2-ene fluorophore

The compound 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO) is a versatile fluorophore widely used in Förster resonance energy transfer (FRET) spectroscopy studies due to its remarkable sensitivity, enabling precise donor-acceptor distance measurements, even for short peptides. Integrating time-resolved and FRET spectroscopies with molecular dynamics simulations provides a robust approach to unravel the structure and dynamics of biopolymers in a solution. This study investigates the structural behavior of three octapeptide variants: Trp-(Gly-Ser)3-Dbo, Trp-(GlyGly)3-Dbo, and Trp-(SerSer)3-Dbo, where Dbo represents the DBO-containing modified aspartic acid, using molecular dynamics simulations. Glycine- and serine-rich amino acid fragments, common in flexible protein regions, play essential roles in functional properties. Results show excellent agreement between end-to-end distances, orientational factors from simulations, and the available experimental and theoretical data, validating the reliability of the GROMOS force field model. The end-to-end distribution, modeled using three Gaussian distributions, reveals a complex shape, confirmed by cluster analysis highlighting a limited number of significant conformations dominating the peptide landscape. All peptides predominantly adopt a disordered state in the solvent, yet exhibit a compact shape, aligning with the model of disordered polypeptide chains in poor solvents. Conformations show marginal dependence on chain composition, with Ser-only chains exhibiting slightly more elongation. This study enhances our understanding of peptide behavior, providing valuable insights into their structural dynamics in solution.

Theoretical models of staurosporine and analogs uncover detailed structural information in biological solution

Staurosporine and its analogs (STA-analogs) are indolocarbazoles (ICZs) compounds able to inhibit kinase proteins in a non-specific way, while present antimicrobial and cytostatic properties. The knowledge of molecular features associated to the complexation, including the ligand shape in solution and thermodynamics of complexation, is substantial to the development of new bioactive ICZs with improved therapeutic properties. In this context, the empirical approach of GROMOS force field is able to accurately reproduce condensed phase physicochemical properties of molecular systems after parameterization. Hence, through parameterization under GROMOS force field and molecular simulations, we assessed STA-analogs dynamics in aqueous solution, as well as its interaction with water to probe conformational and structural features involved in complexation to therapeutic targets. The coexistence of multiple conformers observed in simulations, and confirmed by metadynamics calculations, expanding the conformational space knowledge of these ligands with potential implications in understanding the ligand conformational selection during complexation. Also, changes in availability to H-bonding concerning the different substituents and water can reflect on effects at complexation free energy due to variation at the desolvation energetic costs. Based on these results, we expect the obtained structural data provide systemic framework for rational chemical modification of STA-analogs.

gmak: A Parameter-Space Mapping Strategy for Force-Field Calibration

In the context of classical molecular simulations, the accuracy of a force field is highly influenced by the values of the relevant simulation parameters. In this work, a parameter-space mapping (PSM) workflow is proposed to aid in the calibration of force-field parameters, based mainly on the following features: (i) regular-grid discretization of the search space; (ii) partial sampling of the search-space grid; (iii) training of surrogate models to predict the estimates of the target properties for nonsampled parameter sets; (iv) post hoc interpretation of the results in terms of multiobjective optimization concepts; (v) attenuation of statistical errors achieved via empiric extension of the duration of the simulations; (vi) iterative search-space translation according to a user-defined scalar objective function that measures the accuracy of the force field (e.g., the weighted root-mean-square deviation of the target properties relative to the reference data). This combination of features results in a hybrid of a single- and a multiobjective optimization strategy, allowing for the approximate determination of both a local minimum of the chosen objective function and its neighboring Pareto efficient points. The PSM workflow is implemented in the extensible Python program gmak, which is made available in the Git repository at http://github.com/mssm-labmmol/gmak. Using this implementation, the PSM workflow was tested in a proof-of-concept fashion in the recalibration of the Lennard-Jones parameters of the 3-point Optimal Point Charge (OPC3) water model for compatibility with the GROMOS treatment of nonbonded interactions. The recalibrated model reproduces typical pure-liquid properties with an accuracy similar to the original OPC3 model and represents a significant improvement relative to the Simple Point Charge (SPC) model, which is the official recommendation for simulations using GROMOS force fields.

Force fields optimized against experimental data for large compound families using CombiFF: Validation considering non-target properties and polyfunctional compounds

The CombiFF scheme is a workflow for the automated calibration of force-field parameters against condensed-phase experimental data considering simultaneously entire classes of organic molecules. The main steps of this scheme are: (i) selection of a molecule family; (ii) enumeration of all isomers; (iii) query for experimental data; (iv) automatic construction of the molecular topologies; (v) iterative refinement of the force-field parameters considering the entire family. In two recent articles, CombiFF was applied to the design of GROMOS-compatible united-atom force fields for the saturated acyclic haloalkanes and for saturated acyclic compounds involving eight common chemical functional groups of oxygen and nitrogen. This calibration and the subsequent initial validation involved two limitations: (i) the experimental data considered was restricted to values for the pure-liquid density ρ_liq and the vaporization enthalpy ΔH_vap of the compounds; (ii) beyond monofunctional compounds, the training set only involved homo-polyhaloalkanes (possibly mixing halogen types) in the first study, and homo-polyfunctional compounds of the considered oxygen or nitrogen functional groups (no mixing of different group types) in the second one. The goal of this article is to further test the accuracy of CombiFF-generated force fields by extending the validation to: (i) nine additional properties that were not used as optimization targets (pure-liquid thermodynamic, dielectric and transport properties, as well as solvation properties); (ii) hetero-polyfunctional molecules that were not included in the calibration and initial validation sets. The results for the nine additional properties show good agreement with experiment, except for the shear viscosity and the dielectric permittivity. There, larger discrepancies are observed, likely due to the united-atom representation adopted for the aliphatic groups and to the implicit treatment of electronic polarization effects. The results for the hetero-polyfunctional molecules also show reasonable agreement with experiment in terms of the monitored properties.

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.

Simultaneous parametrization of torsional and third-neighbor interaction terms in force-field development: The LLS-SC algorithm

The calibration of torsional interaction terms by fitting relative gas-phase conformational energies against their quantum-mechanical values is a common procedure in force-field development. However, much less attention has been paid to the optimization of third-neighbor nonbonded interaction parameters, despite their strong coupling with the torsions. This article introduces an algorithm termed LLS-SC, aimed at simultaneously parametrizing torsional and third-neighbor interaction terms based on relative conformational energies. It relies on a self-consistent (SC) procedure where each iteration involves a linear least-squares (LLS) regression followed by a geometry optimization of the reference structures. As a proof-of-principle, this method is applied to obtain torsional and third-neighbor interaction parameters for aliphatic chains in the context of the GROMOS 53A6 united-atom force field. The optimized parameter set is compared to the original one, which has been fitted manually against thermodynamic properties for small linear alkanes. The LLS-SC implementation is freely available under http://github.com/mssm-labmmol/profiler.

Machine Learning of First-Principles Force-Fields for Alkane and Polyene Hydrocarbons

Machine learning (ML) interatomic potentials (ML-IAPs) are generated for alkane and polyene hydrocarbons using on-the-fly adaptive sampling and a sparse Gaussian process regression (SGPR) algorithm. The ML model is generated based on the PBE+D3 level of density functional theory (DFT) with molecular dynamics (MD) for small alkane and polyene molecules. Intermolecular interactions are also trained with clusters and condensed phases of small molecules. It shows excellent transferability to long alkanes and closely describes the ab inito potential energy surface for polyenes. Simulation of liquid ethane also shows reasonable agreement with experimental reports. This is a promising initiative toward a universal ab initio quality force-field for hydrocarbons and organic molecules.

Systematic optimization of a fragment-based force field against experimental pure-liquid properties considering large compound families: application to oxygen and nitrogen compounds

The CombiFF approach is a workflow for the automated refinement of force-field parameters against experimental condensed-phase data, considering entire classes of organic molecules constructed using a fragment library via combinatorial isomer enumeration. One peculiarity of this approach is that it relies on an electronegativity-equalization scheme to account for induction effects within molecules, with values of the atomic hardness and electronegativity as electrostatic parameters, rather than the partial charges themselves. In a previous article [M. P. Oliveira, M. Andrey, S. R. Rieder, L. Kern, D. F. Hahn, S. Riniker, B. A. C. Horta and P. H. Hünenberger, J. Chem. Theory. Comput. 2020, 16, 7525], CombiFF was introduced and applied to calibrate a GROMOS-compatible united-atom force field for the saturated acyclic (halo-)alkane family. Here, this scheme is employed for the construction of a corresponding force field for saturated acyclic compounds encompassing eight common chemical functional groups involving oxygen and/or nitrogen atoms, namely: ether, aldehyde, ketone, ester, alcohol, carboxylic acid, amine, and amide. Monofunctional as well as homo-polyfunctional compounds are considered. A total of 1712 experimental liquid densities ρliq and vaporization enthalpies ΔHvap concerning 1175 molecules are used for the calibration (339 molecules) and validation (836 molecules) of the 102 non-bonded interaction parameters of the force field. Using initial parameter values based on the GROMOS 2016H66 parameter set, convergence is reached after five iterations. Given access to one processor per simulated system, this operation only requires a few days of wall-clock computing time. After optimization, the root-mean-square deviations from experiment are 29.9 (22.4) kg m-3 for ρliq and 4.1 (5.5) kJ mol-1 for ΔHvap for the calibration (validation) set. Thus, a very good level of agreement with experiment is achieved in terms of these two properties, although the errors are inhomogeneously distributed across the different chemical functional groups.

Evaluation of nine condensed-phase force fields of the GROMOS, CHARMM, OPLS, AMBER, and OpenFF families against experimental cross-solvation free energies

Experimental solvation free energies are nowadays commonly included as target properties in the validation of condensed-phase force fields, sometimes even in their calibration. In a previous article [Kashefolgheta et al., J. Chem. Theory. Comput., 2020, 16, 7556-7580], we showed how the involved comparison between experimental and simulation results could be made more systematic by considering a full matrix of cross-solvation free energies . For a set of N molecules that are all in the liquid state under ambient conditions, such a matrix encompasses N×N entries for considering each of the N molecules either as solute (A) or as solvent (B). In the quoted study, a cross-solvation matrix of 25 × 25 experimental value was introduced, considering 25 small molecules representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This experimental data was used to compare the relative accuracies of four popular condensed-phase force fields, namely GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In the present work, the comparison is extended to five additional force fields, namely GROMOS-54A7, GROMOS-ATB, OPLS-LBCC, AMBER-GAFF2, and OpenFF. Considering these nine force fields, the correlation coefficients between experimental values and simulation results range from 0.76 to 0.88, the root-mean-square errors (RMSEs) from 2.9 to 4.8 kJ mol-1, and average errors (AVEEs) from -1.5 to +1.0 kJ mol-1. In terms of RMSEs, GROMOS-2016H66 and OPLS-AA present the best accuracy (2.9 kJ mol-1), followed by OPLS-LBCC, AMBER-GAFF2, AMBER-GAFF, and OpenFF (3.3 to 3.6 kJ mol-1), and then by GROMOS-54A7, CHARM-CGenFF, and GROMOS-ATB (4.0 to 4.8 kJ mol-1). These differences are statistically significant but not very pronounced, and are distributed rather heterogeneously over the set of compounds within the different force fields.

Drug-Loading Capacity of PAMAM Dendrimers Encapsulating Quercetin Molecules: A Molecular Dynamics Study with the 2016H66 Force Field

The complexation of quercetin molecules with poly(amidoamine) (PAMAM) dendrimers of generation 0-3 was studied by molecular dynamics simulations. Three main points were addressed: (i) the effect of starting from different initial structures; (ii) the performance of the 2016H66 force field (recently validated in the context of dendrimer simulations) in predicting the experimental drug(quercetin)-loading capacity of PAMAM dendrimers; and (iii) the stability of quercetin-PAMAM complexes and their interactions. Initial structures generated by different restraint protocols led to faster convergence compared to initial structures generated by randomly placing the drug molecules in the simulation box. The simulations yielded meta-stable complexes where the loading numbers have converged to average values and were compared to experimentally obtained values. Once the first meta-stable state was reached, the drug-dendrimer complexes did not deviate significantly throughout the simulation. They were characterized in terms of structural properties, such as the radius of gyration and radial distribution functions. The results suggest that quercetin molecules interact mostly with the internal dendrimer monomers rather than to their surface.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

The effect of different cutoff schemes in molecular simulations of proteins

Molecular simulations of nanoscale systems invariably involve assumptions and approximations to describe the electrostatic interactions, which are long-ranged in nature. One approach is the use of cutoff schemes with a reaction-field contribution to account for the medium outside the cutoff scheme. Recent reports show that macroscopic properties may depend on the exact choice of cutoff schemes in modern day simulations. In this work, a systematic analysis of the effects of different cutoff schemes was performed using a set of 52 proteins. We find no statistically significant differences between using a twin-range or a single-range cutoff scheme. Applying the cutoff based on charge groups or based on atomic positions, does lead to significant differences, which is traced to the cutoff noise for energies and forces. While group-based cutoff schemes show increased cutoff noise in the potential energy, applying an atomistic cutoff leads to artificial structure in the solvent at the cutoff distance. Carefully setting the temperature control, or using an atomistic cutoff for the solute and a group-based cutoff for the solvent significantly reduces the effects of the cutoff noise, without introducing structure in the solvent. This study aims to deepen the understanding of the implications different cutoffs have on molecular dynamics simulations.

The Effect of Using a Twin-Range Cutoff Scheme for Nonbonded Interactions: Implications for Force-Field Parametrization?

Recently, concerns have been voiced regarding the validity of the GROMOS force fields, being parametrized using a twin-range cutoff scheme, in which longer ranged nonbonded forces and energies are updated less frequently than shorter ranged ones. Here we demonstrate that the influence of such a scheme on the thermodynamic, structural, and dynamic properties used in the parametrization of the GROMOS force fields is minor. We find root-mean-square differences of maximally 0.5 kJ/mol for the solvation free energy and heat of vaporization and of maximally 0.4% for the density. Slightly larger differences are observed when switching from a group-based to an atom-based cutoff scheme. In cases where the twin-range cutoff scheme does result in minor differences compared to a single-range cutoff these are well within the deviation from the experimentally measured values.

Predicting the Miscibility and Rigidity of Poly(lactic-co-glycolic acid)/Polyethylene Glycol Blends via Molecular Dynamics Simulations

The addition of polyethylene glycol (PEG) chains to poly(lactic-co-glycolic acid) (PLGA) matrices is extensively used to modulate the biodegradation, drug loading and release, mechanical properties, and chemical stability of the original system. Multiple parameters, including the molecular weight, relative concentration, polarity, and solubility, affect the physicochemical properties of the polymer blend. Here, molecular dynamics simulations with the united-atom 2016H66 force field are used to model the behavior of PLGA and PEG chains and thus predict the overall physicochemical features of the resulting blend. First, the model accuracy is validated against fundamental properties of pure PLGA and PEG samples. In agreement with previous experimental and theoretical observations, the PLGA solubility results to be higher in acetonitrile than in water, with Flory parameters ν_ACN = 0.63 ± 0.01 and ν_W = 0.21 ± 0.02, and the Young’s modulus of PLGA and PEG equal to Y = 2.0 ± 0.43 and 0.32 ± 0.34 GPa, respectively. Next, four PEG/PLGA blending regimes are identified by varying the relative concentrations and molecular weights of the individual polymers. The computational results demonstrate that at low PEG concentrations (<8% w/w), homogeneous blends are generated for both low and high PEG molecular weights. In contrast, at comparable PEG and PLGA concentrations (∼50% w/w), short PEG chains are only partially miscible whereas long PEG chains segregate within the PLGA matrix. This behavior has been confirmed experimentally via differential scanning calorimetry and is in agreement with previous observations. Finally, the computed Young’s modulus of PLGA/PEG blends is observed to decrease with the PEG content returning the lowest values for the partial and fully segregated regimens (Y ≈ 1.3 GPa). This work proposes a computational scheme for predicting the physicochemical properties of PLGA/PEG blends paving the way toward the rational design of polymer mixtures for biomedical applications.

Structural and molecular bases of angiotensin-converting enzyme inhibition by bovine casein-derived peptides: an in silico molecular dynamics approach

The angiotensin-converting enzyme (ACE) plays a key role in blood pressure regulation process, and its inhibition is one of the main drug targets for the treatment of hypertension. Though various peptides from milk proteins are well-known for their ACE-inhibitory capacity, research devoted to understand the molecular bases of such property remain scarce, specifically for such peptides. Therefore, in this work, computational molecular docking and molecular dynamics calculations were performed to enlighten the intermolecular interactions involved in ACE inhibition by six different casein-derived peptides (FFVAPFPEVFGK, FALPQYLK, ALNEINQFYQK, YLGYLEQLLR, HQGLPQEVLNENLLR and NAVPITPTLNR). Two top ranked docking poses for each peptide (one with N- and the other C-terminal peptide extremity oriented towards the ACE active site) were selected for dynamic simulations (50 ns; GROMOS53A6 force field), and the results were correlated to in vitro ACE inhibition capacity. Two molecular features appeared to be essential for peptides to present high ACE inhibition capacity in vitro: i) to interact with the S1 active site residues (Ala354, Glu384, and Tyr523) by hydrogen bonds; ii) to interact with Zn²⁺ coordinated residues (His383, His387, and Glu411) by short-lenght hydrogen bonds, as observed in the cases of ALNEINQFYQK (IACE = 80.7%), NAVPITPTLNR (IACE = 80.7%), and FALPQYLK (IACE = 79.0%). Regardless of the temporal stability of these strong interactions, they promoted some disruption of Zn²⁺ tetrahedral coordination during the molecular dynamics trajectories, and were pointed as the main reason for the greatest ACE inhibition by these peptides. On the other hand, peptides with intermediate inhibition capacity (50% < I_ACE < 45%) interacted mainly by weaker interactions (e.g.: electrostatic and hydrophobic) with the Zn²⁺ coordinated residues, and were not able to change significantly its tetrahedral coordination structure. These findings may: i) assist the discrimination in silico of "good" and "bad" ACE-inhibitory peptides from other food sources, and/or ii) aid in designing de novo new molecules with ACE-inhibitory capacity. Communicated by Ramaswamy Sarma.

The Lazy Life of Lipid-Linked Oligosaccharides in All Life Domains

Lipid-linked oligosaccharides (LLOs) play an important role in the N-glycosylation pathway as the donor substrate of oligosaccharyltransferases (OSTs), which are responsible for the en bloc transfer of glycan chains onto a nascent polypeptide. The lipid component of LLO in both eukarya and archaea consists of a dolichol, and an undecaprenol in prokarya, whereas the number of isoprene units may change between species. Given the potential relevance of LLOs and their related enzymes to diverse biotechnological applications, obtaining reliable LLO models from distinct domains of life could support further studies on complex formation and their processing by OSTs, as well as protein engineering on such systems. In this work, molecular modeling techniques, such as quantum mechanics calculations, molecular dynamics simulations, and metadynamics were employed to study eukaryotic (Glc₃-Man₉-GlcNAc₂-PP-Dolichol), bacterial (Glc₁-GalNAc₅-Bac₁-PP-Undecaprenol), and archaeal (Glc₁-Man1-Gal₁-Man1-Glc₁-Gal₁-Glc₁-P-Dolichol) LLOs in membrane bilayers. Microsecond molecular dynamics simulations and metadynamics calculations of LLOs revealed that glycan chains are more prone to interact with the membrane lipid head groups, while the PP linkages are positioned at the lipid phosphate head groups level. The dynamics of isoprenoid chains embedded within the bilayer are described, and membrane dynamics and related properties are also investigated. Overall, there are similarities regarding the structure and dynamics of the eukaryotic, the bacterial, and the archaeal LLOs in bilayers, which can support the comprehension of their association with OSTs. These data may support future studies on the transferring mechanism of the oligosaccharide chain to an acceptor protein.

Reaction-field electrostatics in molecular dynamics simulations: development of a conservative scheme compatible with an atomic cutoff

Shifting and switching schemes are developed to enable strict energy conservation in molecular dynamics simulations relying on reaction-field electrostatic (as well as Lennard-Jones) interactions with an atom-based cutoff truncation.