Reparametrization of Protein Force Field Nonbonded Interactions Guided by Osmotic Coefficient Measurements from Molecular Dynamics Simulations

How arginine inhibits substrate-binding domain 2 elucidated using molecular dynamics simulations

The substrate-binding domain 2 (SBD2) is an important part of the bacterial glutamine (GLN) transporter and mediates binding and delivery of GLN to the transporter translocation subunit. The SBD2 consists of two domains, D1 and D2, that bind GLN in the space between domains in a closed structure. In the absence of ligand, the SBD2 adopts an open conformation with larger space between domains. The GLN binding and closing are essential for the subsequent transport into the cell. Arginine (ARG) can also bind to SBD2 but does not induce closing and inhibits GLN transport. We use atomistic molecular dynamics (MD) simulations in explicit solvent to study ARG binding in the presence of the open SBD2 structure and observed reversible binding to the native GLN binding site with similar contacts but no transition to a closed SBD2 state. Absolute binding free energy simulations predict a considerable binding affinity of ARG and GLN to the binding site on the D1 domain. Free energy simulations to induce subsequent closing revealed a strong free energy penalty in case of ARG binding in contrast to GLN binding that favors the closed SBD2 state but still retains a free energy barrier for closing. The simulations allowed the identification of the molecular origin of the closing penalty in case of bound ARG and suggested a mutation of lysine at position 373 to alanine that strongly reduced the penalty and allowed closing even in the presence of bound ARG. The study offers an explanation of the molecular mechanism of how ARG competitively inhibits GLN from binding to SBD2 and from triggering the transition to a closed conformation. The proposed Lys373Ala mutation shows promise as a potential tool to validate whether a conformational mismatch between open SBD2 and the translocator is responsible for preventing ARG uptake to the cell.

Improved Protein Model in SPICA Force Field

The previous version of the SPICA coarse-grained (CG) force field (FF) protein model focused primarily on membrane proteins and successfully reproduced the dimerization free energies of several transmembrane helices and the stable structures of various membrane protein assemblies. However, that model had limited accuracy when applied to other proteins, such as intrinsically disordered proteins (IDPs) and peripheral proteins, because the dimensions of the IDPs in an aqueous solution were too compact, and protein binding on the lipid membrane surface was overstabilized. To improve the accuracy of the SPICA FF model for the simulation of such systems, in this study, we introduce protein secondary structure-dependent nonbonded interaction parameters to the backbone segments and reoptimize almost all nonbonded parameters for amino acids. The improved FF proposed here successfully reproduces the radii of gyration of various IDPs, the binding sensitivity of several peripheral membrane proteins, and the dimerization free energies of several transmembrane helices. The new model also shows improved agreement with experiments on the free energy of peptide association in water. In addition, an extensive library of nonbonded interactions between proteins and lipids, including various glycerophospholipids, sphingolipids, and cholesterol, allows the study of specific interactions between lipids and peripheral and transmembrane proteins. Hence, the new SPICA FF (version 2) proposed herein is applicable with high accuracy for simulating a wide range of protein systems.

Structure, energetics and dynamics in crowded amino acid solutions: a molecular dynamics study

A comprehensive understanding of crowding effects on biomolecular processes necessitates investigating the bulk thermodynamic and kinetic properties of the solutions with an accurate molecular representation of the crowded milieu. Recent studies have reparameterized the non-bonded dispersion interaction of solutes to precisely model intermolecular interactions, which would circumvent artificial aggregation as shown by the original force-fields. However, the performance of this reparameterization is yet to be assessed for concentrated crowded solutions in terms of investigating the hydration shell structure, energetics and dynamics. In this study, we perform molecular dynamics simulations of crowded aqueous solutions of five zwitterionic neutral amino acids (Gly, Ala, Thr, Pro, and Ser), mimicking the molecular crowding environment, using a modified AMBER ff99SB-ILDN force-field. We systematically examine and show that the reproducibility of the osmotic coefficients, density, viscosity and self-diffusivity of amino acids improves using the modified force-field in crowded concentrations. The modified force-field also improves the structuring of the solute solvation shells, solute interaction energy and convergence of tails of radial distribution functions, indicating reduction in the artificial aggregation. Our results also indicate that the hydrogen bonding network of water weakens and water molecules anomalously diffuse at small time scales in the crowded solutions. These results underscore the significance of examining the solution properties and anomalous hydration behaviour of water in crowded solutions, which have implications in shaping the structure and dynamics of biomolecules. The findings also illustrate the improvement in predicting bulk solution properties using the modified force-field, thereby providing an approach towards accurate modeling of crowded molecular solutions.

Cumulative Millisecond-Long Sampling for a Comprehensive Energetic Evaluation of Aqueous Ionic Liquid Effects on Amino Acid Interactions

The interactions of amino acid side-chains confer diverse energetic contributions and physical properties to a protein's stability and function. Various computational tools estimate the effect of changing a given amino acid on the protein's stability based on parametrized (free) energy functions. When parametrized for the prediction of protein stability in water, such energy functions can lead to suboptimal results for other solvents, such as ionic liquids (IL), aqueous ionic liquids (aIL), or salt solutions. However, to our knowledge, no comprehensive data are available describing the energetic effects of aIL on intramolecular protein interactions. Here, we present the most comprehensive set of potential of mean force (PMF) profiles of pairwise protein-residue interactions to date, covering 50 relevant interactions in water, the two biotechnologically relevant aIL [BMIM/Cl] and [BMIM/TfO], and [Na/Cl]. These results are based on a cumulated simulation time of >1 ms. aIL and salt ions can weaken, but also strengthen, specific residue interactions by more than 3 kcal mol^-1, depending on the residue pair, residue-residue configuration, participating ions, and concentration, necessitating considering such interactions specifically. These changes originate from a complex interplay of competitive or cooperative noncovalent ion-residue interactions, changes in solvent structural dynamics, or unspecific charge screening effects and occur at the contact distance but also at larger, solvent-separated distances. This data provide explanations at the atomistic and energetic levels for complex IL effects on protein stability and should help improve the prediction accuracies of computational tools that estimate protein stability based on (free) energy functions.

High throughput data-based, toxicity pathway-oriented development of a quantitative adverse outcome pathway network linking AHR activation to lung damages

The quantitative adverse outcome pathway (qAOP) is proposed to inform dose-responses at multiple biological levels for the purpose of toxicity prediction. So far, qAOP models concerning human health are scarce. Previously, we proposed 5 key molecular pathways that led aryl hydrogen receptor (AHR) activation to lung damages. The present study assembled an AOP network based on the gene expression signatures of these toxicity pathways, and validated the network using publicly available high throughput data combined with machine learning models. In addition, the AOP network was quantitatively evaluated with omics approaches and bioassays, using 16HBE-CYP1A1 cells exposed to benzo(a)pyrene (BaP), a prototypical AHR activator. Benchmark dose (BMD) analysis of transcriptomics revealed that AHR gene held the lowest BMD value, whereas AHR pathway held the lowest point of departure (PoD) compared to the other 4 pathways. Targeted bioassays were further performed to quantitatively understand the cellular responses, including ROS generation, DNA damage, interleukin-6 production, and extracellular matrix increase marked by collagen expression. Eventually, response-response relationships were plotted using nonlinear model fitting. The present study developed a highly reliable AOP model concerning human health, and validated as well as quantitatively evaluated it, and such a method is likely to be adoptable for risk assessment.

Rational Design of Nonbonded Point Charge Models for Monovalent Ions with Lennard-Jones 12-6 Potential

Ions are of central importance in nature, and a variety of potential models was proposed to model ions in different phases for an in-depth exploration of ion-related systems. Here, we developed point charge models of 14 monovalent ions with the traditional 12-6 Lennard-Jones (LJ) potential for use in conjunction with 11 water models of TIP3P, OPC3, SPC/E, SPC/E_b, TIP3P-FB, a99SB-disp, TIP4P-Ew, OPC, TIP4P/2005, TIP4P-D, and TIP4P-FB. The designed models reproduced the real hydration free energy (HFE) of ions and the ion-oxygen distance (IOD) in the first hydration shell accurately and simultaneously, a performance similar to the previously reported 12-6-4 LJ-type ion models (12-6 LJ plus an attractive C₄ term for cations or a repulsive one for anions). This work, along with our previous work on di-, tri-, and tetravalent metal cations (J. Chem. Inf. Model. 2021, 61, 4031-4044; J. Chem. Inf. Model. 2021, 61, 4613-4629), demonstrates the feasibility of the simple 12-6 LJ potential in ion modeling. In order for the 12-6 LJ potential to reproduce both the HFE and IOD, the LJ R parameters need to be close to Shannon's ionic radii for the highly charged cations and to the Stokes's van der Waals (vdW) radii for the monovalent ions. With an additional C₄ term, the R parameters of 12-6-4 LJ ion models agree well with the Stokes's vdW radii and have a more physical meaning. It appears that the C₄ term can be merged into the 12-6 LJ potential by a rational tuning of R and the LJ well depth. Simulations of the osmotic coefficients of alkali chloride solutions and the properties of gaseous and solid alkali halides indicate the necessity of further optimizing ion-ion interactions via, for instance, targeting more properties or using a more physical (polarizable) model.

The automated optimisation of a coarse-grained force field using free energy data

Atomistic models provide a detailed representation of molecular systems, but are sometimes inadequate for simulations of large systems over long timescales. Coarse-grained models enable accelerated simulations by reducing the number of degrees of freedom, at the cost of reduced accuracy. New optimisation processes to parameterise these models could improve their quality and range of applicability. We present an automated approach for the optimisation of coarse-grained force fields, by reproducing free energy data derived from atomistic molecular simulations. To illustrate the approach, we implemented hydration free energy gradients as a new target for force field optimisation in ForceBalance and applied it successfully to optimise the un-charged side-chains and the protein backbone in the SIRAH protein coarse-grain force field. The optimised parameters closely reproduced hydration free energies of atomistic models and gave improved agreement with experiment.

Three-Dimensional Chiral Supramolecular Microenvironment Strategy for Enhanced Biocatalysis

How the three-dimensional (3D) chiral environment affects the biocatalysis remains an important issue, thereby inspiring the development of a microenvironment that highly mimics the natural features of enzyme to guarantee enhanced biocatalysis. In this study, two gelators bearing d/l-phenylalanine as chiral centers are designed to construct the 3D chiral catalytic microenvironment for enhancing the biocatalysis of lipase. Such a microenvironment is programmed through chiral transmission of chirality from molecular chirality to achiral polymers. It shows that the chirality of the microenvironment evidently influences the catalytic efficiency of immobilized lipase inside the system, and the 3D microenvironment constructed by right-handed helical nanostructures can enhance the catalytic activity of lipase inside as high as 10-fold for catalyzing 4-nitrophenyl palmitate (NPP) to 4-nitrophenol (NP) and 1.4-fold for catalyzing lipids to triglycerides (TGs) in 3T3-L1 cells than that of the achiral microenvironment. Moreover, the 3D chiral microenvironment has the merits of good catalytic efficiency, high storage stability, and efficient recyclability. This strategy of designing a 3D chiral microenvironment suitable for biocatalysis will overcome the present limitations of enzymatic immobilization in traditional materials and enhance the understanding of biocatalysis.

Rational Design of Nonbonded Point Charge Models for Highly Charged Metal Cations with Lennard-Jones 12-6 Potential

Here, we developed nonbonded point charge models using a simple Lennard-Jones (LJ) 12-6 potential for highly charged metal cations (18 trivalent and 6 tetravalent ions) for use with 11 water models of TIP3P, OPC3, SPC/E, SPC/E_b, TIP3P-FB, a99SB-disp, TIP4P-Ew, OPC, TIP4P/2005, TIP4P-D, and TIP4P-FB. The designed models simultaneously reproduce the hydration free energy (HFE) and ion-oxygen distance (IOD) in the first hydration shell with an error within 1 kcal/mol and 0.01 Å on average, respectively, and yield reasonable coordination numbers for most cations. Such performance is equivalent to the previously reported point charge models using a more complex 12-6-4 LJ-type potential, while the LJ R parameters of our models are much close to Shannon's revised effective ion radii than that of the 12-6-4 models. Our designed models overestimate the diffusion constants of several trivalent ions by 5-68%. The performance in predicting osmotic coefficients of trivalent chlorides in aqueous solution depends on the salt type. A calibration of cation-anion interacting LJ parameters reproduces the experimental osmotic coefficients of an AlCl₃ solution at 0.2-3.0 mol/L. The effectiveness of our new models is further demonstrated by simulating a metalloprotein system with four force field/water combinations. This work facilitates accurate modeling of metal-containing systems by a variety of force fields and water models in aqueous solution.

NEDD8 Deamidation Inhibits Cullin RING Ligase Dynamics

Cullin-RING ligases (CRLs) are a significant subset of Ubiquitin E3 ligases that regulate multiple cellular substrates involved in innate immunity, cytoskeleton modeling, and cell cycle. The glutamine deamidase Cycle inhibitory factor (Cif) from enteric bacteria inactivates CRLs to modulate these processes in the host cell. The covalent attachment of a Ubiquitin-like protein NEDD8 catalytically activates CRLs by driving conformational changes in the Cullin C-terminal domain (CTD). NEDDylation results in a shift from a compact to an open CTD conformation through non-covalent interactions between NEDD8 and the WHB subdomain of CTD, eliminating the latter’s inhibitory interactions with the RING E3 ligase-Rbx1/2. It is unknown whether the non-covalent interactions are sufficient to stabilize Cullin CTD’s catalytic conformation. We studied the dynamics of Cullin-CTD in the presence and absence of NEDD8 using atomistic molecular dynamics (MD) simulations. We uncovered that NEDD8 engages in non-covalent interactions with 4HB/αβ subdomains in Cullin-CTD to promote open conformations. Cif deamidates glutamine 40 in NEDD8 to inhibit the conformational change in CRLs by an unknown mechanism. We investigated the effect of glutamine deamidation on NEDD8 and its interaction with the WHB subdomain post-NEDDylation using MD simulations and NMR spectroscopy. Our results suggest that deamidation creates a new intramolecular salt bridge in NEDD8 to destabilize the NEDD8/WHB complex and reduce CRL activity.

Force Field Benchmark of Amino Acids. 3. Hydration with Scaled Lennard-Jones Interactions

Classical protein force fields were reported with too weak protein-water interactions relative to protein-protein interactions, leading to more compact structures and artificial protein aggregation. Here we investigated the impacts of scaled Lennard-Jones (LJ) interactions on the hydration of amino acids and the simulation of folded and intrinsically disordered proteins (IDPs). The obtained optimal scaling parameters reproduce accurately hydration free energies of neutral amino acid side chain analogues and do not affect the compactness and structural stability of folded proteins significantly. The scaling leads to less compact IDPs and varies from case to case. Strengthening the interactions between protein and water oxygen or hydrogen atoms by increasing the interacting LJ well depth (ε) appears more effective than weakening protein-protein interactions by reducing the interacting dispersion coefficients (C₆). We demonstrate that weakening water-water interactions is a solution as well to obtaining more favorable protein-water interactions in an indirect way, although modern force fields like Amber ff19SB and a99SB-disp tend to use water models with strong water-water interactions. This is likely a compromise between strong protein-protein interactions and strong water-water interactions. Independent optimization of protein force fields and water models is therefore needed to make both interactions more close to reality, leading to good accuracy without bias or scaling.

Developing and Assessing Nonbonded Dummy Models of Magnesium Ion with Different Hydration Free Energy References

A large diversity in the targeted hydration free energies (HFEs) during model parameterization of metal ions was reported in the literature with a difference by dozens of kcal/mol. Here, we developed a series of nonbonded dummy models of the Mg²⁺ ion targeting different HFE references in TIP3P water, followed by assessments of the designed models in the simulations of MgCl₂ solution and biological systems. Together with the comparison of existing models, we conclude that the difference in the targeted HFEs has a limited influence on the model performance, while the usability of these models differs from case to case. The feasibility of reproducing more properties of Mg²⁺ such as diffusion constants and water exchange rates using a nonbonded dummy model is demonstrated. Underestimated activity derivative and osmotic coefficient of MgCl₂ solutions in high concentration reveal a necessity for further optimization of ion-pair interactions. The developed dummy models are applicable to metal coordination with Asp, Glu, and His residues in metalloenzymes, and the performance in predicting monodentate or bidentate binding modes of Asp/Glu residues depends on the complexity of metal centers and the choice of protein force fields. When both the binding modes coexist, the nonbonded dummy models outperform point charge models, probably in need of considering polarization of metal-binding residues by, for instance, charge calibration in classical force fields. This work is valuable for the use and further development of magnesium ion models for simulations of metal-containing systems with good accuracy.

Kirkwood-Buff-Derived Force Field for Peptides and Proteins: Philosophy and Development of KBFF20

A new classical nonpolarizable force field, KBFF20, for the simulation of peptides and proteins is presented. The force field relies heavily on the use of Kirkwood-Buff theory to provide a comparison of simulated and experimental Kirkwood-Buff integrals for solutes containing the functional groups common in proteins, thus ensuring intermolecular interactions that provide a good balance between the peptide-peptide, peptide-solvent, and solvent-solvent distributions observed in solution mixtures. In this way, it differs significantly from other biomolecular force fields. Further development and testing of the intermolecular potentials are presented here. Subsequently, rotational potentials for the ϕ/ψ and χ dihedral degrees of freedom are obtained by analysis of the Protein Data Bank, followed by small modifications to provide a reasonable balance between simulated and observed α and β percentages for small peptides. This, the first of two articles, describes in detail the philosophy and development behind KBFF20.

Improved Parameterization of Protein-DNA Interactions for Molecular Dynamics Simulations of PCNA Diffusion on DNA

As the field of molecular dynamics simulation utilizing the force fields is moving toward more complex systems, the accuracy of intermolecular interactions has become a central issue of the field. Here, we quantitatively evaluate the accuracy of the protein-DNA interactions in AMBER and CHARMM force fields by comparing experimental and simulated diffusion coefficients of proliferating cell nuclear antigen. We find that both force fields underestimate diffusion coefficients by at least an order of magnitude because the interactions between basic amino acids and DNA phosphate groups are too attractive. Then, we propose Lennard-Jones parameters optimized using the experimental osmotic pressure data of model chemicals, by using which one can reproduce the experimental diffusion coefficients. Newly optimized parameters will have a broad impact on general protein-DNA interactions.

Coarse-Grained Molecular Model for the Glycosylphosphatidylinositol Anchor with and without Protein

Glycosylphosphatidylinositol (GPI) anchors are a unique class of complex glycolipids that anchor a great variety of proteins to the extracellular leaflet of plasma membranes of eukaryotic cells. These anchors can exist either with or without an attached protein called GPI-anchored protein (GPI-AP) both in vitro and in vivo. Although GPIs are known to participate in a broad range of cellular functions, it is to a large extent unknown how these are related to GPI structure and composition. Their conformational flexibility and microheterogeneity make it difficult to study them experimentally. Simplified atomistic models are amenable to all-atom computer simulations in small lipid bilayer patches but not suitable for studying their partitioning and trafficking in complex and heterogeneous membranes. Here, we present a coarse-grained model of the GPI anchor constructed with a modified version of the MARTINI force field that is suited for modeling carbohydrates, proteins, and lipids in an aqueous environment using MARTINI’s polarizable water. The nonbonded interactions for sugars were reparametrized by calculating their partitioning free energies between polar and apolar phases. In addition, sugar–sugar interactions were optimized by adjusting the second virial coefficients of osmotic pressures for solutions of glucose, sucrose, and trehalose to match with experimental data. With respect to the conformational dynamics of GPI-anchored green fluorescent protein, the accessible time scales are now at least an order of magnitude larger than for the all-atom system. This is particularly important for fine-tuning the mutual interactions of lipids, carbohydrates, and amino acids when comparing to experimental results. We discuss the prospective use of the coarse-grained GPI model for studying protein-sorting and trafficking in membrane models.

Development of a Force Field for the Simulation of Single-Chain Proteins and Protein-Protein Complexes

The accuracy of atomistic physics-based force fields for the simulation of biological macromolecules has typically been benchmarked experimentally using biophysical data from simple, often single-chain systems. In the case of proteins, the careful refinement of force field parameters associated with torsion-angle potentials and the use of improved water models have enabled a great deal of progress toward the highly accurate simulation of such monomeric systems in both folded and, more recently, disordered states. In living organisms, however, proteins constantly interact with other macromolecules, such as proteins and nucleic acids, and these interactions are often essential for proper biological function. Here, we show that state-of-the-art force fields tuned to provide an accurate description of both ordered and disordered proteins can be limited in their ability to accurately describe protein-protein complexes. This observation prompted us to perform an extensive reparameterization of one variant of the Amber protein force field. Our objective involved refitting not only the parameters associated with torsion-angle potentials but also the parameters used to model nonbonded interactions, the specification of which is expected to be central to the accurate description of multicomponent systems. The resulting force field, which we call DES-Amber, allows for more accurate simulations of protein-protein complexes, while still providing a state-of-the-art description of both ordered and disordered single-chain proteins. Despite the improvements, calculated protein-protein association free energies still appear to deviate substantially from experiment, a result suggesting that more fundamental changes to the force field, such as the explicit treatment of polarization effects, may simultaneously further improve the modeling of single-chain proteins and protein-protein complexes.

Improving the Performance of the Amber RNA Force Field by Tuning the Hydrogen-Bonding Interactions

Molecular dynamics (MD) simulations became a leading tool for investigation of structural dynamics of nucleic acids. Despite recent efforts to improve the empirical potentials (force fields, ffs), RNA ffs have persisting deficiencies, which hamper their utilization in quantitatively accurate simulations. Previous studies have shown that at least two salient problems contribute to difficulties in the description of free-energy landscapes of small RNA motifs: (i) excessive stabilization of the unfolded single-stranded RNA ensemble by intramolecular base-phosphate and sugar-phosphate interactions and (ii) destabilization of the native folded state by underestimation of stability of base pairing. Here, we introduce a general ff term (gHBfix) that can selectively fine-tune nonbonding interaction terms in RNA ffs, in particular, the H bonds. The gHBfix potential affects the pairwise interactions between all possible pairs of the specific atom types, while all other interactions remain intact; i.e., it is not a structure-based model. In order to probe the ability of the gHBfix potential to refine the ff nonbonded terms, we performed an extensive set of folding simulations of RNA tetranucleotides and tetraloops. On the basis of these data, we propose particular gHBfix parameters to modify the AMBER RNA ff. The suggested parametrization significantly improves the agreement between experimental data and the simulation conformational ensembles, although our current ff version still remains far from being flawless. While attempts to tune the RNA ffs by conventional reparametrizations of dihedral potentials or nonbonded terms can lead to major undesired side effects, as we demonstrate for some recently published ffs, gHBfix has a clear promising potential to improve the ff performance while avoiding introduction of major new imbalances.

On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations

Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ_16-22 peptide and two of its mutants: Aβ_16-22(F19V,F20V), which does not form fibrils, and Aβ_16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.

New tricks for old dogs: improving the accuracy of biomolecular force fields by pair-specific corrections to non-bonded interactions

In contrast to ordinary polymers, the vast majority of biological macromolecules adopt highly ordered three-dimensional structures that define their functions. The key to folding of a biopolymer into a unique 3D structure or to an assembly of several biopolymers into a functional unit is a delicate balance between the attractive and repulsive forces that also makes such self-assembly reversible under physiological conditions. The all-atom molecular dynamics (MD) method has emerged as a powerful tool for studies of individual biomolecules and their functional assemblies, encompassing systems of ever increasing complexity. However, advances in parallel computing technology have outpaced the development of the underlying theoretical models-the molecular force fields, pushing the MD method into an untested territory. Recent tests of the MD method have found the most commonly used molecular force fields to be out of balance, overestimating attractive interactions between charged and hydrophobic groups, which can promote artificial aggregation in MD simulations of multi-component protein, nucleic acid, and lipid systems. One route towards improving the force fields is through the NBFIX corrections method, in which the intermolecular forces are calibrated against experimentally measured quantities such as osmotic pressure by making atom pair-specific adjustments to the non-bonded interactions. In this article, we review development of the NBFIX (Non-Bonded FIX) corrections to the AMBER and CHARMM force fields and discuss their implications for MD simulations of electrolyte solutions, dense DNA systems, Holliday junctions, protein folding, and lipid bilayer membranes.

Efficient Osmotic Pressure Calculations Using Coarse-Grained Molecular Simulations

Osmotic pressure data is increasingly used to parametrize all-atom simulation Force Fields (FFs), leading to large computational cost for larger molecules. Here, we show that the osmotic pressure can be calculated precisely using transferable coarse-grained FFs obtained from short atomistic simulations using an inhomogeneously regularized coarse-graining procedure. This is demonstrated for carbohydrates, where compared to the equivalent atomistic system, an increase of the computational efficiency by a factor of ≈500 is achieved.

Force field development and simulations of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) play important roles in many physiological processes such as signal transduction and transcriptional regulation. Computer simulations that are based on empirical force fields have been increasingly used to understand the biophysics of disordered proteins. In this review, we focus on recent improvement of protein force fields, including polarizable force fields, concerning their accuracy in modeling intrinsically disordered proteins. Some recent benchmarks and applications of these force fields are also overviewed.

Significantly Improved Protein Folding Thermodynamics Using a Dispersion-Corrected Water Model and a New Residue-Specific Force Field

An accurate potential energy model is crucial for biomolecular simulations. Despite many recent improvements of classical protein force fields, there are remaining key issues: much weaker temperature dependence of folding/unfolding equilibrium and overly collapsed unfolded or disordered states. For the latter problem, a new water model (TIP4P-D) has been proposed to correct the significantly underestimated water dispersion interactions. Here, using TIP4P-D, we reveal problems in current force fields through failures in folding model systems (a polyalanine peptide, Trp-cage, and the GB1 hairpin). By using residue-specific parameters to achieve better match between amino acid sequences and native structures and adding a small H-bond correction to partially compensate the missing many-body effects in α-helix formation, the new RSFF2+ force field with the TIP4P-D water model can excellently reproduce experimental melting curves of both α-helical and β-hairpin systems. The RSFF2+/TIP4P-D method also gives less collapsed unfolded structures and describes well folded proteins simultaneously.

Reparameterization of Solute-Solute Interactions for Amino Acid-Sugar Systems Using Isopiestic Osmotic Pressure Molecular Dynamics Simulations

AMBER/GLYCAM and CHARMM are popular force fields for simulations of amino acids and sugars. Here we report excessively attractive amino acid-sugar interactions in both force fields, and corrections to nonbonded interactions that match experimental osmotic pressures of mixed aqueous solutions of diglycine and sucrose. The modified parameters also improve the ΔGtrans of diglycine from water to aqueous sucrose and, with AMBERff99SB/GLYCAM06, eliminate a caging effect seen in previous simulations of the protein ubiquitin with glucose.