Coupled two-dimensional main-chain torsional potential for protein dynamics II: performance and validation.

Structure and dynamics are both critical to RNA’s vital functions in biology. Numerous techniques can elucidate the structural dynamics of RNA, but computational approaches based on experimental data arguably hold the promise of providing the most detail. In this Account, we highlight areas wherein molecular dynamics (MD) and quantum mechanical (QM) techniques are applied to RNA, particularly in relation to complementary experimental studies.We have expanded on atomic-resolution crystal structures of RNAs in functionally relevant states by applying explicit solvent MD simulations to explore their dynamics and conformational changes on the submicrosecond time scale. MD relies on simplified atomistic, pairwise additive interaction potentials (force fields). Because of limited sampling, due to the finite accessible simulation time scale and the approximated force field, high-quality starting structures are required.Despite their imperfection, we find that currently available force fields empower MD to provide meaningful and predictive information on RNA dynamics around a crystallographically defined energy minimum. The performance of force fields can be estimated by precise QM calculations on small model systems. Such calculations agree reasonably well with the Cornell et al. AMBER force field, particularly for stacking and hydrogen-bonding interactions. A final verification of any force field is accomplished by simulations of complex nucleic acid structures.The performance of the Cornell et al. AMBER force field generally corresponds well with and augments experimental data, but one notable exception could be the capping loops of double-helical stems. In addition, the performance of pairwise additive force fields is obviously unsatisfactory for inclusion of divalent cations, because their interactions lead to major polarization and charge-transfer effects neglected by the force field. Neglect of polarization also limits, albeit to a lesser extent, the description accuracy of other contributions, such as interactions with monovalent ions, conformational flexibility of the anionic sugar−phosphate backbone, hydrogen bonding, and solute polarization by solvent. Still, despite limitations, MD simulations are a valid tool for analyzing the structural dynamics of existing experimental structures. Careful analysis of MD simulations can identify problematic aspects of an experimental RNA structure, unveil structural characteristics masked by experimental constraints, reveal functionally significant stochastic fluctuations, evaluate the structural role of base ionization, and predict structurally and potentially functionally important details of the solvent behavior, including the presence of tightly bound water molecules. Moreover, combining classical MD simulations with QM calculations in hybrid QM/MM approaches helps in the assessment of the plausibility of chemical mechanisms of catalytic RNAs (ribozymes).In contrast, the reliable prediction of structure from sequence information is beyond the applicability of MD tools. The ultimate utility of computational studies in understanding RNA function thus requires that the results are neither blindly accepted nor flatly rejected, but rather considered in the context of all available experimental data, with great care given to assessing limitations through the available starting structures, force field approximations, and sampling limitations. The examples given in this Account showcase how the judicious use of basic MD simulations has already served as a powerful tool to help evaluate the role of structural dynamics in biological function of RNA.

Accurate characterization of porous materials is essential for understanding material properties and evaluating their performance for potential applications. In general, any methodology that entails developing an accurate classical force field is computationally expensive as it requires a large number of quantum mechanical nonempirical calculations. In order to expedite such calculations without sacrificing too much accuracy, we have developed a systematic procedure where, starting from an initial trial force field, accurate adsorption isotherms of porous materials can be obtained at low computational cost. Specifically, the procedure involves correcting single-point energy values sampled from the trial force field in grand canonical Monte Carlo simulations from few quantum mechanical calculations. We demonstrate that the methodology yields accurate adsorption data in diverse selection of guest molecules in porous materials such as CH4 and CO2 in zeolites (i.e., MFI, LTA, WEI, RHO, SOD, FAU, RWY, and ABW)...

We compare the conformational distributions of Ace-Ala-Nme and Ace-Gly-Nme sampled in long simulations with several molecular mechanics (MM) force fields and with a fast combined quantum mechanics/molecular mechanics (QM/MM) force field, in which the solute's intramolecular energy and forces are calculated with the self-consistent charge density functional tight binding method (SCCDFTB), and the solvent is represented by either one of the well-known SPC and TIP3P models. All MM force fields give two main states for Ace-Ala-Nme, beta and alpha separated by free energy barriers, but the ratio in which these are sampled varies by a factor of 30, from a high in favor of beta of 6 to a low of 1/5. The frequency of transitions between states is particularly low with the amber and charmm force fields, for which the distributions are noticeably narrower, and the energy barriers between states higher. The lower of the two barriers lies between alpha and beta at values of psi near 0 for all MM simulations except for charmm22. The results of the QM/MM simulations vary less with the choice of MM force field; the ratio beta/alpha varies between 1.5 and 2.2, the easy pass lies at psi near 0, and transitions between states are more frequent than for amber and charmm, but less frequent than for cedar. For Ace-Gly-Nme, all force fields locate a diffuse stable region around phi = pi and psi = pi, whereas the amber force field gives two additional densely sampled states near phi = +/-100 degrees and psi = 0, which are also found with the QM/MM force field. For both solutes, the distribution from the QM/MM simulation shows greater similarity with the distribution in high-resolution protein structures than is the case for any of the MM simulations.

Accurate force fields are essential for reproducing the conformational and dynamic behavior of condensed-phase systems. The popular AMBER force field has parameters for monophosphates, but they do not extend well to polyphorylated molecules such as ADP and ATP. This work presents parameters for the partial charges, atom types, bond angles, and torsions in simple polyphosphorylated compounds. The parameters are based on molecular orbital calculations of methyldiphosphate and methyltriphosphate at the RHF/6-31+G* level. The new parameters were fit to the entire potential energy surface (not just minima) with an RMSD of 0.62 kcal/mol. This is exceptional agreement and a significant improvement over the current parameters that produce a potential surface with an RMSD of 7.8 kcal/mol to that of the ab initio calculations. Testing has shown that the parameters are transferable and capable of reproducing the gas-phase conformations of inorganic diphosphate and triphosphate. Also, the parameters are an improvement over existing parameters in the condensed phase as shown by minimizations of ATP bound in several proteins. These parameters are intended for use with the existing AMBER 94/99 force field, and they will permit users to apply AMBER to a wider variety of important enzymatic systems.

The reliability of molecular dynamics (MD) simulations in predicting macroscopic properties of complex fluids and soft materials, such as liquid crystals, colloidal suspensions, or polymers, relies on the accuracy of the adopted force field (FF). We present an automated protocol to derive specific and accurate FFs, fully based on ab initio quantum mechanical (QM) data. The integration of the Joyce and Picky procedures, recently proposed by our group to provide an accurate description of simple liquids, is here extended to larger molecules, capable of exhibiting more complex fluid phases. While the standard Joyce protocol is employed to parameterize the intramolecular FF term, a new automated procedure is here proposed to handle the computational cost of the QM calculations required for the parameterization of the intermolecular FF term. The latter is thus obtained by integrating the old Picky procedure with a fragmentation reconstruction method (FRM) that allows for a reliable, yet computationally feasible sampling of the intermolecular energy surface at the QM level. The whole FF parameterization protocol is tested on a benchmark liquid crystal, and the performances of the resulting quantum mechanically derived (QMD) FF were compared with those delivered by a general-purpose, transferable one, and by the third, "hybrid" FF, where only the bonded terms were refined against QM data. Lengthy atomistic MD simulations are carried out with each FF on extended 5CB systems in both isotropic and nematic phases, eventually validating the proposed protocol by comparing the resulting macroscopic properties with other computational models and with experiments. The QMD-FF yields the best performances, reproducing both phases in the correct range of temperatures and well describing their structure, dynamics, and thermodynamic properties, thus providing a clear protocol that may be explored to predict such properties on other complex fluids or soft materials.

Replica exchange molecular dynamics (REMD) techniques have emerged as standard tools for simulating peptides and small proteins, in part, to evaluate the accuracy of modern classical force fields for polypeptides. However, it often remains a challenge to unambiguously discriminate force field flaws from simulations that do not reach equilibrium convergence. Here, we examine closely the convergence behavior of REMD runs for 14 test alpha and beta peptide systems, using an AMBER force field with a generalized Born/surface area implicit solvation model. Somewhat surprisingly, we find that convergence times can be quite large compared to the time scales reached in many earlier REMD efforts, with some short peptides requiring up to 60 ns of run time (per replica). Moreover, we detect a high degree of run-to-run heterogeneity, finding that REMD runs of the same peptide seeded with different initial velocities can exhibit a range of fast- and slow-folding behavior. By increasing the number of swap attempts per REMD cycle, we are able to reduce heterogeneity by diminishing the presence of slower-folding trajectories. Finally, we notice that convergence often can be signaled by a spike in the population of the most populated configurational cluster - a metric that is independent of the native structure. These results suggest that the systematic application of long runs, multiple trials, and convergence indicators may be important in future folding studies and in force field development efforts.

Single-stranded regions of RNA are important for folding of sequences into 3D structures and for design of therapeutics targeting RNA. Prediction of ensembles of 3D structures for single-stranded regions often involves classical mechanical approximations of interactions defined by quantum mechanical calculations on small model systems. Nuclear magnetic resonance (NMR) spectra and molecular dynamics (MD) simulations of short single strands provide tests for how well the approximations model many of the interactions. Here, the NMR spectra for UCUCGU at 2, 15, and 30 °C are compared to simulations with the AMBER force fields, OL3 and ROC-RNA. This is the first such comparison to an oligoribonucleotide containing an internal guanosine nucleotide (G). G is particularly interesting because of its many H-bonding groups, large dipole moment, and proclivity for both syn and anti conformations. Results reveal formation of a G amino to phosphate non-bridging oxygen H-bond. The results also demonstrate dramatic differences in details of the predicted structures. The variations emphasize the dependence of predictions on individual parameters and their balance with the rest of the force field. The NMR data can serve as a benchmark for future force fields.

Accurate force fields are one of the major pillars on which successful molecular dynamics simulations of complex biomolecular processes rest. They have been optimized for ambient conditions, whereas high-pressure simulations become increasingly important in pressure perturbation studies, using pressure as an independent thermodynamic variable. Here, we explore the design of non-polarizable force fields tailored to work well in the realm of kilobar pressures--while avoiding complete reparameterization. Our key is to first compute the pressure-induced electronic and structural response of a solute by combining an integral equation approach to include pressure effects on solvent structure with a quantum-chemical treatment of the solute within the embedded cluster reference interaction site model (EC-RISM) framework. Next, the solute's response to compression is taken into account by introducing pressure-dependence into selected parameters of a well-established force field. In our proof-of-principle study, the full machinery is applied to N,N,N-trimethylamine-N-oxide (TMAO) in water being a potent osmolyte that counteracts pressure denaturation. EC-RISM theory is shown to describe well the charge redistribution upon compression of TMAO(aq) to 10 kbar, which is then embodied in force field molecular dynamics by pressure-dependent partial charges. The performance of the high pressure force field is assessed by comparing to experimental and ab initio molecular dynamics data. Beyond its broad usefulness for designing non-polarizable force fields for extreme thermodynamic conditions, a good description of the pressure-response of solutions is highly recommended when constructing and validating polarizable force fields.

Molecular dynamics (MD) simulation in the explicit water is performed to study the interaction mechanism of trypsin-ligand binding under the AMBER force field and polarized protein-specific charge (PPC) force field combined the new developed highly efficient interaction entropy (IE) method for calculation of entropy change. And the detailed analysis and comparison of the results of MD simulation for two trypsin-ligand systems show that the root-mean-square deviation (RMSD) of backbone atoms, B-factor, intra-protein and protein-ligand hydrogen bonds are more stable under PPC force field than AMBER force field. Our results demonstrate that the IE method is superior than the traditional normal mode (Nmode) method in the calculation of entropy change and the calculated binding free energy under the PPC force field combined with the IE method is more close to the experimental value than other three combinations (AMBER-Nmode, AMBER-IE and PPC-Nmode). And three critical hydrogen bonds between trypsin and ligand are broken under AMBER force field. However, they are well preserved under PPC force field. Detailed binding interactions of ligands with trypsin are further analyzed. The present work demonstrates that the polarized force field combined the highly efficient IE method is critical in MD simulation and free energy calculation.

Molecular dynamics (MD) simulations have become a central tool for investigating various biophysical questions with atomistic detail. While many different proxies are used to qualify MD force fields, most are based on largely structural parameters such as the root mean square deviation from experimental coordinates or nuclear magnetic resonance (NMR) chemical shifts and residual dipolar couplings. NMR derived Lipari-Szabo squared generalized order parameter (O(2) ) values of amide NH bond vectors of the polypeptide chain were also often employed for refinement and validation. However, with a few exceptions, side chain methyl symmetry axis order parameters have not been incorporated into experimental reference sets. Using a test set of five diverse proteins, the performance of several force fields implemented in the NAMDD simulation package was examined. It was found that simulations employing explicit water implemented using the TIP3 model generally performed significantly better than those using implicit water in reproducing experimental methyl symmetry axis O(2) values. Overall the CHARMM27 force field performs nominally better than two implementations of the Amber force field. It appeared that recent quantum mechanics modifications to side chain torsional angles of leucine and isoleucine in the Amber force field have significantly hindered proper motional modeling for these residues. There remained significant room for improvement as even the best correlations of experimental and simulated methyl group Lipari-Szabo generalized order parameters fall below an R(2) of 0.8.

Polarization plays important roles in charged and hydrogen bonding containing systems. Much effort ranging from the construction of physics-based models to quantum mechanism (QM)-based and machine learning (ML)-assisted models have been devoted to incorporating the polarization effect into the conventional force fields at different levels, such as atomic and coarse grained (CG). The application of polarizable force fields or polarization models was limited by two aspects, namely, computational cost and transferability. Different from physics-based models, no predetermining parameters were required in the QM-based approaches. Taking advantage of both the accuracy of QM calculations and efficiency of molecular mechanism (MM) and ML, polarization effects could be treated more efficiently while maintaining the QM accuracy. The computational cost could be reduced with variable electrostatic parameters, such as the charge, dipole, and electronic dielectric constant with the help of linear scaling fragmentation-based QM calculations and ML models. Polarization and entropy effects on the prediction of partition coefficient of druglike molecules are demonstrated by using both explicit or implicit all-atom molecular dynamics simulations and machine learning-assisted models. Directions and challenges for future development are also envisioned.

Here, we systematically investigated how the force fields and the partial charge models for ligands affect the ranking performance of the binding free energies predicted by the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) approaches. A total of 46 small molecules targeted to five different protein receptors were employed to test the following issues: (1) the impact of five AMBER force fields (ff99, ff99SB, ff99SB-ILDN, ff03, and ff12SB) on the performance of MM/GBSA, (2) the influence of the time scale of molecular dynamics (MD) simulations on the performance of MM/GBSA with different force fields, (3) the impact of five AMBER force fields on the performance of MM/PBSA, and (4) the impact of four different charge models (RESP, ESP, AM1-BCC, and Gasteiger) for small molecules on the performance of MM/PBSA or MM/GBSA. Based on our simulation results, the following important conclusions can be obtained: (1) for short time-scale MD simulations (1 ns or less), the ff03 force field gives the best predictions by both MM/GBSA and MM/PBSA; (2) for middle time-scale MD simulations (2-4 ns), MM/GBSA based on the ff99 force field yields the best predictions, while MM/PBSA based on the ff99SB force field does the best; however, longer MD simulations, for example, 5 ns or more, may not be quite necessary; (3) for most cases, MM/PBSA with the Tan's parameters shows better ranking capability than MM/GBSA (GB(OBC1)); (4) the RESP charges show the best performance for both MM/PBSA and MM/GBSA, and the AM1-BCC and ESP charges can also give fairly satisfactory predictions. Our results provide useful guidance for the practical applications of the MM/GBSA and MM/PBSA approaches.

Molecular dynamics (MD) simulations of six upgraded empirical force fields were compared and evaluated with short peptides, intrinsically disordered proteins, and folded proteins using trajectories of 1, 1.5, 5, or 10 μs (five replicates of 200 ns, 300 ns, 1 μs, or 2 μs) for each system. Previous studies have shown that different force fields, water models, simulation methods, and parameters can affect simulation outcomes. Here, the MD simulations were done in an explicit solvent with RS-peptide, HEWL19, HIV-rev, β amyloid (Aβ)-40, Aβ-42, phosphodiesterase-γ, CspTm, and ubiquitin using ff99IDPs, ff14IDPs, ff14IDPSFF, ff03w, CHARMM36m, and CHARMM22* force fields. The IDP ensembles generated by six all-atom empirical force fields were compared against NMR data. Despite using identical starting structures and simulation parameters, ensembles obtained with different force fields exhibit significant differences in NMR RMDs, secondary structure contents, and global properties such as the radius of gyration. The intrinsically disordered protein (IDP)-specific force fields could substantially reproduce the experimental observables in force field comparison: they have the lowest error in chemical shifts and J-couplings for short peptides/proteins, reasonably well for large IDPs and reasonably well with the radius of gyration. A high population of disorderness was observed in the IDP-specific force field for the IDP ensemble with a fraction of β sheets for β-amyloids. CHARMM22* performs better for many observables; however, it still has a preference toward the helicity for short peptides. The results of β-amyloid 42 starting from two different initial structures (Aβ421Z0Q and Aβ42model) were also compared with DSSP and NMR data. The results obtained with IDP-specific force fields within 2 μs simulation time are similar, even though starting from different structures. The current force fields perform equally well for folded proteins. The results of currently developed or modified force fields for IDPs are capable of enlightening the overall performance of the force field for disordered as well as folded proteins, thereby contributing to force field development.

Two 250 ns molecular simulations have been carried out to study the structure and dynamics of crystal toxin protein II from the scorpion Androctonus australis Hector employing the polarized protein-specific charge (PPC), as well as the standard AMBER99SB force field, to investigate the electrostatic polarization on the simulated crystal stability. Results show that under PPC, the monomers in unit cell as well as the lattice in supercell are more stable with smaller root-mean-square deviations and more accurate lattice atomic fluctuations compared with the crystallographic B-factors than under AMBER99SB force field. Most of the interactions at interfaces in the X-ray structure are quite well-preserved, underscoring the important effect of polarization on maintaining the crystal stability. However, the results also show that the hydrogen bond between Asp53 and Gln37 and the cation-π interaction between Arg56 and His64 are not stable, indicating that further optimization of force field, especially the van der Waals interaction parameters, is desired.

Polarization and inductive effects are the concepts that have been widely used in qualitative and even quantitative descriptions of experimentally observed properties in chemistry. The polarization effect has proven to be important in cases of biomolecular modeling though still the vast majority of molecular simulations use the classical non-polarizable force fields. In the last few decades, a lot of effort has been put into promoting the polarization effect and incorporating it into modern force fields and charge calculation methods. In contrast, the inductive effect has not attracted such attention and is effectively absent in both classic and modern force fields. Thus, a question is whether this difference corresponds to the difference in the physical significance of the effects and their explicit account, or is an artifact that should be corrected in the next generation of force fields. The significance of the electronic effects is studied in this paper through the prism of performance of specific models for atomic charge calculation that take into explicit account a nested set of effects: the formal charge, the nearest neighbors, the inductive effect, and finally the model, which takes into account all effects, which are possible to account for using atomic charges. The specific choice for the methods is the following: formal charges, MMFF94 bond charge increments, Dynamic Electronegativity Relaxation (DENR), and RESP. We propose a special scheme for the separate estimation of each particular effect contribution. By pairwise comparing the residual molecular electrostatic potential (MEP) errors of those charge models (aimed at best reproducing the quantum chemical reference MEP), we sequentially revealed how the account of each effect contributes to the better-quality MEP reproduction. The following relative importance of effects was estimated; thus, the natural hierarchy of the effects was established. First, the account of formal charges is of primordial importance. Second, the nearest neighbors account is the next in significance. Third, the explicit account of inductive effect in empirical charge calculation schemes was shown to significantly─both qualitatively and quantitatively─improve the quality of MEP reproduction. Fourth, the contribution of polarization is indirectly assessed. Surprisingly, it is of the order of magnitude of the inductive effect even for the molecular systems, for which it is anticipated to be more significant. Finally, the relative importance of anisotropic effects in neutral molecules was additionally reviewed.