The Ad-MD method to calculate NMR shift including effects due to conformational dynamics: The 31 P NMR shift in DNA.

A method for averaging of NMR parameters by molecular dynamics (MD) has been derived from the method of statistical averaging in MD snapshots, benchmarked and applied to structurally dynamic interpretation of the 31 P NMR shift (δ31P ) in DNA phosphates. The method employs adiabatic dependence of an NMR parameter on selected geometric parameter(s) that is weighted by MD-calculated probability distribution(s) for the geometric parameter(s) (Ad-MD method). The usage of Ad-MD for polymers is computationally convenient when one pre-calculated structural dependence of an NMR parameter is employed for all chemically equivalent units differing only in dynamic behavior. The Ad-MD method is benchmarked against the statistical averaging method for δ31P in the model phosphates featuring distinctively different structures and dynamic behavior. The applicability of Ad-MD is illustrated by calculating 31 P NMR spectra in the Dickerson-Drew DNA dodecamer. δ31P was calculated with the B3LYP/IGLO-III/PCM(water) and the probability distributions for the torsion angles adjacent to the phosphorus atoms in the DNA phosphates were calculated using the OL15 force field.

Conformational energies and equilibria of cyclic dinucleotides in vacuo and in solution: computational chemistry vs. NMR experiments.

Performance of computational methods in modelling cyclic dinucleotides - an important and challenging class of compounds - has been evaluated by two different benchmarks: (1) gas-phase conformational energies and (2) qualitative agreement with NMR observations of the orientation of the χ-dihedral angle in solvent. In gas-phase benchmarks, where CCSD(T) and DLPNO-CCSD(T) methods have been used as the reference, most of the (dispersion corrected) density functional approximations are accurate enough to justify prioritizing computational cost and compatibility with other modelling options as the criterion of choice. NMR experiments of 3'3'-c-di-AMP, 3'3'-c-GAMP, and 3'3'-c-di-GMP show the overall prevalence of the anti-conformation of purine bases, but some population of syn-conformations is observed for guanines. Implicit solvation models combined with quantum-chemical methods struggle to reproduce this behaviour, probably due to a lack of dynamics and explicitly modelled solvent, leading to structures that are too compact. Molecular dynamics simulations overrepresent the syn-conformation of guanine due to the overestimation of an intramolecular hydrogen bond. Our combination of experimental and computational benchmarks provides "error bars" for modelling cyclic dinucleotides in solvent, where such information is generally difficult to obtain, and should help gauge the interpretability of studies dealing with binding of cyclic dinucleotides to important pharmaceutical targets. At the same time, the presented analysis calls for improvement in both implicit solvation models and force-field parameters.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview.

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Noncovalent Interactions by Quantum Monte Carlo.

Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-body problems such as the stationary Schrödinger equation. The review introduces basic notions of electronic structure QMC based on random walks in real space as well as its advances and adaptations to systems with noncovalent interactions. Specific issues such as fixed-node error cancellation, construction of trial wave functions, and efficiency considerations that allow for benchmark quality QMC energy differences are described in detail. Comprehensive overview of articles covers QMC applications to systems with noncovalent interactions over the last three decades. The current status of QMC with regard to efficiency, applicability, and usability by nonexperts together with further considerations about QMC developments, limitations, and unsolved challenges are discussed as well.

Influence of BII Backbone Substates on DNA Twist: A Unified View and Comparison of Simulation and Experiment for All 136 Distinct Tetranucleotide Sequences.

Reliable representation of the B-DNA base-pair step twist is one of the crucial requirements for theoretical modeling of DNA supercoiling and other biologically relevant phenomena in B-DNA. It has long been suspected that the twist is inaccurately described by current empirical force fields. Unfortunately, comparison of simulation results with experiments is not straightforward because of the presence of BII backbone substates, whose populations may differ in experimental and simulation ensembles. In this work, we provide a comprehensive view of the effect of BII substates on the overall B-DNA helix twist and show how to reliably compare twist values from experiment and simulation in two scenarios. First, for longer DNA segments freely moving in solution, we show that sequence-averaged twists of different BI/BII ensembles can be compared directly because of approximate cancellation of the opposing BII effects. Second, for sequence-specific data, such as a particular base-pair step or tetranucleotide twist, can be compared only for a clearly defined BI/BII backbone conformation. For the purpose of force field testing, we designed a compact set of fourteen 22-base-pair B-DNA duplexes (Set 14) containing all 136 distinct tetranucleotide sequences and carried out a total of 84 µs of molecular dynamics simulations, primarily with the OL15 force field. Our results show that the ff99bsc0εζOL1χOL4, parmbsc1, and OL15 force fields model the B-DNA helical twist in good agreement with X-ray and minicircle ligation experiments. The comprehensive understanding obtained regarding the effect of BII substates on the base-pair step geometry should aid meaningful comparisons of various conformational ensembles in future research.

On the Use of Molecular Dynamics Simulations for Probing Allostery through DNA.

A recent study described an allosteric effect in which the binding of a protein to DNA is influenced by another protein bound nearby. The effect shows a periodicity of ∼10 basepairs and decays with increasing protein-protein distance. As a mechanistic explanation, the authors reported a similar periodic, decaying pattern of the correlation coefficient between major groove widths inferred from a shorter molecular dynamics simulation. Here we show that in a state-of-the-art, microsecond-long simulation of the same DNA sequence, the periodicity of the correlation coefficient is not observed. To study the problem further, we extend an earlier mechanical model of DNA allostery based on constrained minimization of effective quadratic deformation energy of the DNA. We demonstrate that, if the constraints mimicking the bound proteins are properly applied, the periodicity in the binding energy is indeed recovered.

Modelling of graphene functionalization.

Graphene has attracted great interest because of its remarkable properties and numerous potential applications. A comprehensive understanding of its structural and dynamic properties and those of its derivatives will be required to enable the design and optimization of sophisticated new nanodevices. While it is challenging to perform experimental studies on nanoscale systems at the atomistic level, this is the 'native' scale of computational chemistry. Consequently, computational methods are increasingly being used to complement experimental research in many areas of chemistry and nanotechnology. However, it is difficult for non-experts to get to grips with the plethora of computational tools that are available and their areas of application. This perspective briefly describes the available theoretical methods and models for simulating graphene functionalization based on quantum and classical mechanics. The benefits and drawbacks of the individual methods are discussed, and we provide numerous examples showing how computational methods have provided new insights into the physical and chemical features of complex systems including graphene and graphene derivatives. We believe that this overview will help non-expert readers to understand this field and its great potential.

Mechanical properties of symmetric and asymmetric DNA A-tracts: implications for looping and nucleosome positioning.

A-tracts are functionally important DNA sequences which induce helix bending and have peculiar structural properties. While A-tract structure has been qualitatively well characterized, their mechanical properties remain controversial. A-tracts appear structurally rigid and resist nucleosome formation, but seem flexible in DNA looping. In this work, we investigate mechanical properties of symmetric AnTn and asymmetric A2n tracts for n = 3, 4, 5 using two types of coarse-grained models. The first model represents DNA as an ensemble of interacting rigid bases with non-local quadratic deformation energy, the second one treats DNA as an anisotropically bendable and twistable elastic rod. Parameters for both models are inferred from microsecond long, atomic-resolution molecular dynamics simulations. We find that asymmetric A-tracts are more rigid than the control G/C-rich sequence in localized distortions relevant for nucleosome formation, but are more flexible in global bending and twisting relevant for looping. The symmetric tracts, in contrast, are more rigid than asymmetric tracts and the control, both locally and globally. Our results can reconcile the contradictory stiffness data on A-tracts and suggest symmetric A-tracts to be more efficient in nucleosome exclusion than the asymmetric ones. This would open a new possibility of gene expression manipulation using A-tracts.

Transferability and additivity of dihedral parameters in polarizable and nonpolarizable empirical force fields.

Recent advances in polarizable force fields have revealed that major reparameterization is necessary when the polarization energy is treated explicitly. This study is focused on the torsional parameters, which are crucial for the accurate description of conformational equilibria in biomolecules. In particular, attention is paid to the influence of polarization on the (i) transferability of dihedral terms between molecules, (ii) transferability between different environments, and (iii) additivity of dihedral energies. To this end, three polarizable force fields based on the induced point dipole model designed for use in AMBER are tested, including two recent ff02 reparameterizations. Attention is paid to the contributions due to short range interactions (1-2, 1-3, and 1-4) within the four atoms defining the dihedral angle. The results show that when short range 1-2 and 1-3 polarization interactions are omitted, as for instance in ff02, the 1-4 polarization contribution is rather small and unlikely to improve the description of the torsional energy. Conversely, when screened 1-2 and 1-3 interactions are included, the polarization contribution is sizeable and shows potential to improve the transferability of parameters between different molecules and environments as well as the additivity of dihedral terms. However, to reproduce intramolecular polarization effects accurately, further fine-tuning of the short range damping of polarization is necessary.

Extensions and applications of the A24 data set of accurate interaction energies.

The A24 data set (Rezác and Hobza, J. Chem. Theory Comput. 2013, 9, 2151-2155) is a set of noncovalent complexes large enough to showcase various types of interactions yet small enough to make highly accurate calculations possible. It is intended for the testing of accurate computational methods which are then used as a benchmark in larger model systems. In this work, we improve the best estimate of the interaction energies in the set by updating their CCSD(T)/CBS and CCSDT(Q) components with calculations in larger basis sets. The data set is then used to test a large number of composite CCSD(T) approaches. Special attention is paid to the use of the explicitly correlated MP2-F12 method in these composite calculations. It is shown that an accuracy of 1-2% can be achieved with setups applicable to larger molecules. The effect of frozen natural orbital approximation on the accuracy of composite CCSD(T)/CBS calculations is also quantified. In four trivially saturated complexes where CCSDT(Q)/CBS data are now available, the convergence of the many-body correlation effects is assessed by fixed-node diffusion Monte Carlo (FN-DMC) calculations. A good agreement is achieved between FN-DMC and high-level coupled-cluster which represents an important cross-check of both approaches.

Choosing a density functional for modeling adsorptive hydrogen storage: reference quantum mechanical calculations and a comparison of dispersion-corrected density functionals.

Hydrogen storage in carbonaceous materials and their derivatives is currently a widely investigated topic. The rational design of novel adsorptive materials is often attempted with the help of computational chemistry tools, in particular density functional theory (DFT). However, different exchange-correlation functionals provide a very wide range of hydrogen binding energies. The aim of this article is to offer high level QM reference data based on coupled-cluster singles and doubles calculations with perturbative triple excitations, CCSD(T), and a complete basis set limit estimate that can be used to assess the accuracy of various DFT-based predictions. For one complex, the CCSD(T) result is verified against diffusion quantum Monte Carlo calculations. Reference binding curves are calculated for two model compounds representing weak and strong hydrogen adsorption: coronene (-4.7 kJ mol(-1) per H2), and coronene modified with boron and lithium (-14.3 kJ mol(-1)). The reference data are compared to results obtained with widely used density functionals including pure DFT, M06, DFT-D3, PBE-TS, PBE + MBD, optB88-vdW, vdW-DF, vdW-DF2 and VV10. We find that whereas DFT-D3 shows excellent results for weak hydrogen adsorption on coronene, most of the less empirical density based dispersion functionals except VV10 overestimate this interaction. On the other hand, some of the less empirical density based dispersion functionals better describe stronger binding in the more polar coroB2Li22H2 complex which is one of realistic models for high-capacity hydrogen storage materials. Our results may serve as a guide for choosing suitable DFT methods for quickly evaluating hydrogen binding potential and as a reference for assessing the accuracy of the previously published DFT results.

How to understand quantum chemical computations on DNA and RNA systems? A practical guide for non-specialists.

In this review primarily written for non-experts we explain basic methodological aspects and interpretation of modern quantum chemical (QM) computations applied to nucleic acids. We introduce current reference QM computations on small model systems consisting of dozens of atoms. Then we comment on recent advance of fast and accurate dispersion-corrected density functional theory methods, which will allow computations of small but complete nucleic acids building blocks in the near future. The qualitative difference between QM and molecular mechanics (MM, force field) computations is discussed. We also explain relation of QM and molecular simulation computations to experiments.

Electric quadrupole moment of graphene and its effect on intermolecular interactions.

Carbon atoms in aromatic compounds exhibit a permanent electric quadrupole moment due to the aromatic π electron distribution. In the case of small aromatic hydrocarbons, this quadrupole contributes significantly to their intermolecular interactions, but when the honeycomb lattice is expanded to infinity, the quadrupolar field sums to zero and its significance vanishes. Therefore, electrostatic interactions with graphene are often omitted in force field molecular modeling. However, for a finite sheet, the electrostatic field decays only slowly with increasing size and is always non-negligible near edges. In addition, in a corrugated graphene sheet, the electrostatic field near the surface does not vanish completely and remains sizeable. In the present study, we investigated the magnitude of the graphene quadrupolar field as a function of model size and graphene corrugation, and estimated the error resulting from its neglect in molecular dynamics simulations. Exfoliation energies in benzene and hexafluorobenzene were calculated using the potential of mean force method with and without explicit quadrupoles. The effect on exfoliation energies was found to be quite small. However, the quadrupole moment may be important for graphene sheet association (aggregation) as it affects barrier heights, and consequently kinetics of association. Our results indicate that quadrupolar interactions may need to be considered in molecular modeling when graphene is corrugated or bent.

Quantum Monte Carlo for noncovalent interactions: an efficient protocol attaining benchmark accuracy.

Reliable theoretical prediction of noncovalent interaction energies, which are important e.g. in drug-design and hydrogen-storage applications, is one of the longstanding challenges of contemporary quantum chemistry. In this respect, the fixed-node diffusion Monte Carlo (FN-DMC) method is a promising alternative to the commonly used "gold standard" coupled-cluster CCSD(T)/CBS method due to its benchmark accuracy and favourable scaling, in contrast to other correlated wave function approaches. This work is focused on the analysis of protocols and possible trade-offs for FN-DMC estimations of noncovalent interaction energies, and proposes an efficient yet accurate computational protocol using simplified explicit correlation terms with a favorable O(N(3)) scaling. It achieves results in excellent agreement (mean unsigned error ∼0.2 kcal mol(-1)) with respect to the CCSD(T)/CBS data on a number of complexes, including benzene/hydrogen, the T-shape benzene dimer, stacked adenine-thymine complex and a set of small noncovalent complexes (A24). The high accuracy and reduced computational costs predestinate the reported protocol for practical interaction energy calculations of large noncovalent complexes, where the CCSD(T)/CBS is prohibitively expensive.

Multistate B- to A- transition in protein-DNA Binding - How well is it described by current AMBER force fields?

When DNA interacts with a protein, its structure often undergoes a significant conformational adaptation, usually involving a transition from B-DNA towards the A-DNA form. This is not a two-state, but rather a multistate transition. The A- and B- forms differ mainly in sugar pucker (north/south) and glycosidic torsion χ (anti/high-anti). The combination of A-like pucker and B-like χ (and vice versa) represents the nature of the intermediate states between the pure A- and B- forms. Here we study how the A/B equilibrium and the A/B intermediate states at protein-DNA interfaces are modeled by current AMBER force fields. Eight diverse protein-DNA complexes and their naked (unbound) DNAs were simulated with OL15 and bsc1 force fields and an experimental combination OL15χOL3. We found that while the geometries of the A-like intermediate states agree well with the native X-ray geometries, their populations (stabilities) are significantly underestimated. Different force fields predict different propensities for A-like states growing in the order OL15 < bsc1 < OL15χOL3, yet all underestimate A-like form populations. Interestingly, the force fields seem to predict the correct sequence-dependent A-form propensity, as they predict larger populations of the A-like form in unbound DNA in those steps that acquire A-like conformations in protein-DNA complexes. The instability of A-like geometries in current force fields significantly alters the geometry of simulated protein-DNA complexes and destabilizes the binding motif, suggesting that refinement is required to improve description of protein-DNA interactions in AMBER force fields.Communicated by Ramaswamy H. Sarma.

Adsorption of small organic molecules on graphene.

We present a combined experimental and theoretical quantification of the adsorption enthalpies of seven organic molecules (acetone, acetonitrile, dichloromethane, ethanol, ethyl acetate, hexane, and toluene) on graphene. Adsorption enthalpies were measured by inverse gas chromatography and ranged from -5.9 kcal/mol for dichloromethane to -13.5 kcal/mol for toluene. The strength of interaction between graphene and the organic molecules was estimated by density functional theory (PBE, B97D, M06-2X, and optB88-vdW), wave function theory (MP2, SCS(MI)-MP2, MP2.5, MP2.X, and CCSD(T)), and empirical calculations (OPLS-AA) using two graphene models: coronene and infinite graphene. Symmetry-adapted perturbation theory calculations indicated that the interactions were governed by London dispersive forces (amounting to ∼60% of attractive interactions), even for the polar molecules. The results also showed that the adsorption enthalpies were largely controlled by the interaction energy. Adsorption enthalpies obtained from ab initio molecular dynamics employing non-local optB88-vdW functional were in excellent agreement with the experimental data, indicating that the functional can cover physical phenomena behind adsorption of organic molecules on graphene sufficiently well.

Nature and magnitude of aromatic base stacking in DNA and RNA: Quantum chemistry, molecular mechanics, and experiment.

Base stacking is a major interaction shaping up and stabilizing nucleic acids. During the last decades, base stacking has been extensively studied by experimental and theoretical methods. Advanced quantum-chemical calculations clarified that base stacking is a common interaction, which in the first approximation can be described as combination of the three most basic contributions to molecular interactions, namely, electrostatic interaction, London dispersion attraction and short-range repulsion. There is not any specific π-π energy term associated with the delocalized π electrons of the aromatic rings that cannot be described by the mentioned contributions. The base stacking can be rather reasonably approximated by simple molecular simulation methods based on well-calibrated common force fields although the force fields do not include nonadditivity of stacking, anisotropy of dispersion interactions, and some other effects. However, description of stacking association in condensed phase and understanding of the stacking role in biomolecules remain a difficult problem, as the net base stacking forces always act in a complex and context-specific environment. Moreover, the stacking forces are balanced with many other energy contributions. Differences in definition of stacking in experimental and theoretical studies are explained.

Benchmark quantum-chemical calculations on a complete set of rotameric families of the DNA sugar-phosphate backbone and their comparison with modern density functional theory.

The DNA sugar-phosphate backbone has a substantial influence on the DNA structural dynamics. Structural biology and bioinformatics studies revealed that the DNA backbone in experimental structures samples a wide range of distinct conformational substates, known as rotameric DNA backbone conformational families. Their correct description is essential for methods used to model nucleic acids and is known to be the Achilles heel of force field computations. In this study we report the benchmark database of MP2 calculations extrapolated to the complete basis set of atomic orbitals with aug-cc-pVTZ and aug-cc-pVQZ basis sets, MP2(T,Q), augmented by ΔCCSD(T)/aug-cc-pVDZ corrections. The calculations are performed in the gas phase as well as using a COSMO solvent model. This study includes a complete set of 18 established and biochemically most important families of DNA backbone conformations and several other salient conformations that we identified in experimental structures. We utilize an electronically sufficiently complete DNA sugar-phosphate-sugar (SPS) backbone model system truncated to prevent undesired intramolecular interactions. The calculations are then compared with other QM methods. The BLYP and TPSS functionals supplemented with Grimme's D3(BJ) dispersion term provide the best tradeoff between computational demands and accuracy and can be recommended for preliminary conformational searches as well as calculations on large model systems. Among the tested methods, the best agreement with the benchmark database has been obtained for the double-hybrid DSD-BLYP functional in combination with a quadruple-ζ basis set, which is, however, computationally very demanding. The new hybrid density functionals PW6B95-D3 and MPW1B95-D3 yield outstanding results and even slightly outperform the computationally more demanding PWPB95 double-hybrid functional. B3LYP-D3 is somewhat less accurate compared to the other hybrids. Extrapolated MP2(D,T) calculations are not as accurate as the less demanding DFT-D3 methods. Preliminary force field tests using several charge sets reveal an almost order of magnitude larger deviations from the reference QM data compared to modern DFT-D3, underlining the challenges facing force field simulations of nucleic acids. As expected, inclusion of the solvent environment approximated by a continuum approach has a large impact on the relative stabilities of different backbone substates and is important when comparing the QM data with structural bioinformatics and other experimental data.

Dynamic and Nondynamic Electron Correlation Energy Decomposition Based on the Node of the Hartree-Fock Slater Determinant.

Distinguishing between dynamic and nondynamic electron correlation energy is a fundamental concept in quantum chemistry. It can be challenging to make a clear distinction between the two types of correlation energy or to determine their actual contributions in specific cases using wave function theory. This is because both single-reference and multireference methods cover both types of correlation energy to some extent. Fixed-node diffusion quantum Monte Carlo (FNDMC) accurately covers dynamic correlations, but it is limited in overall accuracy by the node of the trial wave function. We introduce a methodology for partitioning an exact electron correlation energy into its dynamic and nondynamic components. This is accomplished by restricting a ground-state solution from sharing its node with a spin-restricted Hartree-Fock Slater determinant. The FNDMC method is used as a tool to conveniently project out a lowest-energy state obeying such a boundary condition. The proposed approach provides an unambiguous and useful procedure for separating electron correlation energy, as demonstrated on multiple systems, including the He atom, bond breaking of H2, the parametric H2-H2 system, the Be-Ne atomic series with low- and high-spin states for C, N, and O atoms, and small molecules such as BH, HF, and CO at both equilibrium and elongated configurations, respectively.

Assessing the Current State of Amber Force Field Modifications for DNA─2023 Edition.

Advances in molecular dynamics (MD) software alongside enhanced computational power and hardware have allowed for MD simulations to significantly expand our knowledge of biomolecular structure, dynamics, and interactions. Furthermore, it has allowed for the extension of conformational sampling times from nanoseconds to the microsecond level and beyond. This has not only made convergence of conformational ensembles through comprehensive sampling possible but consequently exposed deficiencies and allowed the community to overcome limitations in the available force fields. The reproducibility and accuracy of the force fields are imperative in order to produce biologically relevant data. The Amber nucleic acid force fields have been used widely since the mid-1980s, and improvement of these force fields has been a community effort with several artifacts revealed, corrected, and reevaluated by various research groups. Here, we focus on the Amber force fields for use with double-stranded DNA and present the assessment of two recently developed force field parameter sets (OL21 and Tumuc1). Extensive MD simulations were performed with six test systems and two different water models. We observe the improvement of OL21 and Tumuc1 compared to previous generations of the Amber DNA force. We did not detect any significant improvement in the performance of Tumuc1 compared to OL21 despite the reparameterization of bonded force field terms in the former; however, we did note discrepancies in Tumuc1 when modeling Z-DNA sequences.