Molecular Mechanics Force Field Research Articles

A Fundamental Study of Nano Electrodeposition Using a Combined Molecular Dynamics and Quantum Mechanical Electron Force Field Approach

Nano electrochemical additive manufacturing (Nano ECAM) is an emerging technology that combines the trends of miniaturization and additive manufacturing to fabricate complex 3D parts at the nano scale. A combined molecular dynamics and quantum mechanical electron force field approach is used in this work to study the electrochemical and physical input parameter effects on output deposition behavior to obtain fundamental understanding of Nano ECAM process. It was found that electron tunneling behavior occurs below a threshold interelectrode gap (IEG), which is not solvable by reducing the current. This tunneling would mean the electrons were not available to cause the electrolyte ions to deposit onto the substrate. Additionally, if the IEG was too high and the current was too low, the input electrons and cations from the electrolyte would combine and remain in a constant position near but not adsorbed to the surface. Furthermore, the effects of varying Watt's bath concentration were studied. It was found that there was an ideal concentration to perform Nano ECAM at, with values above and below causing deposition to occur less quickly and less efficiently. Finally, the work reported in this paper provides a very valuable computational framework for predicting the ECAM process results for subsequent experimental verification.

Geometric ergodicity of two-dimensional Hamiltonian systems with a Lennard–Jones-like repulsive potential

Molecular dynamics simulation is among the most important and widely used tools in the study of molecular systems, providing fundamental insights into molecular mechanisms at a level of detail unattainable by experimental methods [AT87, Lea96, FS96, Sch02]. Usage of molecular dynamics spans a diverse array of fields, from physics and chemistry, to molecular and cellular biology, to engineering and materials science. Due to their size and complexity, simulations of large systems such as biological macromolecules (DNA, RNA, proteins, carbohydrates, and lipids) are typically performed under a classical mechanics representation. A critical requirement of such simulations is ergodicity, or convergence in the limit to the equilibrium (typically canonical) Boltzmann measure μ(dq, dp) = Z(β)−1e−βH(q,p)dqdp. Although ergodicity is commonly assumed, recently [CS08] showed that all commonly used deterministic dynamics methods for simulating the canonical (constanttemperature) ensemble fail to be ergodic. They also showed that introduction of a stochastic hybrid Monte Carlo (HMC) correction guarantees ergodicity; however, HMC scales poorly with system dimension and is rarely used for macromolecules. [CS08] also show empirically that more commonly used stochastic Langevin dynamics [Pas94] appear to exhibit ergodic behavior, but were unable to provide rigorous proof. The key difficulty in applying existing arguments [MSH02] is the appearance of singularities in the potential U(q). Most modern molecular mechanics forcefields [PCC95, BBO83, JTR88] take the form

Mechanistic Models of Chemical Exchange Induced Relaxation in Protein NMR.

Long-lived conformational states and their interconversion rates critically determine protein function and regulation. When these states have distinct chemical shifts, the measurement of relaxation by NMR may provide us with useful information about their structure, kinetics, and thermodynamics at atomic resolution. However, as these experimental data are sensitive to many structural and dynamic effects, their interpretation with phenomenological models is challenging, even if only a few metastable states are involved. Consequently, approximations and simplifications must often be used which increase the risk of missing important microscopic features hidden in the data. Here, we show how molecular dynamics simulations analyzed through Markov state models and the related hidden Markov state models may be used to establish mechanistic models that provide a microscopic interpretation of NMR relaxation data. Using ubiquitin and BPTI as examples, we demonstrate how the approach allows us to dissect experimental data into a number of dynamic processes between metastable states. Such a microscopic view may greatly facilitate the mechanistic interpretation of experimental data and serve as a next-generation method for the validation of molecular mechanics force fields and chemical shift prediction algorithms.

CHARMM Force Field Parameterization of Peroxisome Proliferator-Activated Receptor γ Ligands

The peroxisome proliferator-activated receptor γ (PPARγ) ligands are important therapeutic drugs for the treatment of type 2 diabetes, obesity and cardiovascular diseases. In particular, partial agonists and non-agonists are interesting targets to reduce glucose levels, presenting few side effects in comparison to full agonists. In this work, we present a set of CHARMM-based parameters of a molecular mechanics force field for two PPARγ ligands, GQ16 and SR1664. GQ16 belongs to the thiazolidinedione class of drugs and it is a PPARγ partial agonist that has been shown to promote the “browning” of white adipose tissue. SR1664 is the precursor of the PPARγ non-agonist class of ligands that activates PPARγ in a non-classical manner. Here, we use quantum chemical calculations consistent with the CHARMM protocol to obtain bonded and non-bonded parameters, including partial atomic charges and effective torsion potentials for both molecules. The newly parameterized models were evaluated by examining the behavior of GQ16 and SR1664 free in water and bound to the ligand binding pocket of PPARγ using molecular dynamics simulations. The potential parameters derived here are readily transferable to a variety of pharmaceutical compounds and similar PPARγ ligands.

CHARMM force field parameters for 2′-hydroxybiphenyl-2-sulfinate, 2-hydroxybiphenyl, and related analogs

2′-Hydroxybiphenyl-2-sulfinate (HBPS) desulfinase (DszB) catalyzes the cleavage of the carbon-sulfur bond from HBPS in the final step of microbial 4S pathway desulfurization reactions. DszB is notable for its substrate specificity and exhibits product inhibition, both of which hinder the overall 4S pathway turnover rate. To understand the molecular-level contributions to substrate and inhibitor binding to DszB, we plan to perform molecular dynamic simulations bound to an array of naphthenic molecules and biphenyl analogues of HBPS. However, many of the small molecules we are interested in are not included in standard force field packages, and thus, we must first produce accurate molecular mechanics force fields. Here, we develop and validate CHARMM-compatible force field parameters for the HBPS substrate, the 2-hydroxybiphenyl product, and potential inhibitors including: 2,2′-biphenol, 2-biphenyl carboxylic acid, 1,8-naphthosultam, and 1,8-naphthosultone. The selected molecules represent biphenyl compounds having both a single and double functional group and the planar naphthenic molecule class, all likely present in the oil-rich environment surrounding DszB-producing microorganisms. The Force Field Toolkit (ffTK) in VMD was used to optimize charge, bond distance, angle, and dihedral parameters. Optimized geometries were determined from quantum mechanical calculations. Molecular simulations of the molecules in explicit and implicit water solutions were conducted to assess the abilities of optimized parameters to recapitulate optimized geometries. Calculated infrared (IR) spectra were obtained and compared with experimental IR spectra for validation of the optimized MM parameters.

Accurate Modeling of Scaffold Hopping Transformations in Drug Discovery.

The accurate prediction of protein-ligand binding free energies remains a significant challenge of central importance in computational biophysics and structure-based drug design. Multiple recent advances including the development of greatly improved protein and ligand molecular mechanics force fields, more efficient enhanced sampling methods, and low-cost powerful GPU computing clusters have enabled accurate and reliable predictions of relative protein-ligand binding free energies through the free energy perturbation (FEP) methods. However, the existing FEP methods can only be used to calculate the relative binding free energies for R-group modifications or single-atom modifications and cannot be used to efficiently evaluate scaffold hopping modifications to a lead molecule. Scaffold hopping or core hopping, a very common design strategy in drug discovery projects, is critical not only in the early stages of a discovery campaign where novel active matter must be identified but also in lead optimization where the resolution of a variety of ADME/Tox problems may require identification of a novel core structure. In this paper, we introduce a method that enables theoretically rigorous, yet computationally tractable, relative protein-ligand binding free energy calculations to be pursued for scaffold hopping modifications. We apply the method to six pharmaceutically interesting cases where diverse types of scaffold hopping modifications were required to identify the drug molecules ultimately sent into the clinic. For these six diverse cases, the predicted binding affinities were in close agreement with experiment, demonstrating the wide applicability and the significant impact Core Hopping FEP may provide in drug discovery projects.

Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules.

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking have been parametrized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties.

Assessing Ion-Water Interactions in the AMOEBA Force Field Using Energy Decomposition Analysis of Electronic Structure Calculations.

AMOEBA is a molecular mechanics force field that addresses some of the shortcomings of a fixed partial charge model, by including permanent atomic point multipoles through quadrupoles, as well as many-body polarization through the use of point inducible dipoles. In this work, we investigate how well AMOEBA formulates its non-bonded interactions, and how it implicitly incorporates quantum mechanical effects such as charge penetration (CP) and charge transfer (CT), for water-water and water-ion interactions. We find that AMOEBA's total interaction energies, as a function of distance and over angular scans for the water dimer and for a range of water-monovalent cations, agree well with an advanced density functional theory (DFT) model, whereas the water-halides and water-divalent cations show significant disagreement with the DFT result, especially in the compressed region when the two fragments overlap. We use a second-generation energy decomposition analysis (EDA) scheme based on absolutely localized molecular orbitals (ALMOs) to show that in the best cases AMOEBA relies on cancellation of errors by softening of the van der Waals (vdW) wall to balance permanent electrostatics that are too unfavorable, thereby compensating for the missing CP effect. CT, as another important stabilizing effect not explicitly taken into account in AMOEBA, is also found to be incorporated by the softened vdW interaction. For the water-halides and water-divalent cations, this compensatory approach is not as well executed by AMOEBA over all distances and angles, wherein permanent electrostatics remains too unfavorable and polarization is overdamped in the former while overestimated in the latter. We conclude that the DFT-based EDA approach can help refine a next-generation AMOEBA model that either realizes a better cancellation of errors for problematic cases like those illustrated here, or serves to guide the parametrization of explicit functional forms for short-range contributions from CP and/or CT.

Effective Fully Polarizable QM/MM Approach To Model Vibrational Circular Dichroism Spectra of Systems in Aqueous Solution.

We propose a methodology, based on the combination of classical Molecular Dynamics (MD) simulations with a fully polarizable Quantum Mechanical (QM)/Molecular Mechanics (MM)/Polarizable Continuum Model (PCM) Hamiltonian, to calculate Vibrational Circular Dichroism (VCD) spectra of chiral systems in aqueous solution. Polarization effects are included in the MM force field by exploiting an approach based on Fluctuating Charges (FQ). By performing the MD, the description of the solvating environment is enriched by taking into account the dynamical aspects of the solute-solvent interactions. On the other hand, the QM/FQ/PCM calculation of the VCD spectrum ensures an accurate description of the electronic density of the solute and a proper account for the specific interactions in solution. The application of our approach to (R)-methyloxirane and (l)-alanine in aqueous solution gives calculated spectra in remarkable agreement with their experimental counterparts and a substantial improvement with respect to the same spectra calculated with the PCM.

Improving the Force Field Description of Tyrosine-Choline Cation-π Interactions: QM Investigation of Phenol-N(Me)4+ Interactions.

Cation-π interactions between tyrosine amino acids and compounds containing N,N,N-trimethylethanolammonium (N(CH3)3) are involved in the recognition of histone tails by chromodomains and in the recognition of phosphatidylcholine (PC) phospholipids by membrane-binding proteins. Yet, the lack of explicit polarization or charge transfer effects in molecular mechanics force fields raises questions about the reliability of the representation of these interactions in biomolecular simulations. Here, we investigate the nature of phenol-tetramethylammonium (TMA) interactions using quantum mechanical (QM) calculations, which we also use to evaluate the accuracy of the additive CHARMM36 and Drude polarizable force fields in modeling tyrosine-choline interactions. We show that the potential energy surface (PES) obtained using SAPT2+/aug-cc-pVDZ compares well with the large basis-set CCSD(T) PES when TMA approaches the phenol ring perpendicularly. Furthermore, the SAPT energy decomposition reveals comparable contributions from electrostatics and dispersion in phenol-TMA interactions. We then compared the SAPT2+/aug-cc-pVDZ PES obtained along various approach directions to the corresponding PES obtained with CHARMM, and we show that the force field accurately reproduces the minimum distances while the interaction energies are underestimated. The use of the Drude polarizable force field significantly improves the interaction energies but decreases the agreement on distances at energy minima. The best agreement between force field and QM PES is obtained by modifying the Lennard-Jones terms for atom pairs involved in the phenol-TMA cation-π interactions. This is further shown to improve the correlation between the occupancy of tyrosine-choline cation-π interactions obtained from molecular dynamics simulations of a bilayer-bound bacterial phospholipase and experimental affinity data of the wild-type protein and selected mutants.

Recent developments of first‐principles force fields

Molecular mechanics force fields derived from first‐principles calculations represent the next generation of force fields for molecular dynamics simulations. In recent years, a large amount of first‐principles force fields have been developed in the fields of physical and biological fields. Here, we review the first‐principles force fields especially for simulating the adsorption of small molecules in nanoporous materials and on surfaces. We describe the latest developments in force field parameterization and application, primarily in the last 10 years. Emphasis is placed on the procedure in developing these first‐principles force fields. We discuss the selections of first‐principles methods and fragment models during the parameterization. As the first‐principles force fields are available in a wide range of simulation packages, it is anticipated that use of these force fields will lead to new discoveries of the adsorption phenomena in nanoporous materials and on surfaces. WIREs Comput Mol Sci 2017, 7:e1282. doi: 10.1002/wcms.1282This article is categorized under: Structure and Mechanism > Computational Materials Science Software > Simulation Methods Software > Molecular Modeling

Improved ligand geometries in crystallographic refinement using AFITT in PHENIX.

Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows. PHENIX-AFITT refinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentially difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows. PHENIX-AFITT refinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combining AFITT and the PHENIX software suite on a data set of 189 protein-ligand PDB structures are presented. Refinements using PHENIX-AFITT significantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. For the data presented, PHENIX-AFITT refinements result in more chemically accurate models for small-molecule ligands.

Partial hessian fitting for determining force constant parameters in molecular mechanics.

We present a new protocol for deriving force constant parameters that are used in molecular mechanics (MM) force fields to describe the bond-stretching, angle-bending, and dihedral terms. A 3 × 3 partial matrix is chosen from the MM Hessian matrix in Cartesian coordinates according to a simple rule and made as close as possible to the corresponding partial Hessian matrix computed using quantum mechanics (QM). This partial Hessian fitting (PHF) is done analytically and thus rapidly in a least-squares sense, yielding force constant parameters as the output. We herein apply this approach to derive force constant parameters for the AMBER-type energy expression. Test calculations on several different molecules show good performance of the PHF parameter sets in terms of how well they can reproduce QM-calculated frequencies. When soft bonds are involved in the target molecule as in the case of secondary building units of metal-organic frameworks, the MM-optimized geometry sometimes deviates significantly from the QM-optimized one. We show that this problem is rectified effectively by use of a simple procedure called Katachi that modifies the equilibrium bond distances and angles in bond-stretching and angle-bending terms. © 2016 Wiley Periodicals, Inc.

Atomic Spectral Methods for Ab Initio Molecular Electronic Energy Surfaces: Transitioning From Small-Molecule to Biomolecular-Suitable Approaches.

Continuing attention has addressed incorportation of the electronically dynamical attributes of biomolecules in the largely static first-generation molecular-mechanical force fields commonly employed in molecular-dynamics simulations. We describe here a universal quantum-mechanical approach to calculations of the electronic energy surfaces of both small molecules and large aggregates on a common basis which can include such electronic attributes, and which also seems well-suited to adaptation in ab initio molecular-dynamics applications. In contrast to the more familiar orbital-product-based methodologies employed in traditional small-molecule computational quantum chemistry, the present approach is based on an "ex-post-facto" method in which Hamiltonian matrices are evaluated prior to wave function antisymmetrization, implemented here in the support of a Hilbert space of orthonormal products of many-electron atomic spectral eigenstates familiar from the van der Waals theory of long-range interactions. The general theory in its various forms incorporates the early semiempirical atoms- and diatomics-in-molecules approaches of Moffitt, Ellison, Tully, Kuntz, and others in a comprehensive mathematical setting, and generalizes the developments of Eisenschitz, London, Claverie, and others addressing electron permutation symmetry adaptation issues, completing these early attempts to treat van der Waals and chemical forces on a common basis. Exact expressions are obtained for molecular Hamiltonian matrices and for associated energy eigenvalues as sums of separate atomic and interaction-energy terms, similar in this respect to the forms of classical force fields. The latter representation is seen to also provide a long-missing general definition of the energies of individual atoms and of their interactions within molecules and matter free from subjective additional constraints. A computer code suite is described for calculations of the many-electron atomic eigenspectra and the pairwise-atomic Hamiltonian matrices required for practical applications. These matrices can be retained as functions of scalar atomic-pair separations and employed in assembling aggregate Hamiltonian matrices, with Wigner rotation matrices providing analytical representations of their angular degrees of freedom. In this way, ab initio potential energy surfaces are obtained in the complete absence of repeated evaluations and transformations of the one- and two-electron integrals at different molecular geometries required in most ab inito molecular calculations, with large Hamiltonian matrix assembly simplified and explicit diagonalizations avoided employing partitioning and Brillouin-Wigner or Rayleigh-Schrödinger perturbation theory. Illustrative applications of the important components of the formalism, selected aspects of the scaling of the approach, and aspects of "on-the-fly" interfaces with Monte Carlo and molecular-dynamics methods are described in anticipation of subsequent applications to biomolecules and other large aggregates.

MutaBind estimates and interprets the effects of sequence variants on protein–protein interactions

Proteins engage in highly selective interactions with their macromolecular partners. Sequence variants that alter protein binding affinity may cause significant perturbations or complete abolishment of function, potentially leading to diseases. There exists a persistent need to develop a mechanistic understanding of impacts of variants on proteins. To address this need we introduce a new computational method MutaBind to evaluate the effects of sequence variants and disease mutations on protein interactions and calculate the quantitative changes in binding affinity. The MutaBind method uses molecular mechanics force fields, statistical potentials and fast side-chain optimization algorithms. The MutaBind server maps mutations on a structural protein complex, calculates the associated changes in binding affinity, determines the deleterious effect of a mutation, estimates the confidence of this prediction and produces a mutant structural model for download. MutaBind can be applied to a large number of problems, including determination of potential driver mutations in cancer and other diseases, elucidation of the effects of sequence variants on protein fitness in evolution and protein design. MutaBind is available at http://www.ncbi.nlm.nih.gov/projects/mutabind/.

Experimental and density functional study on electronic structure and electronic circular dichroism of the phenylpyrazole insecticides enantiomers and the probable chiral catabolites

The stable conformations of three phenylpyrazole insecticides enantiomers and their probable chiral catabolites, marked A, B, C, a, b and c, are identified via Monte Carlo searching with the MMFF94 molecular mechanics force field. The electronic circular dichroism of flufiprole (A) and ethiprole (B) was recorded. Moreover, the DFT method is utilized to optimize for the searched conformers. Then, the electronically excited states involving the first 30 excited states were computed using the time-dependent density functional theory method. The conformations selected to investigate in this article were the most stable conformers, and the UV and ECD spectra were in accord with the experimental values. The delocalized transition between benzene ring and pyrazole groups causes the strong absorptions of the electronic transitions at the UV–visible range. Three bands appear in the ECD spectra, in which the lower-energy ECD band is a delocalized πpy → πph* electronic transition. In addition, the higher and highest energy bands originate from the localized πph → πph* electronic transition. The calculated UV and ECD spectra were in good accordance with reported experimental values. Since the ECD spectrum at the B3LYP/6-311++G** level is indistinctively different from that at the B3LYP/6-31+G* level, it is necessary for the diffuse functions to be added to the 6-311++G** basis set, especially considering the solvent effect.

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods.

One of the largest challenges of computational chemistry is calculation of accurate free energies for the binding of a small molecule to a biological macromolecule, which has immense implications in drug development. It is well-known that standard molecular-mechanics force fields used in most such calculations have a limited accuracy. Therefore, there has been a great interest in improving the estimates using quantum-mechanical (QM) methods. We review here approaches involving explicit QM energies to calculate binding affinities, with an emphasis on the methods, rather than on specific applications. Many different QM methods have been employed, ranging from semiempirical QM calculations, via density-functional theory, to strict coupled-cluster calculations. Dispersion and other empirical corrections are mandatory for the approximate methods, as well as large basis sets for the stricter methods. QM has been used for the ligand, for a few crucial groups around the ligand, for all the closest atoms (200-1000 atoms), or for the full receptor-ligand complex, but it is likely that with a proper embedding it might be enough to include all groups within ∼6 Å of the ligand. Approaches involving minimized structures, simulations of the end states of the binding reaction, or full free-energy simulations have been tested.

Analysis of the conformational features of Watson–Crick duplex fragments by molecular mechanics and quantum mechanics methods

It is generally accepted that the important characteristic features of the Watson-Crick duplex originate from the molecular structure of its subunits. However, it still remains to elucidate what properties of each subunit are responsible for the significant characteristic features of the DNA structure. The computations of desoxydinucleoside monophosphates complexes with Na-ions using density functional theory revealed a pivotal role of DNA conformational properties of single-chain minimal fragments in the development of unique features of the Watson-Crick duplex. We found that directionality of the sugar-phosphate backbone and the preferable ranges of its torsion angles, combined with the difference between purines and pyrimidines. in ring bases, define the dependence of three-dimensional structure of the Watson-Crick duplex on nucleotide base sequence. In this work, we extended these density functional theory computations to the minimal' fragments of DNA duplex, complementary desoxydinucleoside monophosphates complexes with Na-ions. Using several computational methods and various functionals, we performed a search for energy minima of BI-conformation for complementary desoxydinucleoside monophosphates complexes with different nucleoside sequences. Two sequences are optimized using ab initio method at the MP2/6-31++G** level of theory. The analysis of torsion angles, sugar ring puckering and mutual base positions of optimized structures demonstrates that the conformational characteristic features of complementary desoxydinucleoside monophosphates complexes with Na-ions remain within BI ranges and become closer to the corresponding characteristic features of the Watson-Crick duplex crystals. Qualitatively, the main characteristic features of each studied complementary desoxydinucleoside monophosphates complex remain invariant when different computational methods are used, although the quantitative values of some conformational parameters could vary lying within the limits typical for the corresponding family. We observe that popular functionals in density functional theory calculations lead to the overestimated distances between base pairs, while MP2 computations and the newer complex functionals produce the structures that have too close atom-atom contacts. A detailed study of some complementary desoxydinucleoside monophosphate complexes with Na-ions highlights the existence of several energy minima corresponding to BI-conformations, in other words, the complexity of the relief pattern of the potential energy surface of complementary desoxydinucleoside monophosphate complexes. This accounts for variability of conformational parameters of duplex fragments with the same base sequence. Popular molecular mechanics force fields AMBER and CHARMM reproduce most of the conformational characteristics of desoxydinucleoside monophosphates and their complementary complexes with Na-ions but fail to reproduce some details of the dependence of the Watson-Crick duplex conformation on the nucleotide sequence.

A Unified AMBER-Compatible Molecular Mechanics Force Field for Thiolate-Protected Gold Nanoclusters.

We present transferable AMBER-compatible force field parameters for thiolate-protected gold nanoclusters. Five different sized clusters containing both organo-soluble and water-soluble thiolate ligands served as test systems in MD simulations, and parameters were validated against DFT and experimental results. The cluster geometries remain intact during the MD simulations in various solvents, and structural fluctuations and energetics showed agreement with DFT calculations. Experimental diffusion coefficients and crystal structures were also reproduced with sufficient accuracy. The presented parameter set contains the minimum number of cluster-specific parameters enabling the use of these parameters for several different gold nanoclusters. The parameterization of ligands can also be extended to different types of ligands.