The development of new reactions capable of catalytically transforming the inert C-H bonds of organic molecules into useful functional groups is an important and very active area of research. 1 With this process, problems associated with low reactivity and selectivity are compounded by an only emerging appreciation of the mechanistic possibilities. As a consequence, the discovery of new catalytic reactivity can be of tremendous impact. An illustrative class of C-H functionalization that is limited by mechanistic understanding is direct arylation. 2,3 With these reactions, the most common mechanism of C-H bond cleavage is electrophilic aromatic substitution (S E Ar) involving reaction of an electrophilic metal catalyst with an electron-rich, nucleophilic aromatic ring. 4,5 This pathway is fundamentally limiting since the vast majority of aromatic compounds are not sufficiently nucleophilic. 6 For example, simple and electron-deficient arenes have never been successfully employed in catalytic direct arylation (eq 1) except when a basic directing group can enable the formation of a metallacycle. 7,8 New mechanistic insights that overcome these constraints and enable catalytic direct arylation to be performed with currently inaccessible arene classes would not only be of tremendous importance in biaryl synthesis but would also be transformative in the rational design of other types of catalytic arene functionalization.Herein, we describe intermolecular direct arylation reactions of electron-deficient benzenes and associated computational studies indicating that metallacyclic intermediates are not involved. Underlying these new transformations is a mechanism that actually favors reaction with electron-deficient, C-H acidic benzeness constituting a complete inVersion of reactivity compared to the S E Ar pathway. Computational studies reveal the key C-H bond functionalization step occurs via a concerted arene metalation and carbon-hydrogen bond cleaving process, the accessibility of which depends directly on the acidity of the C-H bond being cleaved. These reactions are scalable, can employ a nearly equimolar ratio of the two benzene cross-coupling components, and produce perfluorobiphenyl products that have demonstrated importance in medicinal chemistry, 9 electron-transport devices, 10 organic light emitting diodes, 11 sensitizers for the photo-splitting of water, 12 and as elements in the rational design of liquid crystals. 13 It is anticipated that these new reactions will begin to replace the use of fluorobenzene organometallics in the synthesis of fluorobiaryl molecules and that the new reactivity should facilitate the design of other catalytic C-H bond functionalizations.As a starting point, we chose to examine the direct arylation of pentafluorobenzene since this substrate would not react via a S E Artype process. Reaction screens were performed with 4-bromotoluene as the second coupling partner, and efforts were made to achieve conditions that were operationally simple. We were excited to find that excellent ...

Predicting the rate of nonfacilitated permeation of solutes across lipid bilayers is important to drug design, toxicology, and signaling. These rates can be estimated using molecular dynamics simulations combined with the inhomogeneous solubility-diffusion model, which requires calculation of the potential of mean force and position-dependent diffusivity of the solute along the transmembrane axis. In this paper, we assess the efficiency and accuracy of several methods for the calculation of the permeability of a model DMPC bilayer to urea, benzoic acid, and codeine. We compare umbrella sampling, replica exchange umbrella sampling, adaptive biasing forces, and multiple-walker adaptive biasing forces for the calculation of the transmembrane PMF. No definitive advantage for any of these methods in their ability to predict the permeability coefficient Pm was found, provided that a sufficiently long equilibration is performed. For diffusivities, a Bayesian inference method was compared to a Generalized Langevin method, both being sensitive to chosen parameters and the slow relaxation of membrane defects. Agreement within 1.5 log units of the computed Pm with experiment is found for all permeants and methods. Remaining discrepancies can likely be attributed to limitations of the force field as well as slowly relaxing collective movements within the lipid environment. Numerical calculations based on model profiles show that Pm can be reliably estimated from only a few data points, leading to recommendations for calculating Pm from simulations.

The calculation of molecular electric moments, polarizabilities, and electrostatic potentials is a widespread application of quantum chemistry. Although a range of wave function and density functional theory (DFT) methods have been applied in these calculations, combined with a variety of basis sets, there has not been a comprehensive evaluation of how accurate these methods are. To benchmark the accuracy of these methods, the dipole moments and polarizabilities of a set of 46 molecules were calculated using a broad set of quantum chemical methods and basis sets. Wave function methods Hartree-Fock (HF), second-order Møller-Plesset (MP2), and coupled cluster-singles and doubles (CCSD) were evaluated, along with the PBE, TPSS, TPSSh, PBE0, B3LYP, M06, and B2PLYP DFT functionals. The cc-pVDZ, cc-pVTZ, aug-cc-pVDZ, aug-cc-pVTZ, and Sadlej cc-pVTZ basis sets were tested. The aug-cc-pVDZ, Sadlej cc-pVTZ, and aug-cc-pVTZ basis sets all yield results with comparable accuracy, with the aug-cc-pVTZ calculations being the most accurate. CCSD, MP2, or hybrid DFT methods using the aug-cc-pVTZ basis set are all able to predict dipole moments with RMSD errors in the 0.12-0.13 D range and polarizabilities with RMSD errors in the 0.30-0.38 Å(3) range. Calculations using Hartree-Fock theory systematically overestimated dipole moments and underestimate polarizabilities. The pure DFT functionals included in this study (PBE and TPSS) slightly underestimate dipole moments and overestimate polarizability. Polarization anisotropy and implications for charge fitting are discussed.

Knowledge of the hydration structure of Na(+) and K(+) in the liquid phase has wide ranging implications in the field of biological chemistry. Despite numerous experimental and computational studies, even basic features such as the coordination number of these alkali ions in liquid water, thought to play a critical role in selectivity, continue to be the subject of intensive debates. Simulations based on accurate potential energy surfaces offer one approach to resolve these issues by providing reliable results on ion hydration. In this article, we report the results from molecular dynamics simulations of Na(+) and K(+) hydration based on a novel and rigorous strategy designed to overcome the challenges of QM/MM simulations of solvent molecules in the liquid phase. In this method, which we call Flexible Inner Region Ensemble Separator (FIRES), the ion and a fixed number of nearest water molecules form a dynamical and flexible inner region that is represented with high level ab initio quantum mechanical (QM) methods, while the water molecules from the surrounding bulk form an outer region that is represented by a polarizable molecular mechanical (MM) force field. Simulations yield rigorously correct thermodynamic averages as long as the solvent molecules in the flexible inner and outer regions are not allowed to exchange. Extensive FIRES simulations were carried out based on a QM/MM model in which the Na(+) or K(+) ion and the 12 nearest water molecules were represented by high level ab initio methods (RI-MP2/def2-TZVP and density functional theory with PBE/def2-TZVP), while the surrounding MM water molecules were represented by the polarizable SWM4-NDP potential. On the basis of these results, the ion coordination numbers are estimated to be within the range of 5.7-5.8 for Na(+) and 6.9-7.0 for K(+).

A multitude of biological processes requires the participation of specific cations, such as H + , Na + , K + , Ca 2+ , and Mg 2+ . Many of these processes can take place only when proteins have the ability to discriminate between different ions with a very high fidelity. How this is possible is a fundamental question that has fascinated scientists for a long time. At the most fundamental level, it is anticipated that ion selectivity must result from a delicate balance of strong interactions. Yet, identifying and quantifying the key microscopic factors is difficult, as many of these cannot be directly measured by experiments. Theory and computations can contribute by providing a virtual route to complement the missing information. Because ion selectivity is often dominated by thermodynamic factors, detailed molecular dynamics (MD) free energy simulations become important tools. This was vividly illustrated early on with studies of ion solvation (Straatsma and Berendsen, 1988;Åqvist, 1990) and ion-selective systems (Lybrand et al., 1986;Grootenhuis and Kollman, 1989;Åqvist, 1992). These pioneering studies inspired our own efforts.In this Perspective, we aim to present our understanding of ion selectivity as it has evolved over approximately 15 years from studies based on various specific structures: gramicidin A channels (e.g.

This is a review. Non-electrolytic compounds typically cross cell membranes by passive diffusion. The rate of permeation is dependent on the chemical properties of the solute and the composition of the lipid bilayer membrane. Predicting the permeability coefficient of a solute is important in pharmaceutical chemistry and toxicology. Molecular simulation has proven to be a valuable tool for modeling permeation of solutes through a lipid bilayer. In particular, the solubility-diffusion model has allowed for the quantitative calculation of permeability coefficients. The underlying theory and computational methods used to calculate membrane permeability are reviewed. We also discuss applications of these methods to examine the permeability of solutes and the effect of membrane composition on permeability. The application of coarse grain and polarizable models is discussed. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Methods for the calculation of the pKa ionizable amino acids are valuable tools for understanding pH-dependent properties of proteins. Cysteine is unique among the amino acids because of the chemical reactivity of its thiol group (S-H), which plays an instrumental role in several biochemical and regulatory functions. The acidity of noncatalytic cysteine residues is a factor in their susceptibility to chemical modification. Despite the plethora of existing pKa computing methods, no definitive protocol exists for accurately calculating the pKa's of cysteine residues in proteins. A cysteine pKa test set was developed, which is comprised of 18 cysteine residues in 12 proteins where the pKa's have been determined experimentally and an experimental structure is available. The pKa's of these residues were calculated using three methods that use an implicit solvent model (H++, MCCE, and PROPKA) and an all-atom replica-exchange thermodynamic integration approach with the CHARMM36 and AMBER ff99SB-ILDNP force fields. The models that use implicit solvation methods were generally unreliable in predicting cysteine residue pKa's, with RMSDs between 3.41 and 4.72 pKa units. On average, the explicit solvent methods performed better than the implicit solvent methods. RMSD values of 2.40 and 3.20 were obtained for simulations with the CHARMM36 and AMBER ff99SB-ILDNP force fields, respectively. Further development of these methods is necessary because the performance of the best method is similar to that of the null-model (RMSD = 2.74) and these differences in RMSD are of limited statistical significance given the small size of our test set.

The textbook mechanism for the addition of a thiol to an olefin is the Michael-type addition, which involves a nucleophilic attack of a thiolate anion on an alkene to form a carbanion intermediate. Previous computational models of these reactions have proposed alternative mechanisms, as no minimum corresponding to the carbanion intermediate was present on the potential energy surface. We show that many popular pure and hybrid DFT functionals, such as PBE and B3LYP, erroneously predict that the carbanion is not an intermediate, favoring a noncovalent charge-transfer complex stabilized spuriously by delocalization error. Range-separated DFT functionals correct this problem and predict stable carbanion structures and energies. In particular, calculations using the ωB97X-D functional are in close agreement with CCSD(T) data for the structures and energies of a series of thio-carbanions. Rangeseparated functionals will make it possible to model the reaction mechanisms of Michael-type additions that occur in biochemistry, such as the covalent modification of a cysteine side chain by drugs containing an electrophilic double bond.