Density functional solvation model based on CM2 atomic charges

Thermodynamic and kinetic modeling of electrocatalytic reactions using a first-principles approach

The computational modeling of electrochemical interfaces and their applications in electrocatalysis has attracted great attention in recent years. While tremendous progress has been made in this area, however, the accurate atomistic descriptions at the electrode/electrolyte interfaces remain a great challenge. The Computational Hydrogen Electrode (CHE) method and continuum modeling of the solvent and electrolyte interactions form the basis for most of these methodological developments. Several posterior corrections have been added to the CHE method to improve its accuracy and widen its applications. The most recently developed grand canonical potential approaches with the embedded diffuse layer models have shown considerable improvement in defining interfacial interactions at electrode/electrolyte interfaces over the state-of-the-art computational models for electrocatalysis. In this Review, we present an overview of these different computational models developed over the years to quantitatively probe the thermodynamics and kinetics of electrochemical reactions in the presence of an electrified catalyst surface under various electrochemical environments. We begin our discussion by giving a brief picture of the different continuum solvation approaches, implemented within the ab initio method to effectively model the solvent and electrolyte interactions. Next, we present the thermodynamic and kinetic modeling approaches to determine the activity and stability of the electrocatalysts. A few applications to these approaches are also discussed. We conclude by giving an outlook on the different machine learning models that have been integrated with the thermodynamic approaches to improve their efficiency and widen their applicability.

Synthesis, structure and in vitro antiproliferative effects of alkyne-linked 1,2,4-thiadiazole hybrids including erlotinib- and ferrocene-containing derivatives

Chemotherapy is an indispensable tool to treat cancer, therefore, the development of new drugs that can treat cancer with minimal side effects and lead to more favorable prognoses is of crucial importance. A series of eleven novel 1,2,4-thiadiazoles bearing erlotinib (a known anticancer agent), phenylethynyl, ferrocenyl, and/or ferrocenethynyl moieties were synthesized in this work and characterized by NMR, IR and mass spectroscopies. The solid-phase structures were determined by single-crystal X-ray diffraction. Partial isomerisation of bis(erlotinib)-1,2,4-thiadiazole into its 1,3,4-thiadiazole isomer, leading to the isolation of a 3 : 2 isomer mixture, was observed and a plausible mechanism for isomerisation is suggested. The in vitro cytostatic effect and the long-term cytotoxicity of these thiadiazole-hybrids, as well as that of erlotinib, 3,5-dichloro-1,2,4-thiadiazole and 3,5-diiodo-1,2,4-thiadiazole were investigated against A2058 human melanoma, HepG2 human hepatocellular carcinoma, U87 human glioma, A431 human epidermoid carcinoma, and PC-3 human prostatic adenocarcinoma cell lines. Interestingly, erlotinib did not exhibit a significant cytostatic effect against these cancer cell lines. 1,2,4-Thiadiazole hybrids bearing one erlotinib moiety or both an iodine and a ferrocenethynyl group, as well as 3,5-diiodo-1,2,4-thiadiazole demonstrated good to moderate cytostatic effects. Among the synthesized 1,2,4-thiadiazole hybrids, the isomer mixture of bis-erlotinib substituted 1,2,4- and 1,3,4-thiadiazoles showed the most potent activity. This isomer mixture was proven to be the most effective in long-term cytotoxicity, too. 3,5-Diiodo-1,2,4-thiadiazole and its hybrid with one erlotinib fragment were also highly active against A431 and PC-3 proliferation. These novel compounds may serve as new leads for further study of their antiproliferative properties.

Computational studies of biologically active alkaloids of plant origin: an overview

Computational studies nowadays constitute a crucial source of information for drug development, because they provide information on many molecular properties and also enable predictions of the properties of not-yet-synthesized compounds. Alkaloids are a vast group of natural products exhibiting a variety of biological activities, many of which are interesting for drug development. On the other hand, computational studies of biologically active alkaloids have so far mostly focused on few particularly relevant or “popular” molecules, such as quinine, caffeine, or cocaine, with only few works on the other molecules. The present work offers an overview of existing computational studies on alkaloid molecules, from the earliest ones to the most recent, and considering all the theoretical approaches with which studies have been performed (both quantum mechanics and molecular dynamics). The considered studies are grouped according to their objectives and outcomes, such as conformational analysis of alkaloid molecules, effects of selected solvents on their properties, docking studies aimed at better understanding of the interactions between alkaloid molecules and biological targets, studies focusing on structure activity relationships, and computational studies performed to confirm experimental results. It is concluded that it would be important that computational studies on many other alkaloid molecules are performed and their results made available, covering their different classes as well as the variety of their biological activities, to attain better understanding of the properties not only of individual molecules, but also of groups of related molecules and of the overall alkaloids family.

Solvent and Substituent Effects on the Phosphine + CO2 Reaction

A theoretical study of the substituent and solvent effects on the reaction of phosphines with CO2 has been carried out by means of Møller-Plesset (MP2) computational level calculations and continuum polarizable method (PCM) solvent models. Three stationary points along the reaction coordinate have been characterized, a pre-transition state (TS) assembly in which a pnicogen bond or tetrel bond is established between the phosphine and the CO2 molecule, followed by a transition state, and leading finally to the adduct in which the P–C bond has been formed. The solvent effects on the stability and geometry of the stationary points are different. Thus, the pnicogen bonded complexes are destabilized as the dielectric constant of the solvent increases while the opposite happens within the adducts with the P–C bond and the TSs trend. A combination of the substituents and solvents can be used to control the most stable minimum.

Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with Application to Chemical Shift Predictions

Full-protein nuclear magnetic resonance (NMR) shielding constants based on ab initio calculations are desirable, because they can assist in elucidating protein structures from NMR experiments. In this work, we present NMR shielding constants computed using a new automated fragmentation (J. Phys. Chem. B 2009, 113, 10380-10388) approach in the framework of polarizable embedding density functional theory. We extend our previous work to give both basis set recommendations and comment on how large the quantum mechanical region should be to successfully compute ¹³C NMR shielding constants that are comparable with experiment. The introduction of a probabilistic linear regression model allows us to substantially reduce the number of snapshots that are needed to make comparisons with experiment. This approach is further improved by augmenting snapshot selection with chemical shift predictions by which we can obtain a representative subset of snapshots that gives the smallest predicted error, compared to experiment. Finally, we use this subset of snapshots to calculate the NMR shielding constants at the PE-KT3/pcSseg-2 level of theory for all atoms in the protein GB3.

Molecular Dynamics Simulation Study of Permeation of Molecules through Skin Lipid Bilayer

Stratum Corneum (SC), the outermost layer of skin, is mainly responsible for skin's barrier function. The complex lipid matrix of SC determines these barrier properties. In this study, the lipid matrix is modeled as an equimolar mixture of ceramide (CER), cholesterol (CHOL), and free fatty acid (FFA). The permeation of water, oxygen, ethanol, acetic acid, urea, butanol, benzene, dimethyl sulfoxide (DMSO), toluene, phenol, styrene, and ethylbenzene across this layer is studied using a constrained MD simulations technique. Several long constrained simulations are performed at a skin temperature of 310 K under NPT conditions. The free energy profiles and diffusion coefficients along the bilayer normal have been calculated for each molecule. Permeability coefficients are also calculated and compared with experimental data. The main resistance for the permeation of hydrophilic and hydrophobic permeants has been found to be in the interior of the lipid bilayer and near the lipid-water interface, respectively. The obtained permeability is found to be a few orders of magnitude higher than experimental values for hydrophilic molecules while for hydrophobic molecules more discrepancy was observed. Overall, the qualitative ranking is consistent with the experiments.

Implementation of the SM12 Solvation Model into ADF and Comparison with COSMO

In this article, an implementation of the newest iteration of the Minnesota solvation model, SM12, into the Amsterdam density functional (ADF) computational package is presented. ADF makes exclusive use of Slater-type orbitals (STO), which correctly represent the true atomic orbitals for atoms, whereas SM12 and the underlying charge model 5 (CM5) have previously only been tested on Gaussian-type orbitals (GTO). This new implementation is used to prove the basis set independence of both CM5 and SM12. A detailed comparison of the SM12 and COSMO solvation models, as implemented in ADF, is also presented. We show that this new implementation of SM12 has a mean unsigned error (MUE) of 0.68 kcal/mol for 272 molecules in water solvent, 4.10 kcal/mol MUE for 112 charged ions in water, and 0.92 kcal/mol MUE for 197 solvent calculations of various molecules. SM12 outperforms COSMO for all neutral molecules and performs as well as COSMO for cationic molecules, only falling short when anionic molecules are taken into consideration, likely due to CM5's use of Hirshfeld charges and their poor description of anionic molecules, though CM5 seems to improve upon this discrepancy.

KECSA-Movable Type Implicit Solvation Model (KMTISM)

Computation of the solvation free energy for chemical and biological processes has long been of significant interest. The key challenges to effective solvation modeling center on the choice of potential function and configurational sampling. Herein, an energy sampling approach termed the “Movable Type” (MT) method, and a statistical energy function for solvation modeling, “Knowledge-based and Empirical Combined Scoring Algorithm” (KECSA) are developed and utilized to create an implicit solvation model: KECSA-Movable Type Implicit Solvation Model (KMTISM) suitable for the study of chemical and biological systems. KMTISM is an implicit solvation model, but the MT method performs energy sampling at the atom pairwise level. For a specific molecular system, the MT method collects energies from prebuilt databases for the requisite atom pairs at all relevant distance ranges, which by its very construction encodes all possible molecular configurations simultaneously. Unlike traditional statistical energy functions, KECSA converts structural statistical information into categorized atom pairwise interaction energies as a function of the radial distance instead of a mean force energy function. Within the implicit solvent model approximation, aqueous solvation free energies are then obtained from the NVT ensemble partition function generated by the MT method. Validation is performed against several subsets selected from the Minnesota Solvation Database v2012. Results are compared with several solvation free energy calculation methods, including a one-to-one comparison against two commonly used classical implicit solvation models: MM-GBSA and MM-PBSA. Comparison against a quantum mechanics based polarizable continuum model is also discussed (Cramer and Truhlar’s Solvation Model 12).

Self-Consistent Reaction Field Model for Aqueous and Nonaqueous Solutions Based on Accurate Polarized Partial Charges

A new universal continuum solvation model (where "universal" denotes applicable to all solvents), called SM8, is presented. It is an implicit solvation model, also called a continuum solvation model, and it improves on earlier SMx universal solvation models by including free energies of solvation of ions in nonaqueous media in the parametrization. SM8 is applicable to any charged or uncharged solute composed of H, C, N, O, F, Si, P, S, Cl, and/or Br in any solvent or liquid medium for which a few key descriptors are known, in particular dielectric constant, refractive index, bulk surface tension, and acidity and basicity parameters. It does not require the user to assign molecular-mechanics types to an atom or group; all parameters are unique and continuous functions of geometry. It may be used with any level of electronic structure theory as long as accurate partial charges can be computed for that level of theory; we recommend using it with self-consistently polarized Charge Model 4 or other self-consistently polarized class IV charges, in which case analytic gradients are available. The model separates the observable solvation free energy into two components:  the long-range bulk electrostatic contribution arising from a self-consistent reaction field treatment using the generalized Born approximation for electrostatics is augmented by the non-bulk-electrostatic contribution arising from short-range interactions between the solute and solvent molecules in the first solvation shell. The cavities for the bulk electrostatics calculation are defined by superpositions of nuclear-centered spheres whose sizes are determined by intrinsic atomic Coulomb radii. The radii used for aqueous solution are the same as parametrized previously for the SM6 aqueous solvation model, and the radii for nonaqueous solution are parametrized by a training set of 220 bare ions and 21 clustered ions in acetonitrile, methanol, and dimethyl sulfoxide. The non-bulk-electrostatic terms are proportional to the solvent-accessible surface areas of the atoms of the solute and have been parametrized using solvation free energies for a training set of 2346 solvation free energies for 318 neutral solutes in 90 nonaqueous solvents and water and 143 transfer free energies for 93 neutral solutes between water and 15 organic solvents. The model is tested with three density functionals and with four basis sets:  6-31+G(d,p), 6-31+G(d), 6-31G(d), and MIDI!6D. The SM8 model achieves mean unsigned errors of 0.5-0.8 kcal/mol in the solvation free energies of tested neutrals and mean unsigned errors of 2.2-7.0 kcal/mol for ions. The model outperforms the earlier SM5.43R and SM7 universal solvation models as well as the default Polarizable Continuum Model (PCM) implemented in Gaussian 98/03, the Conductor-like PCM as implemented in GAMESS, Jaguar's continuum model based on numerical solution of the Poisson equation, and the GCOSMO model implemented in NWChem.

Computational electrochemistry: prediction of liquid-phase reduction potentials

This article reviews recent developments and applications in the area of computational electrochemistry. Our focus is on predicting the reduction potentials of electron transfer and other electrochemical reactions and half-reactions in both aqueous and nonaqueous solutions. Topics covered include various computational protocols that combine quantum mechanical electronic structure methods (such as density functional theory) with implicit-solvent models, explicit-solvent protocols that employ Monte Carlo or molecular dynamics simulations (for example, Car-Parrinello molecular dynamics using the grand canonical ensemble formalism), and the Marcus theory of electronic charge transfer. We also review computational approaches based on empirical relationships between molecular and electronic structure and electron transfer reactivity. The scope of the implicit-solvent protocols is emphasized, and the present status of the theory and future directions are outlined.

The alkaline hydrolysis of sulfonate esters: challenges in interpreting experimental and theoretical data

Sulfonate ester hydrolysis has been the subject of recent debate, with experimental evidence interpreted in terms of both stepwise and concerted mechanisms. In particular, a recent study of the alkaline hydrolysis of a series of benzene arylsulfonates (Babtie et al., Org. Biomol. Chem. 10, 2012, 8095) presented a nonlinear Brønsted plot, which was explained in terms of a change from a stepwise mechanism involving a pentavalent intermediate for poorer leaving groups to a fully concerted mechanism for good leaving groups and supported by a theoretical study. In the present work, we have performed a detailed computational study of the hydrolysis of these compounds and find no computational evidence for a thermodynamically stable intermediate for any of these compounds. Additionally, we have extended the experimental data to include pyridine-3-yl benzene sulfonate and its N-oxide and N-methylpyridinium derivatives. Inclusion of these compounds converts the Brønsted plot to a moderately scattered but linear correlation and gives a very good Hammett correlation. These data suggest a concerted pathway for this reaction that proceeds via an early transition state with little bond cleavage to the leaving group, highlighting the care that needs to be taken with the interpretation of experimental and especially theoretical data.

Generalized Born Solvation Model SM12

We present a new self-consistent reaction-field implicit solvation model that employs the generalized Born approximation for the bulk electrostatic contribution to the free energy of solvation. The new solvation model (SM) is called SM12 (where ″12″ stands for 2012), and it is available with two sets of parameters, SM12CM5 and SM12ESP. The SM12CM5 parametrization is based on CM5 partial atomic charges, and the SM12ESP parametrization is based on charges derived from a quantum-mechanically calculated electrostatic potential (ESP) (in particular, we consider ChElPG and Merz-Kollman-Singh charges). The model was parametrized over 10 combinations of theoretical levels including the 6-31G(d) and MG3S basis sets and the B3LYP, mPW1PW, M06-L, M06, and M06-2X density functionals against 2979 reference experimental data. The reference data include 2503 solvation free energies and 144 transfer free energies of neutral solutes composed of H, C, N, O, F, Si, P, S, Cl, Br, and I in water and in 90 organic solvents as well as 332 solvation free energies of singly charged anions and cations in acetonitrile, dimethyl sulfoxide, methanol, and water. The advantages of the new solvation model over our previous generalized Born model (SM8) and all other previous generalized Born solvation models are (i) like the SMD model based on electron density distributions, it may be applied with a single set of parameters with arbitrary extended basis sets, whereas the SM8 model involves CM4 or CM4M charges that become unstable for extended basis sets, (ii) it is parametrized against a more diverse training sets than any previous solvation model, and (iii) it is defined for the entire periodic table.

Free energy calculation of permeant-membrane interactions using molecular dynamics simulations

Nanotoxicology, the science concerned with the safe use of nanotechnology and nanostructure design for biological applications, is a field of research that has recently received great attention, as a result of the rapid growth in nanotechnology. Many nanostructures are of a scale and chemical composition similar to many biomolecular environments, and recent papers have reported evident toxicity of selected nanoparticles. Molecular simulations can help develop a mechanistic understanding of how structural properties affect bioactivity. In this chapter, we describe how to compute the free energy of interactions between cellular membranes and benzene, the main constituent of some toxic carbonaceous particles, with well-tempered metadynamics. This algorithm reconstructs the free energy surface and accelerates rare events in a coarse-grained representation of the system.

Fragment density functional theory calculation of NMR chemical shifts for proteins with implicit solvation

Fragment density functional theory (DFT) calculation of NMR chemical shifts for several proteins (Trp-cage, Pin1 WW domain, the third IgG-binding domain of Protein G (GB3) and human ubiquitin) has been carried out. The present study is based on a recently developed automatic fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach but the solvent effects are included by using the PB (Poisson-Boltzmann) model. Our calculated chemical shifts of (1)H and (13)C for these four proteins are in excellent agreement with experimentally measured values and represent clear improvement over that from the gas phase calculation. However, although the inclusion of the solvent effect also improves the computed chemical shifts of (15)N, the results do not agree with experimental values as well as (1)H and (13)C. Our study also demonstrates that AF-QM/MM calculated results accurately reproduce the separation of α-helical and β-sheet chemical shifts for (13)C(α) atoms in proteins, and using the (1)H chemical shift to discriminate the native structure of proteins from decoys is quite remarkable.

Dipole preserving and polarization consistent charges

A method for estimating dipole preserving and polarization consistent (DPPC) charges is described, which reproduces exactly the molecular dipole moment as well as the local, atomic hybridization dipoles determined from the corresponding wave function and can yield accurate molecular polarization. The method is based on a model described by Thole and van Duijnen and a new feature is introduced to treat molecular polarization. Thus, the DPPC method offers a convenient procedure to describe molecular polarization in applications using semiempirical models and ab initio molecular orbital theory with relatively small basis functions such as 6-31+G(d,p) or without inclusion of electron correlation; these methods tend to underestimate molecular polarizability. The trends of the DPPC partial atomic charges are found to be in good accord with those of the CM2 model, a class IV charge analysis method that has been used in a variety of applications. The DPPC method is illustrated to mimic the correct molecular polarizability in a water dimer test case and in water-halide ion complexes using the explicit polarization (X-Pol) potential with the Austin model 1 Hamiltonian.

Linear free energy relationships between aqueous phase hydroxyl radical reaction rate constants and free energy of activation

The hydroxyl radical (HO(•)) is a strong oxidant that reacts with electron-rich sites on organic compounds and initiates complex radical chain reactions in aqueous phase advanced oxidation processes (AOPs). Computer based kinetic modeling requires a reaction pathway generator and predictions of associated reaction rate constants. Previously, we reported a reaction pathway generator that can enumerate the most important elementary reactions for aliphatic compounds. For the reaction rate constant predictor, we develop linear free energy relationships (LFERs) between aqueous phase literature-reported HO(•) reaction rate constants and theoretically calculated free energies of activation for H-atom abstraction from a C-H bond and HO(•) addition to alkenes. The theoretical method uses ab initio quantum mechanical calculations, Gaussian 1-3, for gas phase reactions and a solvation method, COSMO-RS theory, to estimate the impact of water. Theoretically calculated free energies of activation are found to be within approximately ±3 kcal/mol of experimental values. Considering errors that arise from quantum mechanical calculations and experiments, this should be within the acceptable errors. The established LFERs are used to predict the HO(•) reaction rate constants within a factor of 5 from the experimental values. This approach may be applied to other reaction mechanisms to establish a library of rate constant predictions for kinetic modeling of AOPs.

Reactivity of alkyl polyhalides toward granular iron: development of QSARs and reactivity cross correlations for reductive dehalogenation

Attempts to develop quantitative structure-activity relationships (QSARs) for reductive dehalogenation by granular iron have been hindered by the unavailability of high quality predictor variables, have included relatively few compounds, and on occasion have relied on data lacking internal consistency. We herein investigate the reduction of 24 alkyl polyhalides by granular iron and the better-defined, homogeneous reductants Cr(H(2)O)(6)(2+) and an Fe(II) porphyrin. QSARs were constructed with a new set of computationally derived gas phase homolytic carbon-halogen bond dissociation energies and solvated one-electron reduction potentials determined using a quantum chemistry composite method (G3MP2). Reactivity cross correlations between reductant systems were also developed. Reactivity trends were generally consistent among all reductants and revealed pronounced structural influences. Compounds reduced at C-Br were orders of magnitude more reactive than analogues reduced at C-Cl; the number and identity of α- (Br ∼ Cl > CH(3) > F > H) and β-substituents (Br > Cl) also influenced reactivity. Nonlinearities encountered during QSAR and cross correlation development suggest that reactions of highly halogenated alkyl polyhalides with granular iron are limited by mass transfer, as supported by estimates of mass transfer coefficients. For species not suspected to exhibit mass transfer limitations, reasonably strong cross correlations and comparable substituent effects are consistent with dissociative electron transfer as the rate-determining step.

Free Energies of Solvation with Surface, Volume, and Local Electrostatic Effects and Atomic Surface Tensions to Represent the First Solvation Shell

Building on the SVPE (surface and volume polarization for electrostatics) model for electrostatic contributions to the free energy of solvation with explicit consideration of both surface and volume polarization effects, on the SMx approach to including first-solvation-shell contributions, and on the linear relationship between the electric field and short-range electrostatic contributions found by Chipman, we have developed a new method for computing absolute aqueous solvation free energies by combining the SVPE method with semiempirical terms that account for effects beyond bulk electrostatics. The new method is called SMVLE, and the elements it contains are denoted by SVPE-CDSL where SVPE denotes accounting for bulk electrostatic interactions between solute and solvent with both surface and volume contributions, CDS denotes the inclusion of solvent cavitation, changes in dispersion energy, and possible changes in local solvent structure by a semiempirical term utilizing geometry-dependent atomic surface tensions as implemented in SMx models, and L represents the local electrostatic effect derived from the outward-directed normal electric field on the cavity surface. The semiempirical CDS and L terms together represent the deviation of short-range contributions to the free energy of solvation from those accounted for by the SVPE term based on the bulk solvent dielectric constant. A solute training set containing a broad range of molecules used previously in the development of SM6 is used here for SMVLE model calibration. The aqueous solvation free energies predicted by the parameterized SMVLE model correlate exceedingly well with experimental values. The square of the correlation coefficient is 0.9949 and the slope is 1.0079. Comparison of the final SMVLE model against the earlier SMx solvation model shows that the parameterized SMVLE model not only yields good accuracy for neutrals but also significantly increases the accuracy for ions, making it the best implicit solvation model to date for aqueous solvation free energies of ions. The semiempirical terms associated with the outward-directed electric field account in a physical way for the improvement in the predictive accuracy for ions. The SMVLE method greatly decreases the need to include explicit water molecules for accurate modeling of solvation free energies of ions.

Protein NMR chemical shift calculations based on the automated fragmentation QM/MM approach

An automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach has been developed to routinely calculate ab initio protein NMR chemical shielding constants. The AF-QM/MM method is linear-scaling and trivially parallel. A general fragmentation scheme is employed to generate each residue-centric region which is treated by quantum mechanics, and the environmental electrostatic field is described with molecular mechanics. The AF-QM/MM method shows good agreement with standard self-consistent field (SCF) calculations of the NMR chemical shieldings for the mini-protein Trp cage. The root-mean-square errors (RMSEs) for 1H, 13C, and 15N NMR chemical shieldings are equal to or less than 0.09, 0.32, and 0.78 ppm, respectively, for all Hartree-Fock (HF) and density functional theory (DFT) calculations reported in this work. The environmental electrostatic potential is necessary to accurately reproduce the NMR chemical shieldings using the AF-QM/MM approach. The point-charge models provided by AMBER, AM1/CM2, PM3/CM1, and PM3/CM2 all effectively model the electrostatic field. The latter three point-charge models are generated via semiempirical linear-scaling SCF calculations of the entire protein system. The correlations between experimental 1H NMR chemical shifts and theoretical predictions are >0.95 for AF-QM/MM calculations using B3LYP with the 6-31G**, 6-311G**, and 6-311++G** basis sets. Our study, not unexpectedly, finds that conformational changes within a protein structure play an important role in the accurate prediction of experimental NMR chemical shifts from theory.

Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions

We present a new continuum solvation model based on the quantum mechanical charge density of a solute molecule interacting with a continuum description of the solvent. The model is called SMD, where the "D" stands for "density" to denote that the full solute electron density is used without defining partial atomic charges. "Continuum" denotes that the solvent is not represented explicitly but rather as a dielectric medium with surface tension at the solute-solvent boundary. SMD is a universal solvation model, where "universal" denotes its applicability to any charged or uncharged solute in any solvent or liquid medium for which a few key descriptors are known (in particular, dielectric constant, refractive index, bulk surface tension, and acidity and basicity parameters). The model separates the observable solvation free energy into two main components. The first component is the bulk electrostatic contribution arising from a self-consistent reaction field treatment that involves the solution of the nonhomogeneous Poisson equation for electrostatics in terms of the integral-equation-formalism polarizable continuum model (IEF-PCM). The cavities for the bulk electrostatic calculation are defined by superpositions of nuclear-centered spheres. The second component is called the cavity-dispersion-solvent-structure term and is the contribution arising from short-range interactions between the solute and solvent molecules in the first solvation shell. This contribution is a sum of terms that are proportional (with geometry-dependent proportionality constants called atomic surface tensions) to the solvent-accessible surface areas of the individual atoms of the solute. The SMD model has been parametrized with a training set of 2821 solvation data including 112 aqueous ionic solvation free energies, 220 solvation free energies for 166 ions in acetonitrile, methanol, and dimethyl sulfoxide, 2346 solvation free energies for 318 neutral solutes in 91 solvents (90 nonaqueous organic solvents and water), and 143 transfer free energies for 93 neutral solutes between water and 15 organic solvents. The elements present in the solutes are H, C, N, O, F, Si, P, S, Cl, and Br. The SMD model employs a single set of parameters (intrinsic atomic Coulomb radii and atomic surface tension coefficients) optimized over six electronic structure methods: M05-2X/MIDI!6D, M05-2X/6-31G, M05-2X/6-31+G, M05-2X/cc-pVTZ, B3LYP/6-31G, and HF/6-31G. Although the SMD model has been parametrized using the IEF-PCM protocol for bulk electrostatics, it may also be employed with other algorithms for solving the nonhomogeneous Poisson equation for continuum solvation calculations in which the solute is represented by its electron density in real space. This includes, for example, the conductor-like screening algorithm. With the 6-31G basis set, the SMD model achieves mean unsigned errors of 0.6-1.0 kcal/mol in the solvation free energies of tested neutrals and mean unsigned errors of 4 kcal/mol on average for ions with either Gaussian03 or GAMESS.

Performance of SM6, SM8, and SMD on the SAMPL1 test set for the prediction of small-molecule solvation free energies

The SM6, SM8, and SMD quantum mechanical aqueous continuum solvation models are applied to predict free energies of aqueous solvation for 61 molecules in the SAMPL1 test set described elsewhere (Guthrie. J. Phys. Chem. B 2009, 113, 4501-4507). For direct comparison to other models, frozen geometries, provided by Guthrie, were used together with the M06-2X density functional and the 6-31G(d) basis set. For the bulk electrostatic component of the solvation free energy, SM6 and SM8 employ a generalized Born model that uses polarized discrete partial atomic charges to model the electron density, with these charges being calculated by the CM4 and CM4M class IV charge models, respectively; SMD uses the polarized continuous quantum mechanical charge density. If five sulfonylureas are removed from the SAMPL1 set, the root-mean-square deviations (RMSDs) of SM6, SM8, and SMD on the remaining 56 molecules are 2.4, 2.6, and 2.5 kcal mol(-1), respectively. The SM6, SM8, and SMD RMSDs on the five sulfonylureas are 14.2, 12.6, and 11.1 kcal mol(-1), respectively; however, we suggest that the uncertainty in the target solvation free energies for these molecules may be quite large.

Assessment of nonequilibrium free energy methods

One of the factors preventing the general application of free energy methods in rational drug design remains the lack of sufficient computational resources. Many nonequilibrium (NE) free energy methods, however, are easily made embarrassingly parallel in comparison to equilibrium methods and may be conveniently run on desktop computers using distributed computing software. In recent years, there has been a proliferation of NE methods, but the general applicability of these approaches has not been determined. In this study, a subset including only those NE methods which are easily parallelised were considered for examination, with a view to their application to the prediction of protein-ligand binding affinities. A number of test systems were examined, including harmonic oscillator (HO) systems and the calculation of relative free energies of hydration of water-methane. The latter system uses identical potentials to the protein ligand case and is therefore an appropriate model system on which methods may be tested. As well as investigating existing protocols, a replica exchange NE approach was developed, which was found to offer advantages over conventional methods. It was found that Rosenbluth-based approaches to optimizing the NE work values used in NE free energy estimates were not consistent in the improvements in accuracy achieved and that, given their computational cost, the simple approach of taking each work value in an unbiased way is to be preferred. Of the two free energy estimators examined, Bennett's acceptance ratio was the most consistent and is, therefore, to be preferred over the Jarzynski estimator. The recommended protocols may be run very efficiently within a distributed computing environment and are of similar accuracy and precision to equilibrium free energy methods.

Hit identification and binding mode predictions by rigorous free energy simulations

The identification of lead molecules using computational modeling often relies on approximate, high-throughput approaches, of limited accuracy. We show here that, with a methodology we recently developed, it is possible to predict the relative binding free energies of structurally diverse ligands of the estrogen receptor-alpha using a rigorous statistical thermodynamics approach. Predictions obtained from the simulations with an explicit solvation model are in good qualitative agreement with experimental data, while simulations with implicit solvent models or rank ordering by empirical scoring functions yield predictions of lower quality. In addition, it is shown that free energy techniques can be used to select the most likely binding mode from a set of possible orientations generated by a docking program. It is suggested that the free energy techniques outlined in this study can be used to rank-order, by potency, structurally diverse compounds identified by virtual screening, de novo design or scaffold hopping programs.

Performance of SM8 on a test to predict small-molecule solvation free energies

The SM8 quantum mechanical aqueous continuum solvation model is applied to a 17-molecule test set proposed by Nicholls et al. (J. Med. Chem. 2008, 51, 769) to predict free energies of solvation. With the M06-2X density functional, the 6-31G(d) basis set, and CM4M charge model, the root-mean-square error (RMSE) of SM8 is 1.08 kcal mol(-1) for aqueous geometries and 1.14 kcal mol(-1) for gas-phase geometries. These errors compare favorably with optimal explicit and continuum models reported by Nicholls et al., having RMSEs of 1.33 and 1.87 kcal mol(-1), respectively. Other models examined by these workers had RMSEs of 1.5-2.6 kcal mol(-1). We also explore the use of other density functionals and charge models with SM8 and the RMSE increases to 1.21 kcal mol(-1) for mPW1/CM4 with gas-phase geometries, to 1.50 kcal mol(-1) for M06-2X/CM4 with gas-phase geometries, and to 1.27-1.64 kcal mol(-1) with three different models at B3LYP gas-phase geometries.

Polarizable atomic multipole solutes in a Poisson-Boltzmann continuum

Modeling the change in the electrostatics of organic molecules upon moving from vacuum into solvent, due to polarization, has long been an interesting problem. In vacuum, experimental values for the dipole moments and polarizabilities of small, rigid molecules are known to high accuracy; however, it has generally been difficult to determine these quantities for a polar molecule in water. A theoretical approach introduced by Onsager [J. Am. Chem. Soc. 58, 1486 (1936)] used vacuum properties of small molecules, including polarizability, dipole moment, and size, to predict experimentally known permittivities of neat liquids via the Poisson equation. Since this important advance in understanding the condensed phase, a large number of computational methods have been developed to study solutes embedded in a continuum via numerical solutions to the Poisson-Boltzmann equation. Only recently have the classical force fields used for studying biomolecules begun to include explicit polarization in their functional forms. Here the authors describe the theory underlying a newly developed polarizable multipole Poisson-Boltzmann (PMPB) continuum electrostatics model, which builds on the atomic multipole optimized energetics for biomolecular applications (AMOEBA) force field. As an application of the PMPB methodology, results are presented for several small folded proteins studied by molecular dynamics in explicit water as well as embedded in the PMPB continuum. The dipole moment of each protein increased on average by a factor of 1.27 in explicit AMOEBA water and 1.26 in continuum solvent. The essentially identical electrostatic response in both models suggests that PMPB electrostatics offers an efficient alternative to sampling explicit solvent molecules for a variety of interesting applications, including binding energies, conformational analysis, and pK(a) prediction. Introduction of 150 mM salt lowered the electrostatic solvation energy between 2 and 13 kcalmole, depending on the formal charge of the protein, but had only a small influence on dipole moments.

Conformational analysis of methyl 5-O-methyl septanosides: effect of glycosylation on conformer populations

Methyl 5-O-methyl-alpha-d-glycero-d-idoseptanoside (3) and methyl 5-O-methyl-beta-d-glycero-d-guloseptanoside (4) were investigated as (1-->5)-linked di-/oligoseptanoside mimetics. Here we report the synthesis of 3 and 4 and describe their preferred solution conformations through a combination of ab initio/DFT calculations and (1)H (3)J(H,H) NMR coupling constant analysis. The conformations of 3 and 4 observed in this study are discussed in comparison to those of the parent (C5 hydroxy) compounds 1 and 2. The results indicate that methyl 5-O-methyl-alpha-septanoside 3 is relatively rigid and adopts the same (3,4)TC(5,6) conformation as 1. Methyl 5-O-methyl-beta-septanoside 4 is somewhat less rigid than its parent septanoside (2). In addition to the (6,O)TC(4,5) conformation adopted by 2, beta-septanoside 4 also populates the adjacent (3,4)TC(5,6) conformation. Glycosylation at C5 on beta-septanoside 4 therefore increases its overall flexibility and allows access to alternative ring conformations.

Elucidating the Vibrational Spectra of Hydrogen-Bonded Aggregates in Solution: Electronic Structure Calculations with Implicit Solvent and First-Principles Molecular Dynamics Simulations with Explicit Solvent for 1-Hexanol in n-Hexane

Fourier transform infrared spectroscopy is a popular method for the experimental investigation of hydrogen-bonded aggregates, but linking spectral information to microscopic information on aggregate size distribution and aggregate architecture is an arduous task. Static electronic structure calculations with an implicit solvent model, Car-Parrinello molecular dynamics (CPMD) using the Becke-Lee-Yang-Parr (BLYP) exchange and correlation energy functionals and classical molecular dynamics simulations for the all-atom version of the optimized parameters for liquid simulations (OPLS-AA) force field were carried out for an ensemble of 1-hexanol aggregates solvated in n-hexane. The initial configurations for these calculations were size-selected from a distribution of aggregates obtained from a large-scale Monte Carlo simulation. The vibrational spectra computed from the static electronic structure calculations for monomers and dimers and from the CPMD simulations for aggregates up to pentamers demonstrate the extent of the contribution of dangling or nondonating hydroxyl groups found in linear and branched aggregates to the "monomeric" peak. Furthermore, the computed spectra show that there is no simple relationship between peak shift and aggregate size nor architecture, but the effect of hydrogen-bond cooperativity is shown to differentiate polymer-like (cooperative) and dimer-like (noncooperative) hydrogen bonds in the vibrational spectrum. In contrast to the static electronic structure calculations and the CPMD simulations, the classical molecular dynamics simulations greatly underestimate the vibrational peak shift due to hydrogen bonding.

Septanose Carbohydrates: Synthesis and Conformational Studies of Methyl α-d-glycero-d-Idoseptanoside and Methyl β-d-glycero-d-Guloseptanoside

We report the synthesis of methyl alpha-D-glycero-D-idoseptanoside (1) and methyl beta-D-glycero-D-guloseptanoside (2) and the characterization of their preferred solution conformations by computational chemistry and (1)H NMR (3)J(H,H) coupling constant analysis. Central to the synthetic approach was the epoxidation of glucose-derived oxepine 3 using DMDO. Nucleophilic attack on the resulting 1,2-anhydroseptanose using NaOCH(3) in CH(3)OH followed by deprotection provided the 1,2-trans diastereomers 1 and 2. The computational approach for determining the preferred low energy septanose conformations began with a pseudo Monte Carlo search for each isomer using minimization with the AMBER force field. Single-point energy calculations (HF/6-31G *and B3LYP/6-31+G**) as well as full geometry optimizations in a model for aqueous solvent were then conducted using the conformers within 5 kcal/mol of the AMBER global minimum. Calculated (3)J(H,H) values, based on a Boltzmann distribution of the computed low energy conformers, were compared to experimental (3)J(H,H) values from (1)H NMR coupling constant analyses. The correlation between calculated and observed values suggest that septanose carbohydrates are not so flexible and should generally prefer one twist-chair (TC) conformation.

The parameterization and validation of generalized born models using the pairwise descreening approximation

Generalized Born Surface Area (GBSA) models for water using the Pairwise Descreening Approximation (PDA) have been parameterized by two different methods. The first method, similar to that used in previously reported parameterizations, optimizes all parameters against the experimental free energies of hydration of organic molecules. The second method optimizes the PDA parameters to compensate only for systematic errors of the PDA. The best models are compared to Poisson-Boltzmann calculations and applied to the computation of potentials of mean force (PMFs) for the association of various molecules. PMFs present a more rigorous test of the ability of a solvation model to correctly reproduce the screening of intermolecular interactions by the solvent, than its accuracy at predicting free energies of hydration of small molecules. Models derived with the first method are sometimes shown to fail to compute accurate potentials of mean force because of large errors in the computation of Born radii, while no such difficulties are observed with the second method. Furthermore, accurate computation of the Born radii appears to be more important than good agreement with experimental free energies of solvation. We discuss the source of errors in the potentials of mean force and suggest means to reduce them. Our findings suggest that Generalized Born models that use the Pairwise Descreening Approximation and that are derived solely by unconstrained optimization of parameters against free energies of hydration should be applied to the modeling of intermolecular interactions with caution.