Implicit Solvent Methods Research Articles

Ab initio electronic absorption spectra of para-nitroaniline in different solvents: Intramolecular charge transfer effects.

Intramolecular charge transfer (ICT) effects of para-nitroaniline (pNA) in eight solvents (cyclohexane, toluene, acetic acid, dichloroethane, acetone, acetonitrile, dimethylsulfoxide, and water) are investigated extensively. The second-order algebraic diagrammatic construction, ADC(2), ab initio wave function is employed with the COSMO implicit and discrete multiscale solvation methods. We found a decreasing amine group torsion angle with increased solvent polarity and a linear correlation between the polarity and ADC(2) transition energies. The first absorption band involves π → π* transitions with ICT from the amine and the benzene ring to the nitro group, increased by 4%-11% for different solvation models of water compared to the vacuum. A second band of pNA is characterized for the first time. This band is primarily a local excitation on the nitro group, including some ICT from the amine group to the benzene ring that decreases with the solvent polarity. For cyclohexane, the COSMO implicit solvent model shows the best agreement with the experiment, while the explicit model has the best agreement for water.

First-Principles study on proton transfer in triazole molecules

Triazole can be used as an effective proton carrier because it has one proton donor and two proton acceptors. Density functional theory calculations were performed to explore the proton transfer mechanism of the triazole molecules in gas and solvents. We employed implicit solvent method to analyze the increase of proton donor–acceptor distance (PDAD) in proton transfer mechanism. The solvents reduce the relative energy in tautomers of 1,2,4-triazole molecules, and their protonated form. Proton transfer occurs only at symmetric pairs in the gas, small PDAD, whereas proton transfer in an asymmetric pair is possible in solvents as the PDAD increases.

Theoretical Investigation of the Adsorbate and Potential-Induced Stability of Cu Facets during Electrochemical CO2 and CO Reduction

The activity and product selectivity of electrocatalysts for reactions like the carbon dioxide and carbon monoxide reduction reactions (CO2RR and CORR) are intimately dependent on the catalyst’s structure and composition. While engineering catalytic surfaces can improve performance, discovering the key sets of rational design principles remains challenging due to limitations in modeling catalyst stability under operating conditions. Herein, we perform first-principles density functional calculations adopting implicit solvation methods with potential control to study the influence of adsorbates and applied potential on the stability of different facets of model Cu electrocatalysts. Using coverage dependencies extracted from microkinetic models, we describe an approach for calculating potential and adsorbate-dependent contributions to surface energies under reaction conditions, where Wulff constructions are used to understand the morphological evolution of Cu electrocatalysts under CO2RR and CORR conditions. We identify that CO*, a key reaction intermediate, exhibits higher kinetically and thermodynamically accessible coverages on (100) relative to (111) facets, which can translate into an increased relative stabilization of the (100) facet during CO2RR. Our results support the known tendency for increased (111) faceting of Cu nanoparticles under more reducing conditions and that the relative increase in (100) faceting observed under CO2RR conditions is likely attributed to differences in CO* coverage between these facets.This work was partially performed under the auspices of the U.S. DOE by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344 and partially supported by the U.S. DOE, Office of Energy Efficiency and Renewable Energy, Advanced Materials & Manufacturing Office.

Cross-section distortion and springback characteristics of double-cavity aluminum profile in force controlled stretch-bending

A 3D elastic-plastic FE model for simulating the force controlled stretch-bending process of double-cavity aluminum profile was established using hybrid explicit−implicit solvent method. Considering the computational accuracy and efficiency, the optimal choices of numerical parameters and algorithms in FE modelling were determined. The formation mechanisms of cross-section distortion and springback were revealed. The effects of pre-stretching, post-stretching, friction, and the addition of internal fillers on forming quality were investigated. The results show that the stress state of profile in stretch-bending is uniaxial with only a circumferential stress. The stress distribution along the length direction of profile is non-uniform and the maximum tensile stress is located at a certain distance away from the center of profile. As aluminum profile is gradually attached to bending die, the distribution characteristic of cross-section distortion along the length direction of profile changes from V-shape to W-shape. After unloading the forming tools, cross-section distortion decreases obviously due to the stress relaxation, with a maximum distortion difference of 13% before and after unloading. As pre-stretching and post-stretching forces increase, cross-section distortion increases gradually, while springback first decreases and then remains unchanged. With increasing friction between bending die and profile, cross-section distortion slightly decreases, while springback increases. Cross-section distortion decreases by 83% with adding PVC fillers into the cavities of profile, while springback increases by 192.2%.

Nitrogen reduction reaction enhanced by single-atom transition metal catalysts on functionalized graphene: A first-principles study

Ammonia production seeks alternatives to the conventional Haber-Bosch process, with nitrogen reduction reaction (NRR) emerging promising. Addressing the challenge of efficient catalysts, the functionalized graphene-based single atom catalysts (SACs) stand out. While prior studies have favored heteroatom-doped catalysts, the coordination of metal centers with nitrogen atoms remains underexplored. This work investigates transition metal (TM) SACs on nitrogen-doped graphene (N3G) using density functional theory (DFT) for electro-catalytic NRR. Results highlight the stability of V@N3G, Mo@N3G, W@N3G, with binding energies of −7.77, −5.43, and −3.89 eV, respectively. Insights into work function, d-band center, N–N bond, and IR stretching's role in N2 activation are gained through this study. Bader charge analysis reveals electron redistribution between the support and adsorbed N2. Employing Computational Hydrogen Electrode (CHE) method, comparative free energy diagrams for TM@N3G (V, Mo, W) via., enzymatic, consecutive, alternating, and distal pathways outline potential rate determining step (PDS) with and without the Implicit solvation method. Remarkably, W@N3G catalyst exhibits the lowest PDS in the presence of solvation energy, surpassing other catalysts. The multi-adsorption of N2 on W@N3G enhances NRR process, stabilizing intermediates for efficient ammonia production. This computational study sheds light on metal center SACs on functionalized graphene support as a potential electro-catalyst for efficient and stable NRR.

Elucidating Solvatochromic Shifts in Two-Dimensional Photocatalysts by Solving the Bethe-Salpeter Equation Coupled with Implicit Solvation Method.

Many studies have focused on tailoring the photophysical properties of two-dimensional (2D) materials for photocatalytic (PC) or photoelectrochemical (PEC) applications. To understand the optical properties of 2D materials in solution, we established a computational method that combined the Bethe-Salpeter equation (BSE) calculations with our GW-GPE method, allowing for GW/BSE-level calculations with implicit solvation described using the generalized Poisson equation (GPE). We applied this method to MoS2, phosphorene (PP), and g-C3N4 and found that when the solvent dielectric increased, it reduced the exciton binding energy and quasiparticle bandgap, resulting in almost no solvatochromic shift in the excitonic peaks of MoS2 and PP, which is consistent with previous experiments. However, our calculations predicted that the solvent dielectric had a significant impact on the excitonic properties of g-C3N4, exhibiting a large solvatochromic shift. We expect that our GW/BSE-GPE method will offer insights into the design of 2D materials for PC and PEC applications.

Theoretical Investigation of the Adsorbate and Potential-Induced Stability of Cu Facets During Electrochemical CO2 and CO Reduction.

The activity and product selectivity of electrocatalysts for reactions like the carbon dioxide reduction reaction (CO2RR) are intimately dependent on the catalyst's structure and composition. While engineering catalytic surfaces can improve performance, discovering the key sets of rational design principles remains challenging due to limitations in modeling catalyst stability under operating conditions. Herein, we perform first-principles density functional calculations adopting implicit solvation methods with potential control to study the influence of adsorbates and applied potential on the stability of different facets of model Cu electrocatalysts. Using coverage dependencies extracted from microkinetic models, we describe an approach for calculating potential and adsorbate-dependent contributions to surface energies under reaction conditions, where Wulff constructions are used to understand the morphological evolution of Cu electrocatalysts under CO2RR conditions. We identify that CO*, a key reaction intermediate, exhibits higher kinetically and thermodynamically accessible coverages on (100) relative to (111) facets, which can translate into an increased relative stabilization of the (100) facet during CO2RR. Our results support the known tendency for increased (111) faceting of Cu nanoparticles under more reducing conditions and that the relative increase in (100) faceting observed under CO2RR conditions is likely attributed to differences in CO* coverage between these facets.

Binding Free Energy Calculation Based on the Fragment Molecular Orbital Method and Its Application in Designing Novel SHP-2 Allosteric Inhibitors.

The accurate prediction of binding free energy is a major challenge in structure-based drug design. Quantum mechanics (QM)-based approaches show promising potential in predicting ligand-protein binding affinity by accurately describing the behavior and structure of electrons. However, traditional QM calculations face computational limitations, hindering their practical application in drug design. Nevertheless, the fragment molecular orbital (FMO) method has gained widespread application in drug design due to its ability to reduce computational costs and achieve efficient ab initio QM calculations. Although the FMO method has demonstrated its reliability in calculating the gas phase potential energy, the binding of proteins and ligands also involves other contributing energy terms, such as solvent effects, the 'deformation energy' of a ligand's bioactive conformations, and entropy. Particularly in cases involving ionized fragments, the calculation of solvation free energy becomes particularly crucial. We conducted an evaluation of some previously reported implicit solvent methods on the same data set to assess their potential for improving the performance of the FMO method. Herein, we develop a new QM-based binding free energy calculation method called FMOScore, which enhances the performance of the FMO method. The FMOScore method incorporates linear fitting of various terms, including gas-phase potential energy, deformation energy, and solvation free energy. Compared to other widely used traditional prediction methods such as FEP+, MM/PBSA, MM/GBSA, and Autodock vina, FMOScore showed good performance in prediction accuracies. By constructing a retrospective case study, it was observed that incorporating calculations for solvation free energy and deformation energy can further enhance the precision of FMO predictions for binding affinity. Furthermore, using FMOScore-guided lead optimization against Src homology-2-containing protein tyrosine phosphatase 2 (SHP-2), we discovered a novel and potent allosteric SHP-2 inhibitor (compound 8).

Exploring borderline SN1-SN2 mechanisms: the role of explicit solvation protocols in the DFT investigation of isopropyl chloride.

Nucleophilic substitution at saturated carbon is a crucial class of organic reactions, playing a pivotal role in various chemical transformations that yield valuable compounds for society. Despite the well-established SN1 and SN2 mechanisms, secondary substrates, particularly in solvolysis reactions, often exhibit a borderline pathway. A molecular-level understanding of these processes is fundamental for developing more efficient chemical transformations. Typically, quantum-chemical simulations of the solvent medium combine explicit and implicit solvation methods. The configuration of explicit molecules can be defined through top-down approaches, such as Monte Carlo (MC) calculations for generating initial configurations, and bottom-up methods that involve user-dependent protocols to add solvent molecules around the substrate. Herein, we investigated the borderline mechanism of the hydrolysis of a secondary substrate, isopropyl chloride (iPrCl), at DFT-M06-2X/aug-cc-pVDZ level, employing explicit and explicit + implicit protocols. Top-down and bottom-up approaches were employed to generate substrate-solvent complexes of varying number (n = 1, 3, 5, 7, 9, and 12) and configurations of H2O molecules. Our findings consistently reveal that regardless of the solvation approach, the hydrolysis of iPrCl follows a loose-SN2-like mechanism with nucleophilic solvent assistance. Increasing the water cluster around the substrate in most cases led to reaction barriers of ΔH‡ ≈ 21 kcal mol-1, with nine water molecules from MC configurations sufficient to describe the reaction. The More O'Ferrall-Jencks plot demonstrates an SN1-like character for all transition state structures, showing a clear merged profile. The fragmentation activation strain analyses indicate that energy barriers are predominantly controlled by solvent-substrate interactions, supported by the leaving group stabilization assessed through CHELPG atomic charges.

Synthesis, characterization, DFT study, and antibacterial activity of a coordination complex of Cu(II) with 1,10-phenanthroline and l-methionine ligands

A crystal of the coordination complex of Cu(II) with 1,10-phenanthroline (phen) and l-methionine anion ([Cu(Phen)(L-methionine)H2O]Cl·1·5H2O) was synthesized and investigated by powder X-ray diffraction (PXRD), Raman spectroscopy, Fourier-transform infrared (FT-IR) spectroscopy, and ultraviolet-visible (UV–Vis) techniques combined with density functional theory (DFT) studies. Chemical, electronic and vibrational properties were properly investigated through experimental and theoretical approaches, including a solvation effects study with an implicit solvation method using ethanol and water as solvents. The electronic structure calculations indicated that the titled complex is chemically stable and showed that a smaller amount of energy is required for a HOMO-LUMO electronic transition in an aqueous medium than in a vacuum. Characteristic bands of the d−d ransitions for five-coordinated Cu(II) were identified for the complex with minor differences in wavelengths of the UV–Vis spectra in water and ethanol. The Raman and infrared experimental results and the calculations on the vibrational properties in different solvent conditions showed spectral changes, especially when comparing the results obtained in water and ethanol solvents in relation to those obtained in a vacuum. Additionally, biological evaluations indicated that the [Cu(Phen)(L-methionine)H2O]Cl·1·5H2O complex has good antibacterial activity against Gram-positive and Gram-negative bacteria, presenting a minimum inhibitory concentration (MIC) value of 50 μg/mL, suggesting it is a promising candidate for commercialization.

Conformations and Solvation of Synthetic Polymers in Water by Generalized Born Implicit-Solvent Molecular Dynamics Simulations: Stereoisomers of Poly(acrylic acid) and Poly(methacrylic acid)

We present the GB-OBC model as an approach for implicit-solvent MD simulations of a synthetic macromolecule in water. The model is tested and found to be successful in reproducing the chain dimensions and predicting the free energy of solvation of carboxylic acid vinyl polymers. The influence of stereochemistry and the hydrophobic nature of the polymer was investigated as a function of chain length (20 < N < 600) for poly(acrylic acid) (PAA) and poly(methacrylic acid) (PMA). The dimensionless parameters of the GB-OBC model were parameterized to be applicable to PAA and PMA. Scaling relations for chain dimensions obtained using implicit-solvent MD simulations in this study are in good agreement with those from experiments, theory of solvated chains in good solvents, and all-atom MD simulations in explicit water. Results show that ⟨Rg2⟩/NL2 is greater for the atactic chain as compared to the isotactic chain, for PAA as well as PMA. ⟨Rg2⟩/NL2 values of chains attain constancy in water for N = 200, with the values being greater for PMA. The PMA chain is conformationally more perturbed than the PAA chain, for both isotactic and atactic stereochemistry. The solvation free energy ΔGhyd of PAA and PMA in water is negative for all chain lengths (N = 20-600) and becomes more favorable with an increase in molecular weight. The ΔGhyd values for isotactic and atactic chains are identical at lower values of N but differ slightly for N > 300. Irrespective of the hydrophobic nature of the polymer, the atactic chain is thermodynamically more soluble in water as compared to the isotactic chain. The isotactic chain is less hydrophilic as compared to the atactic chain due to the closer proximity of the COOH groups along the backbone. This implicit solvent method is an effective way to accurately simulate the configurational properties and solvation of synthetic polymers in water.

HIT web server: A hybrid method to improve electrostatic calculations for biomolecules

The electrostatic features of highly charged biomolecules are crucial and challenging tasks in computational biophysics. The electrostatic calculations by traditional implicit solvent methods are efficient but have difficulties on highly charged biomolecules. We have developed a Hybridizing Ion Treatment (HIT) tool, which successfully hybridizes the explicit ions and implicit solvation model to accurately calculate the electrostatic potential for highly charged biomolecules. Here we implemented the HIT tool into a web server. In this study, a training set was prepared to optimize the number of frames for the HIT web server. The results on tubulins, DNAs, and RNAs, reveal the mechanisms for the motor proteins, DNA of HIV, and tRNA. This HIT web server can be widely used to study highly charged biomolecules, including DNAs, RNAs, molecular motors, and other highly charged biomolecules.

Implicit Solvation Methods for Catalysis at Electrified Interfaces.

Implicit solvation is an effective, highly coarse-grained approach in atomic-scale simulations to account for a surrounding liquid electrolyte on the level of a continuous polarizable medium. Originating in molecular chemistry with finite solutes, implicit solvation techniques are now increasingly used in the context of first-principles modeling of electrochemistry and electrocatalysis at extended (often metallic) electrodes. The prevalent ansatz to model the latter electrodes and the reactive surface chemistry at them through slabs in periodic boundary condition supercells brings its specific challenges. Foremost this concerns the difficulty of describing the entire double layer forming at the electrified solid–liquid interface (SLI) within supercell sizes tractable by commonly employed density functional theory (DFT). We review liquid solvation methodology from this specific application angle, highlighting in particular its use in the widespread ab initio thermodynamics approach to surface catalysis. Notably, implicit solvation can be employed to mimic a polarization of the electrode’s electronic density under the applied potential and the concomitant capacitive charging of the entire double layer beyond the limitations of the employed DFT supercell. Most critical for continuing advances of this effective methodology for the SLI context is the lack of pertinent (experimental or high-level theoretical) reference data needed for parametrization.

Implicit solvation in domain based pair natural orbital coupled cluster (DLPNO-CCSD) theory.

A nearly linear scaling implementation of coupled-cluster with singles and doubles excitations (CCSD) can be achieved by means of the domain-based local pair natural orbital (DLPNO) method. The combination of DLPNO-CCSD with implicit solvation methods allows the calculation of accurate energies and chemical properties of solvated systems at an affordable computational cost. We have efficiently implemented different schemes within the conductor-like polarizable continuum model (C-PCM) for DLPNO-CCSD in the ORCA quantum chemistry suite. In our implementation, the overhead due to the additional solvent terms amounts to less than 5% of the time the equivalent gas phase job takes. Our results for organic neutrals and open-shell ions in water show that for most systems, adding solvation terms to the coupled-cluster amplitudes equations and to the energy leads to small changes in the total energy compared to only considering solvated orbitals and corrections to the reference energy. However, when the solute contains certain functional groups, such as carbonyl or nitrile groups, the changes in the energy are larger and estimated to be around 0.04 and 0.02 kcal/mol for each carbonyl and nitrile group in the solute, respectively. For solutes containing metals, the use of accurate CC/C-PCM schemes is crucial to account for correlation solvation effects. Simultaneously, we have calculated the electrostatic component of the solvation energy for neutrals and ions in water for the different DLPNO-CCSD/C-PCM schemes. We observe negligible changes in the deviation between DLPNO-CCSD and canonical-CCSD data. Here, DLPNO-CCSD results outperform those for Hartree-Fock and density functional theory calculations.

HOMO-LUMO Energy Levels and the Bandgaps to Understand Porpc Photocatalytic Activity

A dye-sensitized solar cell (DSSC) assembly can be used not only to harvest solar energy but also to purify water using suitable dye-sensitizers. Here, we theoretically investigated four dye-sensitizers, namely, PORPC-1, PORPC-2, PORPC-3, and PORPC-4 for photocatalytic water purification using PBE, B3LYP, PBE0 functionals, and ∆SCF, TD-DFT and GW methods to characterize their activity trends. The energy levels of highest occupied molecular orbitals (HOMO) and the lowest unoccupied molecular orbitals (LUMO) were elucidated using gas-phase and aqueous phase calculations to understand charge injection ability and the dye-regeneration process. However, PBE, B3LYP, PBE0, and TD-DFT methods fail to predict the best sensitizers. The ∆SCF coupled with the implicit solvation method and the GW method HOMO-LUMO energies corrected for aqueous environment effect predicted PORPC-2 and PORPC-4 as the best sensitizers. Thus, it emphasized the importance of aqueous environment effect in simulation. However, none of these methods accurately predicted the photocatalytic performance trend of all the four dye-sensitizers. Hence, we have used the dye-molecular aggregation assembly pattern in an aqueous environment to further probe into activity trends and found that the PORPC-3 and the PORPC-4 prefer J-aggregate assembly, whereas the PROPC-1 and the PORPC-2 adopt H-aggregate assembly pattern. Therefore, the synergistic effect of the HOMO-LUMO energy levels and the aggregate assembly pattern determine the photocatalytic performance of the dye-molecules, and the activity trend is PORPC-4>PORPC-2>PORPC-3>PORPC-1, agreed well with the experimental findings. Acknowledgements This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Nos. NRF-2017R1E1A1A01074266, NRF-2015M1A2A2057129, and NRF-2016M1A2A2937151).

SQM/COSMO Scoring Function: Reliable Quantum-Mechanical Tool for Sampling and Ranking in Structure-Based Drug Design.

Quantum mechanical (QM) methods have been gaining importance in structure-based drug design where a reliable description of protein-ligand interactions is of utmost significance. However, strategies i. e. QM/MM, fragmentation or semiempirical (SQM) methods had to be pursued to overcome the unfavorable scaling of QM methods. Various SQM-based approaches have significantly contributed to the accuracy of docking and improvement of lead compounds. Parametrizations of SQM and implicit solvent methods in our laboratory have been instrumental to obtain a reliable SQM-based scoring function. The experience gained in its application for activity ranking of ligands binding to tens of protein targets resulted in setting up a faster SQM/COSMO scoring approach, which outperforms standard scoring methods in native pose identification for two dozen protein targets with ten thousand poses. Recently, SQM/COSMO was effectively applied in a proof-of-concept study of enrichment in virtual screening. Due to its superior performance, feasibility and chemical generality, we propose the SQM/COSMO approach as an efficient tool in structure-based drug design.

Do HOMO-LUMO Energy Levels and Band Gaps Provide Sufficient Understanding of Dye-Sensitizer Activity Trends for Water Purification?

A dye-sensitized solar cell assembly can be used to harvest solar energy, while suitable dye sensitizers can be used to purify water. Here, we characterized the activity trends of four dye sensitizers, namely, PORPC-1, PORPC-2, PORPC-3, and PORPC-4, for water purification applications using density functional theory (DFT) with the Perdew–Burke–Ernzerhof (PBE), B3LYP, and PBE0 functionals, ΔSCF, time-dependent DFT (TD-DFT), and quasiparticle Green’s function (GW) methods. The energy levels of the highest occupied molecular orbitals (HOMOs) and lowest unoccupied molecular orbitals (LUMOs) were calculated using gas-phase and aqueous-phase methods in order to understand charge-injection abilities and the dye regeneration processes. PBE, B3LYP, PBE0, and TD-DFT methods failed to predict PORPC-4 to be the best sensitizer, while PORPC-2 and PORPC-4 were predicted to be the best sensitizers using ΔSCF coupled with the implicit solvation method, and HOMO–LUMO energies were corrected for the aqueous environment in the GW calculations. However, none of these methods accurately predicted the performance trend of all four dye sensitizers. Consequently, we used the aggregation assembly patterns of the dye molecules in an aqueous environment to further probe the activity trends and found that PORPC-3 and PORPC-4 prefer J-aggregated assembly patterns, whereas PROPC-1 and PORPC-2 prefer to be H-aggregated. Therefore, the performance of these dye molecules can be determined by combining HOMO–LUMO energy levels with aggregate-assembly patterns, with the activity trend predicted to be PORPC-4 > PORPC-2 > PORPC-3 > PORPC-1, which is in good agreement with experimental findings.

Theoretical Prediction of the Strong Solvent Effect on Reduced Ethylene Carbonate Ring-Opening and Its Impact on Solid Electrolyte Interphase Evolution

With continuous growth in demand for lithium-ion batteries (LIBs) with higher capacity retention and longer lifetime, solid electrolyte interphase (SEI) formation allowing for tunable structure is critical to improve efficiency in current LIBs and implement next-generation technologies. To enable engineering of the SEI layer, a deeper understanding of the mechanisms and kinetics underlying its formation processes is required. We first demonstrate the importance of the rate of ring opening of reduced ethylene carbonate (c-EC–) to its chain-like conformation (o-EC–). According to our classical molecular dynamics simulations, c-EC– is far more likely to diffuse away from the anode than o-EC–, implying that longer c-EC– lifetimes would correlate with thicker SEI layers and reduced capacity retention. Our work then illustrates that the activation barrier for the c-EC– → o-EC– reaction can be strongly influenced by the entropic effects associated with the reorganization of the surrounding molecules. Ab initio molecular dynamics simulations combined with metadynamics sampling clearly demonstrate a considerable decrease (by a factor of 2.5) in the ring-opening barrier when considering a 50/50 mixture of cyclic EC and linear dimethyl carbonate as the solvent rather than pure liquid EC. This is not predicted by implicit solvent methods owing to their failure to capture the effect of solvent geometry. Our findings also suggest that other perturbations of the local environment not considered, such as those due to interfaces, anions, or other reduction products, may also significantly affect the diffusion/reaction kinetics of EC– radical anion, and, thus, SEI formation and evolution.

Assessing the Accuracy of Different Solvation Models To Describe Protein Adsorption.

In protein adsorption, the surrounding solvent has an important role in mediating protein-surface interactions. Therefore, it is of paramount importance that the solvent methods employed to model these kinds of processes are able to correctly capture the complex mechanisms occurring in the protein-water-surface interface. Here, we test the suitability of the two most popular implicit solvent methods based on the Generalized Born formalism to describe the adsorption process of the immunoglobulin G (IgG) on a hydrophobic graphene surface. Our results show that in both cases, IgG experiences an extreme and early (in less than 40 ns) unfolding as a result of the adsorption to the surface in contrast with previous experimental findings. A detailed energy decomposition analysis of explicit and implicit solvent simulations reveals that this discrepancy arises from the ill-characterization of two energy components in implicit solvent methods. These findings help to elucidate how implicit solvent models may be improved to accurately characterize the protein adsorption process.

Computational Study of the pH-Dependent Competition between Carbonate and Thymine Addition to the Guanine Radical.

When oligonucleotides are oxidized by carbonate radical, thymine and carbonate can add to guanine radical, yielding either a guanine-thymine cross-link product (G∧T) or 8-oxo-7,8-dehydroguanine (8oxoG) and its further oxidation products such as spiroiminodihydantoin (Sp) and guanidinohydantoin (Gh). The ratio of thymine addition to carbonate addition depends strongly on the pH. Details of the mechanism have been explored by density functional calculations using the ωB97XD/6-31+G(d,p) level of theory with the SMD implicit solvation method, augmented with a few explicit waters. Free energies of intermediates and transition states in aqueous solution have been calculated along the pathways for addition of thymine, CO32-/HCO3- and carbonate radical to guanine radical. The pH dependence was examined by using appropriate explicit proton donors/acceptors as computational models for buffers at pH 2.5, 7, and 10. Deprotonation of thymine is required for nucleophilic addition at C8 of guanine radical, and thus is favored at higher pH. The barrier for carbonate radical addition is lower than for bicarbonate or carbonate dianion addition; however, for low concentrations of carbonate radical, the reaction may proceed by addition of bicarbonate/carbonate dianion to guanine radical. Thymine and bicarbonate/carbonate dianion addition are followed by oxidation by O2, loss of a proton from C8 and decarboxylation of the carbonate adduct. At pH 2.5, guanine radical cation can be formed by oxidization with sulfate radical. Water addition to guanine radical cation is the preferred path for forming 8oxoG at pH 2.5.