Quantum Mechanical Assessment of Nitrosamine Potency.

Nitrosamines are in the cohort of concern (CoC) as determined by regulatory guidance. CoC compounds are considered highly potent carcinogens that need to be limited below the threshold of toxicological concern, 1.5 µg/day. Nitrosamines like NDMA and NDEA require strict control, while novel nitrosamine drug substance-related impurities (NDSRIs) may or may not be characterized as potent carcinogens. A risk assessment based on the structural features of NDSRIs is important in order to predict potency because they lack substance-specific carcinogenicity. Herein, we present a quantum mechanical (QM)-based analysis on structurally diverse sets of nitrosamines to better understand how structure influences the reactivity that could result in carcinogenicity. We describe the potency trend through activation energies corresponding to α-hydroxylation, aldehyde formation, diazonium intermediate formation, reaction with DNA base, and hydrolysis reactions, and other probable metabolic pathways associated with the carcinogenicity of nitrosamines. We evaluated activation energies for selected cases such as N-nitroso pyrrolidines, N-nitroso piperidines, N-nitroso piperazines, N-nitroso morpholines, N-nitroso thiomorpholine, N-methyl nitroso aromatic, fluorine-substituted nitrosamines, and substituted aliphatic nitrosamines. We compare these results to the recent framework of the carcinogenic potency characterization approach (CPCA) proposed by health authorities which is meant to give guidance on acceptable intakes (AI) for NDSRIs lacking substance-specific carcinogenicity data. We show examples where QM modeling and CPCA are aligned and examples where CPCA both underestimates and overestimates the AI. In cases where CPCA predicts high potency for NDSRIs, QM modeling can help better estimate an AI. Our results suggest that a combined mechanistic understanding of α-hydroxylation, aldehyde formation, hydrolysis, and reaction with DNA bases could help identify the structural features that underpin the potency of nitrosamines. We anticipate this work will be a valuable addition to the CPCA and provide a more analytical way to estimate AI for novel NDSRIs.

Estimation of acceptable daily intake values based on modeling and in vivo mutagenicity of NDSRIs of fluoxetine, duloxetine and atomoxetine.

Nitrosamine drug substance related impurities or NDSRIs can be formed if an active pharmaceutical ingredient (API) has an intrinsic secondary amine that can undergo nitrosation. This is a concern as 1) nitrosamines are potentially highly potent carcinogens, 2) secondary amines in API are common, and 3) NDSRIs that might form from such secondary amines will be of unknown carcinogenic potency. Approaches for evaluating NDSRIs include read across, quantum mechanical modeling of reactivity, in vitro mutation data, and transgenic in vivo mutation data. These approaches were used here to assess NDSRIs that could potentially form from the drugs fluoxetine, duloxetine and atomoxetine. Based on a read across informed by modeling of physicochemical properties and mechanistic activation from quantum mechanical modeling, NDSRIs of fluoxetine, duloxetine, and atomoxetine were 10-100-fold less potent compared with highly potent nitrosamines such as NDMA or NDEA. While the NDSRIs were all confirmed to be mutagenic in vitro (Ames assay) and in vivo (TGR) studies, the latter data indicated that the potency of the mutation response was ≥4400 ng/day for all compounds-an order of magnitude higher than published regulatory limits for these NDSRIs. The approaches described herein can be used qualitatively to better categorize NDSRIs with respect to potency and inform whether they are in the ICH M7 (R2) designated Cohort of Concern.

Prevalence and risk factors for functional iron deficiency in children with chronic kidney disease.

INTRODUCTION: Anemia in chronic kidney disease (CKD) is multifactorial. The presence of functional iron deficiency (FID), whereby, there is a block in the transport of iron from macrophage to erythroid marrow is one possible etiology. In this study, we aim to assess the prevalence and risk factors of FID in pediatric CKD. METHODS: A cross-sectional study was performed from March to December 2018, after obtaining Institute Ethical Clearance. Children aged ≤ 12 years with CKD, with or without iron supplementation who consented were enrolled. Patients on erythropoietin or on maintenance dialysis were excluded. Details of patients and diseases characteristics were recorded. Various laboratory parameters including complete blood count, red blood cell indices, hypochromic RBC, reticulocyte hemoglobin content, and serum ferritin were measured. Appropriate statistical tests were applied. RESULTS: Out of 174 children, 127 (73%) had structural kidney disease as an etiology of CKD, and 110 (63%) had anemia. Prevalence of anemia was 44%, 43%, 74%, 64% and 92% in CKD stage 1, 2, 3, 4 and 5, respectively. Absolute iron deficiency was found in 66 (38%) even when some children were already on iron supplementation. FID was seen in 44 (25%) and on multivariate analysis, lower estimated glomerular filtration rate and mineral bone disease are associated risk factors. CONCLUSION: FID is present in one-fourth of our CKD cohort. It should be considered when the response to adequate measures of improving hemoglobin level fails. More studies are required to know its impact on short-term and long-term patient-related outcomes such as quality of life and mortality.

Advanced practice clinician care and end-of-life outcomes for community- and nursing home-dwelling Medicare beneficiaries with dementia.

INTRODUCTION: Older adults with Alzheimer's disease and related dementias (ADRD) often face burdensome end-of-life care transfers. Advanced practice clinicians (APCs)-which include nurse practitioners and physician assistants-increasingly provide primary care to this population. To fill current gaps in the literature, we measured the association between APC involvement in end-of-life care versus hospice utilization and hospitalization for older adults with ADRD. METHODS: Using Medicare data, we identified nursing home- (N=517,490) and community-dwelling (N=322,461) beneficiaries with ADRD who died between 2016 and 2018. We employed propensity score-weighted regression methods to examine the association between different levels of APC care during their final 9 months of life versus hospice utilization and hospitalization during their final month. RESULTS: For both nursing home- and community-dwelling beneficiaries, higher APC care involvement associated with lower hospitalization rates and higher hospice rates. DISCUSSION: APCs are an important group of providers delivering end-of-life primary care to individuals with ADRD. HIGHLIGHTS: For both nursing home- and community-dwelling Medicare beneficiaries with ADRD, adjusted hospitalization rates were lower and hospice rates were higher for individuals with higher proportions of APC care involvement during their final 9 months of life. Associations between APC care involvement and both adjusted hospitalization rates and adjusted hospice rates persisted when accounting for primary care visit volume.

Comparative assessment of QM-based and MM-based models for prediction of protein-ligand binding affinity trends.

Methods which accurately predict protein-ligand binding strengths are critical for drug discovery. In the last two decades, advances in chemical modelling have enabled steadily accelerating progress in the discovery and optimization of structure-based drug design. Most computational methods currently used in this context are based on molecular mechanics force fields that often have deficiencies in describing the quantum mechanical (QM) aspects of molecular binding. In this study, we show the competitiveness of our QM-based Molecules-in-Molecules (MIM) fragmentation method for characterizing binding energy trends for seven different datasets of protein-ligand complexes. By using molecular fragmentation, the MIM method allows for accelerated QM calculations. We demonstrate that for classes of structurally similar ligands bound to a common receptor, MIM provides excellent correlation to experiment, surpassing the more popular Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics Generalized Born Surface Area (MM/GBSA) methods. The MIM method offers a relatively simple, well-defined protocol by which binding trends can be ascertained at the QM level and is suggested as a promising option for lead optimization in structure-based drug design.

Use of Data to Understand the Social Determinants of Depression in Two Middle-Income Countries: the 3-D Commission.

Depression accounts for a large share of the global disease burden, with an estimated 264 million people globally suffering from depression. Despite being one of the most common kinds of mental health (MH) disorders, much about depression remains unknown. There are limited data about depression, in terms of its occurrence, distribution, and wider social determinants. This work examined the use of novel data sources for assessing the scope and social determinants of depression, with a view to informing the reduction of the global burden of depression.This study focused on new and traditional sources of data on depression and its social determinants in two middle-income countries (LMICs), namely, Brazil and India. We identified data sources using a combination of a targeted PubMed search, Google search, expert consultations, and snowball sampling of the relevant literature published between October 2010 and September 2020. Our search focused on data sources on the following HEALTHY subset of determinants: healthcare (H), education (E), access to healthy choices (A), labor/employment (L), transportation (T), housing (H), and income (Y).Despite the emergence of a variety of data sources, their use in the study of depression and its HEALTHY determinants in India and Brazil are still limited. Survey-based data are still the most widely used source. In instances where new data sources are used, the most commonly used data sources include social media (twitter data in particular), geographic information systems/global positioning systems (GIS/GPS), mobile phone, and satellite imagery. Often, the new data sources are used in conjunction with traditional sources of data. In Brazil, the limited use of new data sources to study depression and its HEALTHY determinants may be linked to (a) the government's outsized role in coordinating healthcare delivery and controlling the data system, thus limiting innovation that may be expected from the private sector; (b) the government routinely collecting data on depression and other MH disorders (and therefore, does not see the need for other data sources); and (c) insufficient prioritization of MH as a whole. In India, the limited use of new data sources to study depression and its HEALTHY determinants could be a function of (a) the lack of appropriate regulation and incentives to encourage data sharing by and within the private sector, (b) absence of purposeful data collection at subnational levels, and (c) inadequate prioritization of MH. There is a continuing gap in the collection and analysis of data on depression, possibly reflecting the limited priority accorded to mental health as a whole. The relatively limited use of data to inform our understanding of the HEALTHY determinants of depression suggests a substantial need for support of independent research using new data sources. Finally, there is a need to revisit the universal health coverage (UHC) frameworks, as these frameworks currently do not include depression and other mental health-related indicators so as to enable tracking of progress (or lack thereof) on such indicators.

Data Sources for Understanding the Social Determinants of Health: Examples from Two Middle-Income Countries: the 3-D Commission.

The expansion in the scope, scale, and sources of data on the wider social determinants of health (SDH) in the last decades could bridge gaps in information available for decision-making. However, challenges remain in making data widely available, accessible, and useful towards improving population health. While traditional, government-supported data sources and comparable data are most often used to characterize social determinants, there are still capacity and management constraints on data availability and use. Conversely, privately held data may not be shared. This study reviews and discusses the nature, sources, and uses of data on SDH, with illustrations from two middle-income countries: Kenya and the Philippines. The review highlights opportunities presented by new data sources, including the use of big data technologies, to capture data on social determinants that can be useful to inform population health. We conducted a search between October 2010 and September 2020 for grey and scientific publications on social determinants using a search strategy in PubMed and a manual snowball search. We assessed data sources and the data environment in both Kenya and the Philippines. We found limited evidence of the use of new sources of data to study the wider SDH, as most of the studies available used traditional sources. There was also no evidence of qualitative big data being used. Kenya has more publications using new data sources, except on the labor determinant, than the Philippines. The Philippines has a more consistent distribution of the use of new data sources across the HEALTHY determinants than Kenya, where there is greater variation of the number of publications across determinants. The results suggest that both countries use limited SDH data from new data sources. This limited use could be due to a number of factors including the absence of standardized indicators of SDH, inadequate trust and acceptability of data collection methods, and limited infrastructure to pool, analyze, and translate data.

Electrosynthesis of a Biaurone by Controlled Dimerization of Flavone: Mechanistic Insight and Large-Scale Application.

The electrochemistry of flavone (1) has been carefully investigated at glassy carbon cathodes in dimethylformamide containing 0.10 M tetra-n-butylammonium tetrafluoroborate as supporting electrolyte. In this medium, a cyclic voltammogram for a reduction of 1 exhibits a reversible cathodic process (Epc = -1.58 V and Epa = -1.47 V vs SHE) that is followed by an irreversible cathodic peak (Epc = -2.17 V vs SHE). When water (5.0 M) is introduced into the medium, the first peak for 1 becomes irreversible (Epc = -1.56 V vs SHE), and the second (irreversible) peak shifts to -2.07 V vs SHE. Bulk electrolyses of 1 at -1.60 V vs SHE afford flavanone, 2'-hydroxychalcone, 2'-hydroxy-3-phenylpropionate, and two new compounds, namely (Z)-1,6-bis(2-hydroxyphenyl)-3,4-diphenylhex-3-ene-1,6-dione (D1) and (Z)-2,2'-(1,2-diphenylethene-1,2-bis(benzofuran-3(2H))-one) (D2), obtained in significant amounts, that were characterized by means of 1H and 13C NMR spectrometry as well as single-crystal X-ray diffraction. Along with the above findings, we have proposed a mechanism for the electroreduction of 1, which has been further corroborated by our quantum mechanical study.

Quantum Mechanical Investigation of Three-Dimensional Activity Cliffs Using the Molecules-in-Molecules Fragmentation-Based Method.

The concept of activity cliff (AC) (i.e., a small structural modification resulting in a substantial bioactivity change) is widely encountered in medicinal chemistry during compound design. Whereas the study of ACs is of high interest as it provides a wealth of opportunities for effective drug design, its practical application in the actual drug development process has been difficult because of significant computational challenges. To provide some understanding of the ACs, we have carried out a rigorous quantum-mechanical investigation of the electronic interactions of a wide range of ACs (205 cliffs formed by 261 protein-ligand complexes covering 37 different receptor types) using multilayer molecules-in-molecules (MIM) fragmentation-based methodology. The MIM methodology enables performing accurate high-level quantum mechanical (QM) calculations at a substantially lower computational cost, while allowing for a quantitative decomposition of the protein-ligand binding energy into the contributions from individual residues, solvation, and entropy. Our investigation in this study is mainly focused on whether the QM binding energy calculation can correctly identify the higher potency cliff partner for a given ligand pair having a sufficiently high activity difference. We have also analyzed the effect of including crystal water molecules as a part of the receptor as well as the impact of ligand desolvation energy on the correct identification of the more potent ligand in a cliff pair. Our analysis reveals that, in the majority of the cases, the AC prediction could be significantly improved by carefully identifying the critical crystal water molecules, whereas the contribution from the ligand desolvation also remains essential. Additionally, we have exploited the residue-specific interaction energies provided by MIM to identify the key residues and interaction hot-spots that are responsible for the experimentally observed drastic activity changes. The results show that our MIM fragmentation-based protocol provides comprehensive interaction energy profiles that can be employed to understand the distinctiveness of ligand modifications, for potential applications in structure-based drug design.

Accurate and cost-effective NMR chemical shift predictions for proteins using a molecules-in-molecules fragmentation-based method.

We have developed an efficient protocol using our two-layer Molecules-in-Molecules (MIM2) fragmentation-based quantum chemical method for the prediction of NMR chemical shifts of large biomolecules. To investigate the performance of our fragmentation approach and demonstrate its applicability, MIM-NMR calculations are first calibrated on a test set of six proteins. The MIM2-NMR method yields a mean absolute deviation (MAD) from unfragmented full molecule calculations of 0.01 ppm for 1H and 0.06 ppm for 13C chemical shifts. Thus, the errors from fragmentation are only about 3% of our target accuracy of ∼0.3 ppm for 1H and 2-3 ppm for 13C chemical shifts. To compare with experimental chemical shifts, a standard protocol is first derived using two smaller proteins 2LHY (176 atoms) and 2LI1 (146 atoms) for obtaining an appropriate protein structure for NMR chemical shift calculations. The effect of the solvent environment on the calculated NMR chemical shifts is incorporated through implicit, explicit, or explicit-implicit solvation models. The expensive first solvation shell calculations are replaced by a micro-solvation model in which only the immediate interaction between the protein and the explicit solvation environment is considered. A single explicit water molecule for each amine and amide proton is found to be sufficient to yield accurate results for 1H chemical shifts. The 1H and 13C NMR chemical shifts calculated using our protocol give excellent agreement with experiments for two larger proteins, 2MC5 (the helical part with 265 atoms) and 3UMK (33 residue slice with 547 atoms). Overall, our target accuracy of ∼0.3 ppm for 1H and ∼2-3 ppm for 13C has been achieved for the larger proteins. The proposed MIM-NMR method is accurate and computationally cost-effective and should be applicable to study a wide range of large proteins.

G4 accuracy at DFT cost: unlocking accurate redox potentials for organic molecules using systematic error cancellation.

The redox potential is a powerful thermodynamic and kinetic tool used to predict numerous chemical and biochemical mechanisms. However, despite the improving predictive power of density functional theory (DFT), chemically accurate theoretical redox potentials are often difficult to achieve with DFT. For example, calculated redox potentials are sensitive to density functional choice and often fall short of the desired accuracy. Thus, ranges of errors for computed redox potentials between different density functionals can become quite large. The current study presents a cost-effective protocol that utilizes effective error cancellation schemes in order to accurately predict the redox potentials of a wide range of organic molecules. This computational protocol, called CBH-Redox, is an extension of the connectivity-based hierarchy (CBH) method, and produces thermochemical data with near-G4 accuracy. Herein, we test the CBH-Redox protocol against both experimental and G4 reference values and compare these results to DFT alone. Considering 46 C, O, N, F, Cl, and S atom-containing molecules, when using the CBH-Redox correction scheme, the MAEs for all eight density functionals tested are within the 0.09 V target accuracy versus both experiment and G4. Moreover, CBH-Redox achieves an impressive accuracy, with a MAE of 0.05 V or below when compared to G4 for six of the eight density functionals tested. In addition, when the CBH correction is applied, the error range across all functionals tested decreases from 0.12 V to about 0.05 V versus G4, and from 0.13 V to 0.04 V versus experiment.

Primitive Neuroectodermal Tumor in a Child with Human Immunodeficiency Virus Infection: A Rare Association.

Children with human immunodeficiency virus (HIV) infection are reported to have various malignancies, most common being Non-Hodgkin lymphoma. Despite higher risk of malignancies, brain tumors are infrequently described in these children. We report Primitive Neuroectodermal tumor (PNET) in a young boy with HIV infection. PNET has never been described in association with HIV infection. Though a causative association cannot be established, it does emphasize that with longer survivals on effective antiretroviral therapy, we may see a wide range of malignancies more frequently.

Assessment of an Elekta Versa HD linear accelerator for stereotactic radiosurgery with circular cone collimators.

BACKGROUND: Versa HD linear accelerators (linacs) are used for stereotactic radiosurgery treatment. However, the mechanical accuracy of such systems remains a concern. OBJECTIVE: The purpose of this study was to evaluate the accuracy of an Elekta Versa HD linac. METHODS: We performed measurements with a ball bearing phantom to calculate the rotational isocenter radii of the linac's gantry, collimator, and table, and determine the relative locations of those isocenters. We evaluated the accuracy of the cone-beam computed tomography (CBCT) guidance with a film-embedding head phantom and circular cone-collimated radiation beams. We also performed dosimetric simulations to study the effects of the linac mechanical uncertainties on non-coplanar cone arc delivery. RESULTS: The mechanical uncertainty of the linac gantry rotation was 0.78 mm in radius, whereas that of the collimator and the table was <0.1 mm and 0.33 mm, respectively. The axes of rotation of the collimator and the table were coinciding with and 0.13 mm away from the gantry isocenter, respectively. Experiments with test plans demonstrated the limited dosimetric consequences on the circular arc delivery given the aforementioned mechanical uncertainties. End-to-end measurements determined that the uncertainty of the CBCT guidance was≤1 mm in each direction with respect to the reference CT image. CONCLUSIONS: In arc delivery, the mechanical uncertainties associated with the gantry and the table do not require remarkable increases in geometric margins. If large enough, the residual setup errors following CBCT guidance will dominate the overall dosimetric consequence. Therefore, the Versa HD linac is a valid system for stereotactic radiosurgery using non-coplanar arc delivery.

Energy Decomposition Analysis of Protein-Ligand Interactions Using Molecules-in-Molecules Fragmentation-Based Method.

Accurate prediction of protein-ligand binding affinities and their quantitative decomposition into residue-specific contributions represent challenging problems in drug discovery. While quantum mechanical (QM) methods can provide an accurate description of such interactions, the associated computational cost is normally prohibitive for broad-based applications. Recently, we have shown that QM-based protein-ligand interaction energies in the gas phase can be determined accurately using our multilayer molecules-in-molecules (MIM) fragmentation-based method at a significantly lower computational cost. In this paper, we present a new approach for calculating protein-ligand interactions using our three-layer model (MIM3) that allows us to decompose the total binding affinity into quantitative contributions from individual residues (or backbone and side chain), crystal water molecules, solvation energy, and entropy. In our approach, the desolvation energy and entropy changes during protein-ligand binding are modeled using simple and inexpensive empirical models while intermolecular interactions are computed using an accurate QM method. The performance of our approach has been assessed on a congeneric series of 22 thrombin inhibitors, all with experimentally known binding affinities, using a binding pocket cutout of 120 residues with more than 1550 atoms. Comparison of our MIM3-calculated binding affinities calculated at the B97-D3BJ/6-311++G(2d,2p) level with experiment shows a good correlation with an R2 range of 0.81-0.88 and a Spearman rank correlation coefficient (ρ) range of 0.84-0.89 while providing a quantitative description of residue-specific interactions. We show that such residue-specific interaction energies can be employed to identify and rationalize both obvious (e.g., hydrogen bonds, π···π) and nonobvious (e.g., CH···π) interactions that play a critical role in protein-ligand binding. We suggest that such quantitative information can be used to identify the key residues that determine the comparative binding affinities of different ligands in order to improve and optimize the effectiveness of computational drug design.

Computational Study of the Formation of C8, C5, and C4 Guanine:Lysine Adducts via Oxidation of Guanine by Sulfate Radical Anion.

Oxidative damage to DNA can lead to DNA-protein cross-links which can interfere with DNA transcription, replication, and repair. In experimental studies modeling oxidative damage to DNA, oxidation of guanosine by sulfate radical anion in the presence of lysine produced a mixture of lysine (Lys)-substituted spiroiminodihydantoins (Sp): ∼65% 5-Lys-Sp, ∼30% 8-Lys-Sp, and ∼5% 5,8-diLys-Sp. Pathways for formation of the lysine adducts during the oxidation of guanine by sulfate radical anions have been mapped out using B3LYP density functional theory and the SMD solvation model. Methylamine was used as a model for lysine, and imidazole served as a proton acceptor. The lowest barrier for methylamine reaction with guanine radical is addition at C8, yielding mainly 8-NHR-Sp and some 5,8-diNR-Sp. This is in good agreement with the cross-link ratios for mild oxidations mediated by type I photosensitizers such as benzophenone, but this is not in agreement with the product ratios for strong oxidants such as sulfate radical anion. The calculations explored pathways for oxidation of guanine by sulfate radical anion that produced guanine radical and radical cation and doubly oxidized guanine (Gox) and its cation. Sulfate radical anion can also oxidize methylamine to produce neutral methylamine radical (CH3NH•) after deprotonation. The calculations qualitatively reproduced the observed product ratio at pH 7 via a pathway involving the barrierless addition of methylamine radical at C5 and C8 of guanine radical. After C5 addition of methylamine radical, the lowest barrier is for H2O addition at C8 leading exclusively to 5-NHR-Sp. After C8 addition of methylamine radical, H2O and methylamine addition to C5 lead to 8-NHR-Sp and some 5,8-diNR-Sp.

Immobilization of an Amphiphilic Molecular Cobalt Catalyst on Carbon Black for Ligand-Assisted Water Oxidation.

We have prepared the amphiphilic molecular catalyst [CoIII(LOC18)(pyrr)2]ClO4 (1), where LOC18 is the deprotonated form of N, N'-[4,5-bis(octadecyloxy)-1,2-phenylene]dipicolinamide. Species 1 can be anchored onto a carbon black support to yield the assembly 1@CB, which can catalyze water oxidation at an affordable onset overpotential of 0.32 V, with a current density of 10 mA/cm2 at 0.37 V. Moreover, 1@CB displays TOF = 3850 h-1. A mechanism is proposed based on the experimental and density-functional-theory-calculated data.

Computational Study of Oxidation of Guanine by Singlet Oxygen (1 Δg ) and Formation of Guanine:Lysine Cross-Links.

Oxidation of guanine in the presence of lysine can lead to guanine-lysine cross-links. The ratio of the C4, C5 and C8 crosslinks depends on the manner of oxidation. Type II photosensitizers such as Rose Bengal and methylene blue can generate singlet oxygen, which leads to a different ratio of products than oxidation by type I photosensitizers or by one electron oxidants. Modeling reactions of singlet oxygen can be quite challenging. Reactions have been explored using CASSCF, NEVPT2, DFT, CCSD(T), and BD(T) calculations with SMD implicit solvation. The spin contamination in open-shell calculations were corrected by Yamaguchi's approximate spin projection method. The addition of singlet oxygen to guanine to form guanine endo- peroxide proceeds step-wise via a zwitterionic peroxyl intermediate. The subsequent barrier for ring closure is smaller than the initial barrier for singlet oxygen addition. Ring opening of the endoperoxide by protonation at C4-O is followed by loss of a proton from C8 and dehydration to produce 8-oxoGox . The addition of lysine (modelled by methylamine) or water across the C5=N7 double bond of 8-oxoGox is followed by acyl migration to form the final spiro products. The barrier for methylamine addition is significantly lower than for water addition and should be the dominant reaction channel. These results are in good agreement with the experimental results for the formation of guanine-lysine cross-links by oxidation by type II photosensitizers.

Improved pKa Prediction of Substituted Alcohols, Phenols, and Hydroperoxides in Aqueous Medium Using Density Functional Theory and a Cluster-Continuum Solvation Model.

Acid dissociation constants (pKa's) are key physicochemical properties that are needed to understand the structure and reactivity of molecules in solution. Theoretical pKa's have been calculated for a set of 72 organic compounds with -OH and -OOH groups (48 with known experimental pKa's). This test set includes 17 aliphatic alcohols, 25 substituted phenols, and 30 hydroperoxides. Calculations in aqueous medium have been carried out with SMD implicit solvation and three hybrid DFT functionals (B3LYP, ωB97XD, and M06-2X) with two basis sets (6-31+G(d,p) and 6-311++G(d,p)). The effect of explicit water molecules on calculated pKa's was assessed by including up to three water molecules. pKa's calculated with only SMD implicit solvation are found to have average errors greater than 6 pKa units. Including one explicit water reduces the error by about 3 pKa units, but the error is still far from chemical accuracy. With B3LYP/6-311++G(d,p) and three explicit water molecules in SMD solvation, the mean signed error and standard deviation are only -0.02 ± 0.55; a linear fit with zero intercept has a slope of 1.005 and R2 = 0.97. Thus, this level of theory can be used to calculate pKa's directly without the need for linear correlations or thermodynamic cycles. Estimated pKa values are reported for 24 hydroperoxides that have not yet been determined experimentally.

Computational Study of the Radical Mediated Mechanism of the Formation of C8, C5, and C4 Guanine:Lysine Adducts in the Presence of the Benzophenone Photosensitizer.

The oxidation of guanine by triplet benzophenone in the presence of lysine has been shown to produce mono- and dilysine-substituted spiroiminodihydantion products, 8-Lys-Sp and 5,8-diLys-Sp. The potential energy surfaces for C8, C5, and C4 nucleophilic addition have been mapped out using the B3LYP/aug-cc-pVTZ//B3LYP/6-31+G(d,p) level of density functional theory with the SMD solvation model and employing methylamine as a model for the side chain of lysine. Enthalpies, barrier heights, pKa's, and reduction potentials were calculated for intermediates to find the lowest energy paths. For neutral methylamine plus guanine radical and neutral methylamine radical plus guanine, the barrier for addition at C8 is ca. 10 kcal/mol lower than that for addition at C5 and C4. The barriers for water addition at C8, C5, and C4 of guanine radical are 13-20 kcal/mol higher than that for methylamine addition at C8. Further oxidation and loss of a proton leads to 8-methylaminoguanine, the methylamino analogue of 8-oxo-7,8-dihydroguanine (8-oxoG). The barrier for the addition of a second methylamine at C5 of 8-methylaminoguanine is 4.5 kcal/mol lower than that for the corresponding addition of water. Nevertheless, if the concentration of methylamine (or lysine) is very low, water addition could be competitive with methylamine addition. This would lead to comparable fractions of 8-monosubstituted-Sp and 5-8-disubstituted-Sp, in agreement with the experimental observations.

Theoretical Calculation of pKa's of Selenols in Aqueous Solution Using an Implicit Solvation Model and Explicit Water Molecules.

A practical method for calculating the pKa's of selenols in aqueous solution has been developed by using density functional theory with the SMD solvation model and up to three explicit water molecules. The pKa's of 30 different organoselenols, 16 with known experimental pKa's, have been calculated by using three different functionals (ωB97XD, B3LYP, and M06-2X) and two basis sets (6-31+G(d,p) and 6-311++G(d,p)). Calculations using ωB97XD and B3LYP with SMD solvation without explicit waters are found to have errors of 3-6 pKa units; the errors with M06-2X are somewhat smaller. One explicit water interacting with the selenium reduces the calculated pKa's by 1-2 pKa units along with improving the slope and intercept of the fit of the calculated pKa's to experiment. The best results for SMD/M06-2X/6-31+G(d,p) are with one explicit water (MSE = -0.08 ± 0.37 and MUE = 0.32 ± 0.37) whereas ωB97XD and B3LYP still have errors larger than 2 pKa units. The best results for ωB97XD and B3LYP with 6-31+G(d,p) are obtained by using three explicit waters (MSE = 0.36 ± 0.24 and 0.34 ± 0.25, respectively) and a fit to experiment yields a slope of 1.06 with a zero intercept. The errors for M06-2X/6-31+G(d,p) with three explicit waters are significantly larger (-3.59 ± 0.45) because it overstabilizes the anions. On the basis of the molecules studied here, M06-2X/6-31+G(d,p) with one explicit water and ωB97XD/6-31+G(d,p) and B3LYP/6-31+G(d,p) with three explicit waters and the SMD solvation model can produce reliable pKa's for the substituted selenols.