Oxophilicity and thiophilicity are widely used concepts with no quantitative definition. In this paper, a simple, generic scale is developed that solves issues with reference states and system ...dependencies and captures empirically known tendencies toward oxygen. This enables a detailed analysis of the fundamental causes of oxophilicity. Notably, the notion that oxophilicity relates to Lewis acid hardness is invalid. Rather, oxophilicity correlates only modestly and inversely with absolute hardness and more strongly with electronegativity and effective nuclear charge. Since oxygen is highly electronegative, ionic bonding is stronger to metals of low electronegativity. Left-side d-block elements with low effective nuclear charges and electronegativities are thus highly oxophilic, and the f-block elements, not because of their hardness, which is normal, but as a result of the small ionization energies of their outermost valence electrons, can easily transfer electrons to fulfill the electron demands of oxygen. Consistent with empirical experience, the most oxophilic elements are found in the left part of the d block, the lanthanides, and the actinides. The d-block elements differ substantially in oxophilicity, quantifying their different uses in a wide range of chemical reactions; thus, the use of mixed oxo- and thiophilic (i.e., “mesophilic”) surfaces and catalysts as a design principle can explain the success of many recent applications. The proposed scale may therefore help to rationalize and improve chemical reactions more effectively than current qualitative considerations of oxophilicity.
Iron complexes are important spin crossover (SCO) systems with vital roles in oxidative metabolism and promising technological potential. The SCO tendency depends on the free energy balance of high- ...and low-spin states, which again depends on physical effects such as dispersion, relativistic effects, and vibrational entropy. This work studied 30 different iron SCO systems with experimentally known thermochemical data, using 12 different density functionals. Remarkably general entropy–enthalpy compensation across SCO systems was identified (R = 0.82, p = 0.002) that should be considered in rational SCO design. Iron(II) complexes displayed higher ΔH and ΔS values than iron(III) complexes and also less steep compensation effects. First-coordination sphere ΔS values computed from numerical frequencies reproduce most of the experimental entropy and should thus be included when modeling spin-state changes in inorganic chemistry (R = 0.52, p = 3.4 × 10–3; standard error in TΔS ≈ 4.4 kJ/mol at 298 K vs 16 kJ/mol of total TΔS on average). Zero-point energies favored high-spin states by 9 kJ/mol on average. Interestingly, dispersion effects are surprisingly large for the SCO process (average: 9 kJ/mol, but up to 33 kJ/mol) and favor the more compact low-spin state. Relativistic effects favor low-spin by ∼9 kJ/mol on average, but up to 24 kJ/mol. B3LYP*, TPSSh, B2PLYP, and PW6B95 performed best for the typical calculation scheme that includes ZPE. However, if relativistic and dispersion effects are included, only B3LYP* remained accurate. On average, high-spin was favored by LYP by 11–15 kJ/mol relative to other correlation functionals, and by 4.2 kJ/mol per 1% HF exchange in hybrids. 13% HF exchange was optimal without dispersion, and 15% was optimal with all effects included for these systems.
Alzheimer's Disease (AD) is a highly complex disease involving a broad range of clinical, cellular, and biochemical manifestations that are currently not understood in combination. This has led to ...many views of AD, e.g. the amyloid, tau, presenilin, oxidative stress, and metal hypotheses. The amyloid hypothesis has dominated the field with its assumption that buildup of pathogenic β-amyloid (Aβ) peptide causes disease. This paradigm has been criticized, yet most data suggest that Aβ plays a key role in the disease. Here, a new loss-of-function hypothesis is synthesized that accounts for the anomalies of the amyloid hypothesis, e.g. the curious pathogenicity of the Aβ42/Aβ40 ratio, the loss of Aβ caused by presenilin mutation, the mixed phenotypes of APP mutations, the poor clinical-biochemical correlations for genetic variant carriers, and the failure of Aβ reducing drugs. The amyloid-loss view accounts for recent findings on the structure and chemical features of Aβ variants and their coupling to human patient data. The lost normal function of APP/Aβ is argued to be metal transport across neuronal membranes, a view with no apparent anomalies and substantially more explanatory power than the gain-of-function amyloid hypothesis. In the loss-of-function scenario, the central event of Aβ aggregation is interpreted as a loss of soluble, functional monomer Aβ rather than toxic overload of oligomers. Accordingly, new research models and treatment strategies should focus on remediation of the functional amyloid balance, rather than strict containment of Aβ, which, for reasons rationalized in this review, has failed clinically.
Medvedev
(Reports, 6 January 2017, p. 49) argue that recent density functionals stray from the path toward exactness. This conclusion rests on very compact 1s
and 1s
2s
systems favored by the ...Hartree-Fock picture. Comparison to actual energies for the same systems indicates that the "straying" is not chemically relevant and is at best specific to the studied dense systems.
The chemical bonds between a transition metal (M) and oxygen (O) are of major importance in catalysis, mineralogy, biology, and astrophysics, and an adequate theoretical description of these bonds is ...thus highly needed. This paper establishes that despite recent debate on its accuracy for transition-metal systems, CCSD(T) is an excellent benchmark standard for transition-metal oxide interactions, with errors approaching those of experiment. We conclude this from a study of all 60 M–O and M+–O bond dissociation enthalpies (BDEs) of the 3d, 4d, and 5d metals, constituting a balanced data set in terms of dq configurations that also enable an assessment of the trend chemistry in oxygen’s ability to bind to transition metals. The BDEs decrease toward the right of the transition-metal series, with humps at groups 4, 5 and 8, 9. The linear trend follows the increasing electronegativity when going from the left to the right, whereas the humps are caused by differential occupation of bonding δ-orbitals and antibonding π-orbitals. We show that the BDEs correlate strongly with oxophilicity and energies of metal surface chemisorption (R 2 = 0.81–0.89); i.e., the local M–O bond dominates the energetics of transition metals reacting with oxygen. Therefore, theoretical studies of oxygen-involving transition-metal chemistry should emphasize the accuracy of the local M–O bonds. A “bottom-up” approach to theoretical catalysis may thus produce more accurate trend predictions of relevance to, for example, catalyst design. Finally, our analysis explains the large differences in chemisorption of oxygen on metal surfaces as primarily caused by the metal electronegativity relative to oxygen, defining the strength of the polar covalent bonding, and secondarily caused by d-orbital net bonding.
Spin crossover (SCO) plays a major role in biochemistry, catalysis, materials, and emerging technologies such as molecular electronics and sensors, and thus accurate prediction and design of SCO ...systems is of high priority. However, the main tool for this purpose, density functional theory (DFT), is very sensitive to applied methodology. The most abundant SCO systems are Fe(II) and Fe(III) systems. Even with average good agreement, a functional may be significantly more accurate for Fe(II) or Fe(III) systems, preventing balanced study of SCO candidates of both types. The present work investigates DFT’s performance for well-known Fe(II) and Fe(III) SCO complexes, using various design types and customized versions of GGA, hybrid, meta-GGA, meta-hybrid, double-hybrid, and long-range-corrected hybrid functionals. We explore the limits of DFT performance and identify proficient Fe(II)–Fe(III)-balanced functionals. We identify and quantify remarkable differences in the DFT description of Fe(II) and Fe(III) systems. Most functionals become more accurate once Hartree–Fock exchange is adjusted to 10–17%, regardless of the type of functionals involved. However, this typically introduces a clear Fe(II)–Fe(III) bias. The most accurate functionals measured by mean absolute errors <10 kJ/mol are CAMB3LYP-17, B3LYP*, and B97-15 with 15–17% Hartree–Fock exchange, closely followed by CAMB3LYP and CAMB3LYP-15, OPBE, rPBE-10, and B3P86-15. While GGA functionals display a small Fe(II)–Fe(III) bias, they are generally inaccurate, except the O exchange functional. Hybrid functionals (including B2PLYP double hybrids and meta hybrids) tend to favor HS too much in Fe(II) vs Fe(III), which is important in many studies where the oxidation state of iron can vary, e.g. rational SCO design and studies of catalytic processes involving iron. The only functional with a combined bias <5 kJ/mol and a decent MAE (15 kJ/mol) is our customized PBE0-12 functional. Alternatively one has to sacrifice Fe(II)–Fe(III) balance to use the best functionals for each group separately. We also investigated the precision (measured as the standard deviation of errors) and show that the target accuracy for iron SCO is 10 kJ/mol for accuracy and 5 kJ/mol for precision, and DFT is probably not going to break this limit in the near future. Importantly, all four types of functional behavior (accurate/precise, accurate/imprecise, inaccurate/precise, inaccurate/imprecise) are observed. More generally, our work illustrates the importance not only of overall accuracy but also of balanced accuracy for systems likely to occur in context.
Human neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis involve protein aggregation and share many other similarities. It is widely ...assumed that the protein aggregates exhibit a specific molecular mode of toxic action that propagates by molecular contact (seeding). This article presents a simple mathematical model arguing that these diseases are caused by reduced energy available after subtracting cell maintenance because of general turnover of the misfolded proteins rather than a specific toxic molecular action of the protein. Proteomic cost minimization can explain why highly expressed proteins changed less during evolution, leaving more energy for reproducing microorganisms on longer evolutionary timescales. In higher organisms, the excess energy instead defines cognitive capability, and the same equations remarkably apply. Proteomic cost minimization can explain why late-onset neurodegenerative diseases involve protein aggregation. The model rationalizes clinical ages of symptom onset for patients carrying pathogenic protein mutations: Unstable or aggregation-prone mutations confer a direct energy cost of turnover, but other risk modifiers also change the available cellular energy as ultimately defining clinical outcome. Proteomic cost minimization is consistent with current views on biomarker histories, explains conflicting data on overexpression models, is consistent with energy cost tradeoffs causing compensatory hyperconnectivity during early disease, and is supported by specific experiments showing that proteasome activity is required to confer toxicity to pathogenic mutants. The model lends promise to a quantitative personalized medicine of neurodegenerative disease.
•Human neurodegenerative diseases involve protein aggregation.•The computational model explains how protein misfolding causes disease.•It uses proteomic energy cost minimization as its core principle.•Disease onset occurs when all energy is spent on protein maintenance.•The model rationalizes the sigmoidal shape of biomarker histories.
Despite their vast importance to inorganic chemistry, materials science, and catalysis, the accuracy of modeling the formation or cleavage of metal–ligand (M–L) bonds depends greatly on the chosen ...functional and the type of bond in a way that is not systematically understood. In order to approach a state of high-accuracy DFT for rational prediction of chemistry and catalysis, such system-dependencies need to be resolved. We studied 30 different density functionals applied to a “balanced data set” of 60 experimental diatomic M–L bond energies; this data set has no bias toward any dq configuration, metal, bond type, or ligand as all of these occur to the same extent, and we can therefore identify accuracy bottlenecks. We show that the performance of a functional is very dependent on data set choice, and we dissect these effects into system type. In addition to the use of balanced data sets, we also argue that the precision (rather than just accuracy) of a functional is of interest, measured by standard deviations of the errors. There are distinct system dependencies both in the ligand and metal series: Hydrides are best described by a very large HF exchange percentage, possibly due to self-interaction error, whereas halides are best described by very small (0–10%) HF exchange fractions, and double-bond enforcing oxides and sulfides favor 10–25% HF exchange, as is also average for the full data set. Thus, average HF requirements hide major system-dependent requirements. For late transition metals Co–Zn, HF percentage of 0–10% is favored, whereas for the early transition metals Sc–Fe hybrid functionals with 20% HF exchange or higher are commonly favored. Accordingly, B3LYP is an excellent choice for early d-block but a poor choice for late transition metals. We conclude that DFT intrinsically underestimates the bond strengths of late vs early transition metals, correlating with increased effective nuclear charge. Thus, the revised RPBE, which reduces the overbinding tendency of PBE, is mainly an advantage for the early and mid transition metals and not very much for the late transition metals, i.e. there is a metal-dependent effect of the relative performance of RPBE vs PBE, which are widely used to study adsorption energetics on metal surfaces. Overall, the best performing functionals are PW6B95, the MN15 and MN15-L functionals, and the double hybrid B2PLYP.
The limitations of fungal laccases at higher pH and salt concentrations have intensified the search for new extremophilic bacterial laccases. We report the cloning, expression, and characterization ...of the bacterial cotA from Bacillus clausii, a supposed alkalophilic ortholog of cotA from B. subtilis. Both laccases were expressed in E. coli strain BL21(DE3) and characterized fully in parallel for strict benchmarking. We report activity on ABTS, SGZ, DMP, caffeic acid, promazine, phenyl hydrazine, tannic acid, and bilirubin at variable pH. Whereas ABTS, promazine, and phenyl hydrazine activities vs. pH were similar, the activity of B. clausii cotA was shifted upwards by ~0.5-2 pH units for the simple phenolic substrates DMP, SGZ, and caffeic acid. This shift is not due to substrate affinity (K(M)) but to pH dependence of catalytic turnover: The k(cat) of B. clausii cotA was 1 s⁻¹ at pH 6 and 5 s⁻¹ at pH 8 in contrast to 6 s⁻¹ at pH 6 and 2 s⁻¹ at pH 8 for of B. subtilis cotA. Overall, k(cat)/K(M) was 10-fold higher for B. subtilis cotA at pH(opt). While both proteins were heat activated, activation increased with pH and was larger in cotA from B. clausii. NaCl inhibited activity at acidic pH, but not up to 500-700 mM NaCl in alkaline pH, a further advantage of the alkali regime in laccase applications. The B. clausii cotA had ~20 minutes half-life at 80°C, less than the ~50 minutes at 80°C for cotA from B. subtilis. While cotA from B. subtilis had optimal stability at pH~8, the cotA from B. clausii displayed higher combined salt- and alkali-resistance. This resistance is possibly caused by two substitutions (S427Q and V110E) that could repel anions to reduce anion-copper interactions at the expense of catalytic proficiency, a trade-off of potential relevance to laccase optimization.
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