Conceptual density functional theory: status, prospects, issues

Information-theoretic quantities as effective descriptors of electrophilicity and nucleophilicity in density functional theory

CONTEXT

Electrophilicity and nucleophilicity are two vastly important chemical concepts gauging the capability of atoms in molecules to accept and donate the maximal number of electrons. In our earlier studies, we proposed to simultaneously quantify them using the Kullback-Leibler divergence from the information-theoretic approach in density functional theory. However, several issues with this scheme remain to be clarified such as its general validity, predictability, and relationship with other information-theoretic quantities. In this work, we revisit the matter with bigger datasets and deeper theoretical insights. Five information-theoretic quantities including Kullback-Leibler divergence, Hirshfeld charge, Ghost-Berkowitz-Parr entropy, and second and third orders of relative Onicescu information energy are found to be reliable and robust descriptors of electrophilicity and nucleophilicity propensities. Employing these five descriptors, we design a list of new compounds and predict their electrophilicity and nucleophilicity scales. This work should markedly improve our confidence and capability in applying information-theoretic quantities to evaluate electrophilicity and nucleophilicity propensities and henceforth pave the route for more applications of these quantities from information-theoretic approach in density functional theory in the future.

METHODS

All structures were fully optimized at the M06-2X/6-311 + G(d) level of DFT functional using the Gaussian 16 package (version C01) with integration grids and tight self-consistent-field convergence. The solvent effect was taken into account by using the implicit solvent model (CPCM) in the CH2Cl2 solvent, and all 3D contour surfaces of Fukui function, local temperature, and ITA (information-theoretic approach) quantities were generated by GaussView. The Multiwfn 3.8 program was used to calculate the ITA indexes and atomic charges.

On the link between the reaction force constant and conceptual DFT

CONTEXT

The reaction force constant ( κ ), introduced by Professor Alejandro Toro-Labbé, plays a pivotal role in characterizing the reaction pathway by assessing the curvature of the potential energy profile along the intrinsic reaction coordinate. This study establishes a novel link between κ and the reactivity descriptors of conceptual density functional theory (c-DFT). Specifically, we derive expressions that relate the reaction force constant to nuclear softness and variations in chemical potential. Our findings indicate that regions of the reaction pathway where κ is negative match with significant electronic structure rearrangements, while positive κ regions match mostly with geometric rearrangements. This correlation between κ and c-DFT reactivity descriptors enhances our understanding of the underlying forces driving chemical reactions and offers new perspectives for analyzing reaction mechanisms.

METHODS

The internal reaction path for the proton transfer in SNOH, chemical potential, and nuclear softness were computed using DFT with B3LYP exchange-correlation functional and 6-311++G(d,2p) basis set.

The role of linkers and frustrated lewis pairs catalysts in the formation of zwitterionic 1,2-anti-addition product with non-conjugated terminal diacetylenes: A computational study

This study presents a computational investigation into the mechanistic pathway and the linker units involved in forming the zwitterionic 1,2-anti-addition product of non-conjugated diacetylenes, di(propargyl)ether (DPE), di(prop-2yn-1yl)sulfane (DPS) and 1,6-Heptadiyne (HD) catalyzed by the inter-molecular phosphine/borane frustrated Lewis pairs (FLPs), i.e., PPh2[C6H3(CF3)2](P-CF)/[B(C6F5)3]([B]) and P(o-tolyl)3(P-tol)/[B(C6F5)3]([B]). The potential energy surface (PES) calculations reveal that the anti-addition of P-CF to the internal C-atoms of acetylene units is energetically more favored than that of the addition of P-tol in DPE, DPS, and HD by ∼10.0, ∼9.2, and ∼6.0 kcal/mol, respectively. The calculations performed with DPE contain "-O-," linker unit exhibits superior reactivity than DPS and HD, which suggests the electronegativity of linkers plays a significant role and facilitates the addition of Lewis bases. The higher electronegativity of linker units enables the 1,2-addition reaction by lowering the free energy activation barriers, as observed in the DFT calculations. The Molecular Electrostatic Potential (MESP) study shows that the electrostatic interactions favor the addition of P-CF to the active acetylene positions (C5/C4/C4) of [B]-DPE/DPS/HD-π complexes than the P-tol. The Distortion/Interaction (D/I) analysis reveals that transition states involving P-CF (TS1, TS3, and TS5) exhibit more interaction energy (ΔEInt) and less distortion energies (ΔEd) than that of the P-tol (TS2, TS4, and TS6). Further, the Energy Decomposition Analysis (EDA) also rationalizes the preferential approach of the electron-deficient Lewis base over the electron-rich one on the basis of the significant contribution of orbital interaction energies (ΔEorbital) in the cases of P-CF; TS1, TS3, and TS5. This study suggests that the electronic effects of substrates and the FLPs are crucial to facilitate the desired products formed with non-conjugated terminal alkynes.

Density-based quantification of steric effects: validation by Taft steric parameters from acid-catalyzed hydrolysis of esters

The steric effect is one of the most widely used concepts for chemical understanding in publications and textbooks, yet a well-accepted formulation of this effect is still elusive. Experimentally, this concept was quantified by the acid-catalyzed hydrolysis of esters, yielding the so-called Taft steric parameter. Theoretically, we recently proposed a density-based scheme to quantify the effect from density functional theory. In this work, we directly compare these two schemes, one from theory and the other from experiment. To this end, we first establish the ester hydrolysis mechanism with multiple water molecules explicitly considered and then apply the energetic span model to represent the hydrolysis barrier height between the two schemes. Our results show that the barrier height of the reaction series is strongly correlated with both Taft steric parameters from experiment and steric quantification from theory. We also obtained strong correlations with steric potential, steric force, and steric charge from our theoretical scheme. Strong correlations with a few information-theoretic quantities are additionally unveiled. To the best of our knowledge, this is the first time in the literature that such a direct comparison between theoretical and experimental results is made. These results also suggest that our proposed two-water three-step mechanism for ester hydrolysis is effective, and our theoretical quantification of the steric effect is valid, robust, and experimentally comparable. In our view, this work should have satisfactorily addressed the issue of how the steric effect can be formulated and quantified, and thus it lays the groundwork for future applications.

Bond Lengths and Dipole Moments of Diatomic Molecules under Isotropic Pressure with the XP-PCM and GOSTSHYP Models

While high-pressure chemistry has a well-established history, methods to simulate pressure at the single-molecule level have been somewhat lacking. The current work aims at comparing two static models (XP-PCM and GOSTSHYP) to apply isotropic pressure to single molecules, focusing on the equilibrium bond length and electric dipole moment of diatomic molecules. Numerical challenges arising in the potential energy surface using the XP-PCM method were examined, and a pragmatic approach was followed to mitigate these. The definition of the cavity was scrutinized, and two approaches to retrieve the isotropic character that could potentially be lost when using the standard methodology were suggested. Subsequently, equilibrium bond lengths under pressure were evaluated, showing reasonable agreement between GOSTSHYP and XP-PCM, but some discrepancies persist. A Taylor series analysis introduced elsewhere was then applied to rationalize the observed trends in terms of the bond surface. Finally, the dipole moment was shown to be highly sensitive to the cavity definition, and qualitative agreement necessitates the use of our adapted procedure.

Accessing the Cloke-Wilson Rearrangement via Conjugate Addition of Phosphoranes to Michael Acceptors: A Route to Cyclopropanes and 5-Membered Ring Heterocycles Investigated by Density Functional and Ab Initio Theory

Conjugate addition of unstabilized Wittig-type phosphonium ylides to 1,1-diacceptor- and 1-acceptor-substituted alkenes is investigated by density functional theory and high-level ab initio (DLPNO-CCSD(T)) calculations. The results indicate that the initial conjugate addition step should be facile with barriers predicted to be between 0 and 21 kcal mol-1. Potential intramolecular follow-up reactions include the formation of acceptor-substituted cyclopropanes as well as the formation of dihydrofuran derivatives via intramolecular SN2-type transition state structures. The barriers calculated for these potentially valuable cyclization reactions are substantial with Gibbs free energies of activation between 19 and 40 kcal mol-1. Competing reaction channels include Wittig olefination (for ketones and aldehydes), as well as Claisen condensation reactions. The reaction offers an alternative entry point to the nucleophile-catalyzed Cloke-Wilson rearrangement.

CuGBasis: High-performance CUDA/Python library for efficient computation of quantum chemistry density-based descriptors for larger systems

CuGBasis is a free and open-source CUDA®/Python library for efficient computation of scalar, vector, and matrix quantities crucial for the post-processing of electronic structure calculations. CuGBasis integrates high-performance Graphical Processing Unit (GPU) computing with the ease and flexibility of Python programming, making it compatible with a vast ecosystem of libraries. We showcase its utility as a Python library and demonstrate its seamless interoperability with existing Python software to gain chemical insight from quantum chemistry calculations. Leveraging GPU-accelerated code, cuGBasis exhibits remarkable performance, making it highly applicable to larger systems or large databases. Our benchmarks reveal a 100-fold performance gain compared to alternative software packages, including serial/multi-threaded Central Processing Unit and GPU implementations. This paper outlines various features and computational strategies that lead to cuGBasis's enhanced performance, guiding developers of GPU-accelerated code.

Electrochemical and quantum chemical approaches to the study of dopamine sensing using bentonite and l-cysteine modified carbon paste electrode

This work presents a significant investigation involving both electrochemical experiment and quantum chemical simulation approaches. The objective was to characterize the electrochemical detection of dopamine (DA). The detection was carried out using a modified carbon paste electrode (CPE) incorporating bentonite (Bent) and l-cysteine (CySH) (named as CySH/Bent/CPE). To understand and explain the oxidation mechanism of DA on the CySH/Bent modified electrode surface, the coupling of the two approaches were exploited. The CySH/Bent/CPE showed excellent electroactivity toward DA such as good sensibility, selectivity, stability, and regenerative ability. The developed sensor shows a dynamic linear range from 0.8 to 80 μM with a limit of detection and quantification of 0.5 μM and 1.5 μM, respectively. During the quantitative analysis of DA in presence of ascorbic acid (AA) and uric acid (UA) the electrochemical oxidation signals of AA, DA, and UA distinctly appear as three separate peaks. The potential differences between the peaks are 190 mv, 150 mv, and 340 mV for the AA-DA, DA-UA, and AA-UA oxidation pairs, respectively. These observations stem from square wave voltammetry (SWV) studies, along with the corresponding redox peak potential separations. The developed sensor is simple and accurate to monitor DA in human serum samples. On the other hand, CySH acts as an electrocatalyst on the CySH/Bent/CPE surface by increasing its active electron transfer sites, as suggested by the quantum chemical modeling with analytical results of Fukui. Furthermore, the voltammetric results obtained agree well with the theoretical calculations.

Expanding horizons in conceptual density functional theory: Novel ensembles and descriptors to decipher reactivity patterns

Conceptual density functional theory (CDFT) and the quantum reactivity descriptors stemming from it have proven to be valuable tools for understanding the chemical behavior of molecules. This article is presented as being intrinsically of dual character. In a first part, it briefly reviews, in a deliberately didactical way, the main ensembles in CDFT, while the second half presents two additional ensembles, where the chemical hardness acts as a natural variable, and their respective reactivity descriptors. The evaluation of these reactivity descriptors on common organic chemical reagents are presented and discussed.

PBAT is biodegradable but what about the toxicity of its biodegradation products?

CONTEXT

Poly(butylene adipate-co-terephthalate) (PBAT) is a biodegradable plastic. It was introduced to the plastics market in 1998 and since then has been widely used around the world. The main idea of this research is to perform quantum chemical calculations to study the potential toxicity of PBAT and its degradation products. We analyzed the electron transfer capacity to determine its potential toxicity. We found that biodegradable products formed with benzene rings are as good electron acceptors as PBAT and OOH•. Our results indicate that the biodegradation products are potentially as toxic as PBAT. This might explain why biodegradation products alter the photosynthetic system of plants and inhibit their growth. From this and other previous investigations, we can think that biodegradable plastics could represent a potential environmental risk.

METHODS

All DFT computations were performed using the Gaussian16 at M062x/6-311 + g(2d,p) level of theory without symmetry constraints. Electro-donating (ω-) and electro-accepting (ω +) powers were used as response functions.

DFT, GC-MS analysis and biological evaluation of Limbarda crithmoides L. Dumort essential oil; an important edible halophyte grown in Pakistan

Antimicrobial resistance is a major health burden in Pakistan, and therefore new herbal medicine-based therapeutic regimens are being largely investigated. Limbarda crithmoides essential oil was extracted by using hydrodistillation method. Chemical profiling of essential was evaluated by using FTIR and GC-MS analysis. A total of 20 components were identified including, p-xylene, o-xylene, β-linalool, acetophenole and 3-isopropylphenyl methylcarbamate. The HOMO and LUMO analysis in DFT investigations presented that 3-isopropylphenyl methylcarbamate, p-xylene and o-xylene posess a substantial capacity to transfer charge through molecules. The antimicrobial potential of essential oil showed moderate inhibition against E. coli (MIC = 6.25 mg/mL), whereras a significant inhibition Staphylococos aureus was recorded (MIC = 3.12 mg/mL). Further, significant antioxidant activities were recorded in DPPH radical scavenging (IC50 = 80.5 µg/mL), H2O2 (64 ± 1.2%) and FRAP (60.3 µg ferrous equivalents) assays. It was therefore concluded that Limbarda crithmoides essential oil has potential antioxidant and anti-antimicrobial properties and can be used for further investigations.

Revisiting nucleophilicity: an index for chemical reactivity from a CDFT approach

CONTEXT

Understanding and predicting the nucleophilic reactivity are paramount in elucidating organic chemical reactions and designing new synthetic pathways. In this study, we propose a nucleophilicity index within the framework of Conceptual Density Functional Theory (CDFT). Through rigorous theoretical formulations, we introduce an original quantum reactivity descriptor that captures the nucleophilic propensity of molecules based on their electronic structure and chemical environment. Subsequently, this proposed index is applied to a series of nucleophiles (pyrrolidines derivatives), spanning a diverse range of chemical functionalities. Our computational assessments reveal insightful correlations between the predicted nucleophilicity index and experimental observations of nucleophilic behavior. Thereby, they offer a promising avenue for advancing the understanding of organic reactivity and guiding synthetic efforts.

METHODS

Experimentally, Mayr's experimental parameters accounting for nucleophilicity were selected for the pyrrolidines. This study used DFT calculations at the B3LYP/Aug-cc-pVTZ level of theory using the Gaussian 16 program. Geometry optimization was thus performed, and the methodology employed for the computation of quantum reactivity descriptor is presented. Solvent effect was also taken into account using IEFPCM, and empirical dispersion correction (GD3) was employed.

Progress in the Computer-Aided Analysis in Multiple Aspects of Nanocatalysis Research

Making the utmost of the differences and advantages of multiple disciplines, interdisciplinary integration breaks the science boundaries and accelerates the progress in mutual quests. As an organic connection of material science, enzymology, and biomedicine, nanozyme-related research is further supported by computer technology, which injects in new vitality, and contributes to in-depth understanding, unprecedented insights, and broadened application possibilities. Utilizing computer-aided first-principles method, high-speed and high-throughput mathematic, physic, and chemic models are introduced to perform atomic-level kinetic analysis for nanocatalytic reaction process, and theoretically illustrate the underlying nanozymetic mechanism and structure-function relationship. On this basis, nanozymes with desirable properties can be designed and demand-oriented synthesized without repeated trial-and-error experiments. Besides that, computational analysis and device also play an indispensable role in nanozyme-based detecting methods to realize automatic readouts with improved accuracy and reproducibility. Here, this work focuses on the crossing of nanocatalysis research and computational technology, to inspire the research in computer-aided analysis in nanozyme field to a greater extent.

Spin-Polarized Conceptual Density Functional Theory from the Convex Hull

We present a new, nonarbitrary, internally consistent, and unambiguous framework for spin-polarized conceptual density-functional theory (SP-DFT). We explicitly characterize the convex hull of energy, as a function of the number of electrons and their spin, as the only accessible ground states in spin-polarized density functional theory. Then, we construct continuous linear and quadratic models for the energy. The nondifferentiable linear model exactly captures the simplicial geometry of the complex hull about the point of interest and gives exact representations for the conceptual DFT reactivity indicators. The continuous quadratic energy model is the paraboloid of maximum curvature, which most tightly encloses the point of interest and neighboring vertices. The quadratic model is invariant to the choice of coordinate system (i.e., {N, S} vs {Nα, Nβ}) and reduces to a sensible formulation of spin-free conceptual DFT in the appropriate limit. Using the quadratic model, we generalize the Parr functions {P+(r), P-(r)} (and their derivatives with respect to number of electrons) to this new spin-polarized framework, integrating the Parr function concept into the context of (spin-polarized) conceptual DFT, and extending it to include higher-order effects.

Understanding the coupling of non-metallic heteroatoms to CO2 from a Conceptual DFT perspective

CONTEXT

A Conceptual DFT (CDFT) study has been carry out to analyse the coupling reactions of the simplest amine (CH3NH2), alcohol (CH3OH), and thiol (CH3SH) compounds with CO2 to form the corresponding adducts CH3NHCO2H, CH3OCO2H, and CH3SCO2H. The reaction mechanism takes place in a single step comprising two chemical events: nucleophilic attack of the non-metallic heteroatoms to CO2 followed by hydrogen atom transfer (HAT). According to our calculations, the participation of an additional nucleophilic molecule as HAT assistant entails important decreases in activation electronic energies. In such cases, the formation of a six-membered ring in the transition state (TS) reduces the angular stress with respect to the non-assisted paths, characterised by four-membered ring TSs. Through the analysis of the energy and reaction force profiles along the intrinsic reaction coordinate (IRC), the ratio of structural reorganisation and electronic rearrangement for both activation and relaxation energies has been computed. In addition, the analysis of the electronic chemical potential and reaction electronic flux profiles confirms that the highest electronic activity as well as their changes take place in the TS region. Finally, the distortion/interaction model using an energy decomposition scheme based on the electron density along the reaction coordinate has been carried out and the relative energy gradient (REG) method has been applied to identify the most important components associated to the barriers.

METHODS

The theoretical calculation were performed with Gaussian-16 scientific program. The B3LYP-D3(BJ)/aug-cc-pVDZ level was used for optimization of the minima and TSs. IRC calculations has also been carried out connecting the TS with the associated minima. Conceptual-DFT (CDFT) calculations have been carried out with the Eyringpy program and in-house code. The distortion/interaction model along the reaction coordinate have used the decomposition scheme of Mandado et al. and the analysis of the importance of each components have been done with the relative energy gradient (REG) method.

Physicochemical Properties of 4-(4-Hydroxyphenyl)-butan-2-one ("Raspberry Ketone") Evaluated Using a Computational Chemistry Approach

Raspberry ketone (RK) is a product of the phenylpropanoid pathway in a variety of plants and is the second most expensive natural flavouring in the world. It is also widely used as a nutritional supplement due to its reported ability to promote lipolysis and fat oxidation in vivo. We have evaluated the thermodynamics of RK using the correlation consistent ccCA-CBS-2 approach which afforded calculation of (inter alia) the enthalpy of formation. To obtain pK a, log D, electrode potential, solubility, and reactivity indices, we used TPSS/def2-TZVP geometries followed by single-point energies obtained at the M06-2X/def2-TZVPP level of theory. We obtained Δf H o = -299.4 ± 0.17 kJ·mol-1; the pK a and logD were found to be 9.95 and 1.84, respectively, consistent with chemometric predictions. Using the enthalpy of fusion obtained from theory, we evaluated the aqueous solubility of RK to be in the region of 2.5 mg·mL-1 which is in agreement with limited literature reports. In terms of reactivity, we obtained a formal electrode potential of 1.29 V (vs SHE) at pH 7.4 and 298.15 K. The HOMO-LUMO energy separation in an aqueous environment was found to be ca. 7.8 eV, suggesting moderate chemical reactivity. Analysis of the frontier molecular orbitals using conceptual density functional theory supported this and revealed a reactivity pattern consistent with the metabolite profile obtained in mammals, namely, a propensity for nucleophilic attack at the carbonyl carbon and electrophilic addition of the benzene ring.

Symmetry and reactivity of π-systems in electric and magnetic fields: a perspective from conceptual DFT

The extension of conceptual density-functional theory (conceptual DFT) to include external electromagnetic fields in chemical systems is utilised to investigate the effects of strong magnetic fields on the electronic charge distribution and its consequences on the reactivity of π-systems. Formaldehyde, H2CO, is considered as a prototypical example and current-density-functional theory (current-DFT) calculations are used to evaluate the electric dipole moment together with two principal local conceptual DFT descriptors, the electron density and the Fukui functions, which provide insight into how H2CO behaves chemically in a magnetic field. In particular, the symmetry properties of these quantities are analysed on the basis of group, representation, and corepresentation theories using a recently developed automatic program for symbolic symmetry analysis, QSYM2. This allows us to leverage the simple symmetry constraints on the macroscopic electric dipole moment components to make profound predictions on the more nuanced symmetry transformation properties of the microscopic frontier molecular orbitals (MOs), electron densities, and Fukui functions. This is especially useful for complex-valued MOs in magnetic fields whose detailed symmetry analyses lead us to define the new concepts of modular and phasal symmetry breaking. Through these concepts, the deep connection between the vanishing constraints on the electric dipole moment components and the symmetry of electron densities and Fukui functions can be formalised, and the inability of the magnetic field in all three principal orientations considered to induce asymmetry with respect to the molecular plane of H2CO can be understood from a molecular perspective. Furthermore, the detailed forms of the Fukui functions reveal a remarkable reversal in the direction of the dipole moment along the CO bond in the presence of a parallel or perpendicular magnetic field, the origin of which can be attributed to the mixing between the frontier MOs due to their subduced symmetries in magnetic fields. The findings in this work are also discussed in the wider context of a long-standing debate on the possibility to create enantioselectivity by external fields.

Geometric Algebra Jordan-Wigner Transformation for Quantum Simulation

Quantum simulation qubit models of electronic Hamiltonians rely on specific transformations in order to take into account the fermionic permutation properties of electrons. These transformations (principally the Jordan-Wigner transformation (JWT) and the Bravyi-Kitaev transformation) correspond in a quantum circuit to the introduction of a supplementary circuit level. In order to include the fermionic properties in a more straightforward way in quantum computations, we propose to use methods issued from Geometric Algebra (GA), which, due to its commutation properties, are well adapted for fermionic systems. First, we apply the Witt basis method in GA to reformulate the JWT in this framework and use this formulation to express various quantum gates. We then rewrite the general one and two-electron Hamiltonian and use it for building a quantum simulation circuit for the Hydrogen molecule. Finally, the quantum Ising Hamiltonian, widely used in quantum simulation, is reformulated in this framework.

Role of Lewis acid/base anchor atoms in catalyst regeneration: a comprehensive study on biomimetic EP3Fe nitrogenases

In the quest for sustainable ammonia synthesis routes, biomimetic complexes have been intensively studied. Here we focus on the Peter's group Fe-nitrogenase catalyst with EPPP scorpionate ligands, and explore the effect of anchor atom selection (B, Al, Ga, N and P) and the impact of chloro substitution on the phenyl rings on nitrogen fixation. The reaction profiles of complexes with Lewis basic anchor atoms exhibited energy-demanding reduction steps, with more exergonic protonation steps compared to the smoother reaction profiles observed for catalysts with Lewis acid anchor atoms, also implying that catalyst regeneration is especially challenging for catalysts with Lewis basic anchor atoms. The binding affinities of N2 and H2 to the complexes suggest that the autocatalytic hydrogen evolution reaction (HER), which ultimately leads to consumption of reactants and catalyst deactivation, is likely to become more prevalent for heavier anchor atoms and be more significant for Lewis basic anchor atom complexes. Out of the studied complexes, boron showed the smoothest reaction profile and the smallest affinity for H2, which supports its superiour role as an anchor atom in accordance with experimental data.

Substitution Effects in Aryl Halides and Amides into the Reaction Mechanism of Ullmann-Type Coupling Reactions

In this article, we present a comprehensive computational investigation into the reaction mechanism of N-arylation of substituted aryl halides through Ullmann-type coupling reactions. Our computational findings, obtained through DFT ωB97X-D/6-311G(d,p) and ωB97X-D/LanL2DZ calculations, reveal a direct relation between the previously reported experimental reaction yields and the activation energy of haloarene activation, which constitutes the rate-limiting step in the overall coupling process. A detailed analysis of the reaction mechanism employing the Activation Strain Model indicates that the strain in the substituted iodoanilines is the primary contributor to the energy barrier, representing an average of 80% of the total strain energy. Additional analysis based on conceptual Density Functional Theory (DFT) suggests that the nucleophilicity of the nitrogen in the lactam is directly linked to the activation energies. These results provide valuable insights into the factors influencing energetic barriers and, consequently, reaction yields. These insights enable the rational modification of reactants to optimize the N-arylation process.

Chiral Jahn-Teller Distortion in Quasi-Planar Boron Clusters

In this work, we have observed that some chiral boron clusters (B16-, B20-, B24-, and B28-) can simultaneously have helical molecular orbitals and helical spin densities; these seem to be the first compounds discovered to have this intriguing property. We show that chiral Jahn-Teller distortion of quasi-planar boron clusters drives the formation of the helical molecular spin densities in these clusters and show that elongation/enhancement in helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity of these boron clusters is discussed. Chiral boron clusters may find potential applications in spintronics, such as molecular magnets.

Unraveling Reactivity Pathways: Dihydrogen Activation and Hydrogenation of Multiple Bonds by Pyramidalized Boron-Based Frustrated Lewis Pairs

The activation of H2 by pyramidalized boron-based frustrated Lewis Pairs (FLPs) (B/E-FLP systems where "E" refers to N, P, As, Sb, and Bi) have been explored using density functional theory (DFT) based computational study. The activation pathway for the entire process is accurately characterized through the utilization of the activation strain model (ASM) of reactivity, shedding light on the underlying physical factors governing the process. The study also explores the hydrogenation process of multiple bonds with the help of B/N-FLP. The research findings demonstrate that the liberation of activated dihydrogen occurs in a synchronized, albeit noticeably asynchronous, fashion. The transformation is extensively elucidated using the activation strain model and the energy decomposition analysis. This approach suggests a co-operative double hydrogen-transfer mechanism, where the B-H hydride triggers a nucleophilic attack on the carbon atom of the multiple bonds, succeeded by the migration of the protic N-H.

Synthesis of eugenol derivative by the ring opening of epoxide eugenol and its analysis through chemical reactivity: a DFT approach

Eugenol, a plant bioactive component, is frequently found in a variety of medicinal plants with well-defined functional attributes. Essential oils containing eugenol were extracted from buds of Eugenia caryophyllata commonly named clove using hydrodistillation. Afterwards, the analysis of the essential oils using gas chromatography/mass spectrometry (GC/MS) shows that eugenol is the major constituent with 70.14% of it. The alkene group in eugenol was epoxidised using m-chloroperbenzoic acid leading to the synthesis of epoxide eugenol. The epoxide ring was cleaved to vanillyl glycol by mixed the epoxide eugenol with aluminum chloride hydrate in an ethanolic medium. A Density Functional Theory (DFT) study was investigated to understand the reactivity of the epoxide eugenol with the aluminum chloride hydrate. The results obtained from DFT based reactivity descriptors were in good agreement with the experiment results.

Harvesting Chemical Understanding with Machine Learning and Quantum Computers

It is tenable to argue that nobody can predict the future with certainty, yet one can learn from the past and make informed projections for the years ahead. In this Perspective, we overview the status of how theory and computation can be exploited to obtain chemical understanding from wave function theory and density functional theory, and then outlook the likely impact of machine learning (ML) and quantum computers (QC) to appreciate traditional chemical concepts in decades to come. It is maintained that the development and maturation of ML and QC methods in theoretical and computational chemistry represent two paradigm shifts about how the Schrödinger equation can be solved. New chemical understanding can be harnessed in these two new paradigms by making respective use of ML features and QC qubits. Before that happens, however, we still have hurdles to face and obstacles to overcome in both ML and QC arenas. Possible pathways to tackle these challenges are proposed. We anticipate that hierarchical modeling, in contrast to multiscale modeling, will emerge and thrive, becoming the workhorse of in silico simulations in the next few decades.

Fragment-Based Deep Learning for Simultaneous Prediction of Polarizabilities and NMR Shieldings of Macromolecules and Their Aggregates

Simultaneous prediction of the molecular response properties, such as polarizability and the NMR shielding constant, at a low computational cost is an unresolved issue. We propose to combine a linear-scaling generalized energy-based fragmentation (GEBF) method and deep learning (DL) with both molecular and atomic information-theoretic approach (ITA) quantities as effective descriptors. In GEBF, the total molecular polarizability can be assembled as a linear combination of the corresponding quantities calculated from a set of small embedded subsystems in GEBF. In the new GEBF-DL(ITA) protocol, one can predict subsystem polarizabilities based on the corresponding molecular wave function (thus electron density and ITA quantities) and DL model rather than calculate them from the computationally intensive coupled-perturbed Hartree-Fock or Kohn-Sham equations and finally obtain the total molecular polarizability via a linear combination equation. As a proof-of-concept application, we predict the molecular polarizabilities of large proteins and protein aggregates. GEBF-DL(ITA) is shown to be as accurate enough as GEBF, with mean absolute percentage error <1%. For the largest protein aggregate (>4000 atoms), GEBF-DL(ITA) gains a speedup ratio of 3 compared with GEBF. It is anticipated that when more advanced electronic structure methods are used, this advantage will be more appealing. Moreover, one can also predict the NMR chemical shieldings of proteins with reasonably good accuracy. Overall, the cost-efficient GEBF-DL(ITA) protocol should be a robust theoretical tool for simultaneously predicting polarizabilities and NMR shieldings of large systems.

Exploring the Reactivity of Donor-Acceptor Systems through a Combined Conceptual and Constrained DFT Approach

In the context of the conceptual density functional theory (cDFT) and based on the computational efficiency of the constrained DFT (CDFT), we demonstrate that chemical reactivity can be governed by the difference between the local interacting chemical potentials of the reactants (referred as Edual), in agreement with Sanderson's equalization principle. In a proof-of-concept study, we investigated illustrative examples involving typical non-covalent donor-acceptor systems and reactive systems are provided. For the selected systems, our approach reveals significant mimicking between Edual and the DFT-computed intermolecular interaction energy profiles. We further evaluate the influence of the Coulomb and exchange-correlation contributions in Edual. These latter results suggest that numerous potential energy surfaces of clusters can be explored using a Sanderson-like model only based on classical interactions between molecular orbitals domains. To conclude, this study achieved a deeper understanding of the principles of cDFT and assessed, in a wider context, its efficiency in predicting the chemical reactivity.

Toxicity of persistent organic pollutants: a theoretical study

CONTEXT

Polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are two families of persistent organic pollutants that are dangerous as they remain in the atmosphere for long periods and are toxic for humans and animals. They are found all over the world, including the penguins of Antarctica. One of the mechanisms that explains the toxicity of these compounds is related to oxidative stress. The main idea of this theoretical research is to use conceptual density functional theory as a theory of chemical reactivity to analyze the oxidative stress that PCBs and PBDEs can produce. The electron transfer properties as well as the interaction with DNA nitrogenous bases of nine PCBs and ten PBDEs found in Antarctic penguins are investigated. From this study, it can be concluded that compounds with more chlorine or bromine atoms are more oxidizing and produce more oxidative stress. These molecules also interact directly with the nitrogenous bases of DNA, forming hydrogen bonds, and this may be an explanation for the toxicity. Since quinone-type metabolites of PCBs and PBDEs can cause neurotoxicity, examples of quinones are also investigated. Condensed Fukui functions are included to analyze local reactivity. These results are important as the reactivity of these compounds helps to explain the toxicity of PCBs and PBDEs.

METHODS

All DFT computations were performed using Gaussian16 at M06-2x/6-311 + g(2d,p) level of theory without symmetry constraints. Electro-donating (ω-) and electro-accepting (ω +) powers were used as global response functions and condensed Fukui functions as local parameters of reactivity.

Chemical reactivity theory to analyze possible toxicity of microplastics: Polyethylene and polyester as examples

Micro- and nanoplastics are widespread throughout the world. In particular, polyethylene (PE) and polyethylene terephthalate or polyester (PET) are two of the most common polymers, used as plastic bags and textiles. To analyze the toxicity of these two polymers, oligomers with different numbers of units were used as models. The use of oligomers as polymeric templates has been used previously with success. We started with the monomer and continued with different oligomers until the chain length was greater than two nm. According to the results of quantum chemistry, PET is a better oxidant than PE, since it is a better electron acceptor. Additionally, PET has negatively charged oxygen atoms and can promote stronger interactions than PE with other molecules. We found that PET forms stable complexes and can dissociate the guanine-cytosine nucleobase pair. This could affect DNA replication. These preliminary theoretical results may help elucidate the potential harm of micro- and nanoplastics.

Some Recent Advances in Density-Based Reactivity Theory

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Extending the Scope of Conceptual Density Functional Theory with Second Order Analytical Methodologies

In the context of the growing impact of conceptual density functional theory (DFT) as one of the most successful chemical reactivity theories, response functions up to second order have now been widely applied; in recent years, among others, particular attention has been focused on the linear response function and also extensions to higher order have been put forward. As the larger part of these studies have been carried using a finite difference approach to compute these concepts, we now embarked on (an extension of) an analytical approach to conceptual DFT. With the ultimate aim of providing a complete set of analytically computable second order properties, including the softness and hardness kernels, the hardness as the simplest second order response function is scrutinized again with numerical results highlighting the difference in nature between the analytical hardness (referred to as hardness condition) and the Parr-Pearson absolute chemical hardness. The hardness condition is investigated for its capability to gauge the (de)localization error of density functional approximations (DFAs). The analytical Fukui function, besides overcoming the difficulties in the finite difference approach in treating negatively charged systems, also showcases the errors of deviating from the straight-line behavior using fractional occupation number calculations. Subsequently, the softness kernel and its atom-condensed inverse, the hardness matrix, are accessed through the Berkowitz-Parr relation. Revisiting the softness kernel confirms and extends previous discussions on how Kohn's Nearsightedness of Electronic Matter principle can be retrieved and identified as the physicist's version of the chemist's "transferability of functional groups" concept. The accurate, analytical hardness matrix evaluation on the other hand provides further support for the basics of Nalewajski's charge sensitivity analysis. Based on Parr and Liu's functional expansion of the energy functional, a new energy decomposition is introduced with an order of magnitude analysis of the different terms for a series of simple molecules both at their equilibrium geometry and upon variation in bond length and dihedral angle. Finally, for the first time, the perturbation expansion of the energy functional is studied numerically up to second order now that all response functions and integration techniques are at hand. The perturbation expansion energies are in excellent agreement with those obtained directly from DFA calculations giving confidence in the convergence of the perturbation series and its use in judging the importance of the different terms in reactivity investigations.

Mapping the Oxygens in the Oxygen-Evolving Complex of Photosystem II by Their Nucleophilicity Using Quantum Descriptors

The oxygen-evolving complex (OEC) of Photosystem II catalyzes the water-splitting reaction using solar energy. Thus, understanding the reaction mechanism will inspire the design of biomimetic artificial catalysts that convert solar energy to chemical energy. Conceptual Density Functional Theory (CDFT) focuses on understanding the reactivity of molecules and the atomic contribution to the overall nucleophilicity and electrophilicity of the molecule using quantum descriptors. However, this method has not been applied to the OEC before. Here, we use Fukui functions and the dual descriptor to provide quantitative measures of the nucleophilicity and electrophilicity of oxygens in the OEC for different models in different S states. Our results show that the μ-oxo bridges connected to terminal Mn4 are nucleophilic, and those in the cube formed by Mn1, Mn2, and Mn3 are mostly electrophilic. The dual descriptors of the bridging oxygens in the OEC showed a similar reactivity to that of bridging oxygens in Mn model compounds. However, the terminal water W1, which is bound to Mn4, showed very strong reactivity in some of the S3 models. Thus, our calculations support the model that proposes the formation of the O2 molecule through nucleophilic attack by a terminal water.

Chemical-physical behavior of Hydroxyapatite: A modeling approach

Hydroxyapatite (HAp) is a ceramic composed of calcium phosphate, frequently employed as a bone substitute material due to its biocompatibility and bioactivity. Over the past century, there has been substantial attention in fields such as orthopedics and plastic surgery. Remarkably, synthetic HAp exhibits properties akin to those found in natural bone and teeth. Computational theoretical chemistry focuses on numerically computing molecular electronic structures and interactions. As chemistry education evolves, it's imperative to acknowledge the increasing significance of computational tools in research. Density Functional Theory (DFT) stands out as the most widely adopted method in contemporary computational chemistry. In this study, we synthesized Hydroxyapatite (HAp) via the double decomposition method using synthetic sources. The synthesized materials underwent thorough characterization, including X-ray Diffraction (XRD), UV-visible spectroscopy, and Fourier Transform Infrared (FTIR) spectroscopy under various conditions. Additionally, we performed quantum mechanical computations on the HAp molecule using density functional theory. Our results were then compared with experimental data. Our experimental findings highlight the successful synthesis of HAp, particularly under specific temperature conditions. Moreover, the quantum chemistry calculations exhibited excellent agreement with the experimental results, especially in terms of spectroscopic characterizations.

Energy is not a convex function of particle number for r-k interparticle potentials with k > log34

The energy of a many-particle system is not convex with respect to particle number for r-k interparticle repulsion potentials if k > log34 ≈ 1.262. With such potentials, some finite electronic systems have ionization potentials that are less than the electron affinity: they have negative band gap (chemical hardness). Although the energy may be a convex function of the number of electrons (for which k = 1), it suggests that finding an analytic proof of convexity will be very difficult. The bound on k is postulated to be tight. An apparent signature of non-convex behavior is that the Dyson orbital corresponding to the lowest-energy mode of electron attachment has a vanishingly small amplitude.

Marine Toxins as Pharmaceutical Treasure Troves: A Focus on Saxitoxin Derivatives from a Computational Point of View

This work highlights the significant potential of marine toxins, particularly saxitoxin (STX) and its derivatives, in the exploration of novel pharmaceuticals. These toxins, produced by aquatic microorganisms and collected by bivalve mollusks and other filter-feeding organisms, offer a vast reservoir of chemical and biological diversity. They interact with sodium channels in physiological processes, affecting various functions in organisms. Exposure to these toxins can lead to symptoms ranging from tingling sensations to respiratory failure and cardiovascular shock, with STX being one of the most potent. The structural diversity of STX derivatives, categorized into carbamate, N-sulfocarbamoyl, decarbamoyl, and deoxydecarbamoyl toxins, offers potential for drug development. The research described in this work aimed to computationally characterize 18 STX derivatives, exploring their reactivity properties within marine sponges using conceptual density functional theory (CDFT) techniques. Additionally, their pharmacokinetic properties, bioavailability, and drug-likeness scores were assessed. The outcomes of this research were the chemical reactivity parameters calculated via CDFT as well as the estimated pharmacokinetic and ADME properties derived using computational tools. While they may not align directly, the integration of these distinct datasets enriches our comprehensive understanding of the compound's properties and potential applications. Thus, this study holds promise for uncovering new pharmaceutical candidates from the considered marine toxins.

Insights into Hildebrand Solubility Parameters - Contributions from Cohesive Energies or Electrophilicity Densities?

We introduce certain concepts and expressions from conceptual density functional theory (DFT) to study the properties of the Hildebrand solubility parameter. The original form of the Hildebrand solubility parameter is used to qualitatively estimate solubilities for various apolar and aprotic substances and solvents and is based on the square root of the cohesive energy density. Our results show that a revised expression allows the replacement of cohesive energy densities by electrophilicity densities, which are numerically accessible by simple DFT calculations. As an extension, the reformulated expression provides a deeper interpretation of the main contributions and, in particular, emphasizes the importance of charge transfer mechanisms. All calculated values of the Hildebrand parameters for a large number of common solvents are compared with experimental values and show good agreement for non- or moderately polar aprotic solvents in agreement with the original formulation of the Hildebrand solubility parameters. The observed deviations for more polar and protic solvents define robust limits from the original formulation which remain valid. Likewise, we show that the use of machine learning methods leads to only slightly better predictability.

Bioaccumulative chemicals are either too hard or too soft: Conceptual density functional theory as a screening tool for emerging pollutants

Conceptual density functional theory (CDFT) descriptors were computed to predict the environmental fate of approximately 6,000 widely used industrial chemicals. CDFT descriptors aligned with a molecule's possible bioaccumulation mechanism, i.e., soft chemicals are lipophilic, whereas hard chemicals may bioaccumulate by other mechanisms such as protein binding. The results have provided us with a new "rule of thumb" to guide risk assessment of chemical hazards: suspected persistent organic pollutants are either too hard (η > 0.40 hartree) or too soft (α > 200 Å3). This offers a novel approach to environmental risk assessment using two fundamental properties of a molecule.

Wandering through quantum-mechanochemistry: from concepts to reactivity and switches

Mechanochemistry has experienced a renaissance in recent years witnessing, at the molecular level, a remarkable interplay between theory and experiment. Molecular mechanochemistry has welcomed a broad spectrum of quantum-chemical methods to evaluate the influence of an external mechanical force on molecular properties. In this contribution, an overview is given on recent work on quantum mechanochemistry in the Brussels Quantum Chemistry group (ALGC). The effect of an external force was scrutinized both in fundamental topics, like reactivity descriptors in Conceptual DFT, and in applied topics, such as designing molecular force probes and tuning the stereoselectivity of certain types of reactions. In the conceptual part, a brief overview of the techniques introducing mechanical forces into a quantum-mechanical description of a molecule is followed by an introduction to conceptual DFT. The evolution of the electronic chemical potential (or electronegativity), chemical hardness and electrophilicity are investigated when a chemical bond in a series of diatomics is put under mechanical stress. Its counterpart, the influence of mechanical stress on bond angles, is analyzed by varying the strain present in alkyne triple bonds by applying a bending force, taking the strain promoted alkyne-azide coupling cycloaddition as an example. The increase of reactivity of the alkyne upon bending is probed by Fukui functions and the local softness. In the applied part, a new molecular force probe is presented based on an intramolecular 6π-electrocyclization in constrained polyenes operating under thermal conditions. A cyclic process is conceived where ring opening and closure are triggered by applying or removing an external pulling force. The efficiency of mechanical activation strongly depends on the magnitude of the applied force and the distance between the pulling points. The idea of pulling point distances as a tool to identify new mechanochemical processes is then tested in [28]hexaphyrins with an intricate equilibrium between Möbius aromatic and Hückel antiaromatic topologies. A mechanical force is shown to trigger the interconversion between the two topologies, using the distance matrix as a guide to select appropriate pulling points. In a final application, the Felkin-Anh model for the addition of nucleophiles to chiral carbonyls under the presence of an external mechanical force is scrutinized. By applying a force for restricting the conformational freedom of the chiral ketone, otherwise inaccessible reaction pathways are promoted on the force-modified potential energy surfaces resulting in a diastereoselectivity different from the force-free reaction.

Investigating sulfonamides - Human serum albumin interactions: A comprehensive approach using multi-spectroscopy, DFT calculations, and molecular docking

The environmental and health risks associated with sulfonamide antibiotics (SAs) are receiving increasing attention. Through multi-spectroscopy, density functional theory (DFT), and molecular docking, this study investigated the interaction features and mechanisms between six representative SAs and human serum albumin (HSA). Multi-spectroscopy analysis showed that the six SAs had significant binding capabilities with HSA. The order of binding constants at 298 K was as follows: sulfadoxine (SDX): 7.18 × 105 L mol-1 > sulfamethizole (SMT): 6.28 × 105 L mol-1 > sulfamerazine (SMR): 2.70 × 104 L mol-1 > sulfamonomethoxine (SMM): 2.54 × 104 L mol-1 > sulfamethazine (SMZ): 3.06 × 104 L mol-1 > sulfadimethoxine (SDM): 2.50 × 104 L mol-1. During the molecular docking process of the six SAs with HSA, the binding affinity range is from -7.4 kcal mol-1 to -8.6 kcal mol-1. Notably, the docking result of HSA-SDX reached the maximum of -8.6 kcal mol-1, indicating that SDX may possess the highest binding capacity to HSA. HSA-SDX binding, identified as a static quenching and exothermic process, is primarily driven by hydrogen bonds (H bonds) or van der Waals (vdW) interactions. The quenching processes of SMR/SMZ/SMM/SDX/SMT to HSA are a combination of dynamic and static quenching, indicating an endothermic reaction. Hydrophobic interactions are primarily accountable for SMR/SMZ/SMM/SDX/SMT and HSA binding. Competition binding results revealed that the primary HSA-SAs binding sites are in the subdomain IB of the HAS structure, consistent with the results of molecule docking. The correlation analysis based on DFT calculations revealed an inherent relationship between the structural chemical features of SAs and the binding performance of HSA-SAs. The dual descriptor (DD) and the electrophilic Fukui function were found to have a significant relationship (0.71 and -0.71, respectively) with the binding constants of HSA-SAs, predicting the binding performance of SAs and HSA. These insights have substantial scientific value for evaluating the environmental risks of SAs as well as understanding their impact on biological life activities.

Exploring marine toxins: comparative analysis of chemical reactivity properties and potential for drug discovery

Marine toxins, produced by various marine microorganisms, pose significant risks to both marine ecosystems and human health. Understanding their diverse structures and properties is crucial for effective mitigation and exploration of their potential as therapeutic agents. This study presents a comparative analysis of two hydrophilic and two lipophilic marine toxins, examining their reactivity properties and bioavailability scores. By investigating similarities among these structurally diverse toxins, valuable insights into their potential as precursors for novel drug development can be gained. The exploration of lipophilic and hydrophilic properties in drug design is essential due to their distinct implications on drug distribution, elimination, and target interaction. By elucidating shared molecular properties among toxins, this research aims to identify patterns and trends that may guide future drug discovery efforts and contribute to the field of molecular toxinology. The findings from this study have the potential to expand knowledge on toxins, facilitate a deeper understanding of their bioactivities, and unlock new therapeutic possibilities to address unmet biomedical needs. The results showcased similarities among the studied systems, while also highlighting the exceptional attributes of Domoic Acid (DA) in terms of its interaction capabilities and stability.

Directionality and additivity effects of molecular acidity and aromaticity for substituted benzoic acids under external electric fields

Our recent study [M. Li et al.Phys. Chem. Chem. Phys., 2023, 25, 2595-2605] unveiled that the impact of an external electric field on molecular acidity and aromaticity for benzoic acid is directional, which can be understood using changes in frontier orbitals and partial charges. However, it is unclear if the effect will disappear when substituting groups are present and whether new patterns of changes will show up. In this work, as a continuation of our efforts to appreciate the impact of external electric fields on physiochemical properties, we find that the directionality effect is still in place for substituted benzoic acid derivatives and that there exists the additivity effect with respect to the number of substituent groups, regardless of the direction of the applied field and the type of substituting groups. We confirm the findings using electron-donating and electron-accepting groups with the electric field applied either parallelly or perpendicularly to the carboxyl group along the benzene ring. The directionality and additivity effects uncovered from this work should enrich the body of our knowledge about the impact of external electric fields on physiochemical properties and could be applicable to other systems and properties as well.

Machine learning prediction of empirical polarity using SMILES encoding of organic solvents

Machine learning based statistical models have played a significant role in increasing the speed and accuracy with which the chemical and physical properties of chemical compounds can be predicted as compared to the experimental, and traditional ab initio and quantum mechanical approaches. The transformative impact that these techniques have, in the field of chemical sciences has completely changed the way experiments are designed. The last decade has seen the prominence of computer-aided molecular design based on machine learning algorithms. The major challenge has been the generation of machine-readable data in the form of descriptors and observations for training the model, which can again be time-consuming and computationally expensive if atomic coordinates based molecular encoding approach is used. In this study, we have tried to solve this problem using SMILES representation of molecules for generating various topological, physicochemical, electronic and steric descriptors using open-source cheminformatics packages. With the aid of the data generated using these packages, we have been able to develop a simple and explainable quantitative structure property relationship model using artificial neural network based on 7 numerical descriptors and 1 categorical descriptor for predicting the empirical polarity of a wide diversity of organic solvents. Since polarity is the representation of various solute-solvent and solvent-solvent interactions taking place in an organic transformation, its intuition beforehand will definitely help a chemist in a better experimental design. An ANN algorithm based on 8 descriptors was successfully employed to predict the ET(30) values of organic solvents.

Computational Discovery of Marine Molecules of the Cyclopeptide Family with Therapeutic Potential

Stellatolides are natural compounds that have shown promising biological activities, including antitumor, antimicrobial, and anti-inflammatory properties, making them potential candidates for drug development. Chemical Reactivity Theory (CRT) is a branch of chemistry that explains and predicts the behavior of chemical reactions based on the electronic structure of molecules. Conceptual Density Functional Theory (CDFT) and Computational Peptidology (CP) are computational approaches used to study the behavior of atoms, molecules, and peptides. In this study, we present the results of our investigation of the chemical reactivity and ADMET properties of Stellatolides A-H using a novel computational approach called Conceptual DFT-based Computational Peptidology (CDFT-CP). Our study uses CDFT and CP to predict the reactivity and stability of molecules and to understand the behavior of peptides at the molecular level. We also predict the ADMET properties of the Stellatolides A-H to provide insight into their effectiveness, potential side effects, and optimal dosage and route of administration, as well as their biological targets. This study sheds light on the potential of Stellatolides A-H as promising candidates for drug development and highlights the potential of CDFT-CP for the study of other natural compounds and peptides.

Talarolide A and Talaropeptides A-D: Potential Marine-Derived Therapeutic Peptides with Interesting Chemistry and Biological Activity Studied through Density Functional Theory (DFT) and Conceptual DFT

Molecules sourced from marine environments hold immense promise for the development of novel therapeutic drugs, owing to their distinctive chemical compositions and valuable medicinal attributes. Notably, Talarolide A and Talaropeptides A-D have gained recent attention as potential candidates for pharmaceutical applications. This study aims to explore the chemical reactivity of Talarolide A and Talaropeptides A-D through the application of molecular modeling and computational chemistry techniques, specifically employing Conceptual Density Functional Theory (CDFT). By investigating their chemical behaviors, the study seeks to contribute to the understanding of the potential pharmacological uses of these marine-derived compounds. The molecular geometry optimizations and frequency calculations were conducted using the Density Functional Tight Binding (DFTBA) method. This was followed by a subsequent round of geometry optimization, frequency analysis, and computation of electronic properties and chemical reactivity descriptors. We employed the MN12SX/Def2TZVP/H2O model chemistry, utilizing the Gaussian 16 program and the SMD solvation model. The analysis of the global reactivity descriptors arising from CDFT was achieved as well as the graphical comparison of the dual descriptor DD revealing the areas of the molecules with more propensity to suffer a nucleophilic or electrophilic attack. Additionally, Molinspiration and SwissTargetPrediction were considered for the calculation of molecular characteristics and predicted biological targets. These include enzymes, nuclear receptors, kinase inhibitors, GPCR ligands, and ion channel modulators. The graphical results show that Talarolide A and the Talaropeptides A-D are likely to behave as protease inhibitors.

Nucleoside Analog Reverse-Transcriptase Inhibitors in Membrane Environment: Molecular Dynamics Simulations

The behavior of four drugs from the family of nucleoside analog reverse-transcriptase inhibitors (zalcitabine, stavudine, didanosine, and apricitabine) in a membrane environment was traced using molecular dynamics simulations. The simulation models included bilayers and monolayers composed of POPC and POPG phospholipids. It was demonstrated that the drugs have a higher affinity towards POPG membranes than POPC membranes due to attractive long-range electrostatic interactions. The results obtained for monolayers were consistent with those obtained for bilayers. The drugs accumulated in the phospholipid polar headgroup region. Two adsorption modes were distinguished. They differed in the degree of penetration of the hydrophilic headgroup region. Hydrogen bonds between drug molecules and phospholipid heads were responsible for adsorption. It was shown that apricitabine penetrated the hydrophilic part of the POPC and POPG membranes more effectively than the other drugs. Van der Waals interactions between S atoms and lipids were responsible for this.

To Prevent Oxidative Stress, What about Protoporphyrin IX, Biliverdin, and Bilirubin?

The pigments responsible for eggshell color and patterning in birds are protoporphyrin IX (PP) and biliverdin (BV). Both are involved in the catalytic degradation of the hemo group. Bilirubin (BR), another pigment, is produced when BV is broken down. PP, BV, and BR are free radical scavengers. In this study, we theoretically investigated the antioxidant capacities of these three biological meaningful molecules using Density Functional Theory calculations. First, two antioxidant mechanisms were analyzed for PP, BV, and BR: electron transfer and Hydrogen Atom Transfer. Second, since PP and BV interact with the calcium carbonate matrix of the eggshell, we analyzed the interaction of these pigments with Ca2+ and investigated their chelate compounds. Third, we explored the pro-oxidant properties of PP and BV, which have been proposed for PP when photoactivated to the triplet state, but not for BV. Our results show that PP, BV, and BR are just as good antiradical as other important natural pigments (carotenoids). Neither the antiradical properties of PP and BV nor the UV-visible spectra change due to the presence of calcium, suggesting that the signaling function of these pigments is not affected by the link with Ca2+. Finally, we found that both PP and BV (alone and when linked to Ca2+) can transfer energy from its triplet state to molecular-oxygen-producing singlet oxygen, indicating their pro-oxidant capacity. This investigation answers important questions about the function of these pigments, which may help to understand their influence on the reproductive success of birds.

Extending Conceptual Density Functional Theory toward First-Order Reduced Density Matrices: An Open Subsystems Viewpoint on the Fukui Matrix

As a matrix extension of the Fukui function, a reactivity descriptor grounded within Conceptual Density Functional Theory, the Fukui matrix extends Frontier Molecular Orbital Theory to correlated regimes with its eigendecomposition in Fukui occupations and Fukui naturals. Despite successful applications, the questions remain as to whether replacing a quantity derived from a purely density-based framework by its matrix extension is theoretically well-founded and what chemical information is contained in the corresponding eigendecomposition. In this study, we show that the matrix extension of the Fukui function is only well-defined if one also generalizes the external potential to become nonlocal, leading to the introduction of Conceptual First-Order Reduced Density Matrix Functional Theory. By interpreting the Anderson impurity model from an interacting open subsystem perspective, we show how Fukui occupations and Fukui naturals reflect the influence of an increasing (static) correlation and which characteristic patterns we should expect within a molecular context. This study represents a step in generalizing Conceptual Density Functional Theory beyond its density-based perspective.

Topological analysis of information-theoretic quantities in density functional theory

We have witnessed considerable research interest in the recent literature about the development and applications of quantities from the information-theoretic approach (ITA) in density functional theory. These ITA quantities are explicit density functionals, whose local distributions in real space are continuous and well-behaved. In this work, we further develop ITA by systematically analyzing the topological behavior of its four representative quantities, Shannon entropy, two forms of Fisher information, and relative Shannon entropy (also called information gain or Kullback-Leibler divergence). Our results from their topological analyses for 103 molecular systems provide new insights into bonding interactions and physiochemical properties, such as electrophilicity, nucleophilicity, acidity, and aromaticity. We also compare our results with those from the electron density, electron localization function, localized orbital locator, and Laplacian functions. Our results offer a new methodological approach and practical tool for applications that are especially promising for elucidating chemical bonding and reactivity propensity.

Preliminary Evaluation of Lablab purpureus Phytochemicals for Anti-BoHV-1 Activity Using In Vitro and In Silico Approaches

Lablab purpureus from the Fabaceae family has been reported to have antiviral properties and used in traditional medical systems like ayurveda and Chinese medicine and has been employed to treat a variety of illnesses including cholera, food poisoning, diarrhea, and phlegmatic diseases. The bovine alphaherpesvirus-1 (BoHV-1) is notorious for causing significant harm to the veterinary and agriculture industries. The removal of the contagious BoHV-1 from host organs, particularly in those reservoir creatures, has required the use of antiviral drugs that target infected cells. This study developed LP-CuO NPs from methanolic crude extracts, and FTIR, SEM, and EDX analyses were used to confirm their formation. SEM analysis revealed that the LP-CuO NPs had a spherical shape with particle sizes between 22 and 30 nm. Energy-dispersive X-ray pattern analysis revealed the presence of only copper and oxide ions. By preventing viral cytopathic effects in the Madin-Darby bovine kidney cell line, the methanolic extract of Lablab purpureus and LP-CuO NPs demonstrated a remarkable dose-dependent anti-BoHV-1 action in vitro. Furthermore, molecular docking and molecular dynamics simulation studies of bio-actives from Lablab purpureus against the BoHV-1 viral envelope glycoprotein disclosed effective interactions between all phytochemicals and the protein, although kievitone was found to have the highest binding affinity, with the greatest number of interactions, which was also validated with molecular dynamics simulation studies. Understanding the chemical reactivity qualities of the four ligands was taken into consideration facilitated by the global and local descriptors, which aimed to predict the chemical reactivity descriptors of the studied molecules through the conceptual DFT methodology, which, along with ADMET finding, support the in vitro and in silico results.

Accelerating Reaction Network Explorations with Automated Reaction Template Extraction and Application

Autonomously exploring chemical reaction networks with first-principles methods can generate vast data. Especially autonomous explorations without tight constraints risk getting trapped in regions of reaction networks that are not of interest. In many cases, these regions of the networks are only exited once fully searched. Consequently, the required human time for analysis and computer time for data generation can make these investigations unfeasible. Here, we show how simple reaction templates can facilitate the transfer of chemical knowledge from expert input or existing data into new explorations. This process significantly accelerates reaction network explorations and improves cost-effectiveness. We discuss the definition of the reaction templates and their generation based on molecular graphs. The resulting simple filtering mechanism for autonomous reaction network investigations is exemplified with a polymerization reaction.

Reaction mechanism - explored with the unified reaction valley approach

One of the ultimate goals of chemistry is to understand and manipulate chemical reactions, which implies the ability to monitor the reaction and its underlying mechanism at an atomic scale. In this article, we introduce the Unified Reaction Valley Approach (URVA) as a tool for elucidating reaction mechanisms, complementing existing computational procedures. URVA combines the concept of the potential energy surface with vibrational spectroscopy and describes a chemical reaction via the reaction path and the surrounding reaction valley traced out by the reacting species on the potential energy surface on their way from the entrance to the exit channel, where the products are located. The key feature of URVA is the focus on the curving of the reaction path. Moving along the reaction path, any electronic structure change of the reacting species is registered by a change in the normal vibrational modes spanning the reaction valley and their coupling with the path, which recovers the curvature of the reaction path. This leads to a unique curvature profile for each chemical reaction, with curvature minima reflecting minimal change and curvature maxima indicating the location of important chemical events such as bond breaking/formation, charge polarization and transfer, rehybridization, etc. A decomposition of the path curvature into internal coordinate components or other coordinates of relevance for the reaction under consideration, provides comprehensive insight into the origin of the chemical changes taking place. After giving an overview of current experimental and computational efforts to gain insight into the mechanism of a chemical reaction and presenting the theoretical background of URVA, we illustrate how URVA works for three diverse processes, (i) [1,3] hydrogen transfer reactions; (ii) α-keto-amino inhibitor for SARS-CoV-2 Mpro; (iii) Rh-catalyzed cyanation. We hope that this article will inspire our computational colleagues to add URVA to their repertoire and will serve as an incubator for new reaction mechanisms to be studied in collaboration with our experimental experts in the field.