Understanding non-covalent interactions in larger molecular complexes from first principles

Exploring the influence of water micro assemblies on protein folding, enzyme catalysis and membrane dynamics

Water is central to biological processes not only as a solvent, but also as an agent shaping macromolecular behavior. Insights into water micro assemblies (WMA), defined by transient regions of low-density water (LDW) and high-density water (HDW), have highlighted their potential impact on biological phenomena. LDW, with its structured hydrogen bonding networks and reduced density, stabilizes hydrophobic interfaces and promotes ordered molecular configurations. Conversely, HDW, with its dynamic and flexible nature, facilitates transitions, solute mobility and molecular flexibility. By correlating experimental observations with simulations, we explore the influence of WMA on three key biological processes. In protein folding, LDW may stabilize hydrophobic cores and secondary structures by forming structured exclusion zones, while HDW may introduce dynamic flexibility, promoting the resolution of folding intermediates and leading to dynamic rearrangements. In enzyme catalysis, LDW may form structured hydration shells around active sites stabilizing active sites over longer timescales, while HDW may support substrate access and catalytic flexibility within active sites. In membrane dynamics, LDW may stabilize lipid headgroups, forming structured hydration layers that enhance membrane rigidity and stability, while HDW may ensure the nanosecond-scale flexibility required for vesicle formation and fusion. Across these tree processes, the WMA's energy contributions, timescales and spatial scales align with the forces and dynamics involved, highlighting the role of LDW and HDW in modulating cellular interactions. This perspective holds implications for the design of lab-on-chip devices, advancements in sensor technologies, development of biomimetic membranes for drug delivery, creation of novel therapeutics and deeper understanding of protein misfolding diseases.

Graphene and its modifications for enhanced adhesion in dental restoratives: a molecular docking and dynamics study

Graphene has attracted significant attention in dentistry due to its structural and adhesive properties, enhancing the mechanical performance of dental composites. This study investigates the behavior and interaction of monomers and graphene-based adhesives using molecular docking and molecular dynamics (MD) simulations. Binding energies and interactions between monomers and graphene derivatives were assessed using molecular docking, while MD simulations with the Forcite module and COMPASS II force field provided insights into the mechanical properties of the composites. The simulations involved energy minimization, NVT/NPT ensembles, and equilibration for 50 ns. The binding energies of the monomer-graphene complexes ranged from - 16.27 to -18.55 kcal/mol, with the Bis-GMA-Graphene Quantum Dot complex showing the most stable interaction. Mechanical properties such as Young's modulus, shear modulus, and flexural strength were calculated for selected complexes: Bis-GMA-Graphene Quantum Dot (14.74 GPa, 9.32 GPa, 120.51 MPa), EBPADMA-Graphene Quantum Dot (14.28 GPa, 9.13 GPa, 118.22 MPa), HEMA-Nitrogen-doped Graphene (9.85 GPa, 6.86 GPa, 95.7 MPa), TEGDMA-Graphene Oxide (11.96 GPa, 8.12 GPa, 110.23 MPa), and UDMA-CCOOH Functionalized Graphene (13.82 GPa, 8.43 GPa, 115.4 MPa). The Bis-GMA-Graphene Quantum Dot complex showed the highest stability with 20 hydrogen bonds. These results highlight graphene quantum dots and functionalized graphene derivatives as promising candidates for high-performance dental composites, offering strong adhesive properties and improved mechanical strength. Future research may focus on further optimizing these interactions and exploring additional graphene modifications.

Another Angle on Benchmarking Noncovalent Interactions

For noncovalent interactions, the CCSD(T)-coupled cluster method is widely regarded as the "gold standard". With localized orbital approximations, benchmarks for ever larger complexes are being published, yet FN-DMC (fixed-node quantum Monte Carlo) intermolecular interaction energies diverge to a progressively larger degree from CCSD(T) as the system size grows, particularly when π-stacking is involved. Unfortunately, post-CCSD(T) methods like CCSDT(Q) are cost-prohibitive, which requires us to consider alternative means of estimating post-CCSD(T) contributions. In this work, we take a step back by considering the evolution of the correlation energy with respect to the number of subunits for such π-stacked sequences as acene dimers and alkadiene dimers. We show it to be almost perfectly linear and propose the slope of the line as a probe for the behavior of a given electron correlation method. By going further into the coupled cluster expansion and comparing with CCSDT(Q) results for benzene and naphthalene dimers, we show that CCSD(T) does slightly overbind but not as strongly as suggested by the FN-DMC results.

What is the Exchange Repulsion Energy? Insight by Partitioning into Physically Meaningful Contributions

It is shown that the exchange repulsion energy, Exr, can be rationalized by partitioning the respective energy expression for two systems with Hartree-Fock orbitals into physically meaningful contributions. A division of Exr into a positive kinetic and a negative potential part is possible, but these contributions correlate only poorly with the actual exchange repulsion energy. A more meaningful partitioning is derived, where all kinetic energy contributions are collected in a term that vanishes for exact Hartree-Fock orbitals due to their stationarity conditions. The remaining terms can be distinguished into an exchange integral contribution as well as contributions to the repulsion energy with two, three and four orbital indices. The forms, relationships and absolute sizes of these terms suggest an intuitive partitioning of the exchange repulsion energy into Molecular Orbital Pair Contributions to the Exchange repulsion energy (MOPCE). Insight into the analytic form and quantitative size of these contributions is provided by considering the3 Σ u + ( 1 σ g 1 σ u ) ${^3 \Sigma _u^+ (1\sigma _g 1\sigma _u )}$ state of the H2 molecule, the water dimer, as well as an argon atom interacting with Cl2 and N2.

Theoretical monitoring of aromaticity induction from noble gases to Borole structure

Density functional theory (DFT) calculations were conducted to examine the inductive charge transferring from noble gas (Ng) atoms to borole structure. The calculations indicate that all noble gas atoms especially heavier ones can induce charge to the B atom of the borole structure and decrease its antiaromaticity nature. In-depth, Ng∙∙∙B interaction analyses reveal that the noble gas atoms serve as donor fragments in the formation of Ng∙∙∙B donor-acceptor non-covalent interactions. It has been demonstrated that noble gas atoms can successively form aromaticity induction via interacting with B atom in the borole structure.

A brief introduction to the diffusion Monte Carlo method and the fixed-node approximation

Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and powerful approaches to the study of electronic structure, but its application is often hindered by a steep learning curve; hence it is rarely addressed in undergraduate and postgraduate classes. This tutorial is a step toward filling this gap. We offer an introduction to the diffusion Monte Carlo (DMC) method, which aims to solve the imaginary time Schrödinger equation through stochastic sampling of the configuration space. Starting from the theoretical foundations, the discussion leads naturally to the formulation of a step-by-step algorithm. To illustrate how the method works in simplified scenarios, examples such as the harmonic oscillator and the hydrogen atom are provided. The discussion extends to the fixed-node approximation, a crucial approach for addressing the fermionic sign problem in multi-electron systems. In particular, we examine the influence of trial wave function nodal surfaces on the accuracy of DMC energy by evaluating results from a non-interacting two-fermion system. Extending the method to excited states is feasible in principle, but some additional considerations are needed, supported by practical insights. By addressing the fundamental concepts from a hands-on perspective, we hope this tutorial will serve as a valuable guide for researchers and students approaching DMC for the first time.

Canonical coupled cluster binding benchmark for nanoscale noncovalent complexes at the hundred-atom scale

In this study, we introduce two datasets for nanoscale noncovalent binding, featuring complexes at the hundred-atom scale, benchmarked using coupled cluster with single, double, and perturbative triple [CCSD(T)] excitations extrapolated to the complete basis set (CBS) limit. The first dataset, L14, comprises 14 complexes with canonical CCSD(T)/CBS benchmarks, extending the applicability of CCSD(T)/CBS binding benchmarks to systems as large as 113 atoms. The second dataset, vL11, consists of 11 even larger complexes, evaluated using the local CCSD(T)/CBS method with stringent thresholds, covering systems up to 174 atoms. We compare binding energies obtained from local CCSD(T) and fixed-node diffusion Monte Carlo (FN-DMC), which have previously shown discrepancies exceeding the chemical accuracy threshold of 1 kcal/mol in large complexes, with the new canonical CCSD(T)/CBS results. While local CCSD(T)/CBS agrees with canonical CCSD(T)/CBS within binding uncertainties, FN-DMC consistently underestimates binding energies in π-π complexes by over 1 kcal/mol. Potential sources of error in canonical CCSD(T)/CBS are discussed, and we argue that the observed discrepancies are unlikely to originate from CCSD(T) itself. Instead, the fixed-node approximation in FN-DMC warrants further investigation to elucidate these binding discrepancies. Using these datasets as reference, we evaluate the performance of various electronic structure methods, semi-empirical approaches, and machine learning potentials for nanoscale complexes. Based on computational accuracy and stability across system sizes, we recommend MP2+aiD(CCD), PBE0+D4, and ωB97X-3c as reliable methods for investigating noncovalent interactions in nanoscale complexes, maintaining their promising performance observed in smaller systems.

Advancing Non-Atom-Centered Basis Methods for More Accurate Interaction Energies: Benchmarks and Large-Scale Applications

Recent advances in local electron correlation approaches have enabled the relatively routine access to CCSD(T) [that is, coupled cluster (CC) with single, double, and perturbative triple excitations] computations for molecules of a hundred or more atoms. Here, approaching their complete basis set (CBS) limit becomes more challenging due to extensive basis set superposition errors, often necessitating the use of large atomic orbital (AO) basis sets with diffuse functions. Here, we study a potential remedy in the form of non-atom-centered or floating orbitals (FOs). FOs are still rarely employed even for small molecules due to the practical complication of defining their position, number, exponents, etc. The most frequently used FO method thus simply places a single FO center with a large number of FOs toward the middle of noncovalent dimers; however, a single FO center for larger complexes can soon become insufficient. A recent alternative uses a grid of FO centers around the monomers with a single s function per center, which is currently applicable only for H, C, N, and O atoms. Here, we build on the above advantages and mitigate some drawbacks of previous FO approaches by using a layer of FO centers and 4-9 FOs/center for each monomer. Thus, a double layer of FOs is placed between the interacting subsystems. When extending the double-ζ AO basis with this double layer of FOs, the quality of conventional augmented double-ζ or conventional triple-ζ AO bases can be reached or surpassed with less orbitals, leading to few tenths of a kcal/mol basis set errors for medium-sized dimers. This good performance extends to larger molecules (shown here up to 72 atoms), as efficient local natural orbital (LNO) CCSD(T) computations with only double-ζ AO and 4 FOs/center FO bases match our LNO-CCSD(T)/CBS reference within ca. 0.1 kcal/mol. These developments introduce FO methods to the accurate modeling of large molecular complexes without limitations to atom types by further accelerating efficient correlation calculations, like LNO-CCSD(T).

A comprehensive study of experimental and theoretical characterization and in silico toxicity analysis of new molecules

In this study, for the first time in the literature, a 2-(3-methoxyphenylamino)-2-oxoethyl acrylate (3MPAEA) molecule was synthesized in two steps, and a 2-chloro-N-(3-methoxyphenyl)acetamide (m-acetamide) was obtained in the first step. Experimental results were obtained using FTIR, 1H, and 13C NMR spectroscopy methods for m-acetamide and 3MPAEA compounds created in the laboratory environment and compared with theoretical results. Band gap (BG) energy, chemical hardness, electronegativity, chemical potential, and electrophilicity index were calculated. With vibration spectroscopic analysis, atom-molecule vibrations of the theoretical and experimental peaks of the spectrum were observed. The locations of C and H atoms were determined by nuclear magnetic resonance spectroscopy. The green, blue, and red regions of the potential energy map (MEP) map were examined. Some observed that the energy thermal, heat capacity, and entropy graphs increased in direct proportion to increasing the temperature in Kelvin, which is known as thermochemistry. The changes in the rotation, translation, and vibration of the molecule as its temperature increased were examined. When the thermochemistry surface map was examined, some observed that the temperature was high in the middle binding site of the molecules. Covalent interactions were graphed using the non-covalent interactions (NCIs) calculation method. In silico toxicity studies were carried out for m-acetamide and 3MPAEA molecules: fathead minnow LC50 (96 h), Daphnia magna LC50 (48 h), Tetrahymena pyriformis IGC50 (48 h), oral rat LD50, water solubility, bioconcentration factor, developmental toxicity, mutation, normal boiling point, flash point, melting point, density, thermal conductivity, viscosity, vapor pressure, etc. parameters were investigated.

Assessing the Noncovalent Interaction of Deucravacitinib and Ethanol with Special Reference to an Independent Gradient Model Based on Hirshfeld Partition

The current study begins by optimizing the deucravacitinib molecule in the gas phase at the ωB97XD/cc-pVDZ level of theory using density functional theory and proceeds to study its intramolecular interactions. Further, a molecule of EtOH was introduced at different locations on the deucravacitinib molecule, and the noncovalent interactions arising from them were also investigated using several computational tools. In this way, eight deucravacitinib-EtOH systems (1-8) were identified and their electronic environment was studied after evaluating their binding energy. Using natural bond orbital analysis, the localization of charges between the donor and acceptor fragments in these interacting systems was examined. The nature of interactions was analyzed using the reduced gradient approach (NCI analysis), and few hydrogen bonding interactions (intermolecular and intramolecular) were found in each system. The strength of these hydrogen bonding interactions was further investigated by using theoretical tools such as atoms in molecules analysis and independent gradient model based on Hirshfeld partition analysis. The binding energy of deucravacitinib with EtOH was decomposed into energy components based on the domain-based local pair natural orbital coupled cluster technique using LED analysis. The results from the hydrogen bonding interaction analysis using different computational tools were found to be consistent with the calculated order of binding energy of systems 1-8 and they also pointed toward the higher stability of system 3.

State-of-the-art local correlation methods enable affordable gold standard quantum chemistry for up to hundreds of atoms

In this feature, we review the current capabilities of local electron correlation methods up to the coupled cluster model with single, double, and perturbative triple excitations [CCSD(T)], which is a gold standard in quantum chemistry. The main computational aspects of the local method types are assessed from the perspective of applications, but the focus is kept on how to achieve chemical accuracy (i.e., <1 kcal mol-1 uncertainty), as well as on the broad scope of chemical problems made accessible. The performance of state-of-the-art methods is also compared, including the most employed DLPNO and, in particular, our local natural orbital (LNO) CCSD(T) approach. The high accuracy and efficiency of the LNO method makes chemically accurate CCSD(T) computations accessible for molecules of hundreds of atoms with resources affordable to a broad computational community (days on a single CPU and 10-100 GB of memory). Recent developments in LNO-CCSD(T) enable systematic convergence and robust error estimates even for systems of complicated electronic structure or larger size (up to 1000 atoms). The predictive power of current local CCSD(T) methods, usually at about 1-2 order of magnitude higher cost than hybrid density functional theory (DFT), has become outstanding on the palette of computational chemistry applicable for molecules of practical interest. We also review more than 50 LNO-based and other advanced local-CCSD(T) applications for realistic, large systems across molecular interactions as well as main group, transition metal, bio-, and surface chemistry. The examples show that properly executed local-CCSD(T) can contribute to binding, reaction equilibrium, rate constants, etc. which are able to match measurements within the error estimates. These applications demonstrate that modern, open-access, and broadly affordable local methods, such as LNO-CCSD(T), already enable predictive computations and atomistic insight for complicated, real-life molecular processes in realistic environments.

To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water

The extent of ion pairing in solution is an important phenomenon to rationalize transport and thermodynamic properties of electrolytes. A fundamental measure of this pairing is the potential of mean force (PMF) between solvated ions. The relative stabilities of the paired and solvent shared states in the PMF and the barrier between them are highly sensitive to the underlying potential energy surface. However, direct application of accurate electronic structure methods is challenging, since long simulations are required. We develop wave function based machine learning potentials with the random phase approximation (RPA) and second order Møller-Plesset (MP2) perturbation theory for the prototypical system of Na and Cl ions in water. We show both methods in agreement, predicting the paired and solvent shared states to have similar energies (within 0.2 kcal/mol). We also provide the same benchmarks for different DFT functionals as well as insight into the PMF based on simple analyses of the interactions in the system.

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

Many-Body Methods for Surface Chemistry Come of Age: Achieving Consensus with Experiments

The adsorption energy of a molecule onto the surface of a material underpins a wide array of applications, spanning heterogeneous catalysis, gas storage, and many more. It is the key quantity where experimental measurements and theoretical calculations meet, with agreement being necessary for reliable predictions of chemical reaction rates and mechanisms. The prototypical molecule-surface system is CO adsorbed on MgO, but despite intense scrutiny from theory and experiment, there is still no consensus on its adsorption energy. In particular, the large cost of accurate many-body methods makes reaching converged theoretical estimates difficult, generating a wide range of values. In this work, we address this challenge, leveraging the latest advances in diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] to obtain accurate predictions for CO on MgO. These reliable theoretical estimates allow us to evaluate the inconsistencies in published temperature-programed desorption experiments, revealing that they arise from variations in employed pre-exponential factors. Utilizing this insight, we derive new experimental estimates of the (electronic) adsorption energy with a (more) precise pre-exponential factor. As a culmination of all of this effort, we are able to reach a consensus between multiple theoretical calculations and multiple experiments for the first time. In addition, we show that our recently developed cluster-based CCSD(T) approach provides a low-cost route toward achieving accurate adsorption energies. This sets the stage for affordable and reliable theoretical predictions of chemical reactions on surfaces to guide the realization of new catalysts and gas storage materials.

Accurate three-body noncovalent interactions: the insights from energy decomposition

An impressive collection of accurate two-body interaction energies for small complexes has been assembled into benchmark databases and used to improve the performance of multiple density functional, semiempirical, and machine learning methods. Similar benchmark data on nonadditive three-body energies in molecular trimers are comparatively scarce, and the existing ones are practically limited to homotrimers. In this work, we present a benchmark dataset of 20 equilibrium noncovalent interaction energies for a small but diverse selection of 10 heteromolecular trimers. The new 3BHET dataset presents complexes that combine different interactions including π-π, anion-π, cation-π, and various motifs of hydrogen and halogen bonding in each trimer. A detailed symmetry-adapted perturbation theory (SAPT)-based energy decomposition of the two- and three-body interaction energies shows that 3BHET consists of electrostatics- and dispersion-dominated complexes. The nonadditive three-body contribution is dominated by induction, but its influence on the overall bonding type in the complex (as exemplified by its position on the ternary diagram) is quite small. We also tested the extended SAPT (XSAPT) approach which is capable of including some nonadditive interactions in clusters of any size. The resulting three-body dispersion term (obtained from the many-body dispersion formalism) is mostly in good agreement with the supermolecular CCSD(T)-MP2 values and the nonadditive induction term is similar to the three-body SAPT(DFT) data, but the overall three-body XSAPT energies are not very accurate as they are missing the first-order exchange terms.

"Freedom of design" in chemical compound space: towards rational in silico design of molecules with targeted quantum-mechanical properties

The rational design of molecules with targeted quantum-mechanical (QM) properties requires an advanced understanding of the structure-property/property-property relationships (SPR/PPR) that exist across chemical compound space (CCS). In this work, we analyze these fundamental relationships in the sector of CCS spanned by small (primarily organic) molecules using the recently developed QM7-X dataset, a systematic, extensive, and tightly converged collection of 42 QM properties corresponding to ≈4.2M equilibrium and non-equilibrium molecular structures containing up to seven heavy/non-hydrogen atoms (including C, N, O, S, and Cl). By characterizing and enumerating progressively more complex manifolds of molecular property space-the corresponding high-dimensional space defined by the properties of each molecule in this sector of CCS-our analysis reveals that one has a substantial degree of flexibility or "freedom of design" when searching for a single molecule with a desired pair of properties or a set of distinct molecules sharing an array of properties. To explore how this intrinsic flexibility manifests in the molecular design process, we used multi-objective optimization to search for molecules with simultaneously large polarizabilities and HOMO-LUMO gaps; analysis of the resulting Pareto fronts identified non-trivial paths through CCS consisting of sequential structural and/or compositional changes that yield molecules with optimal combinations of these properties.

Regularized and Opposite Spin-Scaled Functionals from Møller-Plesset Adiabatic Connection─Higher Accuracy at Lower Cost

Noncovalent interactions (NCIs) play a crucial role in biology, chemistry, material science, and everything in between. To improve pure quantum-chemical simulations of NCIs, we propose a methodology for constructing approximate correlation energies by combining an interpolation along the Møller-Plesset adiabatic connection (MP AC) with a regularization and spin-scaling strategy applied to MP2 correlation energies. This combination yields cosκos-SPL2, which exhibits superior accuracy for NCIs compared to any of the individual strategies. With the N4 formal scaling, cosκos-SPL2 is competitive or often outperforms more expensive dispersion-corrected double hybrids for NCIs. The accuracy of cosκos-SPL2 particularly shines for anionic halogen bonded complexes, where it surpasses standard dispersion-corrected DFT by a factor of 3 to 5.

When catchers meet - a computational study on the dimerization of the Buckycatcher

We study the dimerization of the buckycatcher in gas phase and in toluene. We created an extensive library of 36 different complexes, which were characterized at semi-empirical and DFT levels. Semi-empirical geometries and dimerization energies compare well against reference data or Density Functional Theory calculations we performed. Born-Oppenheimer molecular dynamics was used to understand what happens when two molecules of the buckycatcher meet, allowing us to infer on the lack of kinetic barriers when dimers form. Thermodynamically, it is possible that room temperature solutions contain dimerized buckycatcher. Using a very simple exchange model, it is shown, however, that dimerization cannot compete thermodynamically against complexation with fullerenes, which accounts for experimental observations.

Quantifying the Impact of Halogenation on Intermolecular Interactions and Binding Modes of Aromatic Molecules

Halogenation of aromatic molecules is frequently used to modulate intermolecular interactions with ramifications for optoelectronic and mechanical properties. In this work, we accurately quantify and understand the nature of intermolecular interactions in perhalogenated benzene (PHB) clusters. Using benchmark binding energies from the fixed-node diffusion Monte Carlo (FN-DMC) method, we show that generalized Kohn-Sham semicanonical projected random phase approximation (GKS-spRPA) plus approximate exchange kernel (AKX) provides reliable interaction energies with mean absolute error (MAE) of 0.23 kcal/mol. Using the GKS-spRPA+AXK method, we quantify the interaction energies of several binding modes of PHB clusters ((C₆X₆)_n; X = F, Cl, Br, I; n = 2, 3). For a given binding mode, the interaction energies increase 3-4 times from X = F to X = I; the X-X binding modes have energies in the range of 2-4 kcal/mol, while the π-π binding mode has interaction energies in the range of 4-12 kcal/mol. SAPT-DFT-based energy decomposition analysis is then used to show that the equilibrium geometries are dictated primarily by the dispersion and exchange interactions. Finally, we test the accuracy of several dispersion-corrected density functional approximations and show that only the r2SCAN-D4 method has a low MAE and correct long-range behavior, which makes it suitable for large-scale simulations and for developing structure-function relationships of halogenated aromatic systems.

Accurate Prediction of Three-Body Intermolecular Interactions via Electron Deformation Density-Based Machine Learning

This work extends the electron deformation density-based descriptor, originally developed in the electron deformation density-based interaction energy machine learning (EDDIE-ML) algorithm to predict dimer interaction energies, to the prediction of three-body interactions in trimers. Using a sequential learning process to select the training data, the resulting Gaussian process regression (GPR) model predicts the three-body interaction energy within 0.2 kcal mol^-1 of the SRS-MP2/cc-pVTZ reference values for the 3B69 and S22-3 trimer data sets. A hybrid kernel function is introduced, which combines contributions from the average and individual atomic environments, allowing the total trimer interaction energy to be predicted in addition to the three-body contribution using the same descriptor. To extend the range and diversity of trimer interaction energies available in the literature, a new data set based on a protein-ligand crystal structure is introduced, consisting of 509 structures of a central ligand with two protein fragments. Benchmark calculations are provided for the new data set, which contains significantly larger molecular interactions than current databases in the literature in addition to charged fragments. Compared to density funtional theory (DFT)- and wavefunction-based methods for calculating the three-body interaction energy, our model makes predictions in a significantly shorter time frame by reducing the number of required SCF calculations from 7 to 4 performed at the PBE0 level of theory, showcasing the utility and efficiency of our Δ-ML method particularly when applied to larger systems.

Non-covalent interactions (NCIs) in π-conjugated functional materials: advances and perspectives

The design and development of functional materials with real-life applications are highly demanding. Understanding and controlling inter- and intra-molecular interactions provide opportunities to design new materials. A judicious manipulation of the molecular structure significantly alters such interactions and can boost selected properties and functions of the material. There is burgeoning evidence of the beneficial effects of non-covalent interactions (NCIs), showing that manipulating NCIs may generate functional materials with a wide variety of physical properties leading to applications in catalysis, drug delivery, crystal engineering, etc. This prompted us to review the implications of NCIs on the molecular packing, optical properties, and applications of functional π-conjugated materials. To this end, this tutorial review will cover different types of interactions (electrostatic, π-interactions, metallophilic, etc.) and their impact on π-conjugated materials. Attempts have also been made to delineate the effects of weak interactions on opto-electronic (O-E) applications.

A benchmark for non-covalent interactions in organometallic crystals

Organometallic complexes are the basis for homogeneous catalysis, have applications in materials science and are also active pharmaceutical ingredients. The interaction between transition metal complexes in the solid state is determining their thermodynamics and bio-availability. Non-covalent interactions such as hydrogen bonding and van der Waals are stabilizing crystals of transition metal complexes. The variation of ligand field, central metal atoms and their oxidation and spin states are determinants of the magnitude of their inter-molecular interactions. A comparison of a set of 43 manually curated experimental heats of sublimation (the new XTMC43 set) and results from periodic DFT calculations shows that an agreement to within 9% can be achieved using GGA or mGGA functionals with atom-centred Gaussian-type basis functions. The need for careful assessments of consistency, calibration and reproducibility of experimental and computational data is discussed. Results regarding the new XTMC43 benchmark set are suggested to serve as a starting point for further method development, systematic screening and crystal engineering.

A Cost Effective Scheme for the Highly Accurate Description of Intermolecular Binding in Large Complexes

There has been a growing interest in quantitative predictions of the intermolecular binding energy of large complexes. One of the most important quantum chemical techniques capable of such predictions is the domain-based local pair natural orbital (DLPNO) scheme for the coupled cluster theory with singles, doubles, and iterative triples [CCSD(T)], whose results are extrapolated to the complete basis set (CBS) limit. Here, the DLPNO-based focal-point method is devised with the aim of obtaining CBS-extrapolated values that are very close to their canonical CCSD(T)/CBS counterparts, and thus may serve for routinely checking a performance of less expensive computational methods, for example, those based on the density-functional theory (DFT). The efficacy of this method is demonstrated for several sets of noncovalent complexes with varying amounts of the electrostatics, induction, and dispersion contributions to binding (as revealed by accurate DFT-based symmetry-adapted perturbation theory (SAPT) calculations). It is shown that when applied to dimeric models of poly(3-hydroxybutyrate) chains in its two polymorphic forms, the DLPNO-CCSD(T) and DFT-SAPT computational schemes agree to within about 2 kJ/mol of an absolute value of the interaction energy. These computational schemes thus should be useful for a reliable description of factors leading to the enthalpic stabilization of extended systems.

Synthesis, Conformational Analysis and Evaluation of the 2-aryl-4-(4-bromo-2-hydroxyphenyl)benzo[1,5]thiazepines as Potential α-Glucosidase and/or α-Amylase Inhibitors

The ambident electrophilic character of the 5-bromo-2-hydroxychalcones and the binucleophilic nature of 2-aminothiophenol were exploited to construct the 2-aryl-4-(4-bromo-2-hydroxyphenyl)benzo[1,5]thiazepines. The structures and conformation of these 2-aryl-4-(4-bromo-2-hydroxyphenyl)benzo[1,5]thiazepines were established with the use of spectroscopic techniques complemented with a single crystal X-ray diffraction method. Both ¹H-NMR and IR spectroscopic techniques confirmed participation of the hydroxyl group in the intramolecular hydrogen-bonding interaction with a nitrogen atom. SC-XRD confirmed the presence of a six-membered intramolecularly hydrogen-bonded pseudo-aromatic ring, which was corroborated by the DFT method on 2b as a representative example in the gas phase. Compounds 2a (Ar = -C₆H₅), 2c (Ar = -C₆H₄(4-Cl)) and 2f (Ar = -C₆H₄(4-CH(CH₃)₂) exhibited increased inhibitory activity against α-glucosidase compared to acarbose (IC₅₀ = 7.56 ± 0.42 µM), with IC₅₀ values of 6.70 ± 0.15 µM, 2.69 ± 0.27 µM and 6.54 ± 0.11 µM, respectively. Compound 2f, which exhibited increased activity against α-glucosidase, also exhibited a significant inhibitory effect against α-amylase (IC₅₀ = 9.71 ± 0.50 µM). The results of some computational approaches on aspects such as noncovalent interactions, calculated binding energies for α-glucosidase and α-amylase, ADME (absorption, distribution, metabolism and excretion) and bioavailability properties, gastrointestinal absorption and blood-brain barrier permeability are also presented.

Structures of the (Imidazole)nH+ ... Ar (n=1,2,3) complexes determined from IR spectroscopy and quantum chemical calculations

Here, we present new cryogenic infrared spectra of the (Imidazole)$$_{n}\mathrm{H}^{+}$$ n H + (n=1,2,3) ions. The data was obtained using helium tagging infrared predissociation spectroscopy. The new results were compared with the data obtained by Gerardi et al. (Chem. Phys. Lett. 501:172–178, 2011) using the same technique but with argon as a tag. Comparison of the two experiments, assisted by theoretical calculations, allowed us to evaluate the preferable attachment positions of argon to the (Imidazole)$$_{n}\mathrm{H}^{+}$$ n H + frame. Argon attaches to nitrogen-bonded hydrogen in the case of the (Imidazole)H$$^+$$ + ion, while in (Imidazole)$$_{2}\mathrm{H}^{+}$$ 2 H + and (Imidazole)$$_{3}\mathrm{H}^{+}$$ 3 H + the preferred docking sites for the argon are in the center of the complex. This conclusion is supported by analyzing the spectral features attributed to the N–H stretching vibrations. Symmetry adapted perturbation theory (SAPT) analysis of the non-covalent forces between argon and the (Imidazole)$$_{n}\mathrm{H}^{+}$$ n H + (n=1,2,3) frame revealed that this switch of docking preference with increasing complex size is caused by an interplay between induction and dispersion interactions.

Theoretical Study of the Structure and Binding Energies of Dimers of Zn(II)-Porphyrin Derivatives

Zinc-complexed porphyrin and chlorophyll derivatives form functional aggregates with remarkable photophysical and optoelectronic properties. Understanding the type and strength of intermolecular interactions between these molecules is essential for designing new materials with desired morphology and functionality. The dimer interactions of a molecular set composed of porphyrin derivatives obtained by substitutional changes starting from free-base porphyrin is studied. It is found that the B97M-rV/def2-TZVP level of theory provides a good compromise between the accuracy and cost to get the dimer geometries and interaction energies (IEs). The neglect of the relaxation energy due to the change in the monomer configurations upon complex formation causes a more significant error than the basis set superposition error. The metal complexation increases the binding energy by about -6 to -8 kcal/mol, and the introduction of keto and hydroxy groups further stabilizes the dimers by about -20 kcal/mol. Although the saturation of one of the pyrrol double bonds does not change the IE, the addition of R groups increases it.

Quantum machine learning corrects classical forcefields: Stretching DNA base pairs in explicit solvent

In order to improve the accuracy of molecular dynamics simulations, classical forcefields are supplemented with a kernel-based machine learning method trained on quantum-mechanical fragment energies. As an example application, a potential-energy surface is generalized for a small DNA duplex, taking into account explicit solvation and long-range electron exchange-correlation effects. A long-standing problem in molecular science is that experimental studies of the structural and thermodynamic behavior of DNA under tension are not well confirmed by simulation; study of the potential energy vs extension taking into account a novel correction shows that leading classical DNA models have excessive stiffness with respect to stretching. This discrepancy is found to be common across multiple forcefields. The quantum correction is in qualitative agreement with the experimental thermodynamics for larger DNA double helices, providing a candidate explanation for the general and long-standing discrepancy between single molecule stretching experiments and classical calculations of DNA stretching. The new dataset of quantum calculations should facilitate multiple types of nucleic acid simulation, and the associated Kernel Modified Molecular Dynamics method (KMMD) is applicable to biomolecular simulations in general. KMMD is made available as part of the AMBER22 simulation software.

Recognition in the Domain of Molecular Chirality: From Noncovalent Interactions to Separation of Enantiomers

It is not a coincidence that both chirality and noncovalent interactions are ubiquitous in nature and synthetic molecular systems. Noncovalent interactivity between chiral molecules underlies enantioselective recognition as a fundamental phenomenon regulating life and human activities. Thus, noncovalent interactions represent the narrative thread of a fascinating story which goes across several disciplines of medical, chemical, physical, biological, and other natural sciences. This review has been conceived with the awareness that a modern attitude toward molecular chirality and its consequences needs to be founded on multidisciplinary approaches to disclose the molecular basis of essential enantioselective phenomena in the domain of chemical, physical, and life sciences. With the primary aim of discussing this topic in an integrated way, a comprehensive pool of rational and systematic multidisciplinary information is provided, which concerns the fundamentals of chirality, a description of noncovalent interactions, and their implications in enantioselective processes occurring in different contexts. A specific focus is devoted to enantioselection in chromatography and electromigration techniques because of their unique feature as "multistep" processes. A second motivation for writing this review is to make a clear statement about the state of the art, the tools we have at our disposal, and what is still missing to fully understand the mechanisms underlying enantioselective recognition.

Coupled Cluster Benchmarking of Large Noncovalent Complexes in L7 and S12L as Well as the C60 Dimer, DNA-Ellipticine, and HIV-Indinavir

In this work, we report the benchmark binding energies of the seven complexes within the L7 data set, six host-guest complexes from the S12L data set, a C₆₀ dimer, the DNA-ellipticine intercalation complex, and the largest system of the study, the HIV-indinavir system, which contained 343 atoms or 139 heavy atoms. The high-quality values reported were obtained via a focal point method that relies on the canonical form of second-order Møller-Plesset theory and the domain-based local pair natural orbital scheme for the coupled cluster with single double and perturbative triple excitations [DLPNO-CCSD(T)] extrapolated to the complete basis set (CBS) limit. The results in this work not only corroborate but also improve upon some previous benchmark values for large noncovalent complexes albeit at a relatively steep cost. Although local CCSD(T) and the largely successful fixed-node diffusion Monte Carlo (FN-DMC) have been shown to generally agree for small- to medium-size systems, a discrepancy in their reported binding energy values arises for large complexes, where the magnitude of the disagreement is a definite cause for concern. For example, the largest deviation in the L7 data set was 2.8 kcal/mol (∼10%) on the low end in C3GC. Such a deviation only grows worse in the S12L set, which showed a difference of up to 10.4 kcal/mol (∼25%) by a conservative estimation in buckycatcher-C₆₀. The DNA-ellipticine complex also generated a disagreement of 4.4 kcal/mol (∼10%) between both state-of-the-art methods. The disagreement between local CCSD(T) and FN-DMC in large noncovalent complexes shows that it is urgently needed to have the canonical CCSD(T), the Monte Carlo CCSD(T), or the full configuration interaction quantum Monte Carlo approaches available to large systems on the hundred-atom scale to solve this dilemma. In addition, the performances of cheaper popular computational methods were assessed for the studied complexes with respect to DLPNO-CCSD(T)/CBS. r²SCAN-3c, B97M-V, and PBE0+D4 work well in large noncovalent complexes in this work, and GFN2-xTB performs well in π-π stacking complexes. B97M-V is the most reliable computationally efficient approach to predicting noncovalent interactions for large complexes, being the only one to have binding errors within the so-called 1 kcal/mol "chemical accuracy". The benchmark interaction energies of these host-guest complexes, molecular materials, and biological systems with electronic and medicinal implications provide crucial reference data for the improvement of current and future lower-cost methods.

A computational inspection of the dissociation energy of mid-sized organic dimers

The gas-phase value of the dissociation energy ( D0) is a key parameter employed in both experimental and theoretical descriptions of noncovalent complexes. The D0 data were obtained for a set of mid-sized organic dimers in their global minima which was located using geometry optimizations that applied ample basis sets together with either the conventional second-order Møller–Plesset (MP2) method or several dispersion-corrected density-functional theory (DFT-D) schemes. The harmonic vibrational zero-point (VZP) and deformation energies from the MP2 calculations were combined with electronic energies from the coupled cluster theory with singles, doubles, and iterative triples [CCSD(T)] extrapolated to the complete basis set (CBS) limit to estimate D0 with the aim of inspecting values that were most recently measured, and an analogous comparison was performed using the DFT-D data. In at least one case (namely, for the aniline⋯methane cluster), the D0 estimate that employed the CCSD(T)/CBS energies differed from experiment in the way that could not be explained by a possible deficiency in the VZP contribution. Curiously, one of the DFT-D schemes (namely, the B3LYP-D3/def2-QZVPPD) was able to reproduce all measured D0 values to within 1.0 kJ/mol from experimental error bars. These findings show the need for further measurements and computations of some of the complexes. In order to facilitate such studies, the physical nature of intermolecular interactions in the investigated dimers was analyzed by means of the DFT-based symmetry-adapted perturbation theory.

External Electric Field Effect on the Strength of σ-Hole Interactions: A Theoretical Perspective in Like⋯Like Carbon-Containing Complexes

For the first time, σ-hole interactions within like⋯like carbon-containing complexes were investigated, in both the absence and presence of the external electric field (EEF). The effects of the directionality and strength of the utilized EEF were thoroughly unveiled in the (F-C-F₃)₂, (F-C-H₃)₂, and (H-C-F₃)₂ complexes. In the absence of the EEF, favorable interaction energies, with negative values, are denoted for the (F-C-F₃)₂ and (H-C-F₃)₂ complexes, whereas the (F-C-H₃)₂ complex exhibits unfavorable interactions. Remarkably, the strength of the applied EEF exhibits a prominent role in turning the repulsive forces within the latter complex into attractive ones. The symmetrical nature of the considered like⋯like carbon-containing complexes eradicated the effect of directionality of the EEF. The quantum theory of atoms in molecules (QTAIM), and the noncovalent interaction (NCI) index, ensured the occurrence of the attractive forces, and also outlined the substantial contributions of the three coplanar atoms to the total strength of the studied complexes. Symmetry-adapted perturbation theory (SAPT) results show the dispersion-driven nature of the interactions.

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

Inclusion of More Physics Leads to Less Data: Learning the Interaction Energy as a Function of Electron Deformation Density with Limited Training Data

Machine learning (ML) approaches to predicting quantum mechanical (QM) properties have made great strides toward achieving the computational chemist's holy grail of structure-based property prediction. In contrast to direct ML methods, which encode a molecule with only structural information, in this work, we show that QM descriptors improve ML predictions of dimer interaction energy, both in terms of accuracy and data efficiency, by incorporating electronic information into the descriptor. We present the electron deformation density interaction energy machine learning (EDDIE-ML) model, which predicts the interaction energy as a function of Hartree-Fock electron deformation density. We compare its performance with leading direct ML schemes and modern DFT methods for the prediction of interaction energies for dimers of varying charge type, size, and intermolecular separation. Under a low-data regime, EDDIE-ML outperforms other direct ML schemes and is the only model readily transferrable to larger, more complex systems including base pair trimers and porous cages. The underlying physical connection between the density and interaction energy enables EDDIE-ML to reach an accuracy comparable to modern DFT functionals in fewer training data points compared to other ML methods.

Behavior of counterpoise correction in many-body molecular clusters of organic compounds: Hartree-Fock interaction energy perspective

The counterpoise (CP) correction by Boys and Bernardi has been well accepted as a reliable strategy to account for basis set superposition error (BSSE) in intermolecular complexes. The behavior of the CP correction was thoroughly studied in individual molecules of molecular complexes. This work studies the performance of the CP correction in many‐body clusters including three‐body clusters of organic compounds in the 3B‐69 dataset. Additionally, we used crystal structures of polymorphs of benzene, aspirin, and oxalyl dihydrazide (ODH) to construct a many‐body cluster dataset, abbreviated as the MBC‐36 dataset, consisting of two, four and eight molecules, and 16 molecules in the case of benzene. A series of Dunning's basis sets—cc‐pXZ and aug‐cc‐pXZ (X = D and T)—were used to predict CP‐corrected Hartree–Fock (HF) interaction energies of the 3B‐69 and MBC‐36 datasets. The CP‐corrected interaction energies were found to be basis‐set independent, whereas the non‐CP corrected interaction energies were found not to a follow a smooth exponential fitting as previously found for electronic energies of individual molecules. This observation was attributed to the presence of non‐additive induction forces in some clusters. Two 2 × 2 × 2 supercells of benzene polymorphs were constructed to explore the local nature of BSSE effects. A cut‐off radius of 10 Å was demonstrated to be sufficient to fully recover these effects. Although the behavior of CP correction was found to be non‐conventional in many‐body clusters of organic compounds, the use of a small basis set such as cc‐pVDZ showed excellent performance in the prediction of HF interaction energies.

Assessment of DFT approaches in noble gas clathrate-like clusters: stability and thermodynamics

We have assessed the performance and accuracy of different wavefunction-based electronic structure methods, such as DFMP2 and domain-based local pair-natural orbital (DLPNO-CCSD(T)), as well as a variety of density functional theory (DFT) approaches on He@(H₂O)_N cage systems. We have selected representative clathrate-like structures corresponding to the building blocks present in each of the sI, sII and sH natural gas clathrate hydrates, and we have carefully studied the interaction between a He atom with each of their individual cages. We reported well-converged DFMP2 and DLPNO-CCSD(T) reference data, together with interaction and cohesive energies of four different density functionals (two GGA, revPBE and PW86PBE, and two hybrids, B3LYP and PBE0), including diverse dispersion correction schemes (D3(0), D3(BJ), D4 and XDM) for both He-filled and empty clathrate-like cages. After the analysis of the results, we came to the conclusion that the PW86PBE functional, with both XDM and D4 corrections, and the PBE0-D4 functional present reasonably adequate approaches to describe the guest-host noncovalent interactions that take place in such He clathrate hydrates. Taking into account that the He@sII is the only helium clathrate that scientists have been able to synthesize recently, we have performed a thermodynamic study on the individual 5¹² and 5¹²6⁴ cages present in the sII crystal. We determined the change in enthalpy, ΔH, and in Gibbs free energy, ΔG, at various temperatures and pressures, and we found out that in the range of experimental conditions the reactions associated with the encapsulation of the He atom inside the cages are exothermic and spontaneous. Finally, we highlighted the importance of an accurate description of the interaction in He@water mixtures, as a crucial component in construction of reliable data-driven models.

DFT-D4 Insight into the Inclusion of Amphetamine and Methamphetamine in Cucurbit[7]uril: Energetic, Structural and Biosensing Properties

The host-guest interactions of cucurbit[7]uril (CB[7]) as host and amphetamine (AMP), methamphetamine (MET) and their enantiomeric forms (S-form and R-form) as guests were computationally investigated using density functional theory calculations with the recent D4 atomic-charge dependent dispersion corrections. The analysis of energetic, structural and electronic properties with the aid of frontier molecular orbital analysis, charge decomposition analysis (CDA), extended charge decomposition analysis (ECDA) and independent gradient model (IGM) approach allowed to characterize the host-guest interactions in the studied systems. Energetic results indicate the formation of stable non-covalent complexes where R-AMP@CB[7] and S-AMP@CB[7] are more stable thermodynamically than R-MET@CB[7] and S-MET@CB[7] in gas phase while the reverse is true in water solvent. Based on structural analysis, a recognition mechanism is proposed, which suggests that the synergistic effect of van der Waals forces, ion-dipole interactions, intermolecular charge transfer interactions and intermolecular hydrogen bonding is responsible for the stabilization of the complexes. The geometries of the complexes obtained theoretically are in good agreement with the X-ray experimental structures and indicate that the phenyl ring of amphetamine and methamphetamine is deeply buried into the cavity of CB[7] through hydrophobic interactions while the ammonium group remains outside the cavity to establish hydrogen bonds with the portal oxygen atoms of CB[7].

Addressing the System-Size Dependence of the Local Approximation Error in Coupled-Cluster Calculations

Over the last two decades, the local approximation has been successfully used to extend the range of applicability of the "gold standard" singles and doubles coupled-cluster method with perturbative triples CCSD(T) to systems with hundreds of atoms. The local approximation error grows in absolute value with the increasing system size, i.e., by increasing the number of electron pairs in the system. In this study, we demonstrate that the recently introduced two-point extrapolation scheme for approaching the complete pair natural orbital (PNOs) space limit in domain-based pair natural orbital CCSD(T) calculations drastically reduces the dependence of the error on the system size, thus opening up unprecedented opportunities for the calculation of benchmark quality relative energies for large systems.

Coupled cluster benchmarks of large noncovalent complexes: The L7 dataset as well as DNA-ellipticine and buckycatcher-fullerene

In this work, benchmark binding energies for dispersion-bound complexes in the L7 dataset, the DNA-ellipticine intercalation complex, and the buckycatcher-C₆₀ complex with 120 heavy atoms using a focal-point method based on the canonical form of second-order Møller-Plesset theory (MP2) and the domain based local pair natural orbital scheme for the coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] extrapolated to the complete basis set (CBS) limit are reported. This work allows for increased confidence given the agreement with respect to values recently obtained using the local natural orbital CCSD(T) for L7 and the canonical CCSD(T)/CBS result for the coronene dimer (C2C2PD). Therefore, these results can be considered pushing the CCSD(T)/CBS binding benchmark to the hundred-atom scale. The disagreements between the two state-of-the-art methods, CCSD(T) and fixed-node diffusion Monte Carlo, are substantial with at least 2.0 (∼10%), 1.9 (∼5%), and 10.3 kcal/mol (∼25%) differences for C2C2PD in L7, DNA-ellipticine, and buckycatcher-C₆₀, respectively. Such sizable discrepancy above "chemical accuracy" for large noncovalent complexes indicates how challenging it is to obtain benchmark binding interactions for systems beyond small molecules, although the three up-to-date density functionals, PBE0+D4, ωB97M-V, and B97M-V, agree better with CCSD(T) for these large systems. In addition to reporting these values, different basis sets and various CBS extrapolation parameters for Hartree-Fock and MP2 correlation energies were tested for the first time in large noncovalent complexes with the goal of providing some indications toward optimal cost effective routes to approach the CBS limit without substantial loss in quality.

On the Potentiality of X-T-X3 Compounds (T = C, Si, and Ge, and X = F, Cl, and Br) as Tetrel- and Halogen-Bond Donors

The versatility of the X-T-X3 compounds (where T = C, Si, and Ge, and X = F, Cl, and Br) to participate in tetrel- and halogen-bonding interactions was settled out, at the MP2/aug-cc-pVTZ level of theory, within a series of configurations for (X-T-X3)2 homodimers. The electrostatic potential computations ensured the remarkable ability of the investigated X-T-X3 monomers to participate in σ-hole halogen and tetrel interactions. The energetic findings significantly unveil the favorability of the tetrel···tetrel directional configuration with considerable negative binding energies over tetrel···halogen, type III halogen···halogen, and type II halogen···halogen analogs. Quantum theory of atoms in molecules and noncovalent interaction analyses were accomplished to disclose the nature of the tetrel- and halogen-bonding interactions within designed configurations, giving good correlations between the total electron densities and binding energies. Further insight into the binding energy physical meanings was invoked through using symmetry-adapted perturbation theory-based energy decomposition analysis, featuring the dispersion term as the most prominent force beyond the examined interactions. The theoretical results were supported by versatile crystal structures which were characterized by the same type of interactions. Presumably, the obtained findings would be considered as a solid underpinning for future supramolecular chemistry, materials science, and crystal engineering studies, as well as a fundamental linchpin for a better understanding of the biological activities of chemicals.

Computational Tools to Rationalize and Predict the Self-Assembly Behavior of Supramolecular Gels

Supramolecular gels form a class of soft materials that has been heavily explored by the chemical community in the past 20 years. While a multitude of experimental techniques has demonstrated its usefulness when characterizing these materials, the potential value of computational techniques has received much less attention. This review aims to provide a complete overview of studies that employ computational tools to obtain a better fundamental understanding of the self-assembly behavior of supramolecular gels or to accelerate their development by means of prediction. As such, we hope to stimulate researchers to consider using computational tools when investigating these intriguing materials. In the concluding remarks, we address future challenges faced by the field and formulate our vision on how computational methods could help overcoming them.

Advancement in functionalized luminescent frameworks and their prospective applications as inkjet-printed sensors and anti-counterfeit materials

Supramolecular luminescent frameworks with conjugated architectures exhibits interesting photophysical properties with phenomenal chemical and thermal stability. This has instigated global researchers towards its extensive application in toxic analyte detection and the formulation of anti-counterfeit materials. In correlation with this present scenario, luminescent metal-organic frameworks (LMOFs), possessing tailorable structural and functional properties and exceptional physicochemical features, have been categorized as emerging 'smart materials'. Interestingly, LMOFs have assisted in the rapid development of an effectual sensing platform and swift fabrication of anti-counterfeit materials on desirable substrates with the aid of 'Inkjet Printing', which is a viable, low-cost, and high-resolution technology. Inkjet printing is an excellent material deposition technique in the modern era owing to its easy settling over flexible substrates, simplistic emergence of large area image patterns with improved throughput, minimal cost, explicit resolution, and least waste generation. The present review provides state-of-the-art progress on LMOFs based (i) luminescent security ink fabrication with static and dynamic multinodal luminescent materials and (ii) sensory device formulation for the easy and instantaneous recognition of hazardous analytes through the 'Inkjet Printing' technology. This techno-chemical integration will be certainly beneficial to prevent the growth of counterfeit materials and monitor the bioaccumulation of hazardous analytes in our ecological system.

Interactions between large molecules pose a puzzle for reference quantum mechanical methods

Quantum-mechanical methods are used for understanding molecular interactions throughout the natural sciences. Quantum diffusion Monte Carlo (DMC) and coupled cluster with single, double, and perturbative triple excitations [CCSD(T)] are state-of-the-art trusted wavefunction methods that have been shown to yield accurate interaction energies for small organic molecules. These methods provide valuable reference information for widely-used semi-empirical and machine learning potentials, especially where experimental information is scarce. However, agreement for systems beyond small molecules is a crucial remaining milestone for cementing the benchmark accuracy of these methods. We show that CCSD(T) and DMC interaction energies are not consistent for a set of polarizable supramolecules. Whilst there is agreement for some of the complexes, in a few key systems disagreements of up to 8 kcal mol^-1 remain. These findings thus indicate that more caution is required when aiming at reproducible non-covalent interactions between extended molecules.

Noncovalent Interactions from Models for the Møller-Plesset Adiabatic Connection

Given the omnipresence of noncovalent interactions (NCIs), their accurate simulations are of crucial importance across various scientific disciplines. Here we construct accurate models for the description of NCIs by an interpolation along the Møller-Plesset adiabatic connection (MP AC). Our interpolation approximates the correlation energy, by recovering MP2 at small coupling strengths and the correct large-coupling strength expansion of the MP AC, recently shown to be a functional of the Hartree-Fock density. Our models are size consistent for fragments with nondegenerate ground states, have the same cost as double hybrids, and require no dispersion corrections to capture NCIs accurately. These interpolations greatly reduce large MP2 errors for typical π-stacking complexes (e.g., benzene-pyridine dimers) and for the L7 data set. They are also competitive with state-of-the-art dispersion enhanced functionals and can even significantly outperform them for a variety of data sets, such as CT7 and L7.

Unveiling Bifunctional Hydrogen Bonding with the Help of Quantum Chemistry: The Imidazole-Water Adduct as Test Case

The ubiquitous role of water and its amphiprotic nature call for a deeper insight into the physical-chemical properties of hydrogen-bonded complexes formed with building blocks of biomolecules. In this work, the semiexperimental (SE) approach combined with the template model (TM) protocol allowed the accurate determination of the equilibrium structure of two isomeric forms of the imidazole-water complex. In this procedure, the integration of experiment (thanks to a recent rotational spectroscopy investigation) and theory is exploited, also providing the means of assessing the reliability and accuracy of different quantum-chemical approaches. Overall, this study demonstrated the robustness of the combined SE-TM approach, which can provide accurate results using affordable quantum-chemical methods. Finally, the structural and energetic characteristics of these complexes have been examined in detail and compared with those of analogous heterocycle-water adducts, also exploiting energy decomposition analyses.

Synthesis, Structure and Evaluation of the N-(2-Acetyl-4-(styryl)phenyl)-4-benzenesulfonamide Derivatives for Anticholinesterase and Antioxidant Activities

N-(2-Acetyl-4-bromophenyl)-4-methylbenzenesulfonamide (2) was transformed into 5-(4-methoxymethylstyryl)-2-(p-tolylsulfonamido)acetophenone (3a) and 5-(4- trifluoromethylstyryl)-2-(p-tolylsulfonamido)acetophenone (3b). Their structures were determined using a combination of NMR (1H & 13C) and mass spectroscopic as well as single crystal X-ray diffraction techniques. These compounds and the corresponding precursor, 2-amino-5-bromoacetophenone (1), were evaluated through enzymatic assays in vitro for inhibitory effect against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activities as well as antioxidant effect through the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) free radical scavenging assays. Molecular docking was performed on 3a to determine plausible protein–ligand interactions on a molecular level. Their drug likeness properties (absorption, distribution, metabolism, and excretion) and ability to cross the blood–brain barrier (BBB) have also been predicted at theoretical level.

A non-empirical intermolecular force-field for trinitrobenzene and its application in crystal structure prediction

An anisotropic atom-atom distributed intermolecular force-field (DIFF) for rigid trinitrobenzene (TNB) is developed using distributed multipole moments, dipolar polarizabilities, and dispersion coefficients derived from the charge density of the isolated molecule. The short-range parameters of the force-field are fitted to first- and second-order symmetry-adapted perturbation theory dimer interaction energy calculations using the distributed density-overlap model to guide the parameterization of the short-range anisotropy. The second-order calculations are used for fitting the damping coefficients of the long-range dispersion and polarization and also for relaxing the isotropic short-range coefficients in the final model, DIFF-srL2(rel). We assess the accuracy of the unrelaxed model, DIFF-srL2(norel), and its equivalent without short-range anisotropy, DIFF-srL0(norel), as these models are easier to derive. The model potentials are contrasted with empirical models for the repulsion-dispersion fitted to organic crystal structures with multipoles of iterated stockholder atoms (ISAs), FIT(ISA,L4), and with Gaussian Distributed Analysis (GDMA) multipoles, FIT(GDMA,L4), commonly used in modeling organic crystals. The potentials are tested for their ability to model the solid state of TNB. The non-empirical models provide more reasonable relative lattice energies of the three polymorphs of TNB and propose more sensible hypothetical structures than the empirical force-field (FIT). The DIFF-srL2(rel) model successfully has the most stable structure as one of the many structures that match the coordination sphere of form III. The neglect of the conformational flexibility of the nitro-groups is a significant approximation. This methodology provides a step toward force-fields capable of representing all phases of a molecule in molecular dynamics simulations.

Accurate Reduced-Cost CCSD(T) Energies: Parallel Implementation, Benchmarks, and Large-Scale Applications

The accurate and systematically improvable frozen natural orbital (FNO) and natural auxiliary function (NAF) cost-reducing approaches are combined with our recent coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] implementations. Both of the closed- and open-shell FNO-CCSD(T) codes benefit from OpenMP parallelism, completely or partially integral-direct density-fitting algorithms, checkpointing, and hand-optimized, memory- and operation count effective implementations exploiting all permutational symmetries. The closed-shell CCSD(T) code requires negligible disk I/O and network bandwidth, is MPI/OpenMP parallel, and exhibits outstanding peak performance utilization of 50-70% up to hundreds of cores. Conservative FNO and NAF truncation thresholds benchmarked for challenging reaction, atomization, and ionization energies of both closed- and open-shell species are shown to maintain 1 kJ/mol accuracy against canonical CCSD(T) for systems of 31-43 atoms even with large basis sets. The cost reduction of up to an order of magnitude achieved extends the reach of FNO-CCSD(T) to systems of 50-75 atoms (up to 2124 atomic orbitals) with triple- and quadruple-ζ basis sets, which is unprecedented without local approximations. Consequently, a considerably larger portion of the chemical compound space can now be covered by the practically "gold standard" quality FNO-CCSD(T) method using affordable resources and about a week of wall time. Large-scale applications are presented for organocatalytic and transition-metal reactions as well as noncovalent interactions. Possible applications for benchmarking local CCSD(T) methods, as well as for the accuracy assessment or parametrization of less complete models, for example, density functional approximations or machine learning potentials, are also outlined.

Conformational stability and structural analysis of methanethiol clusters: a revisit

B3LYP/cc-pV(D/T/Q)Z and CCSD/cc-pVDZ levels of theory predict three minima for both dimers and trimers of methanethiol. Predictions at B3LYP/cc-pVDZ corroborates exceedingly well with the earlier reported experimental value but significantly differ from the previous computational predictions. Interaction energy between the molecules decreases with an increase in the size of the basis set for both the dimer and trimer. The dipole moment of methanethiol dimer gets reduced at the B3LYP/cc-pVDZ level of theory relative to all minima configurations, and the same is seen for trimer also. These new predictions are well supported by atoms in molecules (AIM), frontier molecular orbital (FMO), Mulliken charge (MC), and natural bond orbital (NBO) analysis.

B3LYP/cc-pV(D/T/Q)Z and CCSD/cc-pVDZ levels of theory predict three minima for both dimers and trimers of methanethiol.

He Inclusion in Ice-like and Clathrate-like Frameworks: A Benchmark Quantum Chemistry Study of Guest-Host Interactions

Energetics and structural properties of selected type and size He@hydrate frameworks, e.g., from regular structured ice channels to clathrate-like cages, are presented from first-principles quantum chemistry methods. The scarcity of information on He@hydrates makes such complexes challenging targets, while their computational study entails an interesting and arduous task. Some of them have been synthesized in the laboratory, which motivates further investigations on their stability. Hence, the main focus is to examine the performance and accuracy of different wave function-based electronic structure methods, such as MP2, CCSD(T), their explicitly correlated (F12) and domain-based local pair-natural orbital (DLPNO) analogs, as well as modern and conventional density functional theory (DFT) approaches, and analytical model potentials available. Different structures are considered, starting from the "simplest system" formed by a noble gas atom (such as He) and one water molecule, followed by the study of the "fundamental units" present in all ice-like and clathrate-like frameworks (such as pentamers and hexamers) and finally the description of interactions in the "building blocks" of three-dimensional (3D) ice channels (e.g., horizontal and perpendicular ice II and I_h) and clathrate-like cages, such as the 5¹² present in the most common sI, sII, and sH clathrate-hydrate structures. The idea is to provide well-converged DLPNO-CCSD(T) and DFMP2/CBS reference datasets that in turn are used to validate how DFT functionals (in total, 29 approaches from generalized-gradient approximation (GGA), meta-GGA, to hybrid and range-separated functionals, including dispersion correction treatments, were checked) and analytical semiempirical/ab initio-based potentials perform compared with high-level alternatives. Within all tested approaches, those best-performing were identified and classified. Most of the DFT/DFT-D functionals, as well as available analytical pairwise model potentials, face difficulties in describing both hydrogen-bonded water frameworks and dispersion bound He-water interactions. Including dispersion corrections yields an overall well-balanced performance for LCωPBE-D3BJ and PBE0-D4 functionals. Such benchmark datasets can benefit research into the development of new cheminformatics models, as can serve to guide and cross-check methodologies, lending increased predicted power to future molecular simulations for investigating the role of structures and phase transitions from nanoscale clusters to macroscopic crystalline structures.