Assessment of standard force field models against high-quality ab initio potential curves for prototypes of pi-pi, CH/pi, and SH/pi interactions

Quantum Mechanics Characterization of Non-Covalent Interaction in Nucleotide Fragments

Accurate calculation of non-covalent interaction energies in nucleotides is crucial for understanding the driving forces governing nucleic acid structure and function, as well as developing advanced molecular mechanics forcefields or machine learning potentials tailored to nucleic acids. Here, we dissect the nucleotides' structure into three main constituents: nucleobases (A, G, C, T, and U), sugar moieties (ribose and deoxyribose), and phosphate group. The interactions among these fragments and between fragments and water were analyzed. Different quantum mechanical methods were compared for their accuracy in capturing the interaction energy. The non-covalent interaction energy was decomposed into electrostatics, exchange-repulsion, dispersion, and induction using two ab initio methods: Symmetry-Adapted Perturbation Theory (SAPT) and Absolutely Localized Molecular Orbitals (ALMO). These calculations provide a benchmark for different QM methods, in addition to providing a valuable understanding of the roles of various intermolecular forces in hydrogen bonding and aromatic stacking. With SAPT, a higher theory level and/or larger basis set did not necessarily give more accuracy. It is hard to know which combination would be best for a given system. In contrast, ALMO EDA2 did not show dependence on theory level or basis set; additionally, it is faster.

Linear and ring polypeptides complexed with oppositely charged surfactants: the cohesion of the complexes as revealed in atomistic simulations

The use of linear supercharged unfolded polypeptides (SUPs) and oppositely charged surfactants in aqueous solution has demonstrated impressive adhesive properties. These substances possess biocompatibility, biodegradability and other necessary properties for practical application as a biomedical glue in wound repair. The success of these substances, coupled with limited knowledge about such systems, provides hope for enhancing the performance of the final product. One potential approach involves altering the topology of the polypeptide chain. In this article, we conduct a comparative analysis to examine the behavior of the ring and linear chains of a polypeptide in aqueous solution. This analysis utilizes full-atomic computer modeling to monitor the properties of the chains. We investigate the temperature dependence of the shape and size of individual polypeptides in the solution, as well as the formation of complexes via mixing the polypeptide chains with oppositely charged sodium dodecylbenzene sulfonate (SDBS) surfactant molecules in a stoichiometric ratio. Additionally, we explore the cohesive properties of the resulting complex through power experiments involving the extraction of single polypeptide chains out of the SUP-SDBS complexes.

Understanding the Structure-Activity Relationship through Density Functional Theory: A Simple Method Predicts Relative Binding Free Energies of Metalloenzyme Fragment-like Inhibitors

Despite being involved in several human diseases, metalloenzymes are targeted by a small percentage of FDA-approved drugs. Development of novel and efficient inhibitors is required, as the chemical space of metal binding groups (MBGs) is currently limited to four main classes. The use of computational chemistry methods in drug discovery has gained momentum thanks to accurate estimates of binding modes and binding free energies of ligands to receptors. However, exact predictions of binding free energies in metalloenzymes are challenging due to the occurrence of nonclassical phenomena and interactions that common force field-based methods are unable to correctly describe. In this regard, we applied density functional theory (DFT) to predict the binding free energies and to understand the structure-activity relationship of metalloenzyme fragment-like inhibitors. We tested this method on a set of small-molecule inhibitors with different electronic properties and coordinating two Mn²⁺ ions in the binding site of the influenza RNA polymerase PA_N endonuclease. We modeled the binding site using only atoms from the first coordination shell, hence reducing the computational cost. Thanks to the explicit treatment of electrons by DFT, we highlighted the main contributions to the binding free energies and the electronic features differentiating strong and weak inhibitors, achieving good qualitative correlation with the experimentally determined affinities. By introducing automated docking, we explored alternative ways to coordinate the metal centers and we identified 70% of the highest affinity inhibitors. This methodology provides a fast and predictive tool for the identification of key features of metalloenzyme MBGs, which can be useful for the design of new and efficient drugs targeting these ubiquitous proteins.

Development and Implementation of Atomically Anisotropic First-Principles Force Fields: A Benzene Case Study

π-interactions are an important motif in chemical and biochemical systems. However, due to their anisotropic electron densities and complex balance of intermolecular interactions, aromatic molecules represent an ongoing challenge for accurate and transferable force field development. Historically, ab initio force fields for aromatics have not exhibited good accuracy with respect to bulk properties or have only been used to study gas-phase dimers. Using benzene as a proof of concept, herein we show how our own ab initio MASTIFF force field incorporates an atomically anisotropic description of intermolecular interactions to yield an accurate and robust model for aromatic interactions irrespective of phase. Compared to existing models, the MASTIFF benzene force field not only is accurate for liquid phase properties but also offers transferability to the gas and solid phases. Additionally, we introduce a computationally efficient OpenMM plugin which enables customizable anisotropic intermolecular functional forms and which can be generically used in any MD simulation where a model for nonspherical atomic features is required. Overall, our results demonstrate the importance of atomic-level anisotropy in enabling next-generation ab initio force field development.

Comparison of approximate intermolecular potentials for ab initio fragment calculations on medium sized N-heterocycles

The ground state intermolecular potential of bimolecular complexes of N-heterocycles is analyzed for the impact of individual terms in the interaction energy as provided by various, conceptually different theories. Novel combinations with several formulations of the electrostatic, Pauli repulsion, and dispersion contributions are tested at both short- and long-distance sides of the potential energy surface, for various alignments of the pyrrole dimer as well as the cytosine-uracil complex. The integration of a DFT/CCSD density embedding scheme, with dispersion terms from the effective fragment potential (EFP) method is found to provide good agreement with a reference CCSD(T) potential overall; simultaneously, a quantum mechanics/molecular mechanics approach using CHELPG atomic point charges for the electrostatic interaction, augmented by EFP dispersion and Pauli repulsion, comes also close to the reference result. Both schemes have the advantage of not relying on predefined force fields; rather, the interaction parameters can be determined for the system under study, thus being excellent candidates for ab initio modeling.

Deep Neural Network Model to Predict the Electrostatic Parameters in the Polarizable Classical Drude Oscillator Force Field

The Drude polarizable force field (FF) captures electronic polarization effects via auxiliary Drude particles that are attached to non-hydrogen atoms, distinguishing it from commonly used additive FFs that rely on fixed charges. The Drude FF currently includes parameters for biomolecules such as proteins, nucleic acids, lipids, and carbohydrates and small-molecule representative of those classes of molecules as well as a range of atomic ions. Extension of the Drude FF to novel small druglike molecules is challenging as it requires the assignment of partial charges, atomic polarizabilities, and Thole scaling factors. In the present article, deep neural network (DNN) models are trained on quantum mechanical (QM)-based partial charges and atomic polarizabilities along with Thole scale factors trained to target QM molecular dipole moments and polarizabilities. Training of the DNN model used a collection of 39 421 molecules with molecular weights up to 200 Da and containing H, C, N, O, P, S, F, Cl, Br, or I atoms. The DNN model utilizes bond connectivity, including 1,2, 1,3, 1,4, and 1,5 terms and distances of Drude FF atom types as the feature vector to build the model, allowing it to capture both local and nonlocal effects in the molecules. Novel methods have been developed to determine restrained electrostatic potential (RESP) charges on atoms and external points representing lone pairs and to determine Thole scale factors, which have no QM analogue. A penalty scheme is devised as a performance predictor of the trained model. Validation studies show that these DNN models can precisely predict molecular dipole and polarizabilities of Food and Drug Administration (FDA)-approved drugs compared to reference MP2 calculations. The availability of the DNN model allowing for the rapid estimation of the Drude electrostatic parameters will facilitate its applicability to a wider range of molecular species.

CLIFF: A component-based, machine-learned, intermolecular force field

Computation of intermolecular interactions is a challenge in drug discovery because accurate ab initio techniques are too computationally expensive to be routinely applied to drug-protein models. Classical force fields are more computationally feasible, and force fields designed to match symmetry adapted perturbation theory (SAPT) interaction energies can remain accurate in this context. Unfortunately, the application of such force fields is complicated by the laborious parameterization required for computations on new molecules. Here, we introduce the component-based machine-learned intermolecular force field (CLIFF), which combines accurate, physics-based equations for intermolecular interaction energies with machine-learning models to enable automatic parameterization. The CLIFF uses functional forms corresponding to electrostatic, exchange-repulsion, induction/polarization, and London dispersion components in SAPT. Molecule-independent parameters are fit with respect to SAPT2+(3)δMP2/aug-cc-pVTZ, and molecule-dependent atomic parameters (atomic widths, atomic multipoles, and Hirshfeld ratios) are obtained from machine learning models developed for C, N, O, H, S, F, Cl, and Br. The CLIFF achieves mean absolute errors (MAEs) no worse than 0.70 kcal mol^-1 in both total and component energies across a diverse dimer test set. For the side chain-side chain interaction database derived from protein fragments, the CLIFF produces total interaction energies with an MAE of 0.27 kcal mol^-1 with respect to reference data, outperforming similar and even more expensive methods. In applications to a set of model drug-protein interactions, the CLIFF is able to accurately rank-order ligand binding strengths and achieves less than 10% error with respect to SAPT reference values for most complexes.

Conformational Shifts of Stacked Heteroaromatics: Vacuum vs. Water Studied by Machine Learning

Stacking interactions play a crucial role in drug design, as we can find aromatic cores or scaffolds in almost any available small molecule drug. To predict optimal binding geometries and enhance stacking interactions, usually high-level quantum mechanical calculations are performed. These calculations have two major drawbacks: they are very time consuming, and solvation can only be considered using implicit solvation. Therefore, most calculations are performed in vacuum. However, recent studies have revealed a direct correlation between the desolvation penalty, vacuum stacking interactions and binding affinity, making predictions even more difficult. To overcome the drawbacks of quantum mechanical calculations, in this study we use neural networks to perform fast geometry optimizations and molecular dynamics simulations of heteroaromatics stacked with toluene in vacuum and in explicit solvation. We show that the resulting energies in vacuum are in good agreement with high-level quantum mechanical calculations. Furthermore, we show that using explicit solvation substantially influences the favored orientations of heteroaromatic rings thereby emphasizing the necessity to include solvation properties starting from the earliest phases of drug design.

An Iterative Fragment Scheme for the ACKS2 Electronic Polarization Model: Application to Molecular Dimers and Chains

The treatment of electrostatic interactions is a key ingredient in the force field-based simulation of condensed phase systems. Most approaches used fixed, site-specific point charges. Yet, it is now clear that many applications of force fields (FFs) demand more sophisticated treatments, prompting the implementation of charge equilibration methods in polarizable FFs to allow the redistribution of charge within the system. One approach allowing both, charge redistribution and site-specific polarization, while at the same time solving methodological shortcomings of earlier methods, is the first-principles-derived atom-condensed Kohn-Sham density functional theory method approximated to the second order (ACKS2). In this work, we present two fragment approaches to ACKS2, termed f-ACKS2 and a self-consistent version, scf-ACKS2, that treat condensed phase systems as a collection of electronically polarizable molecular fragments. The fragmentation approach to ACKS2 not only leads to a more transferable and less system-specific collection of electronic response parameters but also opens up the method to large condensed phase systems. We validate the accuracies of f-ACKS2 and scf-ACKS2 by comparing polarization energies and induced dipole moments for a number of charged hydrocarbon dimers against DFT reference calculations. Finally, we also apply both fragmented ACKS2 variants to calculate the polarization energy for electron-hole pair separation along a chain of anthracene molecules and find excellent agreement with reference DFT calculations.

Transition State Force Field for the Asymmetric Redox-Relay Heck Reaction

A transition state force field (TSFF) was developed using the quantum-guided molecular mechanics (Q2MM) method to describe the stereodetermining migratory insertion step of the enantioselective redox-relay Heck reaction for a range of multisubstituted alkenes. We show that the TSFF is highly predictive through an external validation of the TSFF against 151 experimentally determined stereoselectivities resulting in an R² of 0.89 and MUE of 1.8 kJ/mol. In addition, limitations in the underlying force field were identified by comparison of the TSFF results to DFT level calculations. A novel application of the TSFF was demonstrated for 31 cases where the enantiomer predicted by the TSFF differed from the originally published values. Experimental determination of the absolute configuration demonstrated that the computational predictions were accurate, suggesting that TSFFs can be used for the rapid prediction of the absolute stereochemistry for a class of reactions. Finally, a virtual ligand screen was conducted utilizing both the TSFF and a simple molecular correlation method. Both methods were similarly predictive, but the TSFF was able to show greater utility through transferability, speed, and interpretability.

Substituent effect on inter-ring interaction in paracyclophanes

The theoretical calculations, namely multipole-derived charge analysis, quantum theory of atom in molecules, and non-bonding interaction (NCI), were performed for [2.2]paracyclophanes, [2.2]paracyclophane-7,9-dienes, and [3.3]paracyclophanes optimized at B3LYP/6-311++G** level, including dispersion correction. The substituent effect of the electron donor N(Me)2 and electron acceptor NO2 group and the influence of the length of bridges joining the aromatic ring on aromatic ring interaction energy (AIE) and strain energy were discussed. The local and electrostatic character of the substituent effect in paracyclophanes was shown. The presence of the weak orbital through-space C···C interaction between the [3.3]paracyclophane ring and weak CH···O hydrogen bonds between the substituents in the different rings was shown.

Toward Predictive Molecular Dynamics Simulations of Asphaltenes in Toluene and Heptane

The conventional definition of asphaltenes is based on their solubility in toluene and their insolubility in heptane. We have utilized this definition to study the influence of partial charge parametrization on the aggregation behavior of asphaltenes using classical atomistic molecular dynamics simulations performed on the microsecond time scale. Under consideration here are toluene- and heptane-based systems with different partial charges parametrized using the general AMBER force field (GAFF). Systems with standard GAFF partial charges calculated by the AM1-BCC and HF/6-31G*(RESP) methods were simulated alongside systems without partial charges. The partial charges implemented differ in terms of the resulting electrical negativity of the asphaltene polyaromatic core, with the AM1-BCC method giving the greatest magnitude of the total core charge. Based on our analysis of the molecular relaxation and orientation, and on the aggregation behavior of asphaltenes in toluene and heptane, we proposed to use the partial charges obtained by the AM1-BCC method for the study of asphaltene aggregates. A good agreement with available experimental data was observed on the sizes of the aggregates, their fractal dimensions, and the solvent entrainment for the model asphaltenes in toluene and heptane. From the results obtained, we conclude that for a better predictive ability, simulation parameters must be carefully chosen, with particular attention paid to the partial charges owing to their influence on the electrical negativity of the asphaltene core and on the asphaltenes aggregation.

On the importance of accounting for nuclear quantum effects in ab initio calibrated force fields in biological simulations

In many important processes in chemistry, physics, and biology the nuclear degrees of freedom cannot be described using the laws of classical mechanics. At the same time, the vast majority of molecular simulations that employ wide-coverage force fields treat atomic motion classically. In light of the increasing desire for and accelerated development of quantum mechanics (QM)-parameterized interaction models, we reexamine whether the classical treatment is sufficient for a simple but crucial chemical species: alkanes. We show that when using an interaction model or force field in excellent agreement with the "gold standard" QM data, even very basic simulated properties of liquid alkanes, such as densities and heats of vaporization, deviate significantly from experimental values. Inclusion of nuclear quantum effects via techniques that treat nuclear degrees of freedom using the laws of classical mechanics brings the simulated properties much closer to reality.

Impact of Molecular Structure on Properties of n-Hexadecane and Alkylbenzene Binary Mixtures

Because of the complexity of petroleum-based fuels, researchers typically use simplified mixtures, known as surrogates, to study combustion behavior and to attempt to identify how physical properties are related to combustion. The process of determining the surrogate composition to yield a desired set of thermophysical properties can be a complicated and time-consuming task. As a result, the use of computer simulations to narrow the number of possible surrogate compositions is beginning to be explored. Herein, molecular dynamics (MD) simulations are used to model binary mixtures of n-hexadecane with either benzene, toluene, n-ethylbenzene, n-propylbenzene, or n-butylbenzene. Calculated densities are in quantitative agreement with experimental values. With the exception of the mixtures containing benzene, simulated excess molar volumes are also in very good agreement with measured values. Isentropic bulk moduli are in qualitative agreement with experiment, and reproduce interesting trends observed in the experimental data. Specifically, minima in the bulk moduli at intermediate compositions of several of the alkylbenzenes are correctly reproduced. In addition, the structures of the fluids are also examined. For mixtures of n-hexadecane with alkylbenzenes with longer chains, the orientation of the aromatic rings is not substantially impacted by composition. In contrast, increasing n-hexadecane content increases the ratio of parallel to perpendicular arrangements of benzene and toluene molecules. In those mixtures, this change in orientation of the aromatic rings could be responsible for the minima observed in the bulk moduli data. These results show that MD simulations can assist in development of fuel surrogates, both by predicting thermophysical properties and by providing insight into how molecular structure and composition affect those properties.

Steric "attraction": not by dispersion alone

Non-covalent interactions between neutral, sterically hindered organic molecules generally involve a strong stabilizing contribution from dispersion forces that in many systems turns the 'steric repulsion' into a 'steric attraction'. In addition to London dispersion, such systems benefit from electrostatic stabilization, which arises from a short-range effect of charge penetration and gets bigger with increasing steric bulk. In the present work, we quantify this contribution for a diverse set of molecular cores, ranging from unsubstituted benzene and cyclohexane to their derivatives carrying tert-butyl, phenyl, cyclohexyl and adamantyl substituents. While the importance of electrostatic interactions in the dimers of sp2-rich (e.g., π-conjugated) cores is well appreciated, less polarizable assemblies of sp3-rich systems with multiple short-range CH···HC contacts between the bulky cyclohexyl and adamantyl moieties are also significantly influenced by electrostatics. Charge penetration is drastically larger in absolute terms for the sp2-rich cores, but still has a non-negligible effect on the sp3-rich dimers, investigated herein, both in terms of their energetics and equilibrium interaction distances. These results emphasize the importance of this electrostatic effect, which has so far been less recognized in aliphatic systems compared to London dispersion, and are therefore likely to have implications for the development of force fields and methods for crystal structure prediction.

Modeling Protein S-Aromatic Motifs Reveals Their Structural and Redox Flexibility

S-aromatic motifs are important noncovalent forces for protein stability and function but remain poorly understood. Hence, we performed quantum calculations at the MP2(full)/6-311++G(d,p) level on complexes between Cys (H₂S, MeSH) and Met (Me₂S) models with models of Phe (benzene, toluene), Trp (indole, 3-methylindole), Tyr (phenol, 4-methylphenol), and His (imidazole, 4-methylimidazole). The most stable gas-phase conformers exhibit binding energies of -2 to -6 kcal/mol, and the S atom lies perpendicular to the ring plane. This reveals preferential interaction with the ring π-system, except in the imidazoles where S binds edge-on to an N atom. Complexation tunes the gas-phase vertical ionization potentials of the ligands over as much as 1 eV, and strong σ- or π-type H-bonding supports charge transfer to the H-bond donor, rendering it more oxidizable. When the S atom acts as an H-bond acceptor (N/O-H_ar···S), calibration of the CHARMM36 force field (by optimizing pair-specific Lennard-Jones parameters) is required. Implementing the optimized parameters in molecular dynamics simulations in bulk water, we find stable S-aromatic complexes with binding free energies of -0.6 to -1.1 kcal/mol at ligand separations up to 8 Å. The aqueous S-aromatics exhibit flexible binding conformations, but edge-on conformers are less stable in water. Reflecting this, only 0.3 to 10% of the S-indole, S-phenol, and S-imidazole structures are stabilized by N/O-H_ar···S or S-H···O_ar/N_ar σ-type H-bonding. The wide range of energies and geometries found for S-aromatic interactions and their tunable redox properties expose the versatility and variability of the S-aromatic motif in proteins and allow us to predict a number of their reported properties.

An optimized charge penetration model for use with the AMOEBA force field

The principal challenge of using classical physics to model biomolecular interactions is capturing the nature of short-range interactions that drive biological processes from nucleic acid base stacking to protein-ligand binding. In particular most classical force fields suffer from an error in their electrostatic models that arises from an ability to account for the overlap between charge distributions occurring when molecules get close to each other, known as charge penetration. In this work we present a simple, physically motivated model for including charge penetration in the AMOEBA (Atomic Multipole Optimized Energetics for Biomolecular Applications) force field. With a function derived from the charge distribution of a hydrogen-like atom and a limited number of parameters, our charge penetration model dramatically improves the description of electrostatics at short range. On a database of 101 biomolecular dimers, the charge penetration model brings the error in the electrostatic interaction energy relative to the ab initio SAPT electrostatic interaction energy from 13.4 kcal mol^-1 to 1.3 kcal mol^-1. The model is shown not only to be robust and transferable for the AMOEBA model, but also physically meaningful as it universally improves the description of the electrostatic potential around a given molecule.

Aromaticity and Through-Space Interaction between Aromatic Rings in [2.2]Paracyclophanes

The HOMA index calculated for [2.2]paracyclophanes in the solid state reveals a slight decrease of aromaticity. Interactions between aromatic rings of [2.2]paracyclophane have been investigated using AIM and NCI analysis in both crystal and optimized [2.2]paracyclophane structures. AIM analysis showed that the C···C bond path between the two aromatic rings is present only in few [2.2]paracyclophanes. The NCI approach visualized the dispersion and repulsive interactions between the aromatic rings of every [2.2]paracyclophane. Combination of AIM and the NCI approach is necessary for determining and identifying nonbonded interactions in [2.2]paracyclophanes.

Beyond Born-Mayer: Improved Models for Short-Range Repulsion in ab Initio Force Fields

Short-range repulsion within intermolecular force fields is conventionally described by either Lennard-Jones (A/r(12)) or Born-Mayer (A exp(-Br)) forms. Despite their widespread use, these simple functional forms are often unable to describe the interaction energy accurately over a broad range of intermolecular distances, thus creating challenges in the development of ab initio force fields and potentially leading to decreased accuracy and transferability. Herein, we derive a novel short-range functional form based on a simple Slater-like model of overlapping atomic densities and an iterated stockholder atom (ISA) partitioning of the molecular electron density. We demonstrate that this Slater-ISA methodology yields a more accurate, transferable, and robust description of the short-range interactions at minimal additional computational cost compared to standard Lennard-Jones or Born-Mayer approaches. Finally, we show how this methodology can be adapted to yield the standard Born-Mayer functional form while still retaining many of the advantages of the Slater-ISA approach.

Analysis of the interactions of sulfur-containing amino acids in membrane proteins

The interactions of Met and Cys with other amino acid side chains have received little attention, in contrast to aromatic-aromatic, aromatic-aliphatic or/and aliphatic-aliphatic interactions. Precisely, these are the only amino acids that contain a sulfur atom, which is highly polarizable and, thus, likely to participate in strong Van der Waals interactions. Analysis of the interactions present in membrane protein crystal structures, together with the characterization of their strength in small-molecule model systems at the ab-initio level, predicts that Met-Met interactions are stronger than Met-Cys ≈ Met-Phe ≈ Cys-Phe interactions, stronger than Phe-Phe ≈ Phe-Leu interactions, stronger than the Met-Leu interaction, and stronger than Leu-Leu ≈ Cys-Leu interactions. These results show that sulfur-containing amino acids form stronger interactions than aromatic or aliphatic amino acids. Thus, these amino acids may provide additional driving forces for maintaining the 3D structure of membrane proteins and may provide functional specificity.

Exploiting Dispersion-Driven Aggregators as a Route to New One-Dimensional Organic Nanowires

The efficiency of charge carrier mobility in organic semiconductors is heavily dependent upon the long-range organization (i.e., morphology) and the local relative arrangement of the transporting molecules. Here, we exploit London dispersion forces as a design principle to construct compact one-dimensional (1-D) assemblies of quaterthiophene cores. We demonstrate that the substitution of quaterthiophene with dispersion-driven aggregators (e.g., [7]ladderanes, hydrogenated pyrenes, etc.) leads to the formation of highly stable and tightly packed 1-D supramolecular assemblies with electronic compactness superior to that of quaterthiophene crystals. Tunability and even tighter stacking arrangements can be achieved by inserting molecular linkers between the quaterthiophene fragments and the dispersion-driven components. The proposed 1-D nanowires represent an original route toward the rational design of efficient organic semiconductors.

A mixed basis with off-center Gaussian functions for the calculation of the potential energy surfaces for π-stacking interactions: dimers of benzene and planar C₆

A practical mixed basis set was developed to facilitate accurate calculations of potential energy surfaces for π-stacking interactions. Correlation consistent basis sets (cc-PVXZ) were augmented by p-type Gaussian functions placed above and below the planes of C6 moieties. Møller-Plesset (MP2, SCS-MP2) and coupled cluster [CCSD(T)] calculations show that such generated basis sets provide an accurate description of π-stacking systems with favorable computation times compared to the standard augmented basis sets. The addition of these off-center functions eliminates the linear dependence of the augmented basis sets, which is one of the most encountered numerical problems during calculation of the oligomers of polyaromatic hydrocarbons (PAH). In this work, we present a comparative study of the general characteristics of the potential energy surfaces for the parallel stacked and T-shape conformations of benzene and planar C6 clusters, using a combination of cc-PVXZ and our optimized functions. We discuss properties, such as the depth and curvature of the potential functions, short and long distance behavior, and the frictional forces between two model monomers.

Quantum Mechanical Calculation of Noncovalent Interactions: A Large-Scale Evaluation of PMx, DFT, and SAPT Approaches

Quantum mechanical (QM) calculations of noncovalent interactions are uniquely useful as tools to test and improve molecular mechanics force fields and to model the forces involved in biomolecular binding and folding. Because the more computationally tractable QM methods necessarily include approximations, which risk degrading accuracy, it is essential to evaluate such methods by comparison with high-level reference calculations. Here, we use the extensive Benchmark Energy and Geometry Database (BEGDB) of CCSD(T)/CBS reference results to evaluate the accuracy and speed of widely used QM methods for over 1200 chemically varied gas-phase dimers. In particular, we study the semiempirical PM6 and PM7 methods; density functional theory (DFT) approaches B3LYP, B97-D, M062X, and ωB97X-D; and symmetry-adapted perturbation theory (SAPT) approach. For the PM6 and DFT methods, we also examine the effects of post hoc corrections for hydrogen bonding (PM6-DH+, PM6-DH2), halogen atoms (PM6-DH2X), and dispersion (DFT-D3 with zero and Becke–Johnson damping). Several orders of the SAPT expansion are also compared, ranging from SAPT0 up to SAPT2+3, where computationally feasible. We find that all DFT methods with dispersion corrections, as well as SAPT at orders above SAPT2, consistently provide dimer interaction energies within 1.0 kcal/mol RMSE across all systems. We also show that a linear scaling of the perturbative energy terms provided by the fast SAPT0 method yields similar high accuracy, at particularly low computational cost. The energies of all the dimer systems from the various QM approaches are included in the Supporting Information, as are the full SAPT2+(3) energy decomposition for a subset of over 1000 systems. The latter can be used to guide the parametrization of molecular mechanics force fields on a term-by-term basis.

Biomolecular Structure and Modeling: Historical Perspective

physics, chemistry, and biology have been connected by a web of causal explanation organized by induction-based theories that telescope into one another. … Thus, quantum theory underlies atomic physics, which is the foundation of reagent chemistry and its specialized offshoot biochemistry, which interlock with molecular biology — essentially, the chemistry of organic macromolecules — and hence, through successively higher levels of organization, cellular, organismic, and evolutionary biology. … Such is the unifying and highly productive understanding of the world that has evolved in the natural sciences.