Development of an AMOEBA water model using GEM distributed multipoles

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environment effects, which promote competing interactions and alter their static gas-phase properties. Recently, neural network potentials (NNPs) trained on Density Functional Theory (DFT) data have become increasingly popular to simulate molecular phenomena in condensed phase with an accuracy comparable to ab initio methods. To date, most applications have centered on solid-state materials or fairly simple molecules made of a limited number of elements. Herein, we focus on the persistence and strength of chalcogen bonds involving a benzotelluradiazole in condensed phase. While the tellurium-containing heteroaromatic molecules are known to exhibit pronounced interactions with anions and lone pairs of different atoms, the relevance of competing intermolecular interactions, notably with the solvent, is complicated to monitor experimentally but also challenging to model at an accurate electronic structure level. Here, we train direct and baselined NNPs to reproduce hybrid DFT energies and forces in order to identify what are the most prevalent non-covalent interactions occurring in a solute-Cl$^-$-THF mixture. The simulations in explicit solvent highlight competition with chalcogen bonds formed with the solvent and the short-range directionality of the interaction with direct consequences for the molecular properties in the solution. The comparison with other potentials (e.g., AMOEBA, direct NNP and continuum solvent model) also demonstrates that baselined NNPs offer a reliable picture of the non-covalent interaction interplay occurring in solution.

Improvement of the Gaussian Electrostatic Model by separate fitting of Coulomb and exchange-repulsion densities and implementation of a new dispersion term

The description of each separable contribution of the intermolecular interaction is a useful approach to develop polarizable force fields (polFFs). The Gaussian Electrostatic Model (GEM) is based on this approach, coupled with the use of density fitting techniques. In this work, we present the implementation and testing of two improvements of GEM: the Coulomb and exchange-repulsion energies are now computed with separate frozen molecular densities and a new dispersion formulation inspired by the Sum of Interactions Between Fragments Ab initio Computed polFF, which has been implemented to describe the dispersion and charge-transfer interactions. Thanks to the combination of GEM characteristics and these new features, we demonstrate a better agreement of the computed structural and condensed properties for water with experimental results, as well as binding energies in the gas phase with the ab initio reference compared with the previous GEM* potential. This work provides further improvements to GEM and the items that remain to be improved and the importance of the accurate reproduction for each separate contribution.

Polarizable Water Potential Derived from a Model Electron Density

A new empirical potential for efficient, large scale molecular dynamics simulation of water is presented. The HIPPO (Hydrogen-like Intermolecular Polarizable POtential) force field is based upon the model electron density of a hydrogen-like atom. This framework is used to derive and parametrize individual terms describing charge penetration damped permanent electrostatics, damped polarization, charge transfer, anisotropic Pauli repulsion, and damped dispersion interactions. Initial parameter values were fit to Symmetry Adapted Perturbation Theory (SAPT) energy components for ten water dimer configurations, as well as the radial and angular dependence of the canonical dimer. The SAPT-based parameters were then systematically refined to extend the treatment to water bulk phases. The final HIPPO water model provides a balanced representation of a wide variety of properties of gas phase clusters, liquid water, and ice polymorphs, across a range of temperatures and pressures. This water potential yields a rationalization of water structure, dynamics, and thermodynamics explicitly correlated with an ab initio energy decomposition, while providing a level of accuracy comparable or superior to previous polarizable atomic multipole force fields. The HIPPO water model serves as a cornerstone around which similarly detailed physics-based models can be developed for additional molecular species.

Determining the atomic charge of calcium ion requires the information of its coordination geometry in an EF-hand motif

It is challenging to parameterize the force field for calcium ions (Ca²⁺) in calcium-binding proteins because of their unique coordination chemistry that involves the surrounding atoms required for stability. In this work, we observed a wide variation in Ca²⁺ binding loop conformations of the Ca²⁺-binding protein calmodulin, which adopts the most populated ternary structures determined from the molecular dynamics simulations, followed by ab initio quantum mechanical (QM) calculations on all 12 amino acids in the loop that coordinate Ca²⁺ in aqueous solution. Ca²⁺ charges were derived by fitting to the electrostatic potential in the context of a classical or polarizable force field (PFF). We discovered that the atomic radius of Ca²⁺ in conventional force fields is too large for the QM calculation to capture the variation in the coordination geometry of Ca²⁺ in its ionic form, leading to unphysical charges. Specifically, we found that the fitted atomic charges of Ca²⁺ in the context of PFF depend on the coordinating geometry of electronegative atoms from the amino acids in the loop. Although nearby water molecules do not influence the atomic charge of Ca²⁺, they are crucial for compensating for the coordination of Ca²⁺ due to the conformational flexibility in the EF-hand loop. Our method advances the development of force fields for metal ions and protein binding sites in dynamic environments.

Current Status of AMOEBA-IL: A Multipolar/Polarizable Force Field for Ionic Liquids

Computational simulations of ionic liquid solutions have become a useful tool to investigate various physical, chemical and catalytic properties of systems involving these solvents. Classical molecular dynamics and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations of IL systems have provided significant insights at the atomic level. Here, we present a review of the development and application of the multipolar and polarizable force field AMOEBA for ionic liquid systems, termed AMOEBA–IL. The parametrization approach for AMOEBA–IL relies on the reproduction of total quantum mechanical (QM) intermolecular interaction energies and QM energy decomposition analysis. This approach has been used to develop parameters for imidazolium– and pyrrolidinium–based ILs coupled with various inorganic anions. AMOEBA–IL has been used to investigate and predict the properties of a variety of systems including neat ILs and IL mixtures, water exchange reactions on lanthanide ions in IL mixtures, IL–based liquid–liquid extraction, and effects of ILs on an aniline protection reaction.

Molecular Dynamics Simulations of Ionic Liquids and Electrolytes Using Polarizable Force Fields

Many applications in chemistry, biology, and energy storage/conversion research rely on molecular simulations to provide fundamental insight into structural and transport properties of materials with high ionic concentrations. Whether the system is comprised entirely of ions, like ionic liquids, or is a mixture of a polar solvent with a salt, e.g., liquid electrolytes for battery applications, the presence of ions in these materials results in strong local electric fields polarizing solvent molecules and large ions. To predict properties of such systems from molecular simulations often requires either explicit or mean-field inclusion of the influence of polarization on electrostatic interactions. In this manuscript, we review the pros and cons of different treatments of polarization ranging from the mean-field approaches to the most popular explicit polarization models in molecular dynamics simulations of ionic materials. For each method, we discuss their advantages and disadvantages and emphasize key assumptions as well as their adjustable parameters. Strategies for the development of polarizable models are presented with a specific focus on extracting atomic polarizabilities. Finally, we compare simulations using polarizable and nonpolarizable models for several classes of ionic systems, discussing the underlying physics that each approach includes or ignores, implications for implementation and computational efficiency, and the accuracy of properties predicted by these methods compared to experiments.

Toward Learned Chemical Perception of Force Field Typing Rules

Molecular mechanics force fields define how the energy and forces in a molecular system are computed from its atomic positions, thus enabling the study of such systems through computational methods like molecular dynamics and Monte Carlo simulations. Despite progress toward automated force field parametrization, considerable human expertise is required to develop or extend force fields. In particular, human input has long been required to define atom types, which encode chemically unique environments that determine which parameters will be assigned. However, relying on humans to establish atom types is suboptimal. Human-created atom types are often developed without statistical justification, leading to over- or under-fitting of data. Human-created types are also difficult to extend in a systematic and consistent manner when new chemistries must be modeled or new data becomes available. Finally, human effort is not scalable when force fields must be generated for new (bio)polymers, compound classes, or materials. To remedy these deficiencies, our long-term goal is to replace human specification of atom types with an automated approach, based on rigorous statistics and driven by experimental and/or quantum chemical reference data. In this work, we describe novel methods that automate the discovery of appropriate chemical perception: SMARTY allows for the creation of atom types, while SMIRKY goes further by automating the creation of fragment (nonbonded, bonds, angles, and torsions) types. These approaches enable the creation of move sets in atom or fragment type space, which are used within a Monte Carlo optimization approach. We demonstrate the power of these new methods by automating the rediscovery of human defined atom types (SMARTY) or fragment types (SMIRKY) in existing small molecule force fields. We assess these approaches using several molecular data sets, including one which covers a diverse subset of the DrugBank database.

Polarizable ab initio QM/MM Study of the Reaction Mechanism of N-tert-Butyloxycarbonylation of Aniline in [EMIm][BF₄]

N-t e r t-butoxycarbonylation of amines in solution (water, organic solvents, or ionic liquids) is a common reaction for the preparation of drug molecules. To understand the reaction mechanism and the role of the solvent, quantum mechanical/molecular mechanical simulations using a polarizable multipolar force field with long⁻range electrostatic corrections were used to optimize the minimum energy paths (MEPs) associated with various possible reaction mechanisms employing the nudged elastic band (NEB) and the quadratic string method (QSM). The calculated reaction energies and energy barriers were compared with the corresponding gas-phase and dichloromethane results. Complementary Electron Localization Function (ELF)/NCI analyses provide insights on the critical structures along the MEP. The calculated results suggest the most likely path involves a sequential mechanism with the rate⁻limiting step corresponding to the nucleophilic attack of the aniline, followed by proton transfer and the release of CO 2 without the direct involvement of imidazolium cations as catalysts.

QM/MM Simulations with the Gaussian Electrostatic Model: A Density-based Polarizable Potential

The use of advanced polarizable potentials in quantum mechanical/molecular mechanical (QM/MM) simulations has been shown to improve the overall accuracy of the calculation. We have developed a density-based potential called the Gaussian electrostatic model (GEM), which has been shown to provide very accurate environments for QM wave functions in QM/MM. In this contribution we present a new implementation of QM/GEM that extends our implementation to include all components (Coulomb, exchange-repulsion, polarization, and dispersion) for the total intermolecular interaction energy in QM/MM calculations, except for the charge-transfer term. The accuracy of the method is tested using a subset of water dimers from the water dimer potential energy surface reported by Babin et al. ( J. Chem. Theory Comput. 2013 9, 5395-5403). Additionally, results of the new implementation are contrasted with results obtained with the classical AMOEBA potential. Our results indicate that GEM provides an accurate MM environment with average root-mean-square error <0.15 kcal/mol for every intermolecular interaction energy component compared with SAPT2+3/aug-cc-pVTZ reference calculations.

Computational Simulations of DNA Polymerases: Detailed Insights on Structure/Function/Mechanism from Native Proteins to Cancer Variants

Genetic information is vital in the cell cycle of DNA-based organisms. DNA polymerases (DNA Pols) are crucial players in transactions dealing with these processes. Therefore, the detailed understanding of the structure, function, and mechanism of these proteins has been the focus of significant effort. Computational simulations have been applied to investigate various facets of DNA polymerase structure and function. These simulations have provided significant insights over the years. This perspective presents the results of various computational studies that have been employed to research different aspects of DNA polymerases including detailed reaction mechanism investigation, mutagenicity of different metal cations, possible factors for fidelity synthesis, and discovery/functional characterization of cancer-related mutations on DNA polymerases.

Computational investigation of O2 diffusion through an intra-molecular tunnel in AlkB; influence of polarization on O2 transport

E. Coli AlkB catalyzes the direct dealkylation of various alkylated bases in damaged DNA. The diffusion of molecular oxygen to the active site in AlkB is an essential step for the oxidative dealkylation activity. Despite detailed studies on the stepwise oxidation mechanism of AlkB, there is no conclusive picture of how O2 molecules reach the active site of the protein. Yu et al. (Nature, 439, 879) proposed the existence of an intra-molecular tunnel based on their initial crystal structures of AlkB. We have employed computational simulations to investigate possible migration pathways inside AlkB for O2 molecules. Extensive molecular dynamics (MD) simulations, including explicit ligand sampling and potential of mean force (PMF) calculations, have been performed to provide a microscopic description of the O2 delivery pathway in AlkB. Analysis of intra-molecular tunnels using the CAVER software indicates two possible pathways for O2 to diffuse into the AlkB active site. Explicit ligand sampling simulations suggests that only one of these tunnels provides a viable route. The free energy path for an oxygen molecule to travel along each of these tunnels has been determined with AMBER and AMOEBA. Both PMFs indicate passive transport of O2 from the surface of the protein. However, the inclusion of explicit polarization shows a very large barrier for diffusion of the co-substrate out of the active site, compared with the non-polarizable potential. In addition, our results suggest that the mutation of a conserved residue along the tunnel, Y178, has dramatic effects on the dynamics of AlkB and on the transport of O2 along the tunnel.

Induced polarization restricts the conformational distribution of a light-harvesting molecular triad in the ground state

Free energy surface of the light-harvesting triad employing a non-polarizable force field (NFF) and a polarizable force field (PFF) shows that induced polarization limits the motion of rotation about chemical bonds as well as bending at the porphyrin, which are prominent using the NFF, thus limiting the conformational space of the triad.

Modeling Molecular Interactions in Water: From Pairwise to Many-Body Potential Energy Functions

Almost 50 years have passed from the first computer simulations of water, and a large number of molecular models have been proposed since then to elucidate the unique behavior of water across different phases. In this article, we review the recent progress in the development of analytical potential energy functions that aim at correctly representing many-body effects. Starting from the many-body expansion of the interaction energy, specific focus is on different classes of potential energy functions built upon a hierarchy of approximations and on their ability to accurately reproduce reference data obtained from state-of-the-art electronic structure calculations and experimental measurements. We show that most recent potential energy functions, which include explicit short-range representations of two-body and three-body effects along with a physically correct description of many-body effects at all distances, predict the properties of water from the gas to the condensed phase with unprecedented accuracy, thus opening the door to the long-sought "universal model" capable of describing the behavior of water under different conditions and in different environments.