AMOEBA Polarizable Force Field Research Articles

Importance of Polarizable Embedding for Computing Optical Rotation: The Case of Camphor in Ethanol.

Solvation effects on optical rotation are notoriously challenging to model for computational chemistry, as the specific rotatory power of a molecule can vary wildly going from apolar to polar or even protic solvents. To address such a problem, we present a polarizable embedding implementation of an electric and magnetic response property based on density functional theory and the AMOEBA polarizable force field, and apply such an implementation to the study of the optical rotation of camphor in ethanol. By comparing a continuum model, and electrostatic and polarizable embedding QM/MM models, we observe that accounting for the environment's polarization gives rise to not only a different quantitative prediction, in very good agreement with experiments for the QM/AMOEBA model, but also to a very different qualitative picture, with the values of the optical rotation computed along a classical molecular dynamics trajectory with electrostatic embedding being statistically uncorrelated to the ones obtained with the polarizable description.

Crystal Polymorph Search in the NPT Ensemble via a Deposition/Sublimation Alchemical Path.

The formulation of active pharmaceutical ingredients involves discovering stable crystal packing arrangements or polymorphs, each of which has distinct pharmaceutically relevant properties. Traditional experimental screening techniques utilizing various conditions are commonly supplemented with in silico crystal structure prediction (CSP) to inform the crystallization process and mitigate risk. Predictions are often based on advanced classical force fields or quantum mechanical calculations that model the crystal potential energy landscape but do not fully incorporate temperature, pressure, or solution conditions during the search procedure. This study proposes an innovative alchemical path that utilizes an advanced polarizable atomic multipole force field to predict crystal structures based on direct sampling of the NPT ensemble. The use of alchemical (i.e., nonphysical) intermediates, a novel Monte Carlo barostat, and an orthogonal space tempering bias combine to enhance the sampling efficiency of the deposition/sublimation phase transition. The proposed algorithm was applied to 2-((4-(2-(3,4-dichlorophenyl)ethyl)phenyl)amino)benzoic acid (Cambridge Crystallography Database Centre ID: XAFPAY) as a case study to showcase the algorithm. Each experimentally determined polymorph with one molecule in the asymmetric unit was successfully reproduced via approximately 1000 short 1 ns simulations per space group where each simulation was initiated from random rigid body coordinates and unit cell parameters. Utilizing two threads of a recent Intel CPU (a Xeon Gold 6330 CPU at 2.00 GHz), 1 ns of sampling using the polarizable AMOEBA force field can be acquired in 4 h (equating to more than 300 ns/day using all 112 threads/56 cores of a dual CPU node) within the Force Field X software (https://ffx.biochem.uiowa.edu). These results demonstrate a step forward in the rigorous use of the NPT ensemble during the CSP search process and open the door to future algorithms that incorporate solution conditions using continuum solvation methods.

Incorporating Neural Networks into the AMOEBA Polarizable Force Field.

Neural network potentials (NNPs) offer significant promise to bridge the gap between the accuracy of quantum mechanics and the efficiency of molecular mechanics in molecular simulation. Most NNPs rely on the locality assumption that ensures the model's transferability and scalability and thus lack the treatment of long-range interactions, which are essential for molecular systems in the condensed phase. Here we present an integrated hybrid model, AMOEBA+NN, which combines the AMOEBA potential for the short- and long-range noncovalent atomic interactions and an NNP to capture the remaining local covalent contributions. The AMOEBA+NN model was trained on the conformational energy of the ANI-1x data set and tested on several external data sets ranging from small molecules to tetrapeptides. The hybrid model demonstrated substantial improvements over the baseline models in term of accuracy as the molecule size increased, suggesting its potential as a next-generation approach for chemically accurate molecular simulations.

Critical Evaluation of Polarizable and Nonpolarizable Force Fields for Proteins Using Experimentally Derived Nitrile Electric Fields.

Molecular dynamics (MD) simulations are frequently carried out for proteins to investigate the role of electrostatics in their biological function. The choice of force field (FF) can significantly alter the MD results, as the simulated local electrostatic interactions lack benchmarking in the absence of appropriate experimental methods. We recently reported that the transition dipole moment (TDM) of the popular nitrile vibrational probe varies linearly with the environmental electric field, overcoming well-known hydrogen bonding (H-bonding) issues for the nitrile frequency and, thus, enabling the unambiguous measurement of electric fields in proteins (J. Am. Chem. Soc. 2022, 144 (17), 7562-7567). Herein, we utilize this new strategy to enable comparisons of experimental and simulated electric fields in protein environments. Specifically, previously determined TDM electric fields exerted onto nitrile-containing o-cyanophenylalanine residues in photoactive yellow protein are compared with MD electric fields from the fixed-charge AMBER FF and the polarizable AMOEBA FF. We observe that the electric field distributions for H-bonding nitriles are substantially affected by the choice of FF. As such, AMBER underestimates electric fields for nitriles experiencing moderate field strengths; in contrast, AMOEBA robustly recapitulates the TDM electric fields. The FF dependence of the electric fields can be partly explained by the presence of additional negative charge density along the nitrile bond axis in AMOEBA, which is due to the inclusion of higher-order multipole parameters; this, in turn, begets more head-on nitrile H-bonds. We conclude by discussing the implications of the FF dependence for the simulation of nitriles and proteins in general.

Polarizable AMOEBA force field predicts thin and dense hydration layer around monosaccharides.

Polarizable force fields crucially enhance the modeling of macromolecules in polar media. Here, we present new parameters to model six common monosaccharides with the polarizable AMOEBA force field. These parameters yield a thinner, but denser, hydration layer than that previously reported. This denser hydration layer results in eliminating non-physical aggregation of glucose in water-an issue that has plagued molecular dynamics simulations of carbohydrates for decades.

Cooperativity and Frustration Effects (or Lack Thereof) in Polarizable and Non-polarizable Force Fields.

Understanding cooperativity and frustration is crucial for studying biological processes such as molecular recognition and protein aggregation. Force fields have been extensively utilized to explore cooperativity in the formation of protein secondary structures and self-assembled systems. Multiple studies have demonstrated that polarizable force fields provide more accurate descriptions of this phenomenon compared to fixed-charge pairwise nonpolarizable force fields, thanks to the incorporation of polarization effects. In this study, we assess the performance of the AMOEBA polarizable force field and the AMBER and OPLS nonpolarizable pairwise force fields in capturing positive and negative cooperativity recently explored in neutral and charged molecular clusters using density functional theory. Our findings show that polarizable and nonpolarizable force fields qualitatively reproduce the relative cooperativity observed in electron structure calculations. However, AMBER and OPLS fail to describe absolute cooperativity. In contrast, AMOEBA accounts for the absolute cooperativity by considering interactions beyond pairwise interactions. According to the energy decomposition analysis, it is observed that the electrostatic interactions calculated with the AMBER and OPLS force fields seem to play an important and counterintuitive role in reproducing the adiabatic interaction energies calculated with density functional theory. However, it is important to note that these force fields, due to their nature, do not explicitly incorporate many-body effects, which limits their ability to accurately describe cooperativity. On the other hand, frustration in polarizable and nonpolarizable force fields is caused by changes in bond stretching and angle bending terms of the building blocks when they are forming a complex.

RNA-protein complexes and force field polarizability.

Molecular dynamic (MD) simulations offer a way to study biomolecular interactions and their dynamics at the atomistic level. There are only a few studies of RNA-protein complexes in MD simulations, and here we wanted to study how force fields differ when simulating RNA-protein complexes: 1) argonaute 2 with bound guide RNA and a target RNA, 2) CasPhi-2 bound to CRISPR RNA and 3) Retinoic acid-inducible gene I C268F variant in complex with double-stranded RNA. We tested three non-polarizable force fields: Amber protein force fields ff14SB and ff19SB with RNA force field OL3, and the all-atom OPLS4 force field. Due to the highly charged and polar nature of RNA, we also tested the polarizable AMOEBA force field and the ff19SB and OL3 force fields with a polarizable water model O3P. Our results show that the non-polarizable force fields lead to compact and stable complexes. The polarizability in the force field or in the water model allows significantly more movement from the complex, but in some cases, this results in the disintegration of the complex structure, especially if the protein contains longer loop regions. Thus, one should be cautious when running long-scale simulations with polarizability. As a conclusion, all the tested force fields can be used to simulate RNA-protein complexes and the choice of the optimal force field depends on the studied system and research question.

QM/AMOEBA description of properties and dynamics of embedded molecules

AbstractWe describe the development, implementation, and application of a polarizable QM/MM strategy, based on the AMOEBA polarizable force field, for calculating molecular properties and performing dynamics of molecular systems embedded in complex matrices. We show that polarizable QM/MM is a well‐understood, mature technology that can be deployed using a state‐of‐the‐art implementation that combines efficient numerical methods and linear scaling techniques. Thanks to these numerical advances and to the availability of parameters for a wide manifold of systems in the AMOEBA force field, polarizable QM/AMOEBA can be used for advanced production applications, that range from the prediction of spectroscopies to ground‐ and excited‐state multiscale ab initio molecular dynamics simulations.This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Combined QM/MM Methods

Transport Parameters for Combustion Species Based on cAMOEBA Polarizable Force Field.

In this study, we report a simplified yet accurate general AMOEBA polarizable force field for combustion-interested molecular species, denoted as Combustion-AMOEBA or cAMOEBA. By eliminating the permanent atomic dipoles and quadrupoles, retaining the explicit polarization and defining the general atom types of each molecule species, including alkanes, alkenes, alkynes, alcohols, peroxides, and aldehydes, a simplified and general cAMOEBA force field was constructed and validated using the benchmark results obtained at the QCISD(T)/CBS level of theory. In this way, the tedious parametrization step for permanent atomic multipoles of each new molecule in the original AMOEBA (Poltype/MP2) force field could be avoided, hence providing the capability of accurate high-throughput calculation for a large number of molecules at lower computational cost. The averaged difference between the calculated transport parameters, σ and ε, for approximately 100 different molecules and four bath gases (He, Ne, Ar, and N2) using cAMOEBA and AMOEBA (Poltype/MP2) are of 0.09% and 1.27%, respectively, showing a good consistence of the general cAMOEBA force field with the original AMOEBA (Poltype/MP2) force field where the multipole force field parameters were obtained from quantum mechanical calculation for each small molecule. Our results also indicated that the Lorentz-Berthelot combination rule was more applicable than Waldman-Hagler for obtaining the molecular Lennard-Jones parameters of pure gases from one bath gas, while the Waldman-Hagler combination rule was better for obtaining such parameters from all four bath gases. The pure gas parameters obtained using cAMOEBA can be applied to develop high quality transport property database for combustion modeling.

Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: From Force Fields to Machine Learning Potentials.

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.

Development of AMOEBA Polarizable Force Field for Rare-Earth La3+ Interaction with Bioinspired Ligands.

Rare-earth metals (REMs) are crucial for many important industries, such as power generation and storage, in addition to cancer treatment and medical imaging. One promising new REM refinement approach involves mimicking the highly selective and efficient binding of REMs observed in relatively recently discovered proteins. However, realizing any such bioinspired approach requires an understanding of the biological recognition mechanisms. Here, we developed a new classical polarizable force field based on the AMOEBA framework for modeling a lanthanum ion (La3+) interacting with water, acetate, and acetamide, which have been found to coordinate the ion in proteins. The parameters were derived by comparing to high-level ab initio quantum mechanical (QM) calculations that include relativistic effects. The AMOEBA model, with advanced atomic multipoles and electronic polarization, is successful in capturing both the QM distance-dependent La3+-ligand interaction energies and experimental hydration free energy. A new scheme for pairwise polarization damping (POLPAIR) was developed to describe the polarization energy in La3+ interactions with both charged and neutral ligands. Simulations of La3+ in water showed water coordination numbers and ion-water distances consistent with previous experimental and theoretical findings. Water residence time analysis revealed both fast and slow kinetics in water exchange around the ion. This new model will allow investigation of fully solvated lanthanum ion-protein systems using GPU-accelerated dynamics simulations to gain insights on binding selectivity, which may be applied to the design of synthetic analogues.

Binding free energies from the polarizable AMOEBA force field.

A protocol for computing absolute binding free energies with the AMOEBA polarizable force field is presented. Examples discussed include various host-guest complexes from the SAMPL community exercises, binding of ions to an RNA G-quadruplex and a series of protein-ligand interactions. In many cases where calculations are not limited by sampling issues, the AMOEBA model is able to provide binding values within “chemical accuracy,” i.e., roughly 1 kcal/mol from experiment.

Hydrophobic Deep eutectic Solvents based on cineole and organic acids

The hydrophobic Natural Deep Eutectic Solvent formed by the combination of cineole and decanoic acid (capric acid) was studied using a combined experimental and computational approach. Experimental study was carried considering relevant physicochemical properties as density, viscosity, refraction index and thermal conductivity as a function of temperature, as well as Raman spectra for 785 nm excitation wavelength. Thermophysical properties measured showed a low -viscous low-dense fluid, which is of great relevance for its technological application, as well as the Raman spectra confirmed the formation of hydrogen bonding. The analysis of nanoscopic properties and structuring was carried out using theoretical method as the Density Functional Theory (BP86/def2-TZVP plus Grimme’s D3 theoretical level) and classical Molecular Dynamics simulation (using AMOEBA polarizable force field). Molecular modelling studies using quantum chemistry and classical molecular dynamics methods allowed a nanoscopic characterization of the fluid as well as of its intermolecular forces (hydrogen bonding). Phase equilibria were predicted using COSMO method considered solid–liquid (melting behavior) and vapor – liquid (evaporation), as well as excess properties. The COSMO results showed a low volatile, wide liquid range fluid, characterized by non-ideality because of the formation of hydrogen bonding. Likewise, the interaction of the considered material with POPC lipid was studied using COSMOperm method to analyze its behavior at lipid bilayers as models of cell membranes for the consideration of its possible toxicological effects, showing how the considered molecules are able to penetrate and disrupt the model membranes because of the lipophilic nature of the considered molecules.

AMOEBA Polarizable Force Field for Molecular Dynamics Simulations of Glyme Solvents.

Classical molecular dynamics (MD) simulations of electrolyte systems are important to gain insight into the atom-scale properties that determine the battery-relevant performance. The recent Tinker-HP software release enables efficient and accurate MD simulations with the AMOEBA polarizable force field. In this work, we developed a procedure to construct a universal AMOEBA model for the solvent family of glymes (glycol methyl ethers), which involves a refinement scheme for valence parameters by fitting the AMOEBA-derived atomic forces to those computed at the DFT level. The refined AMOEBA model provides a good description of both local and nonlocal properties in terms of the spectroscopic response of glyme molecules, as well as the liquid glyme density and dielectric constant. In addition, the complexation energies of alkali and alkaline-earth metal cations with tetraglyme molecules obtained from AMOEBA calculations are in good agreement with DFT results, demonstrating the suitability of the developed AMOEBA model for an accurate simulation of glyme-based battery electrolytes. We also expect the procedure to be transferable to the development of AMOEBA models for other battery electrolyte systems.

Molecular Dynamics and Free Energy Calculations of Dicyclohexano-18-crown-6 Diastereoisomers with Sm2+, Eu2+, Dy2+, Yb2+, Cf2+, and Three Halide Salts in Tetrahydrofuran and Acetonitrile Using the AMOEBA Force Field.

With the continual development of lanthanides (Ln) in current technological devices, an efficient separation process is needed that can recover greater amounts of these rare elements. Dicyclohexano-18-crown-6 (DCH18C6) is a crown ether that may be a promising candidate for Ln separation, but additional research is required. As such, molecular dynamics (MD) simulations have been performed on four divalent lanthanide halide salts (Sm2+, Eu2+, Dy2+, and Yb2+) and one divalent actinide halide salt (Cf2+) bound to three diastereoisomers of DCH18C6. Dy2+, Yb2+, Cf2+, DCH18C6, and tetrahydrofuran (THF) solvent were parameterized for the AMOEBA polarizable force field for the first time, whereas existing parameters for Sm2+ and Eu2+ were utilized from our previous efforts. A coordination number (CN) of six for Ln2+/An2+-O solvated in THF indicated that the cations interacted almost entirely with the oxygens of the polyether ring. A CN of one for Ln2+/An2+-N solvated in acetonitrile for systems containing iodide suggested that the N atom of acetonitrile was competitive with I- for cation interactions. Fluctuation between five and six CNs for Dy2+ and Yb2+ suggested that although the cations remained in the polyether ring, the size of the ring may not be an ideal fit as these cations possess comparatively smaller ionic radii. Gibbs binding free energies of Sm2+ in all DCH18C6 diastereoisomers solvated in THF were calculated. The binding free energy of the cis-syn-cis diastereoisomer was the most favorable, followed by cis-anti-cis, and then trans-anti-trans. Finally, two major types of conformation were observed for each diastereoisomer that were related to the electrostatic interactions and charge density of the cations.

Improving Condensed-Phase Water Dynamics with Explicit Nuclear Quantum Effects: The Polarizable Q-AMOEBA Force Field.

We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14-7 potential to model van der Waals interactions. It has been obtained by using a ForceBalance fitting strategy including high-level quantum chemistry reference energies and selected condensed-phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas-phase and condensed-phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H-O-H angle compared to its gas-phase equilibrium value, isotope effects, and so on. Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins, and nucleic acids opening the possibility for the large-scale study of the importance of NQEs in biophysics.

An overview of the SAMPL8 host–guest binding challenge

The SAMPL series of challenges aim to focus the community on specific modeling challenges, while testing and hopefully driving progress of computational methods to help guide pharmaceutical drug discovery. In this study, we report on the results of the SAMPL8 host–guest blind challenge for predicting absolute binding affinities. SAMPL8 focused on two host–guest datasets, one involving the cucurbituril CB8 (with a series of common drugs of abuse) and another involving two different Gibb deep-cavity cavitands. The latter dataset involved a previously featured deep cavity cavitand (TEMOA) as well as a new variant (TEETOA), both binding to a series of relatively rigid fragment-like guests. Challenge participants employed a reasonably wide variety of methods, though many of these were based on molecular simulations, and predictive accuracy was mixed. As in some previous SAMPL iterations (SAMPL6 and SAMPL7), we found that one approach to achieve greater accuracy was to apply empirical corrections to the binding free energy predictions, taking advantage of prior data on binding to these hosts. Another approach which performed well was a hybrid MD-based approach with reweighting to a force matched QM potential. In the cavitand challenge, an alchemical method using the AMOEBA-polarizable force field achieved the best success with RMSE less than 1 kcal/mol, while another alchemical approach (ATM/GAFF2-AM1BCC/TIP3P/HREM) had RMSE less than 1.75 kcal/mol. The work discussed here also highlights several important lessons; for example, retrospective studies of reference calculations demonstrate the sensitivity of predicted binding free energies to ethyl group sampling and/or guest starting pose, providing guidance to help improve future studies on these systems.

Molecular Dynamics Simulations of Protein RNA Complexes by Using an Advanced Electrostatic Model.

Protein-RNA interactions are integral to the biological functions of RNA. It is well recognized that molecular dynamics (MD) simulations of protein-RNA complexes are more challenging than those of each component. The difficulty arises from the strong electrostatic interactions and the delicate balance between various types of physical forces at the interface. Previously, MD simulations of protein-RNA complexes have predominantly employed fixed-charge force fields. Although force field modifications have been developed to address problems identified in the simulations, some protein-RNA structures are still hard to reproduce by simulations. Here, we present MD simulations of two representative protein-RNA complexes using the AMOEBA polarizable force field. The van der Waals parameters were refined to reproduce accurate quantum-mechanical data of base-base and base-amino acid interactions. It was found that the refined parameters produced a more stable hydrogen-bond network in the interface. One of the complexes remained stable during the short simulations, whereas it could quickly break down in previous simulations using fixed-charge force fields. There was reversible breaking and formation of hydrogen bonds that are observed in the crystal structure, which may indicate the difference in solution and crystal structures. While further improvement and validation of the force fields are still needed, this work demonstrates that polarizable force fields are promising for the study of protein-RNA complexes.

Trajectory Surface Hopping for a Polarizable Embedding QM/MM Formulation.

We present the implementation of trajectory surface-hopping nonadiabatic dynamics for a polarizable embedding QM/MM formulation. Time-dependent density functional theory was used at the quantum mechanical level of theory, whereas the molecular mechanics description involved the polarizable AMOEBA force field. This implementation has been obtained by integrating the surface-hopping program Newton-X NS with an interface between the Gaussian 16 and the Tinker suites of codes to calculate QM/AMOEBA energies and forces. The implementation has been tested on a photoinduced electron-driven proton-transfer reaction involving pyrimidine and a hydrogen-bonded water surrounded by a small cluster of water molecules and within a large water droplet.

Computational study on the binding of Mango-II RNA aptamer and fluorogen using the polarizable force field AMOEBA.

Fluorescent light-up aptamers (FLAPs) are well-performed biosensors for cellular imaging and the detection of different targets of interest, including RNA, non-nucleic acid molecules, metal ions, and so on. They could be easily designed and emit a strong fluorescence signal once bound to specified fluorogens. Recently, one unique aptamer called Mango-II has been discovered to possess a strong affinity and excellent fluorescent properties with fluorogens TO1-Biotin and TO3-Biotin. To explore the binding mechanisms, computational simulations have been performed to obtain structural and thermodynamic information about FLAPs at atomic resolution. AMOEBA polarizable force field, with the capability of handling the highly charged and flexible RNA system, was utilized for the simulation of Mango-II with TO1-Biotin and TO3-Biotin in this work. The calculated binding free energy using published crystal structures is in excellent agreement with the experimental values. Given the challenges in modeling complex RNA dynamics, our work demonstrates that MD simulation with a polarizable force field is valuable for understanding aptamer-fluorogen binding and potentially designing new aptamers or fluorogens with better performance.