An implicit solvent model for SCC-DFTB with Charge-Dependent Radii

Exploring Molecular Energy Landscapes by Coupling the DFTB Potential with a Tree-Based Stochastic Algorithm: Investigation of the Conformational Diversity of Phthalates

Exploring the global energy landscape of relatively large molecules at the quantum level is a challenging problem. In this work, we report the coupling of a nonredundant conformational space exploration method, namely, the robotics-inspired iterative global exploration and local optimization (IGLOO) algorithm, with the quantum-chemical density functional tight binding (DFTB) potential. The application of this fast and efficient computational approach to three close-sized molecules of the phthalate family (DBP, BBP, and DEHP) showed that they present different conformational landscapes. These differences have been rationalized by making use of descriptors based on distances and dihedral angles. Coulomb interactions, steric hindrance, and dispersive interactions have been found to drive the geometric properties. A strong correlation has been evidenced between the two dihedral angles describing the side-chain orientation of the phthalate molecules. Our approach identifies low-energy minima without prior knowledge of the potential energy surface, paving the way for future investigations into transition paths and states.

Improving Quantum Chemical Solvation Models by Dynamic Radii Adjustment for Continuum Solvation (DRACO)

We present the Dynamic Radii Adjustment for COntinuum solvation (DRACO) approach, which employs precomputed atomic partial charges and coordination numbers of the solute atoms to improve the solute cavity. As such, DRACO is compatible with major solvation models, improving their performance significantly and robustly at virtually no extra cost, especially for charged solutes. Combined with the purely electrostatic CPCM and COSMO models, DRACO reduces the mean absolute deviation (MAD) of the solvation free energy by up to 4.5 kcal mol-1 (67%) for a large data set of polar and ionic solutes. Even in combination with the highly empirical universal solvation model (SMD), DRACO substantially reduces the MAD for charged solutes by up to 1.5 kcal mol-1 (39%), while neutral solutes are slightly improved (0.2 kcal mol-1 or 16%). We present an interface of DRACO with two computationally efficient atomic charge models that enables fully automated, out-of-the-box calculations with the widely used program packages Orca and TurboMole.

Self-Consistent-Charge Density-Functional Tight-Binding Parameters for Modeling an All-Solid-State Lithium Battery

All-solid-state lithium-ion batteries have been a promising solution for next-generation energy storage due to their safety and potentially high energy density. In this work, we developed a density-functional tight-binding (DFTB) parameter set for modeling solid-state lithium batteries, focusing on the band alignment at electrolyte/electrode interfaces. Despite DFTB being widely applied in the simulation of large-scale systems, parametrization is usually done for single materials, and less attention is paid to band alignment among multiple materials. Band offsets at the electrolyte/electrode interfaces are key quantities determining the performance. Here, an automated global optimization method based on DFTB confinement potentials of all elements is developed, while the band offsets between electrodes and electrolytes are introduced as constraints during the optimization. The parameter set is applied to model an all-solid-state Li/Li₂PO₂N/LiCoO₂ battery, and its electronic structure shows a good agreement with that from density-functional theory (DFT) calculations.

Eliminating Transition State Calculations for Faster and More Accurate Reactivity Prediction in Sulfa-Michael Additions Relevant to Human Health and the Environment

Fast and accurate computational approaches to predicting reactivity in sulfa-Michael additions are required for high-throughput screening in toxicology (e.g., predicting excess aquatic toxicity and skin sensitization), chemical synthesis, covalent drug design (e.g., targeting cysteine), and data set generation for machine learning. The kinetic glutathione chemoassay is a time-consuming in chemico method used to extract kinetic data in the form of log(k _GSH) for organic electrophiles. In this work, we use density functional theory to compare the use of transition states (TSs) and enolate intermediate structures following C-S bond formation in the prediction of log(k _GSH) for a diverse group of 1,4 Michael acceptors. Despite the widespread use of transition state calculations in the literature to predict sulfa-Michael reactivity, we observe that intermediate structures show much better performance for the prediction of log(k _GSH), are faster to calculate, and easier to obtain than TSs. Furthermore, we show how linear combinations of atomic charges from the isolated Michael acceptors can further improve predictions, even when using inexpensive semiempirical quantum chemistry methods. Our models can be used widely in the chemical sciences (e.g., in the prediction of toxicity relevant to the environment and human health, synthesis planning, and the design of cysteine-targeting covalent inhibitors), and represent a low-cost, sustainable approach to reactivity assessment.

Robust and Efficient Implicit Solvation Model for Fast Semiempirical Methods

We present a robust and efficient method to implicitly account for solvation effects in modern semiempirical quantum mechanics and force fields. A computationally efficient yet accurate solvation model based on the analytical linearized Poisson-Boltzmann (ALPB) model is parameterized for the extended tight binding (xTB) and density functional tight binding (DFTB) methods as well as for the recently proposed GFN-FF general force field. The proposed methods perform well over a broad range of systems and applications, from conformational energies over transition-metal complexes to large supramolecular association reactions of charged species. For hydration free energies of small molecules, GFN1-xTB(ALPB) is reaching the accuracy of sophisticated explicitly solvated approaches, with a mean absolute deviation of only 1.4 kcal/mol compared to the experiment. Logarithmic octanol-water partition coefficients (log K_ow) are computed with a mean absolute deviation of about 0.65 using GFN2-xTB(ALPB) compared to experimental values indicating a consistent description of differential solvent effects. Overall, more than twenty solvents for each of the six semiempirical methods are parameterized and tested. They are readily available in the xtb and dftb+ programs for diverse computational applications.

Docking Paradigm in Drug Design

Docking is in demand for the rational computer aided structure based drug design. A review of docking methods and programs is presented. Different types of docking programs are described. They include docking of non-covalent small ligands, protein-protein docking, supercomputer docking, quantum docking, the new generation of docking programs and the application of docking for covalent inhibitors discovery. Taking into account the threat of COVID-19, we present here a short review of docking applications to the discovery of inhibitors of SARS-CoV and SARS-CoV-2 target proteins, including our own result of the search for inhibitors of SARS-CoV-2 main protease using docking and quantum chemical post-processing. The conclusion is made that docking is extremely important in the fight against COVID-19 during the process of development of antivirus drugs having a direct action on SARS-CoV-2 target proteins.

Adventures in DFTB: Toward an Automatic Parameterization Scheme

As we push forward on understanding the fate of chemicals in the environment, we need a method that will allow for the simulation of the inherent heterogeneity. Density functional tight binding (DFTB) is a methodology that allows for a detailed electronic description and would be ideal for this problem. While many parameters can be derived directly from DFT, empirical parameters still exist in the confinement and repulsion potentials. In this manuscript, we examine these potentials and present solutions that will minimize the degree of empiricism. Our results show that it is possible to construct confinement potentials from examining the atomic radial wavefunctions. Moreover, we found that the heterogeneous repulsion potentials can be derived from using only homogeneous repulsion curves.

Editing Domain Motions Preorganize the Synthetic Active Site of Prolyl-tRNA Synthetase

Prolyl-tRNA synthetases (ProRSs) catalyze the covalent attachment of proline onto cognate tRNAs, an indispensable step for protein synthesis in all living organisms. ProRSs are modular enzymes and the "prokaryotic-like" ProRSs are distinguished from "eukaryotic-like" ProRSs by the presence of an editing domain (INS) inserted between motifs 2 and 3 of the main catalytic domain. Earlier studies suggested the presence of coupled-domain dynamics could contribute to catalysis; however, the role that the distal, highly mobile INS domain plays in catalysis at the synthetic active site is not completely understood. In the present study, a combination of theoretical and experimental approaches has been used to elucidate the precise role of INS domain dynamics. Quantum mechanical/molecular mechanical simulations were carried out to model catalytic Pro-AMP formation by Enterococcus faecalis ProRS. The energetics of the adenylate formation by the wild-type enzyme was computed and contrasted with variants containing active site mutations, as well as a deletion mutant lacking the INS domain. The combined results revealed that two distinct types of dynamics contribute to the enzyme's catalytic power. One set of motions is intrinsic to the INS domain and leads to conformational preorganization that is essential for catalysis. A second type of motion, stemming from the electrostatic reorganization of active site residues, impacts the height and width of the energy profile and has a critical role in fine tuning the substrate orientation to facilitate reactive collisions. Thus, motions in a distal domain can preorganize the active site of an enzyme to optimize catalysis.

Benchmarking of Semiempirical Quantum-Mechanical Methods on Systems Relevant to Computer-Aided Drug Design

The semiempirical quantum mechanical (SQM) methods used in drug design are commonly parametrized and tested on data sets of systems that may not be representative models for drug-biomolecule interactions in terms of both size and chemical composition. This is addressed here with a new benchmark data set, PLF547, derived from protein-ligand complexes, consisting of complexes of ligands with protein fragments (such as amino-acid side chains), with interaction energies based on MP2-F12 and DLPNO-CCSD(T) calculations. From these, composite benchmark interaction energies are also built for complexes of the ligand with the complete active site of the protein (PLA15 data set). These data sets are used to test multiple SQM methods with corrections for noncovalent interactions; the role of the solvation model in the calculations is tested as well.

Analysis of Density Functional Tight Binding with Natural Bonding Orbitals

The description of chemical bonding by the density functional tight binding (DFTB) model is analyzed using natural bonding orbitals (NBOs) and compared to results from density functional theory (B3LYP/aug-cc-pVTZ) calculations. Several molecular systems have been chosen to represent fairly diverse bonding scenarios that include standard covalent bonds, hypervalent interactions, multicenter bonds, metal-ligand interactions (with and without the pseudo-Jahn-Teller effect), and through-space donor-acceptor interactions. Overall, the results suggest that DFTB3/3OB provides physically sound descriptions for the different bonding scenarios analyzed here, as reflected by the general agreement between DFTB3 and B3LYP NBO properties, such as the nature of the NBOs, the magnitudes of natural charges and bond orders, and the dominant donor-acceptor interactions. The degree of ligand-to-metal charge transfer and the ionic nature of pentavalent phosphate are overestimated, likely reflecting the minimal-basis nature of DFTB3/3OB. Moreover, certain orbital interactions, such as geminal interactions, are observed to be grossly overestimated by DFTB3 for hypervalent phosphate and several transition metal compounds that involve copper and nickel. The study indicates that results from NBO analysis can be instructive for identifying electronic structure descriptions at the approximate quantum-mechanical level that require improvement and thus for guiding the systematic improvement of these methods.

Atomic Radius and Charge Parameter Uncertainty in Biomolecular Solvation Energy Calculations

Atomic radii and charges are two major parameters used in implicit solvent electrostatics and energy calculations. The optimization problem for charges and radii is underdetermined, leading to uncertainty in the values of these parameters and in the results of solvation energy calculations using these parameters. This paper presents a new method for quantifying this uncertainty in implicit solvation calculations of small molecules using surrogate models based on generalized polynomial chaos (gPC) expansions. There are relatively few atom types used to specify radii parameters in implicit solvation calculations; therefore, surrogate models for these low-dimensional spaces could be constructed using least-squares fitting. However, there are many more types of atomic charges; therefore, construction of surrogate models for the charge parameter space requires compressed sensing combined with an iterative rotation method to enhance problem sparsity. We demonstrate the application of the method by presenting results for the uncertainties in small molecule solvation energies based on these approaches. The method presented in this paper is a promising approach for efficiently quantifying uncertainty in a wide range of force field parametrization problems, including those beyond continuum solvation calculations. The intent of this study is to provide a way for developers of implicit solvent model parameter sets to understand the sensitivity of their target properties (solvation energy) on underlying choices for solute radius and charge parameters.

Substrate and Transition State Binding in Alkaline Phosphatase Analyzed by Computation of Oxygen Isotope Effects

Enzymes are powerful catalysts, and a thorough understanding of the sources of their catalytic power will facilitate many medical and industrial applications. Here we have studied the catalytic mechanism of alkaline phosphatase (AP), which is one of the most catalytically proficient enzymes known. We have used quantum mechanics calculations and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations to model a variety of isotope effects relevant to the reaction of AP. We have calculated equilibrium isotope effects (EIEs), binding isotope effects (BIEs), and kinetic isotope effects (KIEs) for a range of phosphate mono- and diester substrates. The results agree well with experimental values, but the model for the reaction's transition state (TS) differs from the original interpretation of those experiments. Our model indicates that isotope effects on binding make important contributions to measured KIEs on V/K, which complicated interpretation of the measured values. Our results provide a detailed interpretation of the measured isotope effects and make predictions that can test the proposed model. The model indicates that the substrate is deformed in the ground state (GS) of the reaction and partially resembles the TS. The highly preorganized active site preferentially binds conformations that resemble the TS and not the GS, which induces the substrate to adapt to the enzyme, rather than the other way around-as with classic "induced fit" models. The preferential stabilization of the TS over the GS is what lowers the barrier to the chemical step.

Origin of Asymmetric Solvation Effects for Ions in Water and Organic Solvents Investigated Using Molecular Dynamics Simulations: The Swain Acity-Basity Scale Revisited

The asymmetric solvation of ions can be defined as the tendency of a solvent to preferentially solvate anions over cations or cations over anions, at identical ionic charge magnitudes and effective sizes. Taking water as a reference, these effects are quantified experimentally for many solvents by the relative acity (A) and basity (B) parameters of the Swain scale. The goal of the present study is to investigate the asymmetric solvation of ions using molecular dynamics simulations, and to connect the results to this empirical scale. To this purpose, the charging free energies of alkali and halide ions, and of their hypothetical oppositely charged counterparts, are calculated in a variety of solvents. In a first set of calculations, artificial solvent models are considered that present either a charge or a shape asymmetry at the molecular level. The solvation asymmetry, probed by the difference in charging free energy between the two oppositely charged ions, is found to encompass a term quadratic in the ion charge, related to the different solvation structures around the anion and cation, and a term linear in the ion charge, related to the solvation structure around the uncharged ion-sized cavity. For these simple solvent models, the two terms are systematically counteracting each other, and it is argued that only the quadratic term should be retained when comparing the results of simulations involving physical solvents to experimental data. In a second set of calculations, 16 physical solvents are considered. The theoretical estimates for the acity A are found to correlate very well with the Swain parameters, whereas the correlation for B is very poor. Based on this observation, the Swain scale is reformulated into a new scale involving an asymmetry parameter Σ, positive for acitic solvents and negative for basitic ones, and a polarity parameter Π. This revised scale has the same predictive power as the original scale, but it characterizes asymmetry in an absolute sense, the atomistic simulations playing the role of an extra-thermodynamic assumption, and is optimally compatible with the simulation results. Considering the 55 solvents in the Swain set, it is observed that a moderate basity (Σ between -0.9 and -0.3, related to electronic polarization) represents the baseline for most solvents, while a highly variable acity (Σ between 0.0 and 3.0, related to hydrogen-bond donor capacity modulated by inductive effects) represents a landmark of protic solvents.

VR-SCOSMO: A smooth conductor-like screening model with charge-dependent radii for modeling chemical reactions

To better represent the solvation effects observed along reaction pathways, and of ionic species in general, a charge-dependent variable-radii smooth conductor-like screening model (VR-SCOSMO) is developed. This model is implemented and parameterized with a third order density-functional tight binding quantum model, DFTB3/3OB-OPhyd, a quantum method which was developed for organic and biological compounds, utilizing a specific parameterization for phosphate hydrolysis reactions. Unlike most other applications with the DFTB3/3OB model, an auxiliary set of atomic multipoles is constructed from the underlying DFTB3 density matrix which is used to interact the solute with the solvent response surface. The resulting method is variational, produces smooth energies, and has analytic gradients. As a baseline, a conventional SCOSMO model with fixed radii is also parameterized. The SCOSMO and VR-SCOSMO models shown have comparable accuracy in reproducing neutral-molecule absolute solvation free energies; however, the VR-SCOSMO model is shown to reduce the mean unsigned errors (MUEs) of ionic compounds by half (about 2-3 kcal/mol). The VR-SCOSMO model presents similar accuracy as a charge-dependent Poisson-Boltzmann model introduced by Hou et al. [J. Chem. Theory Comput. 6, 2303 (2010)]. VR-SCOSMO is then used to examine the hydrolysis of trimethylphosphate and seven other phosphoryl transesterification reactions with different leaving groups. Two-dimensional energy landscapes are constructed for these reactions and calculated barriers are compared to those obtained from ab initio polarizable continuum calculations and experiment. Results of the VR-SCOSMO model are in good agreement in both cases, capturing the rate-limiting reaction barrier and the nature of the transition state.

Proton transfer pathways, energy landscape, and kinetics in creatine-water systems

We study the exchange processes of the metabolite creatine, which is present in both tumorous and normal tissues and has NH2 and NH groups that can transfer protons to water. Creatine produces chemical exchange saturation transfer (CEST) contrast in magnetic resonance imaging (MRI). The proton transfer pathway from zwitterionic creatine to water is examined using a kinetic transition network constructed from the discrete path sampling approach and an approximate quantum-chemical energy function, employing the self-consistent-charge density-functional tight-binding (SCC-DFTB) method. The resulting potential energy surface is visualized by constructing disconnectivity graphs. The energy landscape consists of two distinct regions corresponding to the zwitterionic creatine structures and deprotonated creatine. The activation energy that characterizes the proton transfer from the creatine NH2 group to water was determined from an Arrhenius fit of rate constants as a function of temperature, obtained from harmonic transition state theory. The result is in reasonable agreement with values obtained in water exchange spectroscopy (WEX) experiments.

Field-SEA: a model for computing the solvation free energies of nonpolar, polar, and charged solutes in water

Previous work describes a computational solvation model called semi-explicit assembly (SEA). The SEA water model computes the free energies of solvation of nonpolar and polar solutes in water with good efficiency and accuracy. However, SEA gives systematic errors in the solvation free energies of ions and charged solutes. Here, we describe field-SEA, an improved treatment that gives accurate solvation free energies of charged solutes, including monatomic and polyatomic ions and model dipeptides, as well as nonpolar and polar molecules. Field-SEA is computationally inexpensive for a given solute because explicit-solvent model simulations are relegated to a precomputation step and because it represents solvating waters in terms of a solute’s free-energy field. In essence, field-SEA approximates the physics of explicit-model simulations within a computationally efficient framework. A key finding is that an atom’s solvation shell inherits characteristics of a neighboring atom, especially strongly charged neighbors. Field-SEA may be useful where there is a need for solvation free-energy computations that are faster than explicit-solvent simulations and more accurate than traditional implicit-solvent simulations for a wide range of solutes.

Stabilization of different types of transition states in a single enzyme active site: QM/MM analysis of enzymes in the alkaline phosphatase superfamily

The first step for the hydrolysis of a phosphate monoester (pNPP(2-)) in enzymes of the alkaline phosphatase (AP) superfamily, R166S AP and wild-type NPP, is studied using QM/MM simulations based on an approximate density functional theory (SCC-DFTBPR) and a recently introduced QM/MM interaction Hamiltonian. The calculations suggest that similar loose transition states are involved in both enzymes, despite the fact that phosphate monoesters are the cognate substrates for AP but promiscuous substrates for NPP. The computed loose transition states are clearly different from the more synchronous ones previously calculated for diester reactions in the same AP enzymes. Therefore, our results explicitly support the proposal that AP enzymes are able to recognize and stabilize different types of transition states in a single active site. Analysis of the structural features of computed transition states indicates that the plastic nature of the bimetallic site plays a minor role in accommodating multiple types of transition states and that the high degree of solvent accessibility of the AP active site also contributes to its ability to stabilize diverse transition-state structures without the need of causing large structural distortions of the bimetallic motif. The binding mode of the leaving group in the transition state highlights that vanadate may not always be an ideal transition state analog for loose phosphoryl transfer transition states.

A modified QM/MM Hamiltonian with the Self-Consistent-Charge Density-Functional-Tight-Binding Theory for highly charged QM regions

To improve the description of electrostatic interaction between QM and MM atoms when the QM is SCC-DFTB, we adopt a Klopman-Ohno (KO) functional form which considers the finite size of the QM and MM charge distributions. Compared to the original implementation that used a simple Coulombic interaction between QM Mulliken and MM point charges, the KO based QM/MM scheme takes charge penetration effect into consideration and therefore significantly improves the description of QM/MM interaction at short range, especially when the QM region is highly charged. To be consistent with the third-order formulation of SCC-DFTB, the Hubbard parameter in the KO functional is dependent on the QM charge. As a result, the effective size of the QM charge distribution naturally adjusts as the QM region undergoes chemical transformations, making the KO based QM/MM scheme particularly attractive for describing chemical reactions in the condensed phase. Together with the van der Waals parameters for the QM atom, the KO based QM/MM model introduces four parameters for each element type. They are fitted here based on microsolvation models of small solutes, focusing on negatively charged molecular ions, for elements O, C, H and P with a specific version of SCC-DFTB (SCC-DFTBPR). Test calculations confirm that the KO based QM/MM scheme significantly improves the interactions between QM and MM atoms over the original point charge based model and it is transferable due to the small number of parameters. The new form of QM/MM Hamiltonian will greatly improve the applicability of SCC-DFTB based QM/MM methods to problems that involve highly charged QM regions, such as enzyme catalyzed phosphoryl transfers.

QM/MM analysis suggests that Alkaline Phosphatase (AP) and nucleotide pyrophosphatase/phosphodiesterase slightly tighten the transition state for phosphate diester hydrolysis relative to solution: implication for catalytic promiscuity in the AP superfamily

Several members of the Alkaline Phosphatase (AP) superfamily exhibit a high level of catalytic proffciency and promiscuity in structurally similar active sites. A thorough characterization of the nature of transition state for different substrates in these enzymes is crucial for understanding the molecular mechanisms that govern those remarkable catalytic properties. In this work, we study the hydrolysis of a phosphate diester, MpNPP(-), in solution, two experimentally well-characterized variants of AP (R166S AP, R166S/E322Y AP) and wild type Nucleotide pyrophosphatase/phosphodiesterase (NPP) by QM/MM calculations in which the QM method is an approximate density functional theory previously parametrized for phosphate hydrolysis (SCC-DFTBPR). The general agreements found between these calculations and available experimental data for both solution and enzymes support the use of SCC-DFTBPR/MM for a semiquantitative analysis of the catalytic mechanism and nature of transition state in AP and NPP. Although phosphate diesters are cognate substrates for NPP but promiscuous substrates for AP, the calculations suggest that their hydrolysis reactions catalyzed by AP and NPP feature similar synchronous transition states that are slightly tighter in nature compared to that in solution, due in part to the geometry of the bimetallic zinc motif. Therefore, this study provides the first direct computational support to the hypothesis that enzymes in the AP superfamily catalyze cognate and promiscuous substrates via similar transition states to those in solution. Our calculations do not support the finding of recent QM/MM studies by López-Canut and co-workers, who suggested that the same diester substrate goes through a much looser transition state in NPP/AP than in solution, a result likely biased by the large structural distortion of the bimetallic zinc site in their simulations. Finally, our calculations for different phosphate diester orientations and phosphorothioate diesters highlight that the interpretation of thio-substitution experiments is not always straightforward.

Silicon Nanocrystal Functionalization: Analytic Fitting of DFTB Parameters

A density functional tight binding (DFTB) scheme has been applied to functionalized silicon nanocrystals. Using an analytic functional representation of DFTB parameters, the scheme has been used to compute the adsorption energies in the organic functionalization of reconstructed Si(100) and H-terminated Si(111) surfaces of hundreds-of-atoms nanocrystals. We adopt an ONIOM(QM:QM') approach that corrects the overbinding of DFTB, obtaining nice agreement with high-level reaction energies and structural configurations.

Advances in implicit models of water solvent to compute conformational free energy and molecular dynamics of proteins at constant pH

Modern implicit solvent models for macromolecular simulations in water-proton bath are considered. The fundamental quantity that implicit models approximate is the solute potential of mean force, which is obtained by averaging over solvent degrees of freedom. The implicit solvent models suggest practical ways to calculate free energies of macromolecular conformations taking into account equilibrium interactions with water solvent and proton bath, while the explicit solvent approach is unable to do that due to the need to account for a large number of solvent degrees of freedom. The most advanced realizations of the implicit continuum models by different research groups are discussed, their accuracy are examined, and some applications of the implicit solvent models to macromolecular modeling, such as free energy calculations, protein folding, and constant pH molecular dynamics are highlighted.