An Efficient Fragment-Based Approach for Predicting the Ground-State Energies and Structures of Large Molecules

Automated property optimization via ab initio O(N) elongation method: Application to (hyper-)polarizability in DNA

An automated property optimization method was developed based on the ab initio O(N) elongation (ELG) method and applied to the optimization of nonlinear optical (NLO) properties in DNA as a first test. The ELG method mimics a polymerization reaction on a computer, and the reaction terminal of a starting cluster is attacked by monomers sequentially to elongate the electronic structure of the system by solving in each step a limited space including the terminal (localized molecular orbitals at the terminal) and monomer. The ELG-finite field (ELG-FF) method for calculating (hyper-)polarizabilities was used as the engine program of the optimization method, and it was found to show linear scaling efficiency while maintaining high computational accuracy for a random sequenced DNA model. Furthermore, the self-consistent field convergence was significantly improved by using the ELG-FF method compared with a conventional method, and it can lead to more feasible NLO property values in the FF treatment. The automated optimization method successfully chose an appropriate base pair from four base pairs (A, T, G, and C) for each elongation step according to an evaluation function. From test optimizations for the first order hyper-polarizability (β) in DNA, a substantial difference was observed depending on optimization conditions between "choose-maximum" (choose a base pair giving the maximum β for each step) and "choose-minimum" (choose a base pair giving the minimum β). In contrast, there was an ambiguous difference between these conditions for optimizing the second order hyper-polarizability (γ) because of the small absolute value of γ and the limitation of numerical differential calculations in the FF method. It can be concluded that the ab initio level property optimization method introduced here can be an effective step towards an advanced computer aided material design method as long as the numerical limitation of the FF method is taken into account.

Factor Analysis of Conformations and NMR Signals of Rotaxanes: AIMD and Polarizable MD Simulations

The interlocked ⟨rod | ring⟩ structures of pseudorotaxanes and [2]rotaxanes are usually maintained by the complex hydrogen-bonding (H-bonding) network between the rod and ring. Ab initio molecular dynamics (AIMD) using generalized energy-based fragmentation approach and polarizable force field (polar FF)-based molecular dynamics (MD) simulations were performed to investigate the conformational changes of mechanically interlocked systems and to obtain the ensemble-averaged NMR chemical shifts. Factor analysis (FA) demonstrates that the ring H-donor (2,6 pyridinedicarboxamide group) plays an important role in the ring-rod recognition. In comparison to the conventional fixed-charge force field, the polarization effect is crucial to account for the H-bonding interactions in supramolecular systems. In the hybrid scheme, the polar FF-based MD simulations are used to generate different initial states for the AIMD simulations, which are able to give better prediction of ensemble-averaged NMR signals for chemically equivalent amide protons. The magnitude of the deshielding shift of NMR signal is correlated with the length of hydrogen bond. The polar FF model with variable charges shows that the dipole-dipole interactions between the flexible diethylene glycol chain of ring and polar solvents induce the upfield shifts of NMR signals of rod H-donors and the directional distribution of the neighboring CH3CN solvents.

Libraries of Extremely Localized Molecular Orbitals. 1. Model Molecules Approximation and Molecular Orbitals Transferability

Despite more and more remarkable computational ab initio results are nowadays continuously obtained for large macromolecular systems, the development of new linear-scaling techniques is still an open and stimulating field of research in theoretical chemistry. In this family of methods, an important role is occupied by those strategies based on the observation that molecules are generally constituted by recurrent functional units with well-defined intrinsic features. In this context, we propose to exploit the notion of extremely localized molecular orbitals (ELMOs) that, due to their strict localization on small molecular fragments (e.g., atoms, bonds, or functional groups), are in principle transferable from one molecule to another. Accordingly, the construction of orbital libraries to almost instantaneously build up approximate wave functions and electron densities of very large systems becomes conceivable. In this work, the ELMOs transferability is further investigated in detail and, furthermore, suitable rules to construct model molecules for the computation of ELMOs to be stored in future databanks are also defined. The obtained results confirm the reliable transferability of the ELMOs and show that electron densities obtained from the transfer of extremely localized molecular orbitals are very close to the corresponding Hartree-Fock ones. These observations prompt us to construct new ELMOs databases that could represent an alternative/complement to the already popular pseudoatoms databanks both for determining electron densities and for refining crystallographic structures of very large molecules.

Pair-Pair Approximation to the Generalized Many-Body Expansion: An Alternative to the Four-Body Expansion for ab Initio Prediction of Protein Energetics via Molecular Fragmentation

We introduce a "pair-pair" approximation to the generalized many-body expansion (pp-GMBE) as an approximation to a traditional four-body expansion, the latter of which is accurate but quickly becomes numerically unstable and ultimately intractable as the number of "bodies" (fragments) increases. The pp-GMBE method achieves a good balance between accuracy and efficiency by defining significant fragment pairs and then fragment quartets. An efficient fragmentation scheme is introduced for proteins such that the largest subsystems contain about 60 atoms. Application of the pp-GMBE method to proteins with as many as 70 amino acids (1142 atoms) reveals that pp-GMBE energies are quite faithful to those obtained when the same level of density functional theory is applied to the entire macromolecule. When combined with embedding charges obtained from natural population analysis, the pp-GMBE approach affords absolute energies that differ by 1-3 kcal/mol from full supersystem results, but it yields conformational energy profiles that are practically indistinguishable from the supersystem calculation at the same level of theory.

Fragment quantum chemical approach to geometry optimization and vibrational spectrum calculation of proteins

Geometry optimization and vibrational spectra (infrared and Raman spectra) calculations of proteins are carried out by a quantum chemical approach using the EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) method (J. Phys. Chem. A, 2013, 117, 7149).

Simulations of molecular self-assembled monolayers on surfaces: packing structures, formation processes and functions tuned by intermolecular and interfacial interactions

Simulations using QM and MM methods guide the rational design of functionalized SAMs on surfaces.

Electrostatically Embedded Many-Body Correlation Energy, with Applications to the Calculation of Accurate Second-Order Møller-Plesset Perturbation Theory Energies for Large Water Clusters

The electrostatically embedded many-body expansion (EE-MB), previously applied to the total electronic energy, is here applied only to the electronic correlation energy (CE), combined with a Hartree-Fock calculation on the entire system. The separate treatment of the Hartree-Fock and correlation energies provides an efficient way to approximate correlation energy for extended systems. We illustrate this here by calculating accurate Møller-Plesset second-order perturbation theory (MP2) energies for a series of clusters ranging in size from 5 to 20 water molecules. In this new method, called EE-MB-CE, where MB is pairwise additive (PA) or three-body (3B), the full Hartree-Fock energy of a system of N monomers is calculated (i.e., the many-body expansion is carried out to the Nth order), while the EE-MB method is used to calculate the correlation energy of the system. We find that not only does this new method lead to better energetics than the original EE-MB method but also that one is able to obtain excellent agreement with full MP2 calculations by considering only a two-body expansion of the correlation energy, leading to a considerable savings in computational time as compared to the three-body expansion. Additionally, we propose the use of a cutoff to further reduce the number of two-body terms that must be calculated, and we show that if a cutoff of 6 Å is used, then one can eliminate up to 44% of the pairs and still calculate energies to within 0.1% of the net interaction energy of the full cluster.

Molecular forces, geometries, and frequencies by systematic molecular fragmentation including embedded charges

The accuracy of energies, energy gradients, and hessians evaluated by systematic molecular fragmentation is examined for a wide range of neutral molecules, zwitterions, and ions. A protocol is established that may employ embedded charges in conjunction with fragmentation to provide accurate evaluation of minimum energy geometries and vibrational frequencies in an automated procedure.

The combined fragmentation and systematic molecular fragmentation methods

Conspectus Chemistry, particularly organic chemistry, is mostly concerned with functional groups: amines, amides, alcohols, ketones, and so forth. This is because the reactivity of molecules can be categorized in terms of the reactions of these functional groups, and by the influence of other adjacent groups in the molecule. These simple truths ought to be reflected in the electronic structure and electronic energy of molecules, as reactivity is determined by electronic structure. However, sophisticated ab initio quantum calculations of the molecular electronic energy usually do not make these truths apparent. In recent years, several computational chemistry groups have discovered methods for estimating the electronic energy as a sum of the energies of small molecular fragments, or small sets of groups. By decomposing molecules into such fragments of adjacent functional groups, researchers can estimate the electronic energy to chemical accuracy; not just qualitative trends, but accurate enough to understand reactivity. In addition, this has the benefit of cutting down on both computational time and cost, as the necessary calculation time increases rapidly with an increasing number of electrons. Even with steady advances in computer technology, progress in the study of large molecules is slow. In this Account, we describe two related "fragmentation" methods for treating molecules, the combined fragmentation method (CFM) and systematic molecular fragmentation (SMF). In addition, we show how we can use the SMF approach to estimate the energy and properties of nonconducting crystals, by fragmenting the periodic crystal structure into relatively small pieces. A large part of this Account is devoted to simple overviews of how the methods work. We also discuss the application of these approaches to calculating reactivity and other useful properties, such as the NMR and vibrational spectra of molecules and crystals. These applications rely on the ability of these fragmentation methods to accurately estimate derivatives of the molecular and crystal energies. Finally, to provide some common applications of CFM and SMF, we present some specific examples of energy calculations for moderately large molecules. For computational chemists, this fragmentation approach represents an important practical advance. It reduces the computer time required to estimate the energies of molecules so dramatically, that accurate calculations of the energies and reactivity of very large organic and biological molecules become feasible.

Fragment quantum mechanical calculation of proteins and its applications

Conspectus The desire to study molecular systems that are much larger than what the current state-of-the-art ab initio or density functional theory methods could handle has naturally led to the development of novel approximate methods, including semiempirical approaches, reduced-scaling methods, and fragmentation methods. The major computational limitation of ab initio methods is the scaling problem, because the cost of ab initio calculation scales nth power or worse with system size. In the past decade, the fragmentation approach based on chemical locality has opened a new door for developing linear-scaling quantum mechanical (QM) methods for large systems and for applications to large molecular systems such as biomolecules. The fragmentation approach is highly attractive from a computational standpoint. First, the ab initio calculation of individual fragments can be conducted almost independently, which makes it suitable for massively parallel computations. Second, the electron properties, such as density and energy, are typically combined in a linear fashion to reproduce those for the entire molecular system, which makes the overall computation scale linearly with the size of the system. In this Account, two fragmentation methods and their applications to macromolecules are described. They are the electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method and the automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) approach. The EE-GMFCC method is developed from the MFCC approach, which was initially used to obtain accurate protein-ligand QM interaction energies. The main idea of the MFCC approach is that a pair of conjugate caps (concaps) is inserted at the location where the subsystem is divided by cutting the chemical bond. In addition, the pair of concaps is fused to form molecular species such that the overcounted effect from added concaps can be properly removed. By introducing the electrostatic embedding field in each fragment calculation and two-body interaction energy correction on top of the MFCC approach, the EE-GMFCC method is capable of accurately reproducing the QM molecular properties (such as the dipole moment, electron density, and electrostatic potential), the total energy, and the electrostatic solvation energy from full system calculations for proteins. On the other hand, the AF-QM/MM method was used for the efficient QM calculation of protein nuclear magnetic resonance (NMR) parameters, including the chemical shift, chemical shift anisotropy tensor, and spin-spin coupling constant. In the AF-QM/MM approach, each amino acid and all the residues in its vicinity are automatically assigned as the QM region through a distance cutoff for each residue-centric QM/MM calculation. Local chemical properties of the central residue can be obtained from individual QM/MM calculations. The AF-QM/MM approach precisely reproduces the NMR chemical shifts of proteins in the gas phase from full system QM calculations. Furthermore, via the incorporation of implicit and explicit solvent models, the protein NMR chemical shifts calculated by the AF-QM/MM method are in excellent agreement with experimental values. The applications of the AF-QM/MM method may also be extended to more general biological systems such as DNA/RNA and protein-ligand complexes.

Generalized energy-based fragmentation approach and its applications to macromolecules and molecular aggregates

Conspectus The generalized energy-based fragmentation (GEBF) approach provides a very simple way of approximately evaluating the ground-state energy or properties of a large system in terms of ground-state energies of various small "electrostatically embedded" subsystems, which can be calculated with any traditional ab initio quantum chemistry (X) method (X = Hartree-Fock, density functional theory, and so on). Due to its excellent parallel efficiency, the GEBF approach at the X theory level (GEBF-X) allows full quantum mechanical (QM) calculations to be accessible for systems with hundreds and even thousands of atoms on ordinary workstations. The implementation of the GEBF approach at various theoretical levels can be easily done with existing quantum chemistry programs. This Account reviews the methodology, implementation, and applications of the GEBF-X approach. This method has been successfully applied to optimize the structures of various large systems including molecular clusters, polypeptides, proteins, and foldamers. Such investigations could allow us to elucidate the origin and nature of the cooperative interaction in secondary structures of long peptides or the driving force of the self-assembly processes of aromatic oligoamides. These GEBF-based QM calculations reveal that the structures and stability of various complex systems result from a subtle balance of many types of noncovalent interactions such as hydrogen bonding and van der Waals interactions. The GEBF-based ab initio molecular dynamics (AIMD) method also allows the investigation of dynamic behaviors of large systems on the order of tens of picoseconds. It was demonstrated that the conformational dynamics of two model peptides predicted by GEBF-based AIMD are noticeably different from those predicted by the classical force field MD method. With the target of extending QM calculations to molecular aggregates in the condensed phase, we have implemented the GEBF-based multilayer hybrid models, which could provide satisfactory descriptions of the binding energies between a solute molecule and its surrounding waters and the chain-length dependence of the conformational changes of oligomers in aqueous solutions. A coarse-grained polarizable molecular mechanics model, furnished with GEBF-X dipole moments of subsystems, exhibits some advantages of treating the electrostatic polarization with reduced computational costs. We anticipate that the GEBF approach will continue to develop with the ultimate goal of studying complicated phenomena at mesoscopic scales and serve as a practical tool to elucidate the structure and dynamics of chemical and biological systems.

Density functional calculations of extended, periodic systems using Coulomb corrected molecular fractionation with conjugated caps method (CC-MFCC)

A consistent DFT based formulation of the order-N molecular fractionation with conjugated caps method in which a molecular system is calculated considering a set of finite fragments, is proposed. Here we apply the method and test its performance on a periodic metal–organic framework system.

Analysis of the Errors in the Electrostatically Embedded Many-Body Expansion of the Energy and the Correlation Energy for Zn and Cd Coordination Complexes with Five and Six Ligands and Use of the Analysis to Develop a Generally Successful Fragmentation Strategy

In the present paper, we apply the electrostatically embedded many-body expansion of the correlation energy (EE-MB-CE) to the calculation of zinc-ligand and cadmium-ligand bond dissociation energies, and we analyze the errors due to various fragmentation schemes in a variety of neutral, positively charged, and negatively charged Zn²⁺ and Cd²⁺ coordination complexes. As a result of the analysis, we are able to present a new, simple, and unambiguous fragmentation strategy. Following this strategy, we show that both methods perform well for zinc-ligand and cadmium-ligand bond dissociation energies for all systems studied in the paper, including a model of the catalytic site of the zinc-bearing anthrax toxin lethal factor (LF), which has garnered substantial attention as a target for drug development. To draw general conclusions we consider ten pentacoordinate and hexacoordinate zinc and cadmium containing coordination complexes, each with 10 or 15 different fragmentation schemes. By analyzing errors, we developed a prescription for the optimal fragmentation strategy. With this scheme, and using MP2 correlation energies as a test, we find that the electrostatically embedded three-body expansion of the correlation energy (EE-3B-CE) method is able to reproduce all 53 conventionally calculated bond energies with an average absolute error of only 0.59 kcal/mol. The paper also presents EE-MB-CE calculations using the CCSD(T) level of theory on an LF model system. With CCSD(T), EE-3B-CE has an average error of 0.30 kcal/mol.

Electrostatically embedded generalized molecular fractionation with conjugate caps method for full quantum mechanical calculation of protein energy

An electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method is developed for efficient linear-scaling quantum mechanical (QM) calculation of protein energy. This approach is based on our previously proposed GMFCC/MM method (He; et al. J. Chem. Phys. 2006, 124, 184703), In this EE-GMFCC scheme, the total energy of protein is calculated by taking a linear combination of the QM energy of the neighboring residues and the two-body QM interaction energy between non-neighboring residues that are spatially in close contact. All the fragment calculations are embedded in a field of point charges representing the remaining protein environment, which is the major improvement over our previous GMFCC/MM approach. Numerical studies are carried out to calculate the total energies of 18 real three-dimensional proteins of up to 1142 atoms using the EE-GMFCC approach at the HF/6-31G* level. The overall mean unsigned error of EE-GMFCC for the 18 proteins is 2.39 kcal/mol with reference to the full system HF/6-31G* energies. The EE-GMFCC approach is also applied for proteins at the levels of the density functional theory (DFT) and second-order many-body perturbation theory (MP2), also showing only a few kcal/mol deviation from the corresponding full system result. The EE-GMFCC method is linear-scaling with a low prefactor, trivially parallel, and can be readily applied to routinely perform structural optimization of proteins and molecular dynamics simulation with high level ab initio electronic structure theories.

How Accurate Can a Local Coupled Cluster Approach Be in Computing the Activation Energies of Late-Transition-Metal-Catalyzed Reactions with Au, Pt, and Ir?

To improve the accuracy of local coupled cluster (LCC) methods in computing activation energies, we propose herein a new computational scheme. Its applications to various types of late-transition-metal-catalyzed reactions involving Au, Pt, and Ir indicate that the new corrective approach for LCC methods can downsize the mean unsigned deviation and maximum deviation, from the CCSD(T)/CBS reference, to about 0.3 and 0.9 kcal/mol. Using this method, we also calibrated the performance of popular density functionals, with respect to the same test set of reactions. It is concluded that the best functional is the general-purpose double hybrid functional B2GP-PLYP. Other well-performing functionals include the "kinetic" functionals M06-2X and BMK, which have a large percentage of HF exchange, and general-purpose functionals like PBE0 and wB97X. Comparatively, general-purpose functionals like PBE0 and TPSSh perform much better than the tested "kinetic" functionals for Pt-/Ir-catalyzed reactions, while the opposite is true for Au-catalyzed reactions. In contrast, wB97X performs more uniformly in these two classes of reactions. These findings hint that even within the scope of late transition metals, different types of reactions may require different types of optimal DFT methods. Empirical dispersion correction of DFT was found to have a small or no effect on the studied reactions barriers.

QM/MM Prediction of the Stark Shift in the Active Site of a Protein

Recent developments in the biophysical characterization of proteins have provided a means of directly measuring electrostatic fields by introducing a probe molecule to the system of interest and interpreting photon absorption in the context of the Stark effect. To fully account for this effect, the development of accurate atomistic models is of paramount importance. However, suitable computational protocols for evaluating Stark shifts in proteins are yet to be established. In this work, we present a comprehensive computational method to predict the change in absorption frequency of a probe functional group as a direct result of a perturbation in its surrounding electrostatic field created by a protein environment, i.e., the Stark shift. We apply the method to human aldose reductase, a key protein enzyme that catalyzes the reduction of monosaccharides. We develop a protocol based on a combination of molecular dynamics and moving-domain QM/MM methods, which achieves quantitative agreement with experiment. We outline the difficulties in predicting localized electrostatic field changes within a protein environment, and by extension the Stark shift, due to a protein site mutation. Furthermore, the combined use of Stark effect spectroscopy and computational modeling is used to predict the protonation state of ionizable residues in the vicinity of the electrostatic probe.