Journal of Chemical Theory and Computation最新文献

Despite the apparent simplicity of water molecules, the kinetics of ice nucleation under natural conditions can be surprisingly intricate. Previous studies have yielded critical nucleation sizes that vary widely due to differences in experimental and computational approaches. In our investigation, we employed all-atom molecular dynamics simulations to explore spontaneously grown and ideal ice nuclei, revealing significant disparities in their kinetics. Notably, nucleation defects challenge the applicability of the classical nucleation theory (CNT) to spontaneously grown ice nuclei. To address this, we propose a generalized nucleation theory that effectively describes the kinetics of ice crystal nucleation across diverse conditions. The kinetics of ice nuclei, as characterized by the "corrected" critical nucleus size, follow a linear law akin to that assumed by CNT. This generalized nucleation theory also provides insights for studying the kinetics of other crystalline materials.

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst-Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

New Delhi metallo-β-lactamase 1 (NDM-1) is an enzyme involved in the drug resistance of many bacteria against most of the widely adopted antibiotics, such as penicillins, cephalosporins, and carbapenems. Consequently, inhibiting NDM-1 swiftly has gained significant interest as a strategy to counteract this bacterial defense mechanism, thereby restoring the effectiveness of antibiotics. Among the inhibitors tested against the enzyme, ebselen (EbSe) showed particularly promising results. This molecule, renowned for its numerous benefits to the human body, targets the enzyme's active site at Cys208 with its selenium atom, facilitating the expulsion of the catalytic zinc ion from the active pocket. Since the inhibitory mechanism of EbSe remains poorly understood, gaining detailed information about it is highly desirable. In the present work, density functional theory calculations and μs-long molecular dynamics simulations are carried out to investigate the reaction mechanism of EbSe with NDM-1, unveiling the structural implications of the inhibition. A large model of the NDM-1 active site is built to investigate the different mechanistic proposals for the Se_EbSe-S_Cys208 bond formation. Deeper insights into Lys211 are also provided to consolidate its role during the inhibition process. Furthermore, the chemical reaction with the ebsulfur (EbS) molecule is also investigated to compare its behavior with that of the periodic relative selenium. Molecular dynamics simulations, besides evidencing the role of the L3 and L10 loops in the occurrence of the inhibition, corroborate the Zn ion release from the active site as a result of the complete disruption of its coordination sphere caused by the creation of the Se_EbSe-S_Cys208 covalent bond.

Given a number of data sets for evaluating the performance of single reference methods for the low-lying excited states of closed-shell molecules, a comprehensive data set for assessing the performance of multireference methods for the low-lying excited states of open-shell systems is still lacking. For this reason, we propose an extension (QUEST#4X) of the radical subset of QUEST#4 (J. Chem. Theory Comput. 2020, 16, 3720) to cover 110 doublet and 39 quartet excited states. Near-exact results obtained by iterative configuration interaction with selection and second-order perturbation correction (iCIPT2) are taken as benchmark to calibrate static-dynamic-static configuration interaction (SDSCI) and static-dynamic-static second-order perturbation theory (SDSPT2), which are minimal MRCI and CI-like perturbation theory, respectively. It is found that SDSCI is very close in accuracy to internally contracted multireference configuration interaction with singles and doubles (ic-MRCISD), although its computational cost is just that of one iteration of the latter. Unlike most variants of MRPT2, SDSPT2 treats single and multiple states in the same way and performs similarly to multistate n-electron valence second-order perturbation theory (MS-NEVPT2). These findings put SDSCI and SDSPT2 on a firm basis.

Exploring the conformational space of molecules remains a challenge of fundamental importance to quantum chemistry: identification of relevant conformers at ambient conditions enables predictive simulations of almost arbitrary properties. Here, we propose a novel approach, called TTConf, to enable conformational sampling of large organic molecules where the combinatorial explosion of possible conformers prevents the use of a brute-force systematic conformer search. We employ tensor trains as a highly efficient dimensionality reduction algorithm, effectively reducing the scaling from exponential to polynomial. In our approach, the conformational search is expressed as global energy minimization task in a high-dimensional grid of dihedral angles. Dimensionality reduction is achieved through a tensor train representation of the high-dimensional torsion space. The performance of the approach is assessed on a variety of drug-like molecules in direct comparison to the state-of-the-art metadynamics based conformer search as implemented in CREST. The comparison shows significant acceleration of up to an order of magnitude, while maintaining comparable accuracy. More importantly, the presented approach allows treatment of larger molecules than typically accessible with metadynamics.

Milestoning is an efficient method for calculating rare event kinetics by constructing a continuous-time kinetic network that connects the reactant and product states. Its accuracy depends on both the quality of the underlying force fields and the trajectory sampling. The sampling error can be effectively controlled through various methods. However, the force fields are often not accurate enough, leading to quantitative discrepancies between simulations and experimental data. To address this challenge, we present a refinement approach for Milestoning network based on the maximum caliber (MaxCal), a general variational principle for dynamical systems, to combine simulations and experimental data. The Kullback-Leibler divergence rate between two Milestoning networks is analytically evaluated and minimized as the loss function. Meanwhile, experimental thermodynamic (equilibrium constants) and kinetic (rate constants) data are incorporated as constraints. The use of MaxCal implies that the refined kinetic network is minimally perturbed from the original one while satisfying the experimental constraints. The refined network is expected to align better with available experimental data. The refinement approach is demonstrated using the binding and unbinding dynamics of a series of six small molecule ligands for the model host system, β-cyclodextrin.

As an approximation to SDSCI [static-dynamic-static (SDS) configuration interaction (CI), a minimal MRCI; Theor. Chem. Acc. 2014, 133, 1481], SDSPT2 [Mol. Phys. 2017, 115, 2696] is a CI-like multireference (MR) second-order perturbation theory (PT2) that treats single and multiple roots in the same manner. This feature permits the use of configuration selection over a large complete active space (CAS) P to end up with a much reduced reference space P̃, which is connected only with a small portion (Q̃₁) of the full first-order interacting space Q connected to P. The most expensive portion of the reduced interacting Q̃₁ space (which involves three active orbitals) can further be truncated by partially bypassing its generation followed by an integral-based cutoff. With marginal loss of accuracy, the selection-truncation procedure, along with an efficient evaluation and storage of internal contraction coefficients, renders SDSPT2s (SDSPT2 with selection) applicable to systems that cannot be handled by the parent CAS-based SDSPT2, as demonstrated by several challenging showcases.

Hubbard-corrected density-functional theory (DFT+U) is widely employed to predict the physical properties of correlated materials; however, reliable predictions can be hindered by the presence of metastable solutions in the DFT+U calculations. This issue stems from the orbital physics inherent in DFT+U. To address this, we propose a method to circumvent metastable states by applying a random orbital-dependent local perturbation to the localized orbitals. This perturbation lifts the orbital degeneracy within the corrective functional of DFT+U, ensuring that the system converges to a low-energy state. We validate this approach by comparing it with results obtained using an occupation matrix control scheme in several test cases, including PuO₂, UO₂, β-Pu₂O₃, and NiO.

Determining the energetics of triplet electronic states of nucleobases in the biological macromolecular environment of nucleic acids is essential for an accurate description of the mechanism of photosensitization and the design of drugs for cancer treatment. In this work, we aim at developing a methodological approach to obtain accurate free energies of triplets in DNA beyond the state of the art, able to reproduce the decrease of triplet energies measured experimentally for T in DNA (270 kJ/mol) vs in the isolated nucleotide in aqueous solution (310 kJ/mol). For such purposes, we adapt the free energy perturbation method to compute the free energy related to the transformation of a pure singlet state into a pure triplet state via "alchemical" intermediates with mixed singlet-triplet nature. By this means, standard deviation errors are only a few kJ/mol, contrary to the large errors of tenths of kJ/mol obtained by averaging the singlet and triplet energies derived from molecular dynamics simulations. The reduced statistical errors obtained by the free energy perturbation approach allow us to rationalize with confidence the triplet stabilization observed experimentally when comparing the thymine nucleotide and thymine in DNA. Spin polarization rather than excimer interactions between the π-stacked nucleobases originates the lower values of the triplet energies in DNA. The developed approach implemented in QM³ shall be useful for determining free energies of triplets and other states like ionic or charge separation states in any other macromolecular system with impact in biomedicine and materials science.

Computer-aided drug discovery (CADD) utilizes computational methods to accelerate the identification and optimization of potential drug candidates. Free energy perturbation (FEP) and thermodynamic integration (TI) play a critical role in predicting differences in protein binding affinities between drug molecules. Here, we implement SPONGE-FEP, which incorporates selective integrated tempering sampling (SITS) to enhance sampling efficiency and contains an automated workflow for relative binding free energy (RBFE) calculations. We first provide an overview of the workflow, which encompasses the generation of a perturbation map, alchemical free energy calculations, and cycle closure analysis. Two case studies were then performed to demonstrate the enhanced sampling of conformational states of ligands and proteins during the alchemical transformation process. The results show that the refined SITS method in SPONGE-FEP can significantly improve the sampling efficiency of rare events and the performance of RBFE predictions. Three series of comparative RBFE tests were conducted to demonstrate the accuracy of SPONGE-FEP, which is comparable to FEP+, using an average computation time of 4 h for a pair of ligands on an A100 GPU device.