Journal of Computational Chemistry最新文献

Voltage-dependent anion channel (VDAC) is the primary conduit for regulated passage of ions and metabolites into and out of a mitochondrion. Calculating the solvation free energy for VDAC is crucial for understanding its stability, function, and interactions within the cellular environment. In this article, numerical schemes for computing the total solvation free energy for VDAC—comprising electrostatic, ideal gas, and excess free energies plus the nonpolar energy—are developed based on a nonuniform size modified Poisson–Boltzmann ion channel (nuSMPBIC) finite element solver along with tetrahedral meshes for VDAC proteins. The current mesh generation package is also updated to improve mesh quality and accelerate mesh generation. A VDAC Solvation Free Energy Calculation (VSFEC) package is then created by integrating these schemes with the updated mesh package, the nuSMPBIC finite element package, the PDB2PQR package, and the OPM database, as well as one uniform SMPBIC finite element package and one Poisson–Boltzmann ion channel (PBIC) finite element package. With the VSFEC package, many numerical experiments are made using six VDAC proteins, eight ionic solutions containing up to four ionic species, including ATP⁴⁻ and Ca²⁺, two reference states, different boundary values, and different permittivity constants. The test results underscore the importance of considering nonuniform ionic size effects to explore the varying patterns of the total solvation free energy, and demonstrate the high performance of the VSFEC package for VDAC solvation free energy calculation.

Accurate prediction of physicochemical properties, such as electronic energy, enthalpy, free energy, and average vibrational frequencies, is critical for optimizing lithium-ion battery (LIB) performance. Traditional methods like density functional theory (DFT) are computationally expensive and inefficient for large-scale screening. In this study, we apply active learning on top of graph neural networks (GNNs) to efficiently predict these properties. By focusing on uncertain data points, active learning reduces training data size while maintaining high accuracy. Applied to the LIBE and MPcules datasets, the model achieved an R-squared (R²) values of 0.9977 with a mean absolute error (MAE) of 9.66 Ha for electronic energy and an R² values of 0.957 with an MAE of 13.94 cm⁻¹ for average vibrational frequencies. SHapley Additive exPlanations (SHAP) provided insights into key features influencing predictions, such as atomic number and spin multiplicity. This approach enhances both predictive accuracy and model interpretability, offering a scalable solution for LIB electrolyte discovery.

Multi-copper oxidases (MCOs) are enzymes of significant interest in biotechnology due to their efficient catalysis of oxygen reduction to water, making them valuable in sustainable energy production and bio-electrochemical applications. This study employs time-dependent density functional theory (TDDFT) to investigate the electronic structure and spectroscopic properties of the Type 1 (T1) copper site in Azurin, which serves as a model for similar sites in MCOs. Four model complexes of varying complexity were derived from the T1 site, including 3 three-coordinate models and 1 four-coordinate model with axial methionine ligation, to explore the impact of molecular branches and axial coordination. Calculations using ωB97X-D3 functional, def2-TZVP basis set, and conductor-like polarizable continuum model (CPCM) solvation model reproduced key experimental spectral features, with increased model complexity improving agreement, particularly for the ~400 cm⁻¹ band splitting in resonance Raman spectra. This work enhances our understanding of T1 copper sites' electronic properties and spectra, bridging the gap between simplified models and complex proteins. The findings contribute to the interpretation of spectroscopic data in blue copper proteins and may inform future studies on similar biological systems.

We investigate the comprehensive analysis's structural, electronic, optical, and elastic properties of Cs₂NaScX₆ (X = Cl, Br) double perovskites using density functional theory (DFT) implemented by the WIEN2k code. The results show that both compounds are in cubic phases. The calculated tolerance factors show both are stable compounds. The computed optimized lattice parameters are Cs₂NaScX₆ (X = Cl, Br) are 10.72 Å and 12.01 Å, respectively. Employing a modified Becke–Johnson (mBJ) potential electronic nature shows that both compounds are in semiconductor nature, that is, 3.138 eV and 3.977 eV. The calculated elastic constant and perimeters show the Cs₂NaScX₆ (X = Cl, Br) are mechanical stables and also ductile and anisotropic nature. The optical properties described the range of photon energies from 0 to 10 eV, revealing pronounced absorption within the visible spectrum, highlighting their considerable promise for transformative innovations in photovoltaic technology. These double perovskites exhibit superior absorption characteristics compared to their Cs₂NaScX₆ (X = Cl, Br) analogues, thus laying the groundwork for significant advancements in solar energy conversion and photovoltaic applications.

The difficulty of quantum chemically computing vibrational, rotational, and rovibrational reference data via quartic force fields (QFFs) for molecules containing aluminum appears to be alleviated herein using a hybrid approach based upon CCSD(T)-F12b/cc-pCVTZ further corrected for conventional CCSD(T) scalar relativity within the harmonic terms and simple CCSD(T)-F12b/cc-pVTZ for the cubic and quartic terms: the F12-TcCR+TZ QFF. Aluminum containing molecules are theorized to participate in significant chemical processes in both the Earth's upper atmosphere as well as within circumstellar and interstellar media. However, experimental data for the identification of these molecules are limited, showcasing the potential for quantum chemistry to contribute significant amounts of spectral reference data. Unfortunately, current methods for the computation of rovibrational spectral data have been shown previously to exhibit large errors for aluminum-containing molecules. In this work, ten different methods are benchmarked to determine a method to produce experimentally-accurate rovibrational data for theorized aluminum species. Of the benchmarked methods, the explicitly correlated, hybrid F12-TcCR+TZ QFF consistently produces the most accurate results compared to both gas-phase and Ar-matrix experimental data. This method combines the accuracy of the composite F12-TcCR energies along with the numerical stability of non-composite anharmonic terms where the non-rigid nature of aluminum bonding can be sufficiently treated.

Folates comprise a crucial class of biologically active compounds related to folic acid, playing a vital role in numerous enzymatic reactions. One-carbon metabolism, facilitated by the folate cofactor, supports numerous physiological processes, including biosynthesis, amino acid homeostasis, epigenetic maintenance, and redox defense. Folates share a common pterin heterocyclic ring structure capable of undergoing redox reactions and existing in various protonation states. This study aimed to derive molecular mechanics (MM) parameters compatible with the CHARMM36 all-atom additive force field for pterins and biologically important folates, including pterin, biopterin, and folic acid. Three redox forms were considered: oxidized, dihydrofolate, and tetrahydrofolate states. Across all protonation states, a total of 18 folates were parameterized. Partial charges were derived using the CHARMM force field parametrization protocol, based on targeting reference quantum mechanics monohydrate interactions, electrostatic potential, and dipole moment. Bonded terms were parameterized using one-dimensional adiabatic potential energy surface scans, and two-dimensional scans to parametrize in-ring torsions associated with the puckering states of dihydropterin and tetrahydropterin. The quality of the model was demonstrated through simulations of three protein complexes using optimized and initial parameters. These simulations underscored the significantly enhanced performance of the folate model developed in this study compared to the initial model without optimization in reproducing structural properties of folate–protein complexes. Overall, the presented MM model will be valuable for modeling folates in various redox states and serve as a starting point for parameterizing other folate derivatives.

Deuterium isotope effects on interaction energies and geometrical parameters in several H₃O⁺(D₃O⁺)^…ene and H₃O+(D₃O⁺)^…yne complexes, which involve O-H(D)^…π interactions, have been analyzed using the MP2 level of the multi-component molecular orbital method (MC_MP2), which can incorporate the nuclear quantum effects of light nuclei, such as protons and deuterons. The MC_MP2 calculations revealed that D₃O⁺ replacement reduced the interaction energies of the complexes and induced changes in geometrical parameters. In addition, natural energy decomposition analysis (NEDA) revealed a strong correlation between the H/D isotope effects on the H/D^…π distances and on each energy component.