Journal of Computational Chemistry

Hehre, Thomas; Klunzinger, Philip E.; Deppmeier, Bernard; Ohlinger, William; Hehre, Warren

doi: 10.1002/jcc.70016pmid: 39757343

A correction to the MMFF molecular mechanics model, based on a neural network trained to reproduce conformer energy differences obtained from ωB97X‐V/6‐311+G(2df,2p)[6‐311G*]//MMFF calculations is described. It is supported for molecules containing H, C, N, O, F, S, Cl, and Br. The correction adds only slightly to the cost of MMFF, and the resulting corrected model is several orders of magnitude faster than ωB97X‐V/6‐311+G(2df,2p)[6‐311G*]. It properly identifies the lowest energy conformer for 82% of the molecules in a test set of flexible organic molecules (3553 total conformers), compared with 38% for MMFF. While the corrected MMFF model cannot be expected to provide sufficiently accurate Boltzmann weights for use in spectra and property calculations on flexible molecules, it is able to reduce the number of “reasonable” conformers that need to be passed on to more rigorous computational models, that can.

Nottoli, Tommaso; Bondanza, Mattia; Lipparini, Filippo; Mennucci, Benedetta

doi: 10.1002/jcc.27550pmid: 39718467

We present a polarizable embedding quantum mechanics/molecular mechanics (QM/MM) framework for ground‐ and excited‐state Complete Active Space Self‐Consistent Field (CASSCF) calculations on molecules within complex environments, such as biological systems. These environments are modeled using the AMOEBA polarizable force field. This approach is implemented by integrating the OpenMMPol library with the CFour quantum chemistry software suite. The implementation supports both single‐point energy evaluations and geometry optimizations, facilitated by the availability of analytical gradients. We demonstrate the methodology by applying it to two distinct photoreceptors, exploring the impact of the protein environment on the structural and photophysical properties of their embedded chromophores.

Pomogaeva, Anna V.; Lisovenko, Anna S.; Timoshkin, Alexey Y.

doi: 10.1002/jcc.27507pmid: 39311721

Formation of molecular complexes and subsequent heterolytic halogen‐halogen bond splitting upon reactions of molecular Cl2 with nitrogen‐containing Lewis bases (LB) are computationally studied at M06‐2X/def2‐TZVPD and for selected compounds at CCSD(T)/aug‐cc‐pvtz//CCSD/aug‐cc‐pvtz levels of theory. Obtained results are compared with data for ICl and I2 molecules. Reaction pathways indicate, that in case of Cl2∙LB complexes the activation energies for the heterolytic Cl‐Cl bond splitting are lower than the activation energies of the homolytic splitting of Cl2 molecule into chlorine radicals. The heterolytic halogen splitting of molecular complexes of X2∙Py with formation of [XPy2]+…X3− contact ion pairs in the gas phase is slightly endothermic in case of Cl2 and I2, but slightly exothermic in the case of ICl. Formation of {[ClPy2]+…Cl3−}2 dimers makes the overall process exothermic. Taking into account that polar solvents favor ionic species, generation of donor‐stabilized Cl+ in the presence of the Lewis bases is expected to be favorable. Thus, in polar solvents the oxidation pathway via donor‐stabilized Cl+ species is viable alternative to the homolytic Cl‐Cl bond breaking.

Liu, Ruichen; Wang, Li; Zhang, Xiangwen; Li, Guozhu

doi: 10.1002/jcc.27527pmid: 39679975

In this work, an open‐source, versatile, and flexible code named Groupy is present for calculating various molecular properties and preparing input files of molecular simulation software such as Gaussian. This code requires only SMILES as input, but can output many new useful data and files in multiple formats. The output information is clear and easy to read. The tips to the users are very detailed and easy to follow when using. Message passing interface (MPI) parallelization is supported to reduce computing time when the properties of a large number of molecules are calculated. Groupy not only supports the calculation of molecular properties using the traditional group contribution method, but also directly outputs the group‐contribution‐style molecular fingerprints for machine learning. The code has strong extensibility, which can be used as an external library to build other programs. We hope that Groupy brings great convenience to both computational and experimental chemists in their daily research. The code of Groupy can be freely obtained at https://github.com/47‐5/Groupy

Panday, Shailesh Kumar; Chakravorty, Arghya; Zhao, Shan; Alexov, Emil

doi: 10.1002/jcc.27496pmid: 39476329

The biomolecules interact with their partners in an aqueous media; thus, their solvation energy is an important thermodynamics quantity. In previous works (J. Chem. Theory Comput. 14(2): 1020–1032), we demonstrated that the Poisson–Boltzmann (PB) approach reproduces solvation energy calculated via thermodynamic integration (TI) protocol if the structures of proteins are kept rigid. However, proteins are not rigid bodies and computing their solvation energy must account for their flexibility. Typically, in the framework of PB calculations, this is done by collecting snapshots from molecular dynamics (MD) simulations, computing their solvation energies, and averaging to obtain the ensemble‐averaged solvation energy, which is computationally demanding. To reduce the computational cost, we have proposed Gaussian/super‐Gaussian‐based methods for the dielectric function that use the atomic packing to deliver smooth dielectric function for the entire computational space, the protein and water phase, which allows the ensemble‐averaged solvation energy to be computed from a single structure. One of the technical difficulties associated with the smooth dielectric function presentation with respect to polar solvation energy is the absence of a dielectric border between the protein and water where induced charges should be positioned. This motivated the present work, where we report a super‐Gaussian regularized Poisson–Boltzmann method and use it for computing the polar solvation energy from single energy minimized structures and assess its ability to reproduce the ensemble‐averaged polar solvation on a dataset of 74 high‐resolution monomeric proteins.

Li, Huixue; Wang, Yvhua; Pan, Sujuan; Wang, Changqing; Liu, Yanzhi; Yuan, Kun; Lv, Lingling; Li, Zhifeng

doi: 10.1002/jcc.27506pmid: 39325015

The photophysical and photochemical properties of the sulfonyl azide‐based fluorescent probe DNS–Az and its reduction product DNS by hydrogen sulfide (H2S) have been investigated theoretically. The calculated results indicated the first excited states of DNS–Az was dark state (oscillator strength less than 0.03) and DNS was bright state (oscillator strength more than 0.1), which determined the predicted radiative rate kr of DNS–Az was much smaller than that of DNS, meanwhile, due to more larger reorganization energy of DNS–Az, its predicted internal conversion rate kic was four times larger than that of DNS; moreover, owing to the effect of heavy atom from sulfur atom in DNS–Az, its predicted intersystem crossing rate kisc was seven times larger than that of DNS, thus the calculated fluorescence quantum yield of DNS–Az was only 2.16% and that of DNS was more than 77.2%, the above factors is the basis for DNS–Az molecule to function as a fluorescent probe. Regarding both DNS‐Az and DNS molecules, their maximum Huang‐Rhys factors, which are less than unity, signify the reliability of 0–0 transitions between their S0 and S1 electronic states. In addition, for DNS, our simulated emission peak of the 0–0 transition is 515 nm, a value that exhibits enhanced accuracy and coherence when compared to the experimental datum of 528 nm. The reaction mechanism of DNS‐Az generating DNS by H2S has been investigated too, according to the potential energy profile, we found that the fluorescent probe firstly protonated, then this organic ion broke down into DNS with the aid of a proton.

Gao, Cai‐Yue; Pei, Bin‐Bin; Li, Si‐Dian

doi: 10.1002/jcc.27483pmid: 39350679

The fluxional nature of halogen bonds (XBs) in small molecular clusters, supramolecules, and molecular crystals has received considerable attention in recent years. In this work, based on extensive density‐functional theory calculations and detailed electrostatic potential (ESP), natural bonding orbital (NBO), non‐covalent interactions‐reduced density gradient (NCI‐RDG), and quantum theory of atoms in molecules (QTAIM) analyses, we unveil the existence of fluxional halogen bonds (FXBs) in a series of linear (IC6F4I)m(OONC6H4NOO)n (m + n = 2–5) complexes of tetrafluorodiiodobenzene with dinitrobenzene which appear to be similar to the previously reported fluxional hydrogen bonds (FHBs) in small water clusters (H2O)n (n = 2–6). The obtained GS⇌TS⇌GS' fluxional mechanisms involve one FXB in the systems which fluctuates reversibly between two linear CI···O XBs in the ground states (GS and GS') via a bifurcated CI  O2N van der Waals interaction in the transition state (TS). The cohesive energies (Ecoh) of these complexes with up to four XBs exhibit an almost perfect linear relationship with the numbers of XBs in the systems, with the average calculated halogen bond energy of Ecoh/XB = 3.48 kcal·mol−1 in the ground states which appears to be about 55% of the average calculated hydrogen bond energy (Ecoh/HB = 6.28 kcal·mol−1) in small water clusters.

Yesylevskyy, Semen

doi: 10.1002/jcc.27536pmid: 39618095

Transition to the memory safe natively compiled programming languages is a major software development trend in recent years, which eliminates memory‐related security exploits, enables a fearless concurrency and parallelization, and drastically improves ergonomics and speed of software development. Modern memory‐safe programing languages, such as Rust, are currently not used for developing molecular modeling and simulation software despite such obvious benefits as faster development cycle, better performance and smaller amount of bugs. This work introduces MolAR—the first memory‐safe library for analysis of MD simulations written in Rust. MolAR is intended to explore the advantages and challenges of implementing molecular analysis software in the memory‐safe natively compiled language and to develop specific memory‐safe abstractions for this kind of software. MolAR demonstrates an excellent performance in benchmarks outperforming popular molecular analysis libraries and tools, which makes it attractive for implementing computationally intensive analysis tasks. MolAR is freely available under Artistic License 2.0 at https://github.com/yesint/molar.

Al‐Jaaidi, Ali; Toldo, Josene M.; Barbatti, Mario

doi: 10.1002/jcc.27547pmid: 39673543

Diketopyrrolopyrroles (DPPs) have attracted attention for their potential applications in organic photovoltaics due to their tunable optical properties and charge‐carrier mobilities. In this study, we investigate the excited‐state dynamics of a DPP dimer using time‐dependent density functional theory (TDDFT) and nonadiabatic molecular dynamics simulations. Our results reveal a near‐barrierless hydrogen migration state intersection that facilitates ultrafast internal conversion with a lifetime of about 400 fs, leading to fluorescence quenching. Electronic density analysis along the relaxation pathway confirms a hydrogen atom transfer mechanism. These findings highlight the critical role of state intersections in the photophysical properties of DPP dimers, providing new insights for the design of functionalized DPP systems aimed at suppressing nonradiative decay for enhanced performance in photovoltaic applications.

Ghysbrecht, Simon; Donati, Luca; Keller, Bettina G.

doi: 10.1002/jcc.27529pmid: 39659054

Modern potential energy surfaces have shifted attention to molecular simulations of chemical reactions. While various methods can estimate rate constants for conformational transitions in molecular dynamics simulations, their applicability to studying chemical reactions remains uncertain due to the high and sharp energy barriers and complex reaction coordinates involved. This study focuses on the thermal cis‐trans isomerization in retinal, employing molecular simulations and comparing rate constant estimates based on one‐dimensional rate theories with those based on sampling transitions and grid‐based models for low‐dimensional collective variable spaces. Even though each individual method to estimate the rate passes its quality tests, the rate constant estimates exhibit considerable disparities. Rate constant estimates based on one‐dimensional reaction coordinates prove challenging to converge, even if the reaction coordinate is optimized. However, consistent estimates of the rate constant are achieved by sampling transitions and by multi‐dimensional grid‐based models.