ONIOM meets : efficient, accurate, and robust multi-layer simulations across the periodic table

Pyrolytic Depolymerization of Polyolefins Catalysed by Zirconium-based UiO-66 Metal-Organic Frameworks

Polyolefins such as polyethylenes and polypropylenes are the most-produced plastic waste globally, yet are difficult to convert into useful products due to their unreactivity. Pyrolysis is a practical method for large-scale treatment of mixed, contaminated plastic, allowing for their conversion into industrially-relevant petrochemicals. Metal-organic frameworks (MOFs), despite their tremendous utility in heterogeneous catalysis, have been overlooked for polyolefin depolymerization due to their perceived thermal instabilities and inability of polyethylenes and polypropylenes to penetrate their pores. Herein, we demonstrate the viability of UiO-66 MOFs containing coordinatively-unsaturated zirconium nodes, as effective catalysts for pyrolysis that significantly enhances the yields of valuable liquid and gas hydrocarbons, whilst halving the amounts of residual solids produced. Reactions occur on the Lewis-acidic UiO-66 nodes, without the need for noble metals, and yield aliphatic product distributions distinctly different from the aromatic-rich hydrocarbons that can be obtained from zeolite catalysis. We also demonstrate the first unambiguous characterization of polyolefin penetration into UiO-66 pores at pyrolytic temperatures, allowing access to the abundant Zr-oxo nodes within the MOF interior for efficient C-C cleavage. Our work highlights the potential of MOFs as highly-designable heterogeneous catalysts for depolymerisation of plastics, which can complement conventional catalysts in reactivity.

Extension of the D3 and D4 London dispersion corrections to the full actinides series

Efficient dispersion corrections are an indispensable component of modern density functional theory, semi-empirical quantum mechanical, and even force field methods. In this work, we extend the well established D3 and D4 London dispersion corrections to the full actinides series, francium, and radium. To keep consistency with the existing versions, the original parameterization strategy of the D4 model was only slightly modified. This includes improved reference Hirshfeld atomic partial charges at the ωB97M-V/ma-def-TZVP level to fit the required electronegativity equilibration charge (EEQ) model. In this context, we developed a new actinide data set called AcQM, which covers the most common molecular actinide compound space. Furthermore, the efficient calculation of dynamic polarizabilities that are needed to construct CAB6 dispersion coefficients was implemented into the ORCA program package. The extended models are assessed for the computation of dissociation curves of actinide atoms and ions, geometry optimizations of crystal structure cutouts, gas-phase structures of small uranium compounds, and an example extracted from a small actinide complex protein assembly. We found that the novel parameterizations perform on par with the computationally more demanding density-dependent VV10 dispersion correction. With the presented extension, the excellent cost-accuracy ratio of the D3 and D4 models can now be utilized in various fields of computational actinide chemistry and, e.g., in efficient composite DFT methods such as r2SCAN-3c. They are implemented in our freely available standalone codes (dftd4, s-dftd3) and the D4 version will be also available in the upcoming ORCA 6.0 program package.

Sorting drug conformers in enzyme active sites: the XTB way

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Multilevel Framework for Analysis of Protein Folding Involving Disulfide Bond Formation

In this study, a three-layered multicenter ONIOM approach is implemented to characterize the naive folding pathway of bovine pancreatic trypsin inhibitor (BPTI). Each layer represents a distinct level of theory, where the initial layer, encompassing the entire protein, is modeled by a general all-atom force-field GFN-FF. An intermediate electronic structure layer consisting of three multicenter fragments is introduced with the state-of-the-art semiempirical tight-binding method GFN2-xTB. Higher accuracy, specifically addressing the breaking and formation of the three disulfide bonds, is achieved at the innermost layer using the composite DFT method r2SCAN-3c. Our analysis sheds light on the structural stability of BPTI, particularly the significance of interlinking disulfide bonds. The accuracy and efficiency of the multicenter QM/SQM/MM approach are benchmarked using the oxidative formation of cystine. For the folding pathway of BPTI, relative stabilities are investigated through the calculation of free energy contributions for selected intermediates, focusing on the impact of the disulfide bond. Our results highlight the intricate trade-off between accuracy and computational cost, demonstrating that the multicenter ONIOM approach provides a well-balanced and comprehensive solution to describe electronic structure effects in biomolecular systems. We conclude that multiscale energy landscape exploration provides a robust methodology for the study of intriguing biological targets.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.

Fabrication strategies for chiral self-assembly surface

Chiral self-assembly is the spontaneous organization of individual building blocks from chiral (bio)molecules to macroscopic objects into ordered superstructures. Chiral self-assembly is ubiquitous in nature, such as DNA and proteins, which formed the foundation of biological structures. In addition to chiral (bio) molecules, chiral ordered superstructures constructed by self-assembly have also attracted much attention. Chiral self-assembly usually refers to the process of forming chiral aggregates in an ordered arrangement under various non-covalent bonding such as H-bond, π-π interactions, van der Waals forces (dipole-dipole, electrostatic effects, etc.), and hydrophobic interactions. Chiral assembly involves the spontaneous process, which followed the minimum energy rule. It is essentially an intermolecular interaction force. Self-assembled chiral materials based on chiral recognition in electrochemistry, chiral catalysis, optical sensing, chiral separation, etc. have a broad application potential with the research development of chiral materials in recent years.

A quantum mechanical approach to the oxidation mechanism of graphene oxide (GO)

Elucidation of the reaction mechanism concerning the oxidation above the face and at the edge of a large, oxidized graphene (GO) cluster, namely C80H22O, by molecular oxygen in the first excited state (1Δg) was achieved with quantum mechanical calculations using the ONIOM two-layer method. Oxidation on the face of the aforementioned cluster leads to the formation of an ozone molecule, whereas oxygen molecule attack at the edge of the oxidized graphene surface either launches an ozonide -a five-membered ring species- formation during its outward approach or an 1,3-dioxetane -a four-membered ring species- production along its inward invasion. A detailed examination of the proposed pathways suggests that the ozonide formation should overcome almost one and a half times an adiabatic energy barrier with respect to the ozone production and is strongly exergonic by up to -50.1 kcal mol-1, supporting the experimental findings that both compounds are critically involved in the explosive deoxygenation of GO. On the other hand, the 1,3-dioxetane alternative pathway is considered even more exergonic, although it requires an overwhelming adiabatic energy barrier of 29.8 kcal mol-1 to accomplish its target.