The ONIOM Method and Its Applications

Multiscale calculations reveal new insights into the reaction mechanism between KRASG12C and α, β-unsaturated carbonyl of covalent inhibitors

Utilizing α,β-unsaturated carbonyl group as Michael acceptors to react with thiols represents a successful strategy for developing KRASG12C inhibitors. Despite this, the precise reaction mechanism between KRASG12C and covalent inhibitors remains a subject of debate, primarily due to the absence of an appropriate residue capable of deprotonating the cysteine thiol as a base. To uncover this reaction mechanism, we first discussed the chemical reaction mechanism in solvent conditions via density functional theory (DFT) calculation. Based on this, we then proposed and validated the enzymatic reaction mechanism by employing quantum mechanics/molecular mechanics (QM/MM) calculation. Our QM/MM analysis suggests that, in biological conditions, proton transfer and nucleophilic addition may proceed through a concerted process to form an enolate intermediate, bypassing the need for a base catalyst. This proposed mechanism differs from previous findings. Following the formation of the enolate intermediate, solvent-assisted tautomerization results in the final product. Our calculations indicate that solvent-assisted tautomerization is the rate-limiting step in the catalytic cycle under biological conditions. On the basis of this reaction mechanism, the calculated kinact/ki for two inhibitors is consistent well with the experimental results. Our findings provide new insights into the reaction mechanism between the cysteine of KRASG12C and the covalent inhibitors and may provide valuable information for designing effective covalent inhibitors targeting KRASG12C and other similar targets.

Driving forces and large scale affinity calculations for piperine/γ-cyclodxetrin complexes: Mechanistic insights from umbrella sampling simulation and DFT calculations

Piperine (PiP), a bioactive molecule, exhibits numerous health benefits and is frequently employed as a co-delivery agent with various phytomedicines (e.g., curcumin) to enhance their bioavailability. This is attributed to PiP's inhibitory activity against drug-metabolizing proteins, notably CYP3A4. Nevertheless, PiP encounters solubility challenges addressed in this study using cyclodextrins (CDs). Specifically, γ-CD and its derivatives, Hydroxypropyl-γ-CD (HP-γ-CD), and Octakis (6-O-sulfo)-γ-CD (Octakis-S-γ-CD), were employed to form supramolecular complexes with PiP. The conformational space of the complexes was assessed through 1 μs molecular dynamics simulations and umbrella sampling. Additionally, quantum mechanical calculations using wB97X-D dispersion-corrected DFT functional and 6-311 + G(d,p) basis set were conducted on the complexes to examine the thermodynamics and kinetic stability. Results indicated that Octakis-S-γ-CD exhibits superior host capabilities for PiP, with the most favorable complexation energy (-457.05 kJ/mol), followed by HP-γ-CD (-249.16 kJ/mol). Furthermore, two conformations of the Octakis-S-γ-CD/PiP complex were explored to elucidate the optimal binding orientation of PiP within the binding pocket of Octakis-S-γ-CD. Supramolecular chemistry relies significantly on non-covalent interactions. Therefore, our investigation extensively explores the critical atoms involved in these interactions, elucidating the influence of substituted groups on the stability of inclusion complexes. This comprehensive analysis contributes to emphasizing the γ-CD derivatives with improved host capacity.

Energetic Landscape and Terminal Emitters of Phycobilisome Cores from Quantum Chemical Modeling

Phycobilisomes (PBs) are giant antenna supercomplexes of cyanobacteria that use phycobilin pigments to capture sunlight and transfer the collected energy to membrane-bound photosystems. In the PB core, phycobilins are bound to particular allophycocyanin (APC) proteins. Some phycobilins are thought to be terminal emitters (TEs) with red-shifted fluorescence. However, the precise identification of TEs is still under debate. In this work, we employ multiscale quantum-mechanical calculations to disentangle the excitation energy landscape of PB cores. Using the recent atomistic PB structures from Synechoccoccus PCC 7002 and Synechocystis PCC 6803, we compute the spectral properties of different APC trimers and assign the low-energy pigments. We show that the excitation energy of APC phycobilins is determined by geometric and electrostatic factors and is tuned by the specific protein-protein interactions within the core. Our findings challenge the simple picture of a few red-shifted bilins in the PB core and instead suggest that the red-shifts are established by the entire TE-containing APC trimers. Our work provides a theoretical microscopic basis for the interpretation of energy migration and time-resolved spectroscopy in phycobilisomes.

Tuning the circularly polarized phosphorescence of platinum(II) complexes through a chiral cation strategy

Circularly polarized phosphorescent (CPP) materials, especially chiral platinum(II) complexes, which combine the advantages of both circularly polarized luminescence (CPL) and phosphorescence, show broad potential applications in chiral optoelectronic devices. Developing CPP emitters with both excellent chiroptical properties and high yield is urgently needed. Here, a chiral cation strategy is employed to construct the CPP Pt(II) complexes R/S-ABA·[Pt(ppy)Cl2] and R/S-MBA·[Pt(ppy)Cl2] through a simple one-step reaction with almost 100% yield. The circular dichroism and CPL spectra confirm that the chirality was successfully transferred to the [Pt(ppy)Cl2]- anion. The luminescence asymmetry factors (glum) are +1.4/-1.8 × 10-3 for R/S-ABA·[Pt(ppy)Cl2] and +4.4/-2.8 × 10-3 for R/S-MBA·[Pt(ppy)Cl2]. The stronger chiroptical property of R/S-MBA·[Pt(ppy)Cl2] is attributed to the enhanced chiral structural deformation and better matched electric and magnetic transition dipole moments. This chiral cation strategy is confirmed to efficiently construct CPP Pt(II) complexes, which will accelerate the development of CPP emitters towards commercialization.

β-Lactoglobulin Enhances Clay and Activated Carbon Binding and Protection Properties for Cadmium and Lead

The removal of heavy metals from wastewater remains a challenge due to the limitations of current remediation methods. This study aims to develop multicomponent composites as inexpensive and environmentally friendly sorbents with enhanced capture of cadmium (Cd) and lead (Pb). The composites are based on calcium montmorillonite (CM) and activated carbon (AC) because of their proven effectiveness as sorbents for diverse toxins in environmental settings. In this study, we used a combination of computational and experimental methods to delineate that β-lactoglobulin enhances CM and AC binding and protection properties for Cd and Pb. Modeling and molecular dynamics simulations investigated the formation of material systems formed by CM and AC in complex with β-lactoglobulin and predicted their capacity to bind heavy metal ions at neutral pH conditions. Our simulations suggest that the enhanced binding properties of the material systems are attributed to the presence of several binding pockets formed by β-lactoglobulin for the two heavy metal ions. At neutral pH conditions, divalent Cd and Pb shared comparable binding propensities in all material systems, with the former being consistently higher than the latter. To validate the interactions depicted in simulations, two ecotoxicological models (L. minor and H. vulgaris) were exposed to Cd, Pb, and a mixture of the two. The inclusion of CM-lactoglobulin (β-lactoglobulin amended CM) and AC-lactoglobulin (β-lactoglobulin amended AC) at 0.05-0.2% efficiently and dose-dependently reduced the severe toxicity of metals and increased the growth parameters. This high efficacy of protection shown in the ecotoxicological models may result from the numerous possible interaction pockets of the β-lactoglobulin-amended materials depicted in simulations. The ecotoxicological models support the agreement with computations. This study serves as a proof of concept on how computations in tandem with experiments can be used in the design of multicomponent clay- and carbon-based sorbent amended systems with augmented functionalities for particular toxins.

BhrPETase catalyzed polyethylene terephthalate depolymerization: A quantum mechanics/molecular mechanics approach

Polyethylene terephthalate (PET) is a widely used material in our daily life, particularly in areas such as packaging, fibers, and engineering plastics. However, PET waste can accumulate in the environment and pose a great threat to our ecosystem. Recently enzymatic conversion has emerged as an efficient and green strategy to address the PET crisis. Here, using a theoretical approach combining molecular dynamics simulation and quantum mechanics/molecular mechanics calculations, the depolymerization mechanism of the thermophilic cutinase BhrPETase was fully deciphered. Surprisingly, unlike the previously studied cutinase LCCICCG, our results indicate that the first step, catalytic triad assisted nucleophilic attack, is the rate-determining step. The corresponding Boltzmann weighted average energy barrier is 18.2 kcal/mol. Through extensive comparison between BhrPETase and LCCICCG, we evidence that key features like charge CHis@N1 and angle APET@C1-Ser@O1-His@H1 significantly impact the depolymerization efficiency of BhrPETase. Non-covalent bond interaction and distortion/interaction analysis inform new insights on enzyme engineer and may aid the recycling of enzymatic PET waste. This study will aid the advancement of the plastic bio-recycling economy and promote resource conservation and reuse.

Silicon Analogues of Cyclopropyl Radical Derived from a Highly Stable Cyclic Disilene Compound Featuring a Si-Br Bond

A halogen-substituted cyclic disilene compound, bromocyclotrisilene, Si3Br(Eind)3 (3a), bearing fused-ring bulky Eind (a: R1 = R2 = Et) groups, has been synthesized as an extraordinarily air-stable compound by the reduction of 1,2-dibromodisilene, (Eind)BrSi═SiBr(Eind) (2a), or tribromosilane, (Eind)SiBr3 (1a), with the Mg or Li metal. The X-ray diffraction analysis of 3a showed that the disilene moiety has an almost planar, but slightly trans-bent structure. Even though 3a is quite air-stable both in solutions and in the solid state, its Si-Br bond is reactive under reducing conditions. The further treatment of 3a with the Li metal leads to the formation of room-temperature thermally stable silicon homologues of the cyclopropyl radical, i.e., the cyclotrisilanyl radicals (6a) [6a(syn) and 6a(anti)], via intramolecular C-H bond activation in a transient silicon homologue of the cyclopropenyl radical, i.e., the cyclotrisilenyl radical, [Si3(Eind)3]• (5a). The formation mechanism of 6a from 5a is discussed based on the theoretical calculations. The unique structural and electronic properties of these Si3 three-membered ring species incorporating the Eind groups have been experimentally and theoretically investigated.

Comprehensive Computational Investigation of the Porphyrin-Based COF as a Nanocarrier for Delivering Anti-Cancer Drugs: A Combined MD Simulation and DFT Calculation

As nanomaterials have gained prominence in drug delivery technology, exploring their feasibility through computational methods is beneficial before practical tests. In this study, we aim to evaluate the capability of the porphyrin-based covalent organic framework COF-366 as a nanocarrier for two anticancer drugs, irinotecan (IRI) and doxorubicin (DOX). The optimal binding conformation of the drug molecules on the COF surface was predicted by using molecular docking. Subsequently, molecular dynamic simulation (MD) was performed to assess the adsorption mechanism of drug molecules on the COF in the aqueous environment. The free energy of adsorption for DOX and IRI was estimated to be -20.07 and -23.89 kcal/mol, respectively. The adsorption of both drugs on the COF surface is mainly influenced by the π-π interaction. Furthermore, density functional theory (DFT) calculation, natural bond orbital (NBO), and quantum theory of atoms in molecules (QTAIM) analyses were employed to investigate the structural stability of Drug@COF complexes and gain a detailed understanding of the interaction between them at the molecular level. Based on DFT results, it was found that in addition to π-π interaction, the bis-piperidine-phenylene interaction affects the adsorption of IRI on the COF surface. Moreover, the diffusion behavior of the drug molecule inside the COF pore was simulated using a ten-layer COF. Based on the mean square displacement analysis, the diffusion coefficients of DOX and IRI within the COF pore were calculated to be 108 and 97 um2/s, respectively. This computational study sheds light on how different types of interactions between the drug molecule and COF affect the adsorption and diffusion process. Our findings validated that the porphyrin-based COF-366 can serve as a nanobased platform for delivering DOX and IRI.

Massively Parallel Computational Chemistry with the Super Instruction Architecture and ACES4

The task of developing high-performing parallel software must be made easier and more cost-effective in order to fully exploit existing and emerging large-scale computer systems for the advancement of science. The Super Instruction Architecture (SIA) is a parallel programming platform geared toward applications that need to manage large amounts of data stored in potentially sparse multidimensional arrays during calculations. The SIA platform was originally designed for the quantum chemistry software package ACESIII. More recently, the SIA was reimplemented to overcome the limitations in the original ACESIII program. It has now been successfully employed in the new ACES4 quantum chemistry software package. This paper describes the SIA and ACES4 and illustrates their capabilities with some difficult quantum chemistry open-shell coupled-cluster benchmark calculations.

Exploring the Esterase Catalytic Activity of Minimalist Heptapeptide Amyloid Fibers

This paper investigates the esterase activity of minimalist amyloid fibers composed of short seven-residue peptides, IHIHIHI (IH7) and IHIHIQI (IH7Q), with a particular focus on the role of the sixth residue position within the peptide sequence. Through computational simulations and analyses, we explore the molecular mechanisms underlying catalysis in these amyloid-based enzymes. Contrary to initial hypotheses, our study reveals that the twist angle of the fiber, and thus the catalytic site's environment, is not notably affected by the sixth residue. Instead, the sixth residue interacts with the p-nitrophenylacetate (pNPA) substrate, particularly through its -NO2 group, potentially enhancing catalysis. Quantum mechanics/molecular mechanics (QM/MM) simulations of the reaction mechanism suggest that the polarizing effect of glutamine enhances catalytic activity by forming a stabilizing network of hydrogen bonds with pNPA, leading to lower energy barriers and a more exergonic reaction. Our findings provide valuable insights into the intricate interplay between peptide sequence, structural arrangement, and catalytic function in amyloid-based enzymes, offering potentially valuable information for the design and optimization of biomimetic catalysts.

Theoretical Investigation and Molecular Design: A Series of Tripod-Type Cu(I) Blue Light Thermally Activated Delayed Fluorescence Materials

The photophysical properties and luminescent mechanism of a series of tripod-type Cu(I) complexes in solution and solids were comprehensively investigated through theoretical simulations. From a microscopic perspective, the experimental phenomenon is explained: (1) The intrinsic reason for the quenching of complex 1 in solution was attributed to the significant nonradiative transition caused by structural deformation; (2) In the solid, the reduced ΔEST for complex 2 effectively facilitate reverse intersystem crossing (RISC) and improves its luminescence efficiency; (3) The enhanced performance of complex 3 in solution is attributed to that its stronger steric hindrance is advantageous to decrease not only the ΔEST but also the reorganization energy through intramolecular weak interactions. Based on complex 3, the tert-butyl substituted isomeric complex 4 was designed. Complex 4 further amplifies the advantages of 3 to further promote the RISC to make full use of excitons. Meanwhile, it has an emission wavelength of 462.6 nm, which makes it an excellent candidate for high-efficiency deep-blue TADF materials. This study provides valuable information for obtaining efficient blue phosphorescence and TADF dual-channel luminescent materials.

Gold(III) complexes with chloride and cyanopyridines: Facilitated hydrolysis of nitrile ligand to amide and antibacterial activity

A range of novel simple gold(III) compounds has been synthesized in their monocrystalline form, including two previously unknown chloro-complexes of Au3+ with 2-cyanopyridine or 3-cyanopyridine, respectively. Our investigations have revealed the intricate nature of the reaction between 2-cyanopyridine and tetrachloroauric acid, yielding at least three distinct products. The main product, obtained in high yield, is a salt featuring a tetrachloroauric anion and a pyridinium cation stabilized by a hydrogen bond to a further 2-cyanopyridine molecule. Moreover, we observed the in-situ formation of a 2-cyanopyridine-AuCl3 complex, which undergoes hydrolysis of the nitrile bond to yield a picolinamide-Au(III) complex. The complexes were characterized by IR and Raman spectroscopies, NMR spectroscopy, and single-crystal XRD studies. Additional computational studies were conducted to explain unusual spectral features, the observed disparities in the complexation reactions of the three isomeric cyanopyridine ligands and the distinct reactivity of the complex with 2-cyanopyridine. Based on these studies, we propose a mechanism for the catalyzed hydrolysis of the nitrile bond within the Au(III) complex. Finally, we assessed the antimicrobial efficacy of the synthesized gold(III) complexes against a spectrum of bacteria and fungi.

Computational Methodologies in Synthesis, Preparation and Application of Antimicrobial Polymers, Biomolecules, and Nanocomposites

The design and optimization of antimicrobial materials (polymers, biomolecules, or nanocomposites) can be significantly advanced by computational methodologies like molecular dynamics (MD), which provide insights into the interactions and stability of the antimicrobial agents within the polymer matrix, and machine learning (ML) or design of experiment (DOE), which predicts and optimizes antimicrobial efficacy and material properties. These innovations not only enhance the efficiency of developing antimicrobial polymers but also enable the creation of materials with tailored properties to meet specific application needs, ensuring safety and longevity in their usage. Therefore, this paper will present the computational methodologies employed in the synthesis and application of antimicrobial polymers, biomolecules, and nanocomposites. By leveraging advanced computational techniques such as MD, ML, or DOE, significant advancements in the design and optimization of antimicrobial materials are achieved. A comprehensive review on recent progress, together with highlights of the most relevant methodologies' contributions to state-of-the-art materials science will be discussed, as well as future directions in the field will be foreseen. Finally, future possibilities and opportunities will be derived from the current state-of-the-art methodologies, providing perspectives on the potential evolution of polymer science and engineering of novel materials.

Photolysis of dinotefuran and nitenpyram in water and ice phase: Influence mechanism of temperature over photolysis

Neonicotinoids are widely used pesticides around the world, but the photolysis of neonicotinoids in cold agricultural region are still in blank. This paper aimed to study the influence of cold temperature over photolysis of neonicotinoids. To this end, the photolysis rates and photoproducts of dinotefuran and nitenpyram in water, ice and freeze-thawing condition were determined. Coupled with quantum chemistry calculation, the influence mechanisms of temperature and medium were investigated. The results showed the photolysis rates of neonicotinoids in water condition slightly declined with the lowered temperature due to the photolysis reactions were endothermic reactions. However, the photolysis rates increased by 89.8 %, 59.2 %, 49.4 % and 9.5 % for dinotefuran and nitenpyram in ice and thawing condition, respectively. This phenomenon was posed by the concentration-enhancing effect and change of photo-chemical properties of neonicotinoids in ice condition, which included lowered bond cleavage energy, lowered first excited singlet state energy and expanded light absorption range. The photolysis pathways of the two neonicotinoids did not change in different medium, but the concentration of carboxyl products was relatively higher than that of water condition due to the more amounts of reactive oxygen species in ice medium, which might increase the secondary pollution risk after ice-off in spring due to the higher ecotoxicity to nontarget organism of these photoproducts. The influence of cold temperature and medium change should be considered for the environmental fate and risk assessment of neonicotinoids in cold agricultural region.

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.

Thermo-responsive emission induced by different delocalized excited-states in isomorphous Pd(ii) and Pt(ii) one-dimensional chains

The self-assembly of d8 transition metal complexes is essential for the development of optoelectronic and sensing materials with superior photofunctional properties. However, detailed insight into the electronic delocalization of excited states across multiple molecules, particularly in comparing 5d8 (Pt(ii)) and 4d8 (Pd(ii)) systems, remains ambiguous but important. In this study, we have successfully evaluated the differences in the excited-state delocalization and thermal responses of self-assembled Pt(ii) and Pd(ii) complexes. Although the complexes presented herein, K[M(CN)2(dFppy)]·H2O (M = Pt or Pd, dFppy = 2-(4,6-difluorophenyl)pyridinate), are crystallographically isomorphous with similarly short metal⋯metal contacts, only the Pt(ii) complex exhibited thermal equilibria between delocalized excited states, resulting in a drastic thermochromic luminescence with a red-shift of greater than 100 nm. In contrast, the dimeric localized emission from the Pd(ii) complex showed a significant increase in the quantum yield upon cooling, approaching almost unity.

Functional characterization, structural basis, and protein engineering of a rare flavonoid 2'-O-glycosyltransferase from Scutellaria baicalensis

Glycosylation is an important post-modification reaction in plant secondary metabolism, and contributes to structural diversity of bioactive natural products. In plants, glycosylation is usually catalyzed by UDP-glycosyltransferases. Flavonoid 2'-O-glycosides are rare glycosides. However, no UGTs have been reported, thus far, to specifically catalyze 2'-O-glycosylation of flavonoids. In this work, UGT71AP2 was identified from the medicinal plant Scutellaria baicalensis as the first flavonoid 2'-O-glycosyltransferase. It could preferentially transfer a glycosyl moiety to 2'-hydroxy of at least nine flavonoids to yield six new compounds. Some of the 2'-O-glycosides showed noticeable inhibitory activities against cyclooxygenase 2. The crystal structure of UGT71AP2 (2.15 Å) was solved, and mechanisms of its regio-selectivity was interpreted by pK a calculations, molecular docking, MD simulation, MM/GBSA binding free energy, QM/MM, and hydrogen‒deuterium exchange mass spectrometry analysis. Through structure-guided rational design, we obtained the L138T/V179D/M180T mutant with remarkably enhanced regio-selectivity (the ratio of 7-O-glycosylation byproducts decreased from 48% to 4%) and catalytic efficiency of 2'-O-glycosylation (k cat/K m, 0.23 L/(s·μmol), 12-fold higher than the native). Moreover, UGT71AP2 also possesses moderate UDP-dependent de-glycosylation activity, and is a dual function glycosyltransferase. This work provides an efficient biocatalyst and sets a good example for protein engineering to optimize enzyme catalytic features through rational design.

Modeling Electrochemical Vacancy Regeneration in Single-Walled Carbon Nanotubes

Synthesis-induced defects in single-walled carbon nanotubes (SWCNTs) enable diverse catalytic reactions, but the nature of catalytic intermediates and how active species regeneration occurs are unclear. Using a quantum mechanics/molecular mechanics (QM/MM) hybrid methodology based on density functional theory (DFT) and a classical force-field, we explore the reactivity and electrochemical regeneration of a vacancy defect in a zigzag SWCNT. Our findings indicate that hydrolysis of the defect forms a ketone group on one carbon atom and C-H bonds on two adjacent carbons. Applying an electrochemical potential of ESHE = -0.740 V triggers a proton-coupled electron transfer (PCET), converting the ketone to a hydroxyl group. Further reduction at ESHE = -1.08 V induces another PCET, expelling the hydroxyl as water and forming an active carbon with carbene character that can react with hydrogen peroxide and perchlorate. The hydrogen atoms on neighboring carbons prevent further water dissociation, maintaining the catalytic vacancy.

Importance of Polarizable Embedding for Computing Optical Rotation: The Case of Camphor in Ethanol

Solvation effects on optical rotation are notoriously challenging to model for computational chemistry, as the specific rotatory power of a molecule can vary wildly going from apolar to polar or even protic solvents. To address such a problem, we present a polarizable embedding implementation of an electric and magnetic response property based on density functional theory and the AMOEBA polarizable force field, and apply such an implementation to the study of the optical rotation of camphor in ethanol. By comparing a continuum model, and electrostatic and polarizable embedding QM/MM models, we observe that accounting for the environment's polarization gives rise to not only a different quantitative prediction, in very good agreement with experiments for the QM/AMOEBA model, but also to a very different qualitative picture, with the values of the optical rotation computed along a classical molecular dynamics trajectory with electrostatic embedding being statistically uncorrelated to the ones obtained with the polarizable description.

Pentaphosphorylation via the Anhydride of Dihydrogen Pentametaphosphate: Access to Nucleoside Hexa- and Heptaphosphates and Study of Their Interaction with Ribonuclease A

Pentametaphosphate is the little studied cyclic pentamer of the metaphosphate ion, [PO3]5 5-. We show that the doubly protonated form of this pentamer can be selectively dehydrated to provide the anhydride [P5O14]3- (1). This trianion is the well-defined condensed phosphate component of a novel reagent for attachment of a pentaphosphate chain to biomolecules all in one go. Here, we demonstrate by extending adenosine monophosphate (AMP) and uridine monophosphate (UMP) to their corresponding nucleoside hexaphosphates, while adenosine diphosphate (ADP) and uridine diphosphate (UDP) are phosphate chain-extended to the corresponding nucleoside heptaphosphates. Such constructs are of interest for their potential biological function with respect to RNA-processing enzymes. Thus, we go on to investigate in detail the interaction of the polyanionic constructs with ribonuclease A, a model protein containing a polycationic active site and for which X-ray crystal structures are relatively straightforward to obtain. This work presents a combined experimental and quantum chemical approach to understanding the interactions of RNase A with the new nucleoside hexa- and heptaphosphate constructs.

PyDFT-QMMM: A modular, extensible software framework for DFT-based QM/MM molecular dynamics

PyDFT-QMMM is a Python-based package for performing hybrid quantum mechanics/molecular mechanics (QM/MM) simulations at the density functional level of theory. The program is designed to treat short-range and long-range interactions through user-specified combinations of electrostatic and mechanical embedding procedures within periodic simulation domains, providing necessary interfaces to external quantum chemistry and molecular dynamics software. To enable direct embedding of long-range electrostatics in periodic systems, we have derived and implemented force terms for our previously described QM/MM/PME approach [Pederson and McDaniel, J. Chem. Phys. 156, 174105 (2022)]. Communication with external software packages Psi4 and OpenMM is facilitated through Python application programming interfaces (APIs). The core library contains basic utilities for running QM/MM molecular dynamics simulations, and plug-in entry-points are provided for users to implement custom energy/force calculation and integration routines, within an extensible architecture. The user interacts with PyDFT-QMMM primarily through its Python API, allowing for complex workflow development with Python scripting, for example, interfacing with PLUMED for free energy simulations. We provide benchmarks of forces and energy conservation for the QM/MM/PME and alternative QM/MM electrostatic embedding approaches. We further demonstrate a simple example use case for water solute in a water solvent system, for which radial distribution functions are computed from 100 ps QM/MM simulations; in this example, we highlight how the solvation structure is sensitive to different basis-set choices due to under- or over-polarization of the QM water molecule's electron density.

Modeling solvent effects and convergence of 31P-NMR shielding calculations with COBRAMM

Solvent effects on 31P-NMR parameters for triphenylphosphine oxide and triphenylphosphine in chloroform have been extensively investigated by testing different solvation models. The solvent is described implicitly, mixed implicitly/explicitly, and using full explicit models. Polarizable continuum model (PCM), molecular dynamic (MD) simulations, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations are used to disclose the effects of solute/solvent interactions and, more generally, the role of the embedding in NMR simulations. The results show the beneficial effect of carrying out QM/MM optimizations on top of geometries directly extracted from classical MD simulations, used to ensure representative conformational sampling. The nuclear shielding convergence has been tested against a different number of snapshots and with the inclusion of solvent shells into the QM region. An automated MD//QM/MM//GIAO protocol, implemented in the COBRAMM package, is here proposed and tested on trimethyl phosphite showing that our approach boosts the convergence of nuclear shielding satisfactorily. The present work aims to be a stepping-stone to assess proper QM/MM computational strategies in simulating chemical shifts in non-homogeneous systems like supramolecular and biological systems.

Paving the road towards automated homogeneous catalyst design

In the past decade, computational tools have become integral to catalyst design. They continue to offer significant support to experimental organic synthesis and catalysis researchers aiming for optimal reaction outcomes. More recently, data-driven approaches utilizing machine learning have garnered considerable attention for their expansive capabilities. This Perspective provides an overview of diverse initiatives in the realm of computational catalyst design and introduces our automated tools tailored for high-throughput in silico exploration of the chemical space. While valuable insights are gained through methods for high-throughput in silico exploration and analysis of chemical space, their degree of automation and modularity are key. We argue that the integration of data-driven, automated and modular workflows is key to enhancing homogeneous catalyst design on an unprecedented scale, contributing to the advancement of catalysis research.

Intramolecular bridging strategies to suppress two-phonon Raman spin relaxation in dysprosocenium single-molecule magnets

Dy(III) bis-cyclopentadienyl (Cp) sandwich compounds exhibit extremely strong single-ion magnetic anisotropy which imbues them with magnetic memory effects such as magnetic hysteresis, and has put them at the forefront of high-performance single-molecule magnets (SMMs). Owing to the great success of design principles focused on maximising the anisotropy barrier, ever higher Ueff values have been reported leading to significant slow down of single-phonon Orbach spin relaxation. However, anisotropy-based SMM design has largely ignored two-phonon Raman spin relaxation, which is still limiting the temperatures at which a memory effect can be observed. In this work, we study the suppression of Raman relaxation through covalent bridging of the Cp ligands by alkyl chains, testing the hypothesis that increasing the rigidity of the ligand framework results in a blue shift of low frequency vibrations in the first coordination sphere of the Dy(III) ion. This reshaping of the vibrational low-energy density of states (DOS) results in lower occupation of pseudo-acoustic phonons available to drive Raman relaxation at low temperatures. We simulate Orbach and Raman spin relaxation in a series of zero-, mono-, di- and tri-bridged [Dy(Cpttt)2]+ analogues fully ab initio, using a quantum mechanics (QM)/molecular mechanics (MM) condensed phase embedding protocol in a periodic solvent matrix as a generic and experimentally testable environment model that can include (pseudo-)acoustic phononic degrees of freedom. We show that this approach can simulate magnetic relaxation dynamics in the condensed phase for the existing non-bridged [Dy(Cpttt)2]+ compound with quantitative experimental accuracy. Subsequently, we find a significant slowing down of Raman relaxation can be achieved for the singly-bridged SMM, while the introduction of further bridges leads to faster relaxation. A key result being that we find the two-phonon Raman rates correlate with the purity of the first-excited Kramers doublet in terms of its mJ = ±13/2 content. Even though the bridging design principle is successful at progressively reshaping the low-energy DOS, the introduction of linker atoms in the equatorial plane successively degrades magnetic anisotropy, suggesting the importance of refined design of the linker chemistry. The accuracy of our results emphasises the value of a generic periodic solvent embedding model, such that it permits the modelling of molecular spin dynamics in the condensed phase without knowledge of a crystal structure. This allows the study of hypothetical molecules or aggregates under real-world conditions, which we expect to have utility beyond the field of molecular magnetism.

Nanoscale chemical reaction exploration with a quantum magnifying glass

Nanoscopic systems exhibit diverse molecular substructures by which they facilitate specific functions. Theoretical models of them, which aim at describing, understanding, and predicting these capabilities, are difficult to build. Viable quantum-classical hybrid models come with specific challenges regarding atomistic structure construction and quantum region selection. Moreover, if their dynamics are mapped onto a state-to-state mechanism such as a chemical reaction network, its exhaustive exploration will be impossible due to the combinatorial explosion of the reaction space. Here, we introduce a "quantum magnifying glass" that allows one to interactively manipulate nanoscale structures at the quantum level. The quantum magnifying glass seamlessly combines autonomous model parametrization, ultra-fast quantum mechanical calculations, and automated reaction exploration. It represents an approach to investigate complex reaction sequences in a physically consistent manner with unprecedented effortlessness in real time. We demonstrate these features for reactions in bio-macromolecules and metal-organic frameworks, diverse systems that highlight general applicability.

The development of the QM/MM interface and its application for the on-the-fly QM/MM nonadiabatic dynamics in JADE package: Theory, implementation, and applications

Understanding the nonadiabatic dynamics of complex systems is a challenging task in computational photochemistry. Herein, we present an efficient and user-friendly quantum mechanics/molecular mechanics (QM/MM) interface to run on-the-fly nonadiabatic dynamics. Currently, this interface consists of an independent set of codes designed for general-purpose use. Herein, we demonstrate the ability and feasibility of the QM/MM interface by integrating it with our long-term developed JADE package. Tailored to handle nonadiabatic processes in various complex systems, especially condensed phases and protein environments, we delve into the theories, implementations, and applications of on-the-fly QM/MM nonadiabatic dynamics. The QM/MM approach is established within the framework of the additive QM/MM scheme, employing electrostatic embedding, link-atom inclusion, and charge-redistribution schemes to treat the QM/MM boundary. Trajectory surface-hopping dynamics are facilitated using the fewest switches algorithm, encompassing classical and quantum treatments for nuclear and electronic motions, respectively. Finally, we report simulations of nonadiabatic dynamics for two typical systems: azomethane in water and the retinal chromophore PSB3 in a protein environment. Our results not only illustrate the power of the QM/MM program but also reveal the important roles of environmental factors in nonadiabatic processes.

Computational Chemistry Strategies to Investigate the Antioxidant Activity of Flavonoids-An Overview

Despite several decades of research, the beneficial effect of flavonoids on health is still enigmatic. Here, we focus on the antioxidant effect of flavonoids, which is elementary to their biological activity. A relatively new strategy for obtaining a more accurate understanding of this effect is to leverage computational chemistry. This review systematically presents various computational chemistry indicators employed over the past five years to investigate the antioxidant activity of flavonoids. We categorize these strategies into five aspects: electronic structure analysis, thermodynamic analysis, kinetic analysis, interaction analysis, and bioavailability analysis. The principles, characteristics, and limitations of these methods are discussed, along with current trends.

Binding interactions and in silico ADME prediction of isoconessimine derivatives as potent acetylcholinesterase inhibitors

In pursuit of new acetylcholinesterase (AChE) inhibitors for treating Alzheimer's disease (AD), a series of ten previously synthesized isoconessimine compounds (7a-7j) was in silico investigated for their binding interactions with AChE and pharmacokinetics based on absorption, distribution, metabolism, and excretion (ADME) properties using molecular docking, ONIOM (Our own N-layered Integrated molecular Orbital and molecular Mechanics) method and SwissADME tools. Docking experiments showed that all compounds bind within the active site gorge of AChE (PDB entry 1C2B), posing its aryloxy-substitutional ethyl group to catalytic site and conessine skeleton to peripheral anionic site. ONIOM interaction energy was used as an ONIOM score to improve docking score, and it ranked 7b as the most potent AChE inhibitor, in agreement with previous experiment. Residues, ASP74, TRP86, GLY122, GLU202, TRP286, GLU292, SER293, ILE294, TYR337, TYR341, and HIS447 were identified as important for the binding of the AChE-isoconessimine complex. The SwissADME investigation suggested that four compounds (7a, 7c, 7d and 7f) agree with the rules of drug-likeness. The steric and electronic effects on the aryloxy-substitutional ethyl group as important factors in the AChE inhibition were also discussed, which brings a better understanding of Alzheimer's disease drug development.

Narrowband emission from fully-bridged triphenylamine derivatives: insights into effects of structure modification and pressure

Triphenylamine derivatives with narrowband emission have attracted growing attention in purely organic thermally-activated fluorescence (TADF) materials owing to their enhanced color purity and flexible molecular design strategy. Combined time-dependent density functional theory (TD-DFT) and ONIOM (QM/MM) calculations indicate that the excellent planarity of the experimentally developed DQAO could result in gradually decreased intermolecular interactions in the aggregated state at ambient pressure and upon compression, which is unfavorable for suppressing structural relaxation and achieving narrowband emission in its non-doped practical application. Therefore, three structure-modified derivatives, DQAO-Cb, DQAO-Ph, and DQAO-PhCb, were theoretically designed by introducing the spherical o-carborane and dangling phenyl units positioned para to the N atom of the DQAO to provide additional geometrical distortion and steric hindrance. The explorations on the reported DQAO, OQAO, and SQAO found that small structural relaxations, suppressed low-frequency vibrations, and noticeable short-range charge-transfer (SR-CT) natures of DQAO and OQAO are responsible for their much narrower emission spectral full-width at half-maxima (FWHMs) compared to that of SQAO. Introducing the o-carborane unit directly at the para position of the N atom could result in additional scissoring and stretching vibrations of the corresponding DQAO-Cb while the presence of the phenyl unit in DQAO-Ph is beneficial for suppressing the high-frequency vibrations of the pristine DQAO. More importantly, the bridged phenyl unit incorporated in DQAO-PhCb is of particular importance to inhibit the undesired low-frequency scissoring and high-frequency stretching vibrations of the o-carborane unit, which is crucial to reduce the reorganization energy of DQAO-PhCb and achieve narrowband emission. Also, the phenyl unit in DQAO-Ph and DQAO-PhCb helps to shorten charge transfer distances and improve ISC and RISC processes. Since the o-carborane unit is an adopted building block to achieve piezochromic behaviors, the theoretically structure-modified DQAO-PhCb is expected to exhibit narrowband emission, TADF, and piezochromic features all together. Our findings will hopefully provide ideas for designing triphenylamine-based TADF emitters with narrowband emission and piezochromic behaviors.

Strongly facet-dependent activity of iron-doped β-nickel oxyhydroxide for the oxygen evolution reaction

Iron (Fe)-doped β-nickel oxyhydroxide (β-NiOOH) is a highly active, noble-metal-free electrocatalyst for the oxygen evolution reaction (OER), with the latter being the bottleneck in electrochemical water splitting for sustainable hydrogen production. The mechanisms underlying how the Fe dopant modulates this host material's water electro-oxidation activity are still not entirely clear. Here, we combine hybrid density functional theory (DFT) and Hubbard-corrected DFT to investigate the OER activity of the most thermodynamically favorable (and therefore, expected to be the majority) crystallographic facets of β-NiOOH, namely (0001) and (101̄0). By considering active sites involving both oxidation and reduction of the transition-metal active center during the redox cycle on these two different facets, we show that six-fold-lattice-coordinated Fe in β-NiOOH is redox inactive towards both oxidation and reduction while five-fold-lattice-coordinated Fe in β-NiOOH does exhibit redox activity. However, the determined redox activity of Fe (or lack of it) is not indicative of good (or bad) performance as a dopant on these two facets. Three of the four active sites investigated (oxo and hydroxo sites on (0001) and a hydrated site on (101̄0)) exhibit only a marginal (<0.1 V) decrease or increase in the thermodynamic overpotential upon doping with Fe. Only one of the redox-active sites investigated, the hydroxo site on (101̄0), exhibits a large attenuation in the thermodynamic overpotential upon doping (to ∼0.52 V from 0.86 V), although the doped overpotential is larger than that observed experimentally for Fe-doped NiOOH. Thus, although pure β-NiOOH facets containing four-, five-, or six-fold lattice-coordinated Ni sites have roughly equal OER activities, yielding similar OER onset potentials (shown in A. Govind Rajan, J. M. P. Martirez and E. A. Carter, J. Am. Chem. Soc., 2020, 142, 3600-3612), only those facets containing four-fold lattice-coordinated Fe (e.g., as shown in J. M. P. Martirez and E. A. Carter, J. Am. Chem. Soc., 2019, 141, 693-705) would be active under analogous conditions for the Fe-doped material. It follows that, while undoped β-NiOOH demonstrates a roughly facet-independent oxygen evolution activity, the activity of Fe-doped β-NiOOH strongly depends on the crystallographic facet. Our study further motivates the investigation of strategies for the selective growth of facets with low iron coordination number to enhance the water splitting activity of Fe-doped β-NiOOH.

A Vision for the Future of Multiscale Modeling

The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural and artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient to thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic and photophysical processes require ab initio treatments to be properly described, but the breadth of length and time scales involved makes it practically unfeasible. A way to address these issues is to couple theories and algorithms working at different scales by dividing the system into domains treated at different levels of approximation, ranging from quantum mechanics to classical molecular dynamics, even including continuum electrodynamics. This approach is known as multiscale modeling and its use over the past 60 years has led to remarkable results. Considering the rapid advances in theory, algorithm design, and computing power, we believe multiscale modeling will massively grow into a dominant research methodology in the forthcoming years. Hereby we describe the main approaches developed within its realm, highlighting their achievements and current drawbacks, eventually proposing a plausible direction for future developments considering also the emergence of new computational techniques such as machine learning and quantum computing. We then discuss how advanced multiscale modeling methods could be exploited to address critical scientific challenges, focusing on the simulation of complex light-harvesting processes, such as natural photosynthesis. While doing so, we suggest a cutting-edge computational paradigm consisting in performing simultaneous multiscale calculations on a system allowing the various domains, treated with appropriate accuracy, to move and extend while they properly interact with each other. Although this vision is very ambitious, we believe the quick development of computer science will lead to both massive improvements and widespread use of these techniques, resulting in enormous progresses in physical chemistry and, eventually, in our society.

Accelerating reliable multiscale quantum refinement of protein-drug systems enabled by machine learning

Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechanics (QM) methods in crystallographic refinement, showed promise in improving the structural quality or even correcting the structure of biomacromolecules. However, vast computational costs and complex quantum mechanics/molecular mechanics (QM/MM) setups limit QR applications. Here we incorporate robust machine learning potentials (MLPs) in multiscale ONIOM(QM:MM) schemes to describe the core parts (e.g., drugs/inhibitors), replacing the expensive QM method. Additionally, two levels of MLPs are combined for the first time to overcome MLP limitations. Our unique MLPs+ONIOM-based QR methods achieve QM-level accuracy with significantly higher efficiency. Furthermore, our refinements provide computational evidence for the existence of bonded and nonbonded forms of the Food and Drug Administration (FDA)-approved drug nirmatrelvir in one SARS-CoV-2 main protease structure. This study highlights that powerful MLPs accelerate QRs for reliable protein-drug complexes, promote broader QR applications and provide more atomistic insights into drug development.

Computational Discovery of Intermolecular Singlet Fission Materials Using Many-Body Perturbation Theory

Intermolecular singlet fission (SF) is the conversion of a photogenerated singlet exciton into two triplet excitons residing on different molecules. SF has the potential to enhance the conversion efficiency of solar cells by harvesting two charge carriers from one high-energy photon, whose surplus energy would otherwise be lost to heat. The development of commercial SF-augmented modules is hindered by the limited selection of molecular crystals that exhibit intermolecular SF in the solid state. Computational exploration may accelerate the discovery of new SF materials. The GW approximation and Bethe-Salpeter equation (GW+BSE) within the framework of many-body perturbation theory is the current state-of-the-art method for calculating the excited-state properties of molecular crystals with periodic boundary conditions. In this Review, we discuss the usage of GW+BSE to assess candidate SF materials as well as its combination with low-cost physical or machine learned models in materials discovery workflows. We demonstrate three successful strategies for the discovery of new SF materials: (i) functionalization of known materials to tune their properties, (ii) finding potential polymorphs with improved crystal packing, and (iii) exploring new classes of materials. In addition, three new candidate SF materials are proposed here, which have not been published previously.

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling

In this work, we introduce the Solvate Suite, a comprehensive and modular command-line interface designed for molecular simulation and microsolvation modeling. The suite interfaces with widely used scientific software, streamlining computational experiments for liquid systems through the automated creation of simulation boxes and topology with adjustable simulation parameters. Furthermore, it has features for graphical and statistical analysis of simulated properties and extraction of trajectory configurations with various filters. Additionally, it introduces innovative strategies for microsolvation modeling with a multiscale approach, employing equilibrated dynamics to identify favorable solute-solvent interactions and enabling full cluster optimization for free-energy calculations without imaginary frequency contamination.

Theoretical Insights into the Photophysical Properties of 4CzIPN Doped in Different Hosts: A Multiscale Study

As a typical thermally activated delayed fluorescence (TADF) emitter with green emission, 4CzIPN has attracted much attention recently. Most studies indicated that 4CzIPN doped in different hosts presented different performances; thus, the hosts should have an obvious influence on its photophysical properties. Herein, the influence of four kinds of hosts, including m-CzPym, m-CzTrz, p-CzPym, and p-CzTrz, on the photophysical properties of 4CzIPN is investigated. Molecular dynamics simulations were performed to simulate the host-guest conformations, and the photophysical properties were studied using the combined quantum mechanics/molecular mechanics method coupled with the thermal-vibration correlation function method. It is found that 4CzIPN in doped films has larger transition dipole moments and spin-orbital coupling constants compared to that in nondoped films. Faster radiative decay, intersystem crossing rates, and higher fluorescence efficiency could be obtained in doped films. Our work helps to better understand the photophysical properties of 4CzIPN in doped films and may favor the design of new hosts.

Acidity of Isomorphic Substituted Zeolites with B, Al and Ga Revisited

Isomorphic substitution of zeolites with B, Al and Ga is a widely used approach in catalysis. The experimentally reported trend of their acidities decreases in the order: Al>Ga>B. However, a consistent explanation is still lacking in the literature. To bring more understanding of this trend, density functional theory computations were conducted on several model systems. First, the acidity of small clusters with two (2T) and five (5T) tetrahedral sites was analyzed. These systems were then projected onto three large void structures: H-[A]-BEA (52T), H-[A]-FAU (84T) and H-[A]-MOR (112T) with A=B, Al, Ga. Our electron density and Interacting Quantum Atom analyses show that the acidity of Al zeolites originates from the much stronger O-Al bond, which is dominated by the electrostatic attraction. The bridging hydroxyl therefore donates more charge density to the metal, the proton becomes more positive and consequently more acidic. Ga zeolites are more acidic than B zeolites due to the greater covalent nature on the O-Ga bond. The resulting acidity, as seen by ammonia, depends on both the acidic oxygen and the charge distribution of the surrounding oxygens exerted by the substituents.

Interoperable workflows by exchanging grid-based data between quantum-chemical program packages

Quantum-chemical subsystem and embedding methods require complex workflows that may involve multiple quantum-chemical program packages. Moreover, such workflows require the exchange of voluminous data that go beyond simple quantities, such as molecular structures and energies. Here, we describe our approach for addressing this interoperability challenge by exchanging electron densities and embedding potentials as grid-based data. We describe the approach that we have implemented to this end in a dedicated code, PyEmbed, currently part of a Python scripting framework. We discuss how it has facilitated the development of quantum-chemical subsystem and embedding methods and highlight several applications that have been enabled by PyEmbed, including wave-function theory (WFT) in density-functional theory (DFT) embedding schemes mixing non-relativistic and relativistic electronic structure methods, real-time time-dependent DFT-in-DFT approaches, the density-based many-body expansion, and workflows including real-space data analysis and visualization. Our approach demonstrates, in particular, the merits of exchanging (complex) grid-based data and, in general, the potential of modular software development in quantum chemistry, which hinges upon libraries that facilitate interoperability.

QM/MM Study Into the Mechanism of Oxidative C=C Double Bond Cleavage by Lignostilbene-α,β-Dioxygenase

The enzymatic biosynthesis of fragrance molecules from lignin fragments is an important reaction in biotechnology for the sustainable production of fine chemicals. In this work we investigated the biosynthesis of vanillin from lignostilbene by a nonheme iron dioxygenase using QM/MM and tested several suggested proposals via either an epoxide or dioxetane intermediate. Binding of dioxygen to the active site of the protein results in the formation of an iron(II)-superoxo species with lignostilbene cation radical. The dioxygenase mechanism starts with electrophilic attack of the terminal oxygen atom of the superoxo group on the central C=C bond of lignostilbene, and the second-coordination sphere effects in the substrate binding pocket guide the reaction towards dioxetane formation. The computed mechanism is rationalized with thermochemical cycles and valence bond schemes that explain the electron transfer processes during the reaction mechanism. Particularly, the polarity of the protein and the local electric field and dipole moments enable a facile electron transfer and an exergonic dioxetane formation pathway.

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.

Bacteria at Work - Experimental and Theoretical Studies Reveal the Catalytic Mechanism of Ectoine Synthase

Ectoine synthase (EctC) catalyses the ultimate step of ectoine biosynthesis, a kosmotropic compound produced as compatible solute by many bacteria and some archaea or eukaryotes. EctC is an Fe2+-dependent homodimeric cytoplasmic protein. Using Mössbauer spectroscopy, molecular dynamics simulations and QM/MM calculations, we determined the most likely coordination number and geometry of the Fe2+ ion and proposed a mechanism of the EctC-catalysed reaction. Most notably, we show that apart from the three amino acids binding to the iron ion (Glu57, Tyr84 and His92), one water molecule and one hydroxide ion are required as additional ligands for the reaction to occur. They fill the first coordination sphere of the Fe2+-cofactor and act as critical proton donors and acceptors during the cyclization reaction.

Mechanism of AGT-Mediated Repair of dG-dC Cross-Links in the Drug Resistance to Chloroethylnitrosoureas: Molecular Docking, MD Simulation, and ONIOM (QM/MM) Investigation

Chloroethylnitrosoureas (CENUs) are important chemotherapies applied in the treatment of cancer. They exert anticancer activity by inducing DNA interstrand cross-links (ICLs) via the formation of two O6-alkylguanine intermediates, O6-chloroethylguanine (O6-ClEtG) and N1,O6-ethanoguanine (N1,O6-EtG). However, O6-alkylguanine-DNA alkyltransferase (AGT), a DNA-repair enzyme, can restore the O6-alkylguanine damages and thereby obstruct the formation of ICLs (dG-dC cross-link). In this study, the inhibitory mechanism of ICL formation was investigated to elucidate the drug resistance of CENUs mediated by AGT in detail. Based on the structures of the substrate-enzyme complexes obtained from docking and MD simulations, two ONIOM (QM/MM) models with different sizes of the QM region were constructed. The model with a larger QM region, which included the substrate (O6-ClEtG or N1,O6-EtG), a water molecule, and five residues (Tyr114, Cys145, His146, Lys165, and Glu172) in the active pocket of AGT, accurately described the repairing reaction and generated the results coinciding with the experimental outcomes. The repair process consists of two sequential steps: hydrogen transfer to form a thiolate anion on Cys145 and alkyl transfer from the O6 site of guanine (the rate-limiting step). The repair of N1,O6-EtG was more favorable than that of O6-ClEtG from both kinetics and thermodynamics aspects. Moreover, the comparison of the repairing process with the formation of dG-dC cross-link and the inhibition of AGT by O6-benzylguanine (O6-BG) showed that the presence of AGT could effectively interrupt the formation of ICLs leading to drug resistance, and the inhibition of AGT by O6-BG that was energetically more favorable than the repair of O6-ClEtG could not prevent the repair of N1,O6-EtG. Therefore, it is necessary to completely eliminate AGT activity before CENUs medication to enhance the chemotherapeutic effectiveness. This work provides reasonable explanations for the supposed mechanism of AGT-mediated drug resistance of CENUs and will assist in the development of novel CENU chemotherapies and their medication strategies.

Three-metal ion mechanism of cross-linked and uncross-linked DNA polymerase β: A theoretical study

In our recent publication, we have proposed a revised base excision repair pathway in which DNA polymerase β (Polβ) catalyzes Schiff base formation prior to the gap-filling DNA synthesis followed by β-elimination. In addition, the polymerase activity of Polβ employs the "three-metal ion mechanism" instead of the long-standing "two-metal ion mechanism" to catalyze phosphodiester bond formation based on the fact derived from time-resolved x-ray crystallography that a third Mg2+ was captured in the polymerase active site after the chemical reaction was initiated. In this study, we develop the models of the uncross-linked and cross-linked Polβ complexes and investigate the "three-metal ion mechanism" vs the "two-metal ion mechanism" by using the quantum mechanics/molecular mechanics molecular dynamics simulations. Our results suggest that the presence of the third Mg2+ ion stabilizes the reaction-state structures, strengthens correct nucleotide binding, and accelerates phosphodiester bond formation. The improved understanding of Polβ's catalytic mechanism provides valuable insights into DNA replication and damage repair.

Effective stabilization of heavy metals in solid waste and sludge pyrolysis using intercalated-exfoliated modified vermiculite: Experiment and simulation study

Pyrolysis is effective in reducing the volume of solid waste and sludge, and produces less pollutants than incineration and landfill, but the process still suffers from heavy metal pollution. Four types of intercalated-exfoliated modified vermiculite (UIV, DIV, TIV and 3IV) were prepared using urea, dimethylsulfoxide, tributyl phosphate and 3-aminopropyltriethoxysilane as intercalators for the control of Cd, Cr, Cu, Pb and Zn in municipal sewage sludge (MSL), paper mill sludge (PML), municipal domestic waste (MWA) and aged refuse (AFE). The larger the interlayer spacing of the vermiculite, the more favorable the retention of heavy metals. 3IV was the most effective additive, with an average retention of more than 75 % of all heavy metals at 450 ℃ for the four raw materials. Cr, Cu, Pb and Zn were all at low potential ecological risk (Pr), while Cd was moderate or considerable Pr, and the addition of 3IV reduced the Pr. Distribution of intercalators between vermiculite interlayers was haphazard, and interlayer spacing results were close to those of the experiment (except for tributyl phosphate). The reactive electrons mainly flowed from the Highest Occupied Molecular Orbital (HOMO) of vermiculite flakes to the Lower Unoccupied Molecular Orbital (LUMO) of heavy metal chlorides. In contrast, the reactive electrons mostly flowed from the HOMO of heavy metal oxides to the LUMO of vermiculite flakes. Heavy metal oxides were more readily adsorbed on vermiculite flakes than heavy metal chlorides, and the adsorption capacity of Cr and Zn was stronger than that of Cd, Pb and Cu.

Toward Post-Hartree-Fock Accuracy for Protein-Ligand Affinities Using the Molecules-in-Molecules Fragmentation-Based Method

The complexity and size of large molecular systems, such as protein-ligand complexes, pose computational challenges for accurate post-Hartree-Fock calculations. This study delivers a thorough benchmarking of the Molecules-in-Molecules (MIM) method, presenting a clear and accessible strategy for layer/theory selections in post-Hartree-Fock computations on substantial molecular systems, notably protein-ligand complexes. An approach is articulated, enabling augmented computational efficiency by strategically canceling out common subsystem energy terms between complexes and proteins within the supermolecular equation. Employing DLPNO-based post-Hartree-Fock methods in conjunction with the three-layer MIM method (MIM3), this study demonstrates the achievement of protein-ligand binding energies with remarkable accuracy (errors <1 kcal mol-1), while significantly reducing computational costs. Furthermore, noteworthy correlations between theoretically computed interaction energies and their experimental equivalents were observed, with R2 values of approximately 0.90 and 0.78 for CDK2 and BZT-ITK sets, respectively, thus validating the efficacy of the MIM method in calculating binding energies. By highlighting the crucial role of diffuse or small Pople-style basis sets in the middle layer for reducing energy errors, this work provides valuable insights and practical methodologies for interaction energy computations in large molecular complexes and opens avenues for their application across a diverse range of molecular systems.

Iron-histidine bonding in bishistidyl hemoproteins-A local vibrational mode study

We investigated the intrinsic strength of distal and proximal FeN bonds for both ferric and ferrous oxidation states of bishistidyl hemoproteins from bacteria, animals, human, and plants, including two cytoglobins, ten hemoglobins, two myoglobins, six neuroglobins, and six phytoglobins. As a qualified measure of bond strength, we used local vibrational force constants ka (FeN) based on local mode theory developed in our group. All calculations were performed with a hybrid QM/MM ansatz. Starting geometries were taken from available x-ray structures. ka (FeN) values were correlated with FeN bond lengths and covalent bond character. We also investigated the stiffness of the axial NFeN bond angle. Our results highlight that protein effects are sensitively reflected in ka (FeN), allowing one to compare trends in diverse protein groups. Moreover, ka (NFeN) is a perfect tool to monitor changes in the axial heme framework caused by different protein environments as well as different Fe oxidation states.

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.

Development of analytic gradients for the Huzinaga quantum embedding method and its applications to large-scale hybrid and double hybrid DFT forces

The theory of analytic gradients is presented for the projector-based density functional theory (DFT) embedding approach utilizing the Huzinaga-equation. The advantages of the Huzinaga-equation-based formulation are demonstrated. In particular, it is shown that the projector employed does not appear in the Lagrangian, and the potential risk of numerical problems is avoided at the evaluation of the gradients. The efficient implementation of the analytic gradient theory is presented for approaches where hybrid DFT, second-order Møller-Plesset perturbation theory, or double hybrid DFT are embedded in lower-level DFT environments. To demonstrate the applicability of the method and to gain insight into its accuracy, it is applied to equilibrium geometry optimizations, transition state searches, and potential energy surface scans. Our results show that bond lengths and angles converge rapidly with the size of the embedded system. While providing structural parameters close to high-level quality for the embedded atoms, the embedding approach has the potential to relax the coordinates of the environment as well. Our demonstrations on a 171-atom zeolite and a 570-atom protein system show that the Huzinaga-equation-based embedding can accelerate (double) hybrid gradient computations by an order of magnitude with sufficient active regions and enables affordable force evaluations or geometry optimizations for molecules of hundreds of atoms.

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.

Benzazole-Based ESIPT Fluorophores: Proton Transfer from the Chalcogen Perspective. A Combined Theoretical and Experimental Study

In this study, we present a comprehensive photophysical investigation of ESIPT-reactive benzazole derivatives in both solution and the solid state. These derivatives incorporate different chalcogen atoms (O, S, and Se) into their structures, and we explore how these variations impact their electronic properties in both ground and excited states. Changes in the UV-Vis absorption and fluorescence emission spectra were analyzed and correlated with the chalcogen atom and solvent polarity. In general, the spectral band of the benzazole derivative containing selenium was redshifted in both the ground and excited states compared to that of its oxygen and sulfur counterparts. Furthermore, we observed that the solvent played a distinctive role in influencing the ESIPT process within these compounds, underscoring once again the significant influence of the chalcogen atom on their photophysical behavior. Theoretical calculations provided a deeper understanding of the molecular dynamics, electronic structures, and photophysical properties of these compounds. These calculations highlighted the effect of chalcogen atoms on the molecular geometry, absorption and emission characteristics, and intramolecular hydrogen bonding, revealing intricate details of the ESIPT mechanism. The integration of experimental and computational data offers a detailed view of the structural and electronic factors governing the photophysical behavior of benzazole derivatives.

Simulating chemical reactions promoted by self-assembled peptides with catalytic properties

Peptides that self-assemble exhibit distinct three-dimensional structures and attributes, positioning them as promising candidates for biocatalysts. Exploring their catalytic processes enhances our comprehension of the catalytic actions inherent to self-assembling peptides, laying a theoretical foundation for creating novel biocatalysts. The investigation into the intricate reaction mechanisms of these entities is rendered challenging due to the vast variability in peptide sequences, their aggregated formations, supportive elements, structures of active sites, types of catalytic reactions, and the interplay between these variables. This complexity hampers the elucidation of the linkage between sequence, structure, and catalytic efficiency in self-assembling peptide catalysts. This chapter delves into the latest progress in understanding the mechanisms behind peptide self-assembly, serving as a catalyst in hydrolysis and oxidation reactions, and employing computational analyses. It discusses the establishment of models, selection of computational strategies, and analysis of computational procedures, emphasizing the application of modeling techniques in probing the catalytic mechanisms of peptide self-assemblies. It also looks ahead to the potential future trajectories within this research domain. Despite facing numerous obstacles, a thorough investigation into the structural and catalytic mechanisms of peptide self-assemblies, combined with the ongoing advancement in computational simulations and experimental methodologies, is set to offer valuable theoretical insights for the development of new biocatalysts, thereby significantly advancing the biocatalysis field.