Quantum Mechanical And Molecular Mechanical Research Articles

Determination of the Dipole Moment Variation Upon Excitation in the Chromophore of Green Fluorescent Protein From Molecular Dynamic Trajectories with QM/MM Potentials Using Machine Learning Methods

Quantum and molecular mechanics (QM/MM) potentials are used to calculate molecular dynamics trajectories for the EYFP protein of the green fluorescent protein family. Machine learning models are constructed to establish the relationship between the geometric parameters of the chromophore in the frame of its trajectory and the properties of its electronic excitation. It is shown that it is not enough to use only bridging bonds between the phenyl and imidazolidone fragments of the chromophore as a geometric parameter, and at least two more neighboring bonds must be added to the model. The proposed models allow determination of the dipole moment variation upon excitation with an average error of 0.11 a.u.

Hydrogen-Bond-Assisted Catalysis: Hydroxylation of Paclitaxel by Human CYP2C8.

Paclitaxel (PTX, or Taxol), a chemotherapeutic agent widely employed in the treatment of various cancers, undergoes metabolic transformations through the cytochrome P450 enzymes CYP3A4 and CYP2C8. CYP3A4 catalyzes the aromatic hydroxylation reaction of PTX, whereas CYP2C8 demonstrates a distinct reactivity pattern, producing 6α-hydroxypaclitaxel via alkane hydroxylation. Despite the significant impact of PTX metabolism on its anticancer efficacy, the detailed mechanisms underlying these transformations have remained largely unclear. In this study, we employed hybrid quantum mechanics and molecular mechanics (QM/MM) calculations to elucidate the mechanism of PTX metabolism by human CYP2C8. Our QM/MM results reveal that the hydroxylation of PTX by CYP2C8 follows an atypical rebound mechanism. Either of the two hydrogen atoms at the C6 position of PTX can be abstracted, leading to a common radical intermediate. Although the subsequent rebound barrier is unusually high, stereochemical scrambling is unlikely, as the rebound barrier for the formation of the 6α-hydroxylated PTX─the actual product─is significantly lower than that for the 6β-hydroxylated metabolite. Thus, product selectivity is determined by the non-rate-determining rebound step. Furthermore, the hydroxyl group at the C7 position of PTX plays a catalytic role by facilitating the hydrogen abstraction and rebound steps. Our study also confirms a pronounced stability of the transition state in the high-spin sextet spin state, enabled by the enzyme's specific substrate positioning.

Tutorial on Umbrella Sampling Simulation with a Combined QM/MM Potential: The Potential of Mean Force for an SN2 Reaction in Water.

We present a tutorial to carry out umbrella-sampling free-energy simulations with a combined quantum mechanical and molecular mechanical (QM/MM) potential, which may also be used in a computational or biophysical chemistry curriculum for first-year graduate and undergraduate students. In this article, we choose the Type II SN2 Menshutkin reaction between ammonia and chloromethane to construct the potential of mean force (PMF) for the reaction in aqueous solution. In this exercise, we wish to accomplish three tasks: (1) an understanding of the concept of PMF and the umbrella-sampling free-energy simulation method, (2) the use of a combined QM/MM potential in molecular dynamics simulation of chemical reactions, and (3) an understanding of solvent effects and intermolecular interactions on chemical reactions through comparison with gas-phase results. Analysis of the simulation results allows students to appreciate the difference between the transition state along a PMF from statistical simulations versus the optimized saddle point in the gas phase, the shift of transition state with respect to solvation, and the significance of electronic polarization. Through this tutorial, students will gain the necessary skills to carry out free energy simulations of chemical reactions in solution and in enzymes both in a classroom and in the laboratory.

Theoretical Insight into the Fluorescence Spectral Tuning Mechanism: A Case Study of Flavin-Dependent Bacterial Luciferase.

Bioluminescence of bacteria is widely applied in biological imaging, environmental toxicant detection, and many other situations. Understanding the spectral tuning mechanism not only helps explain the diversity of colors observed in nature but also provides principles for bioengineering new color variants for practical applications. In this study, time-dependent density functional theory (TD-DFT) and quantum mechanics and molecular mechanics (QM/MM) calculations have been employed to understand the fluorescence spectral tuning mechanism of bacterial luciferase with a focus on the electrostatic effect. The spectrum can be tuned by both a homogeneous dielectric environment and oriented external electric fields (OEEFs). Increasing the solvent polarity leads to a redshift of the fluorescence emission maximum, λF, accompanied by a substantial increase in density. In contrast, applying an OEEF along the long axis of the isoalloxazine ring (X-axis) leads to a significant red- or blue-shift in λF, depending on the direction of the OEEF, yet with much smaller changes in intensity. The effect of polar solvents is directionless, and the red-shifts can be attributed to the larger dipole moment of the S1 state compared with that of the S0 state. However, the effect of OEEFs directly correlates with the difference dipole moment between the S1 and S0 states, which is directional and is determined by the charge redistribution upon deexcitation. Moreover, the electrostatic effect of bacterial luciferase is in line with the presence of an internal electric field (IEF) pointing in the negative X direction. Finally, the key residues that contribute to this IEF and strategies for modulating the spectrum through site-directed point mutations are discussed.

Molecular modelling of luciferyl adenylate deprotonation in the active site of Photinus pyralis luciferase

Firefly bioluminescence is a product of chemical reactions that involve luciferin chromophore oxidation in the active site of luciferase proteins. We perform a series of classical molecular dynamic simulations and combined quantum and molecular mechanics (QM/MM) calculations to expose the molecular mechanism of C4 carbon atom deprotonation in luciferyl adenylate molecule. QM/MM calculations confirm that ND-protonated His245 residue is a suitable proton acceptor in the wild-type Photinus pyralis luciferase. Classical molecular dynamic simulations reveal oxygen-binding cavities inside the protein including the one located close to the C4 atom of luciferin. In mutant forms that lack direct interactions with the His245 side chain, a proton wire comprising water molecules stimulates either protonation of the phosphate group of the luciferyl adenylate forming an unstable intermediate or keto–enol tautomerisation of luciferin. The comparison of the ionisation potentials of molecular systems with the ‘deprotonated’ C4 carbon atom revealed that the ionisation energy for the enol tautomeric form is close to the system with the His245 proton acceptor. Thus, the existence of the keto–enol tautomerisation channel might explain bioluminescence in case of the absence of the amino acid proton acceptor.

Integrating Blood Biomarkers and Marine Brown Algae-Derived Inhibitors in Parkinson's Disease: A Multi-scale Approach from Interactomics to Quantum Mechanics.

Parkinson's disease (PD) involves alpha-synuclein accumulation according to Braak's pattern, with diverse clinical progressions that complicate diagnosis and treatment. We aimed to correlate Braak's pattern with rapid progressive PD to identify blood-based biomarkers and therapeutic targets exploiting brown algae-derived bioactives for potential treatment. We implemented a systematic workflow of transcriptomic profiling, co-expression networks, cluster profiling, transcriptional regulator identification, molecular docking, quantum calculations, and dynamic simulations. The transcriptomic analyses exhibited highly expressed genes at each Braak's stage and in rapidly progressive PD. Co-expression networks for Braak's stages were built, and the top five clusters from each stage displayed significant overlap with differentially expressed genes in rapidly progressive PD, indicating shared biomarkers between the blood and the PD brain. Further investigation showed, NF-kappa-B p105 as the master transcriptional regulator of these biomarkers. Molecular docking screened phlorethopentafuhalol-A from brown algae, exhibiting a superior inhibitory effect with p105 (- 7.51kcal/mol) by outperforming PD drugs and anti-inflammatory compounds (- 5.73 to - 4.38kcal/mol). Quantum mechanics and molecular mechanics (QM/MM) calculations and dynamic simulations have confirmed the interactive stability of phlorethopentafuhalol-A with p105. Overall, our combined computational study shows that phlorethopentafuhalol-A derived from brown algae, may have healing properties that could help treat PD.

Monte Carlo QM/MM simulation studies of the Cannizzaro reaction in ionic liquids for improved biofuel production.

The conversion of biomass to 5-hydroxymethylfurfural (HMF) holds substantial promise as a renewable energy source. Notably, HMF can be transformed into 2,5-bis(hydroxymethyl)furan (BHMF), a crucial reactant in biofuel production, but requires harsh operating conditions, H2, and precious metal catalysts. A recently reported Cannizzaro reaction of HMF to BHMF, characterized by its efficiency, mild conditions, and eco-friendliness, instead employed ionic liquids (ILs) to achieve high yields. In this study, combined quantum mechanical and molecular mechanical (QM/MM) simulations in conjunction with Metropolis Monte Carlo statistical mechanics and free-energy perturbation theory utilized M06-2X/6-31+G(d), PDDG/PM3, and the OPLS-VSIL force field to uncover important solute-solvent interactions present in the HMF to BHMF reaction pathway. The Cannizzaro reaction was examined in water and in five ILs composed of the 1-butyl-3-methylimidazolium [BMIM] cation coupled to hexafluorophosphate, tetrafluoroborate, thiocyanate, chloride, and bromide. Energetic and structural analysis of the rate-determining hydride transfer between HMF and the hydride-donor anion HMFOH- attributed the enhanced reactivity to highly organized solvent interactions featuring (1) hydrogen bonding between the ring protons of [BMIM] and the negatively charged carbonyl oxygen atoms on the transition structure, (2) favorable electrostatic interactions between the IL anions and solute hydroxyl groups, and (3) beneficial π-π stacking interactions between [BMIM] and the two aromatic rings present in HMF and HMFOH-.

Computational studies on the catalytic potential of the double active site for enzyme engineering

Proteins possessing double active sites have the potential to revolutionise enzyme design strategies. This study extensively explored an enzyme that contains both a natural active site (NAS) and an engineered active site (EAS), focusing on understanding its structural and functional properties. Metadynamics simulations were employed to investigate how substrates interacted with their respective active sites. The results revealed that both the NAS and EAS exhibited similar minimum energy states, indicating comparable binding affinities. However, it became apparent that the EAS had a weaker binding site for the substrate due to its smaller pocket and constrained conformation. Interestingly, the EAS also displayed dynamic behaviour, with the substrate observed to move outside the pocket, suggesting the possibility of substrate translocation. To gain further insights, steered molecular dynamics (SMD) simulations were conducted to study the conformational changes of the substrate and its interactions with catalytic residues. Notably, the substrate adopted distinct conformations, including near-attack conformations, in both the EAS and NAS. Nevertheless, the NAS demonstrated superior binding minima for the substrate compared to the EAS, reinforcing the observation that the engineered active site was less favourable for substrate binding due to its limitations. The QM/MM (Quantum mechanics and molecular mechanics) analyses highlight the energy disparity between NAS and EAS. Specifically, EAS exhibited elevated energy levels due to its engineered active site being located on the surface. This positioning exposes the substrate to solvents and water molecules, adding to the energy challenge. Consequently, the engineered enzyme did not provide a significant advantage in substrate binding over the single active site protein. Further, the investigation of internal channels and tunnels within the protein shed light on the pathways facilitating transport between the two active sites. By unravelling the complex dynamics and functional characteristics of this double-active site protein, this study offers valuable insights into novel strategies of enzyme engineering. These findings establish a solid foundation for future research endeavours aimed at harnessing the potential of double-active site proteins in diverse biotechnological applications.

Putative reaction mechanism of nitrogenase with a half-dissociated S2B ligand.

We have studied whether dissociation of the S2B sulfide ligand from one of its two coordinating Fe ions may affect the later parts of the reaction mechanism of nitrogenase. Such dissociation has been shown to be favourable for the E2-E4 states in the reaction mechanism, but previous studies have assumed that S2B either remains bridging or has fully dissociated from the active-site FeMo cluster. We employ combined quantum mechanical and molecular mechanical (QM/MM) calculations with two density-functional theory methods, r2SCAN and TPSSh. To make dissociation of S2B possible, we have added a proton to this group throughout the reaction. We study the reaction starting from the E4 state with N2H2 bound to the cluster. Our results indicate that half-dissociation of S2B is unfavourable in most steps of the reaction mechanism. We observe favourable half-dissociation of S2B only when NH or NH2 is bound to the cluster, bridging Fe2 and Fe6. However, the former state is most likely not involved in the reaction mechanism and the latter state is only an intermittent intermediate of the E7 state. Therefore, half-dissociation of S2B seems to play only a minor role in the later parts of the reaction mechanism of nitrogenase. Our suggested mechanism with a protonated S2B is alternating (the two N atoms of the substrate is protonated in an alternating manner) and the substrate prefers to bind to Fe2, in contrast to the preferred binding to Fe6 observed when S2B is unprotonated and bridging Fe2 and Fe6.

QM/MM study of the catalytic reaction of aphid myrosinase

Brevicoryne brassicae, an aphid species, exclusively consumes plants from the Brassicaceae family and employs a sophisticated defense mechanism involving a myrosinase enzyme that breaks down glucosinolates obtained from its host plants. In this work, we employed combined quantum mechanical and molecular mechanical (QM/MM) calculations and molecular dynamics (MD) simulations to study the catalytic reaction of aphid myrosinase. A proper QM region to study the myrosinase reaction should contain the whole substrate, models of Gln-19, His-122, Asp-124, Asn-166, Glu-167, Lys-173, Tyr-180, Val-228, Tyr-309, Tyr-346, Ile-347, Glu-374, Glu-423, Trp-424, and a water molecule. The calculations show that Asp-124 and Glu-423 must be charged, His-122 must be protonated on NE2, and Glu-167 must be protonated on OE2. Our model reproduces the anomeric retaining characteristic of myrosinase and indicates that the deglycosylation reaction is the rate-determining step of the reaction. Based on the calculations, we propose a reaction mechanism for aphid myrosinase-mediated hydrolysis of glucosinolates with an overall barrier of 15.2 kcal/mol. According to the results, removing a proton from Arg-312 or altering it to valine or methionine increases glycosylation barriers but decreases the deglycosylation barrier.

Level-Shifted Embedded Cluster Method for Modeling the Chemistry of Metal Oxides.

The embedded cluster method has been used extensively in the study of the chemical and physical properties of metal oxides. This method has been a popular tool due to its relatively high accuracy and low computational cost. An even more promising option may entail integrating the embedded cluster method with the combined quantum mechanical and molecular mechanical (QM/MM) approach, thereby enabling further consideration of interactions within the entire system for superior results. We aim to accurately model the chemistry of metal oxides using this combined scheme. Here, using the prototypical MgO(100) surface as a test system, with Mg9O14 as the cluster in the quantum mechanical region, we show that the embedded cluster with untailored boundary effective core potentials (ECPs) can have frontier orbital energy levels that substantially deviate from the quantum mechanical reference results. This occurs even when Mg9O9, which retains the stoichiometry of MgO, is used as the cluster in the quantum mechanical region. As a result, the chemical properties of the embedded cluster models differ from those of the quantum mechanical reference model. To address this issue, we propose a new variant of the embedded cluster method called the level-shifted embedded cluster (LSEC) method, which allows the energy levels to be shifted to match the reference levels by tuning the boundary ECPs. Our validation calculations on the adsorption of various adsorbates with different properties on the MgO(100) surface show that the overall performance of QM/MM with the LSEC method is excellent for the adsorption energies, geometries, and charge properties. The excellent performance holds for both the nonstoichiometric and stoichiometric clusters (i.e., Mg9O14 and Mg9O9, respectively), demonstrating the robustness of the LSEC method. We expect that the LSEC method can be combined with QM/MM or used separately for future chemical studies of metal oxides and other ionically bonded systems.

Solid-state effect on the luminescence mechanism of thermally activated delayed fluorescence with aggregation induced emission: A theoretical perspective

An investigation of high-performance organic green thermally activated delayed fluorescence (TADF) material, PyB-DPAC, with aggregation-induced luminescence (AIE) characteristics was theoretically conducted by the first principle calculations method in this work. The polarizable continuum mode (PCM) and the combination of quantum mechanics and molecular mechanics (QM/MM) method were employed to consider the liquid-phase and solid-phase environments, respectively. Results show that TADF mechanism of the molecule is mainly due to the occurrence of efficient intersystem crossing (ISC) and reverse intersystem crossing (RISC) processes between S1 and T2, which benefits from the small energy gap, large SOC and the limited changes of molecular geometry structures in solid-phase environment. The increase of radiative transition rate (Kr) and significant decrease of non-radiative transition rate (Knr) is responsible for the AIE property. Our calculations reasonably explained the experimental results and showed that PyB-DPAC is an excellent TADF material with AIE characteristics, this may help to better understand the influence of solid-state effect and the luminescence mechanism of AIE-TADF molecules.

Pressure induced emission enhancement (PIEE) in solid-state 2,3,4,5-tetraphenylthiophene: a QM/MM study.

Organic fluorophores exhibit pressure-dependent behaviors that are often irregular and contingent upon the specific system. Elucidating how pressure influences these behaviors is essential for the accurate design of piezochromic materials. Here, we conducted an exhaustive theoretical analysis of the excited-state decay processes of crystalline 2,3,4,5-tetraphenylthiophene (TPT) at high pressure through a combined quantum mechanics and molecular mechanics (QM/MM) method. The study revealed that the fluorescence quantum yield experiences a pronounced initial increase owing to the decrease of nonradiative decay IC rate (k ic). The suppression of low-frequency modes results in the decrease of λ e, and then reduces the electron-vibration couplings, and finally slows down the non-radiative process. Our research provides detailed mechanism analyses on PIEE properties of solid state TPT, aiding the rational design of advanced PIEE materials.

Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.

Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conventional pharmacophore screening approach has limitations in conformation sampling and data mining. Here, we offered an innovative solution to identify Mcl1 inhibitors with molecular dynamics-refined pharmacophore and machine learning methods. Considering the safety and druggability of FDA-approved drugs, virtual screening of the database was performed to discover Mcl1 inhibitors, and the hit was subsequently validated via TR-FRET, cytotoxicity, and flow cytometry assays. To reveal the binding characteristics shared by the hit and a typical Mcl1 selective inhibitor, we employed quantum mechanics and molecular mechanics (QM/MM) calculations, umbrella sampling, and metadynamics in this work. The combined studies suggested that fluvastatin had promising cell inhibitory potency and was suitable for further investigation. We believe that this research will shed light on the discovery of novel Mcl1 inhibitors that can be used as a supplemental treatment against leukemia and provide a possible method to improve the accuracy of drug repurposing with limited computational resources while balancing the costs of experimentation well.

H2 formation from the E2-E4 states of nitrogenase.

Nitrogenase is the only enzyme that can cleave the strong triple bond in N2, making nitrogen available for biological lifeforms. The active site is a MoFe7S9C cluster (the FeMo cluster) that binds eight electrons and protons during one catalytic cycle, giving rise to eight intermediate states E0-E7. It is experimentally known that N2 binds to the E4 state and that H2 is a compulsory byproduct of the reaction. However, formation of H2 is also an unproductive side reaction that should be avoided, especially in the early steps of the reaction mechanism (E2 and E3). Here, we study the formation of H2 for various structural interpretations of the E2-E4 states using combined quantum mechanical and molecular mechanical (QM/MM) calculations and four different density-functional theory methods. We find large differences in the predictions of the different methods. B3LYP strongly favours protonation of the central carbide ion and H2 cannot form from such structures. On the other hand, with TPSS, r2SCAN and TPSSh, H2 formation is strongly exothermic for all structures and En and therefore need strict kinetic control to be avoided. For the E2 state, the kinetic barriers for the low-energy structures are high enough to avoid H2 formation. However, for both the E3 and E4 states, all three methods predict that the best structure has two hydride ions bridging the same pair of Fe ions (Fe2 and Fe6) and these two ions can combine to form H2 with an activation barrier of only 29-57 kJ mol-1, corresponding to rates of 7 ×102 to 5 × 107 s-1, i.e. much faster than the turnover rate of the enzyme (1-5 s-1). We have also studied H-atom movements within the FeMo cluster, showing that the various protonation states can quite freely be interconverted (activation barriers of 12-69 kJ mol-1).

Enhancing the high-spin reactivity in C-H bond activation by Iron (IV)-Oxo species: insights from paclitaxel hydroxylation by CYP2C8.

Previous theoretical studies have revealed that high-spin states possess flatter potential energy surfaces than low-spin states in reactions involving iron(IV)-oxo species of cytochrome P450 enzymes (P450s), nonheme enzymes, or biomimetic complexes. Therefore, actively utilizing high-spin states to enhance challenging chemical transformations, such as C-H bond activation, represents an intriguing research avenue. However, the inherent instability of high-spin states relative to low-spin states in pre-reaction complexes often hinders their accessibility around the transition state, especially in heme systems with strong ligand fields. Counterintuitively, our investigation of the metabolic hydroxylation of paclitaxel by human CYP2C8 using a hybrid quantum mechanics and molecular mechanics (QM/MM) approach showed that the high-spin sextet state exhibits unusually high stability, when the reaction follows a secondary reaction pathway leading to 6β-hydroxypaclitaxel. We thoroughly analyzed the factors contributing to the enhanced stabilization of the high-spin state, and the knowledge obtained could be instrumental in designing competent biomimetic catalysts and biocatalysts for C-H bond activation.

Protonation of Homocitrate and the E1 State of Fe-Nitrogenase Studied by QM/MM Calculations.

Nitrogenase is the only enzyme that can cleave the strong triple bond in N2, making nitrogen available for biological life. There are three isozymes of nitrogenase, differing in the composition of the active site, viz., Mo, V, and Fe-nitrogenase. Recently, the first crystal structure of Fe-nitrogenase was presented. We have performed the first combined quantum mechanical and molecular mechanical (QM/MM) study of Fe-nitrogenase. We show with QM/MM and quantum-refinement calculations that the homocitrate ligand is most likely protonated on the alcohol oxygen in the resting E0 state. The most stable broken-symmetry (BS) states are the same as for Mo-nitrogenase, i.e., the three Noodleman BS7-type states (with a surplus of β spin on the eighth Fe ion), which maximize the number of nearby antiferromagnetically coupled Fe-Fe pairs. For the E1 state, we find that protonation of the S2B μ2 belt sulfide ion is most favorable, 14-117 kJ/mol more stable than structures with a Fe-bound hydride ion (the best has a hydride ion on the Fe2 ion) calculated with four different density-functional theory methods. This is similar to what was found for Mo-nitrogenase, but it does not explain the recent EPR observation that the E1 state of Fe-nitrogenase should contain a photolyzable hydride ion. For the E1 state, many BS states are close in energy, and the preferred BS state differs depending on the position of the extra proton and which density functional is used.

QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. The adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems. Program SummaryProgram Title: QMMM 2023.CPC Library link to program files:https://doi.org/10.17632/zmkc9db4zj.1.Licensing provisions: Apache-2.0 for the program and CC-BY-4.0 for the manual.Programming languages: Fortran90, Perl, and shell scripting.Nature of problem: Multiscale modeling and simulations by the combined quantum mechanical and molecular mechanical (QM/MM) method.Solution method: The program performs single-point calculations, geometry optimizations, transition state optimizations, and molecular dynamics (MD) by the QM/MM method by interfacing calls to binary executables in a QM package (GAMESS-US, Gaussian, or ORCA) and an MM package (TINKER) for the required calculations. QMMM 2023 supports various types of embedding schemes and multiple ways of treating a QM-MM boundary passing through a covalent bond.Additional comments including restrictions and unusual features: (1) QMMM 2023 supports polarizable-embedding and flexible-embedding schemes based on the electronegativity equalization principle and allowing charge transfer between the QM and MM regions. (2) For a QM-MM boundary passing through covalent bonds, all link-atom-based treatments preserve the charge of the MM region (and MM bond dipoles if desired) while effectively avoiding the over-polarization of the QM region. Further tuning is available to account for the charge penetration effects at the QM-MM boundary. (3) For dynamics simulations, Hamiltonian-based adaptive-partitioning algorithms allow on-the-fly reclassification of atoms or groups into the QM or MM regions without abrupt changes in the energy of the entire system or in the forces on all atoms.

Structural insights in the permeation mechanism of an activated GIRK2 channel

G protein-gated inwardly rectifying potassium (GIRK) channels play a significant role in physiopathology by the regulation of cell excitability. This regulation depends on the K+ ion conduction induced by structural constrictions: the selectivity filters (SFs), helix bundle crossings (HBCs), and G-loop gates. To explore why no permeation occurred when the constrictions were kept in the open state, a 4-K+-related occupancy mechanism was proposed. Unfortunately, this hypothesis was neither assessed, nor was the energetic characteristics presented. To identify the permeation mechanism on an atomic level, all-atom molecular dynamic (MD) simulations and a coupled quantum mechanics and molecular mechanics (QM/MM) method were used for the GIRK2 mutant R201A. It was found that the R201A had a moderate conductive capability in the presence of PIP2. Furthermore, the 4-K+ group of ions was found to dominate the conduction through the activated HBC gate. This shielding-like mechanism was assessed by the potential energy barrier along the conduction pathway. Mutation studies did further support the assumption that E152 was responsible for the mechanism. Moreover, E152 was most probably facilitating the inflow of ions from the SF to the cavity. On the contrary, N184 had no remarkable effect on this mechanism, except for the conduction efficiency. These findings highlighted the necessity of a multi-ion distribution for the conduction to take place, and indicated that the K+ migration was not only determined by the channel conductive state in the GIRK channel. The here presented multi-ion permeation mechanism may help to provide an effective way to regulate the channelopathies.

Bridging semiempirical and abinitio QM/MM potentials by Gaussian process regression and its sparse variants for free energy simulation.

Free energy simulations that employ combined quantum mechanical and molecular mechanical (QM/MM) potentials at abinitio QM (AI) levels are computationally highly demanding. Here, we present a machine-learning-facilitated approach for obtaining AI/MM-quality free energy profiles at the cost of efficient semiempirical QM/MM (SE/MM) methods. Specifically, we use Gaussian process regression (GPR) to learn the potential energy corrections needed for an SE/MM level to match an AI/MM target along the minimum free energy path (MFEP). Force modification using gradients of the GPR potential allows us to improve configurational sampling and update the MFEP. To adaptively train our model, we further employ the sparse variational GP (SVGP) and streaming sparse GPR (SSGPR) methods, which efficiently incorporate previous sample information without significantly increasing the training data size. We applied the QM-(SS)GPR/MM method to the solution-phase SN2 Menshutkin reaction, NH3+CH3Cl→CH3NH3++Cl-, using AM1/MM and B3LYP/6-31+G(d,p)/MM as the base and target levels, respectively. For 4000 configurations sampled along the MFEP, the iteratively optimized AM1-SSGPR-4/MM model reduces the energy error in AM1/MM from 18.2 to 4.4 kcal/mol. Although not explicitly fitting forces, our method also reduces the key internal force errors from 25.5 to 11.1 kcal/mol/Å and from 30.2 to 10.3 kcal/mol/Å for the N-C and C-Cl bonds, respectively. Compared to the uncorrected simulations, the AM1-SSGPR-4/MM method lowers the predicted free energy barrier from 28.7 to 11.7 kcal/mol and decreases the reaction free energy from -12.4 to -41.9 kcal/mol, bringing these results into closer agreement with their AI/MM and experimental benchmarks.