Metal Ion Modeling Using Classical Mechanics

Theoretical study of the in situ formation of H2O2 by lytic polysaccharide monooxygenases: the reaction mechanism depends on the type of reductant

Lytic polysaccharide monooxygenases (LPMOs) are a unique group of monocopper enzymes that exhibit remarkable ability to catalyze the oxidative cleavage of recalcitrant carbohydrate substrates, such as cellulose and chitin, by utilizing O2 or H2O2 as the oxygen source. One of the key challenges in understanding the catalytic mechanism of LPMOs lies in deciphering how they activate dioxygen using diverse reductants. To shed light on this intricate process, we conducted in-depth investigations using quantum mechanical/molecular mechanical (QM/MM) metadynamics simulations, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations. Specifically, our study focuses on elucidating the in situ formation mechanism of H2O2 by LPMOs in the presence of cellobiose dehydrogenase (CDH), a proposed natural reductant of LPMOs. Our findings reveal a proton-coupled electron transfer (PCET) process in generating the Cu(ii)-hydroperoxide intermediate from the Cu(ii)-superoxide intermediate. Subsequently, a direct proton transfer to the proximal oxygen of Cu(ii)-hydroperoxide results in the formation of H2O2 and LPMO-Cu(ii). Notably, this mechanism significantly differs from the LPMO/ascorbate system, where two hydrogen atom transfer reactions are responsible for generating H2O2 and LPMO-Cu(i). Based on our simulations, we propose a catalytic mechanism of LPMO in the presence of CDH and the polysaccharide substrate, which involves competitive binding of the substrate and CDH to the reduced LPMOs. While the CDH-bound LPMOs can activate dioxygen to generate H2O2, the substrate-bound LPMOs can employ the H2O2 generated from the LPMO/CDH system to perform the peroxygenase reactions of the polysaccharide substrate. Our work not only provides valuable insights into the reductant-dependent mechanisms of O2 activation in LPMOs but also holds implications for understanding the functions of these enzymes in their natural environment.

Computational approaches for the identification of novel metal-binding pharmacophores: advances and challenges

Metalloenzymes are important therapeutic targets for a variety of human diseases. Computational approaches have recently emerged as effective tools to understand metal-ligand interactions and expand the structural diversity of both metalloenzyme inhibitors (MIs) and metal-binding pharmacophores (MBPs). In this review, we highlight key advances in currently available fine-tuning modeling methods and data-driven cheminformatic approaches. We also discuss major challenges to the recognition of novel MBPs and MIs. The evidence provided herein could expedite future computational efforts to guide metalloenzyme-based drug discovery.

Structural and catalytic insights into MhpB: A dioxygenase enzyme for degrading catecholic pollutants

The increasing environmental pollution from persistent aromatic compounds requires effective biodegradation strategies. In this study, we focused on MhpB, an extradiol dioxygenase (EDO) from Escherichia coli. It is known for its role in the degradation of catechols, key intermediates in the degradation of aromatic compounds. We report the high-resolution structure of MhpB determined by cryo-electron microscopy, revealing a decameric conformation with the catalytic chamber at the side. The structure-based analysis allowed us to investigate the substrate-enzyme interaction and the substrate selectivity, which are crucial for its catalytic function. Site-directed mutagenesis was used to modulate the in vitro and in vivo substrate preference of MhpB, enhancing its potential for industrial applications in pollutant degradation. The study provides insight into the mechanism of the enzyme and paves the way for the development of engineered EDOs for environmental remediation of aromatic pollutants.

Charge Arrangement Determines the Sensitivity of Aggregation Patterns between Peptide-Chains to the Surrounding Ionic Environment

The molecular basis for the liquid-liquid phase separation (LLPS) behavior of various biomolecular components in the cell is the formation of multivalent and low-affinity interactions. When the content of these components exceeds a certain critical concentration, the molecules will spontaneously coalesce to form a new liquid phase; i.e., LLPS occurs. Intrinsically disordered proteins (IDPs) are usually rich in amino acids with charged side-chains, and thus, LLPS-involving interactions between their side-chains are of great interest. However, the molecular details of the coalescence of such charged IDPs in a salt solution are still lacking. Here, we focus on two types of peptide-chains with oppositely charged amino acids in extreme arrangements and investigate their aggregation patterns in various ionic environments. The results show that the interaction patterns between peptide-chains with nonuniform charge arrangement sequences are more sensitive to the surrounding cationic environment, and Na+ ions are more likely to cause aggregation of ASP residues compared to Mg2+ ions. As the ionic concentration increases, the electrostatic interactions between oppositely charged residues are gradually converted into a negative-negative amino acid interaction network bridged by Na+ ions, while the positive charge-rich regions are more strongly inclined to be exposed to the solvent environment and gain greater freedom of movement. Simultaneously, this effect will reach saturation with a further increase of salt concentration. The present study enriches insights into the electrostatic dominant factors in phase separation phenomena at the atomic level, which will hopefully inspire the design and application of targeted LLPS in the future.

Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems

Molecular dynamics (MD) simulations are an important and well-established tool for investigating RNA structural dynamics, but their accuracy relies heavily on the quality of the employed force field (ff). In this work, we present a comprehensive evaluation of widely used pair-additive and polarizable RNA ffs using the challenging UUCG tetraloop (TL) benchmark system. Extensive standard MD simulations, initiated from the NMR structure of the 14-mer UUCG TL, revealed that most ffs did not maintain the native state, instead favoring alternative loop conformations. Notably, three very recent variants of pair-additive ffs, OL3CP-gHBfix21, DES-Amber, and OL3R2.7, successfully preserved the native structure over a 10 × 20 μs time scale. To further assess these ffs, we performed enhanced sampling folding simulations of the shorter 8-mer UUCG TL, starting from the single-stranded conformation. Estimated folding free energies (ΔG°fold) varied significantly among these three ffs, with values of 0.0 ± 0.6, 2.4 ± 0.8, and 7.4 ± 0.2 kcal/mol for OL3CP-gHBfix21, DES-Amber, and OL3R2.7, respectively. The ΔG°fold value predicted by the OL3CP-gHBfix21 ff was closest to experimental estimates, ranging from -1.6 to -0.7 kcal/mol. In contrast, the higher ΔG°fold values obtained using DES-Amber and OL3R2.7 were unexpected, suggesting that key interactions are inaccurately described in the folded, unfolded, or misfolded ensembles. These discrepancies led us to further test DES-Amber and OL3R2.7 ffs on additional RNA and DNA systems, where further performance issues were observed. Our results emphasize the complexity of accurately modeling RNA dynamics and suggest that creating an RNA ff capable of reliably performing across a wide range of RNA systems remains extremely challenging. In conclusion, our study provides valuable insights into the capabilities of current RNA ffs and highlights key areas for future ff development.

Toward mitigating the impact of non-bulk defects on describing water structure in salt aqueous solutions: Characterizing solution density with a network-based structural indicator

Structural indicators, also known as structural descriptors, including order parameters, have been proposed to quantify the structural properties of water to account for its anomalous behaviors. However, these indicators, mainly designed for bulk water, are not naturally transferrable to the vicinity of ions due to disruptions in the immediate neighboring space and a resulting loss of feature completeness. To address these non-bulk defects, we introduced a structural indicator that draws on the concept of clique number from graph theory and the criterion in agglomerative clustering, denoted as the average cluster number. This structural indicator aims to discern intrinsic structural characteristics within the water molecules regardless of the ions occupying the neighboring space, without requiring additional corrections. From molecular dynamics simulation results for neat water and salt aqueous solutions utilizing the TIP4P/2005 water model and the Madrid-2019 force field, we characterized the variations in densities with temperature using this network-based indicator, thereby demonstrating its practical utility. The findings suggest that at lower temperatures, the addition of ions disrupts the intrinsic structure of water molecules, with this effect diminishing as the temperature rises. Cations with larger charge density tend to induce stronger disruptions. This study highlights the importance of mitigating the impact of non-bulk defects before applying the indicators to analyze water's intrinsic structural properties in solutions. By doing so, the relationship between changes in water structure and solution behaviors can be more accurately assessed.

Modelling ligand exchange in metal complexes with machine learning potentials

Metal ions are irreplaceable in many areas of chemistry, including (bio)catalysis, self-assembly and charge transfer processes. Yet, modelling their structural and dynamic properties in diverse chemical environments remains challenging for both force fields and ab initio methods. Here, we introduce a strategy to train machine learning potentials (MLPs) using MACE, an equivariant message-passing neural network, for metal-ligand complexes in explicit solvents. We explore the structure and ligand exchange dynamics of Mg2+ in water and Pd2+ in acetonitrile as two illustrative model systems. The trained potentials accurately reproduce equilibrium structures of the complexes in solution, including different coordination numbers and geometries. Furthermore, the MLPs can model structural changes between metal ions and ligands in the first coordination shell, and reproduce the free energy barriers for the corresponding ligand exchange. The strategy presented here provides a computationally efficient approach to model metal ions in solution, paving the way for modelling larger and more diverse metal complexes relevant to biomolecules and supramolecular assemblies.

Light-Driven Hybrid Nanoreactor Harnessing the Synergy of Carboxysomes and Organic Frameworks for Efficient Hydrogen Production

Synthetic photobiocatalysts are promising catalysts for valuable chemical transformations by harnessing solar energy inspired by natural photosynthesis. However, the synergistic integration of all of the components for efficient light harvesting, cascade electron transfer, and efficient biocatalytic reactions presents a formidable challenge. In particular, replicating intricate multiscale hierarchical assembly and functional segregation involved in natural photosystems, such as photosystems I and II, remains particularly demanding within artificial structures. Here, we report the bottom-up construction of a visible-light-driven chemical-biological hybrid nanoreactor with augmented photocatalytic efficiency by anchoring an α-carboxysome shell encasing [FeFe]-hydrogenases (H-S) on the surface of a hydrogen-bonded organic molecular crystal, a microporous α-polymorph of 1,3,6,8-tetra(4'-carboxyphenyl)pyrene (TBAP-α). The self-association of this chemical-biological hybrid system is facilitated by hydrogen bonds, as revealed by molecular dynamics simulations. Within this hybrid photobiocatalyst, TBAP-α functions as an antenna for visible-light absorption and exciton generation, supplying electrons for sacrificial hydrogen production by H-S in aqueous solutions. This coordination allows the hybrid nanoreactor, H-S|TBAP-α, to execute hydrogen evolution exclusively driven by light irradiation with a rate comparable to that of photocatalyst-loaded precious cocatalyst. The established approach to constructing new light-driven biocatalysts combines the synergistic power of biological nanotechnology with the multilength-scale structure and functional control offered by supramolecular organic semiconductors. It opens up innovative opportunities for the fabrication of biomimetic nanoreactors for sustainable fuel production and enzymatic reactions.

Protocols for Metallo- and Serine-β-Lactamase Free Energy Predictions: Insights from Cross-Class Inhibitors

While relative binding free energy (RBFE) calculations using alchemical methods are routinely carried out for many pharmaceutically relevant protein targets, challenges remain. For example, open-source tools do not support the easy setup and simulation of metalloproteins, particularly when ligands directly coordinate to the metal site. Here, we evaluate the performance of RBFE methods for KPC-2, a serine-β-lactamase (SBL), and two nonbonded metal parameter setups for VIM-2, a metallo-β-lactamase (MBL) with two active site zinc ions. We tested two different ways of modeling the ligand-zinc interactions. First, a restraint-based approach, in which FF14SB zinc parameters are combined with harmonic restraints between the zincs and their coordinating residues. The second approach uses an upgraded Amber force field (UAFF) for zinc-metalloproteins with adjusted partial charges and nonbonded terms of zinc-coordinating residues. Molecular mechanics (MM) and quantum mechanics/molecular mechanics (QM/MM) simulations show that the crystallographically observed zinc coordination is not retained in MM simulations with either zinc parameter set for a series of known phosphonic acid-based inhibitors bound to VIM-2. These phosphonic acid-based inhibitors exhibit known cross-class affinity for SBLs and MBLs and serve as a benchmark for RBFE calculations for VIM-2, after validation with KPC-2. The KPC-2 free energy of binding estimates are within expected literature accuracies for the ligand series with a mean absolute error of 0.45 0.28 0.66 kcal/mol and a Pearson's correlation coefficient of 0.93 0.85 0.98 . For VIM-2, the UAFF approach has improved correlation from 0.55 - 0.04 0.88 to 0.78 0.38 0.92 , compared to the restraint approach. The presented strategies for handling ligands coordinating to metal sites highlight that simple metal parameter models can provide some predictive free energy estimates for metalloprotein-ligand systems, but leave room for improvement in their ease of use, modeling of coordination sites and as a result, their accuracy.

Zr-MOF composites with zipped and unzipped carbon nanotubes for high-performance electrochemical supercapacitors

Metal-organic frameworks (MOFs) have gained considerable interest as crystalline porous materials with notable characteristics, such as high surface area and excellent electrochemical performance, particularly in supercapacitor applications. The combination of MOFs with various nanocarbon materials further enhances their performance. This study investigated the combination of zirconium-based MOFs (Zr-MOFs) with graphene oxide nanoribbons (GONRs), zipped carbon nanotubes, and functionalized carbon nanotubes (FCNTs) to fabricate composites with elevated electrical conductivity, adjustable surface area, chemical robustness, mechanical strength, and customizable attributes for specific applications. Zr-MOFs exhibit remarkable capacitance, making them promising electrode materials for supercapacitors. GONRs and FCNTs have recently emerged as focal materials owing to their unique properties, which make them promising materials for electrochemical energy storage devices. A thorough investigation of the supercapacitive behavior of GONRs, FCNTs, Zr-MOFs, Zr-MOFs/FCNTs, and Zr-MOFs/GONRs in 1 M H2SO4 using different evaluation systems (three- and two-electrode systems) revealed a significant enhancement in the capacitance of Zr-MOFs after the introduction of GONRs and FCNTs. Employing Zr-MOF/GONR and Zr-MOF/FCNT composites as positive electrodes and GONRs as negative electrodes in two-electrode measurements demonstrated remarkable cycling stability by retaining their specific capacitances (Cs) even after 10 000 consecutive charge/discharge cycles at a high current density of 10 A g-1. Moreover, they feature a broad potential window of 1.7 V in the three-electrode system. This extends to 2 V in the two-electrode system, achieving high Cs. This highlights the remarkable electrochemical performance of the Zr-MOF/GONR and Zr-MOF/FCNT composites, offering a compelling approach for energy storage applications.

Development of Accurate Force Fields for Mg2+ and Triphosphate Interactions in ATP·Mg2+ and GTP·Mg2+ Complexes

In cells, adenosine triphosphate (ATP) and guanosine triphosphate (GTP) molecules typically form tricoordinated or bicoordinated ATP·Mg2+ or GTP·Mg2+ complexes with Mg2+ ions and bind to proteins, participating in and regulating many important cellular functions. The accuracy of their force field parameters plays a crucial role in studying the function-related conformations of ATP·Mg2+ or GTP·Mg2+ using molecular dynamics (MD) simulations. The parameters developed based on the methyl triphosphate model in existing AMBER force fields cannot accurately describe the conformational distribution of tricoordinated or bicoordinated ATP·Mg2+ or GTP·Mg2+ complexes in solution. In this study, we develop force field parameters for the triphosphate group based on the new ribosyl triphosphate model, considering the dihedral coupling effect, accurate van der Waals (vdW) interactions, and the influence of strongly polarized charges on conformational balance. The new force fields can accurately describe the conformational balance of tricoordinated and bicoordinated ATP·Mg2+ or GTP·Mg2+ conformations in solution and can be applied to simulate biological systems containing ATP·Mg2+ or GTP·Mg2+ complexes.

Metallicious: Automated Force-Field Parameterization of Covalently Bound Metals for Supramolecular Structures

Metal ions play a central, functional, and structural role in many molecular structures, from small catalysts to metal-organic frameworks (MOFs) and proteins. Computational studies of these systems typically employ classical or quantum mechanical approaches or a combination of both. Among classical models, only the covalent metal model reproduces both geometries and charge transfer effects but requires time-consuming parameterization, especially for supramolecular systems containing repetitive units. To streamline this process, we introduce metallicious, a Python tool designed for efficient force-field parameterization of supramolecular structures. Metallicious has been tested on diverse systems including supramolecular cages, knots, and MOFs. Our benchmarks demonstrate that parameters accurately reproduce the reference properties obtained from quantum calculations and crystal structures. Molecular dynamics simulations of the generated structures consistently yield stable simulations in explicit solvent, in contrast to similar simulations performed with nonbonded and cationic dummy models. Overall, metallicious facilitates the atomistic modeling of supramolecular systems, key for understanding their dynamic properties and host-guest interactions. The tool is freely available on GitHub (https://github.com/duartegroup/metallicious).

Metabolic regulation mechanism of melatonin for reducing cadmium accumulation and improving quality in rice

Melatonin acts as a potential regulator of cadmium (Cd) tolerance in rice. However, its practical value in rice production remains unclear. To validate the hypothesis that melatonin affects Cd accumulation and rice quality, a series of experiments were conducted. The results showed that exogenous melatonin application was associated with reduced Cd accumulation (23-43%) in brown rice. Fourier transform infrared spectroscopy (FTIR) analysis showed that exogenous melatonin affected the rice protein secondary structure and starch short-range structure. Metabolomics based on LC-MS/MS revealed that exogenous melatonin altered the brown rice metabolic profile, decreased fatty acid metabolite content, but increased amino acid metabolite, citric acid, melatonin biosynthetic metabolite, and plant hormone contents. These findings indicate that exogenous melatonin can effectively reduced Cd accumulation and improve rice quality through metabolic network regulation, serving as an effective treatment for rice cultivated in Cd-contaminated soil.

Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning

Understanding structural flexibility of metal-organic frameworks (MOFs) via molecular dynamics simulations is crucial to design better MOFs. Density functional theory (DFT) and quantum-chemistry methods provide highly accurate molecular dynamics, but the computational overheads limit their use in long time-dependent simulations. In contrast, classical force fields struggle with the description of coordination bonds. Here we develop a DFT-accurate machine-learning spectral neighbor analysis potentials for two representative MOFs. Their structural and vibrational properties are then studied and tightly compared with available experimental data. Most importantly, we demonstrate an active-learning algorithm, based on mapping the relevant internal coordinates, which drastically reduces the number of training data to be computed at the DFT level. Thus, the workflow presented here appears as an efficient strategy for the study of flexible MOFs with DFT accuracy, but at a fraction of the DFT computational cost.

Modeling solvation dynamics of transition metal redox ion through on-the-fly multi-objective Bayesian-optimized force field

Modeling solvation dynamics and properties is crucial for developing electrolytes for electrochemical energy storage and conversion devices. This work reports an on-the-fly multi-objective Bayesian optimization (OTF-MOBO) method to parameterize force fields for modeling ionic solvation structures, thermodynamics, and transport properties using molecular dynamics simulations. By leveraging solvation-free energy and solvation radii as training data, we employ the data-driven OTF-MOBO algorithm to actively optimize the force field parameters. The modeling accuracy was evaluated in molecular dynamics simulations until the Pareto front in the parameter space was reached through minimized prediction errors in both solvation-free energy and solvation radii. Using transition metal redox ions (Fe3+/Fe2+, Cr3+/Cr2+, and Cu2+/Cu+) in aqueous solution as examples, we demonstrate that simple force fields combining the Lenard-Jones potential and Coulombic potential can achieve relative error below 2% in both solvation free energy and solvation radii. The optimized force fields can be further extrapolated to predict solvation entropy and diffusivities with relative error below 10% compared with experiments.

Force Fields, Quantum-Mechanical- and Molecular-Dynamics-Based Descriptors of Radiometal-Chelator Complexes

Radiopharmaceuticals are currently a key tool in cancer diagnosis and therapy. Metal-based radiopharmaceuticals are characterized by a radiometal-chelator moiety linked to a bio-vector that binds the biological target (e.g., a protein overexpressed in a particular tumor). The right match between radiometal and chelator influences the stability of the complex and the drug's efficacy. Therefore, the coupling of the radioactive element to the correct chelator requires consideration of several features of the radiometal, such as its oxidation state, ionic radius, and coordination geometry. In this work, we systematically investigated about 120 radiometal-chelator complexes taken from the Cambridge Structural Database. We considered 25 radiometals and about 30 chelators, featuring both cyclic and acyclic geometries. We used quantum mechanics methods at the density functional theoretical level to generate the general AMBER force field parameters and to perform 1 µs-long all-atom molecular dynamics simulations in explicit water solution. From these calculations, we extracted several key molecular descriptors accounting for both electronic- and dynamical-based properties. The whole workflow was carefully validated, and selected test-cases were investigated in detail. Molecular descriptors and force field parameters for the complexes considered in this study are made freely available, thus enabling their use in predictive models, molecular modelling, and molecular dynamics investigations of the interaction of compounds with macromolecular targets. Our work provides new insights in understanding the properties of radiometal-chelator complexes, with a direct impact for rational drug design of this important class of drugs.

Simulating Metal-Imidazole Complexes

One commonly observed binding motif in metalloproteins involves the interaction between a metal ion and histidine's imidazole side chains. Although previous imidazole-M(II) parameters established the flexibility and reliability of the 12-6-4 Lennard-Jones (LJ)-type nonbonded model by simply tuning the ligating atom's polarizability, they have not been applied to multiple-imidazole complexes. To fill this gap, we systematically simulate multiple-imidazole complexes (ranging from one to six) for five metal ions (Co(II), Cu(II), Mn(II), Ni(II), and Zn(II)) which commonly appear in metalloproteins. Using extensive (40 ns per PMF window) sampling to assemble free energy association profiles (using OPC water and standard HID imidazole charge models from AMBER) and comparing the equilibrium distances to DFT calculations, a new set of parameters was developed to focus on energetic and geometric features of multiple-imidazole complexes. The obtained free energy profiles agree with the experimental binding free energy and DFT calculated distances. To validate our model, we show that we can close the thermodynamic cycle for metal-imidazole complexes with up to six imidazole molecules in the first solvation shell. Given the success in closing the thermodynamic cycles, we then used the same extended sampling method for six other metal ions (Ag(I), Ca(II), Cd(II), Cu(I), Fe(II), and Mg(II)) to obtain new parameters. Since these new parameters can reproduce the one-imidazole geometry and energy accurately, we hypothesize that they will reasonably predict the binding free energy of higher-level coordination numbers. Hence, we did not extend the analysis of these ions up to six imidazole complexes. Overall, the results shed light on metal-protein interactions by emphasizing the importance of ligand-ligand interaction and metal-π-stacking within metalloproteins.

Combined Multireference-Multiscale Approach to the Description of Photosynthetic Reaction Centers

A first-principles description of the primary photochemical processes that drive photosynthesis and sustain life on our planet remains one of the grand challenges of modern science. Recent research established that explicit incorporation of protein electrostatics in excited-state calculations of photosynthetic pigments, achieved for example with quantum-mechanics/molecular-mechanics (QM/MM) approaches, is essential for a meaningful description of the properties and function of pigment-protein complexes. Although time-dependent density functional theory has been used productively so far in QM/MM approaches for the study of such systems, this methodology has limitations. Here we pursue for the first time a QM/MM description of the reaction center in the principal enzyme of oxygenic photosynthesis, Photosystem II, using multireference wave function theory for the high-level QM region. We identify best practices and establish guidelines regarding the rational choice of active space and appropriate state-averaging for the efficient and reliable use of complete active space self-consistent field (CASSCF) and the N-electron valence state perturbation theory (NEVPT2) in the prediction of low-lying excited states of chlorophyll and pheophytin pigments. Given that the Gouterman orbitals are inadequate as a minimal active space, we define specific minimal and extended active spaces for the NEVPT2 description of electronic states that fall within the Q and B bands. Subsequently, we apply our multireference-QM/MM protocol to the description of all pigments in the reaction center of Photosystem II. The calculations reproduce the electrochromic shifts induced by the protein matrix and the ordering of site energies consistent with the identity of the primary donor (ChlD1) and the experimentally known asymmetric and directional electron transfer. The optimized protocol sets the stage for future multireference treatments of multiple pigments, and hence for multireference studies of charge separation, while it is transferable to the study of any photoactive embedded tetrapyrrole system.

Unraveling the Mechanism of the Oxidative C-C Bond Coupling Reaction Catalyzed by Deoxypodophyllotoxin Synthase

Deoxypodophyllotoxin synthase (DPS), a nonheme Fe(II)/2-oxoglutarate (2OG)-dependent oxygenase, is a key enzyme that is involved in the construction of the fused-ring system in (-)-podophyllotoxin biosynthesis by catalyzing the C-C coupling reaction. However, the mechanistic details of DPS-catalyzed ring formation remain unclear. Herein, our quantum mechanics/molecular mechanics (QM/MM) calculations reveal a novel mechanism that involves the recycling of CO2 (a product of decarboxylation of 2OG) to prevent the formation of hydroxylated byproducts. Our results show that CO2 can react with the FeIII-OH species to generate an unusual FeIII-bicarbonate species. In this way, hydroxylation is avoided by consuming the OH group. Then, the C-C coupling followed by desaturation yields the final product, deoxypodophyllotoxin. This work highlights the crucial role of the CO2 molecule, generated in the crevice between the iron active site and the substrate, in controlling the reaction selectivity.

Precision Atomistic Structures of Actinium-/Radium-/Barium-Doped Lanthanide Nanoconstructs for Radiotherapeutic Applications

Lanthanide vanadate (LnVO4) nanoconstructs have generated considerable interest in radiotherapeutic applications as a medium for nanoscale-targeted drug delivery. For cancer treatment, LnVO4 nanoconstructs have shown promise in encapsulating and retaining radionuclides that emit alpha-particles. In this work, we examined the structure formation of LnVO4 nanoconstructs doped with actinium (Ac) and radium (Ra), both experimentally and using large-scale atomistic molecular dynamics simulations. LnVO4 nanoconstructs were synthesized via a precipitation method in aqueous media. The reaction conditions and elemental compositions were varied to control the structure, fluorescence properties, and size distribution of the LnVO4 nanoconstructs. LnVO4 nanoconstructs were characterized by X-ray diffraction, Raman spectroscopy, and fluorescence spectroscopy. Molecular dynamics simulations were performed to obtain a fundamental understanding of the structure-property relationship between radionuclides and LnVO4 nanoconstructs at the atomic length scale. Molecular dynamics simulations with well-established force field (FF) parameters show that Ra atoms tend to distribute across the nanoconstructs' surface in a broader coordination shell, while the Ac atoms are arranged inside a smaller coordination shell within the nanocluster. The Ba atoms prefer to self-assemble around the surface. These theoretical/simulation predictions of the atomistic structures and an understanding of the relationship between radionuclides and LnVO4 nanoconstructs at the atomic scale are important because they provide design principles for the future development of nanoconstructs for targeted radionuclide delivery.

The multi-scale polarizable pseudo-particle solvent coarse-grained approach: From NaCl salt solutions to polyelectrolyte hydration

We discuss key parameters that affect the reliability of hybrid simulations in the aqueous phase based on an efficient multi-scale coarse-grained polarizable pseudo-particle approach, denoted as pppl, to model the solvent water, whereas solutes are modeled using an all atom polarizable force field. Among those parameters, the extension of the solvent domain (SD) at the solute vicinity (domain in which each solvent particle corresponds to a single water molecule) and the magnitude of solute/solvent short range polarization damping effects are shown to be pivotal to model NaCl salty aqueous solutions and the hydration of charged systems, such as the hydrophobic polyelectrolyte polymer that we have recently investigated [Masella et al., J. Chem. Phys. 155, 114903 (2021)]. Strong short range damping is pivotal to simulate aqueous salt NaCl solutions at moderate concentration (up to 1.0M). The SD extension (as well as short range damping) has a weak effect on the polymer conformation; however, it plays a pivotal role in computing accurate polymer/solvent interaction energies. As the pppl approach is up to two orders of magnitude computationally more efficient than all atom polarizable force field methods, our results show it to be an efficient alternative route to investigate the equilibrium properties of complex charged molecular systems in extended chemical environments.

Binding of Phosphate Species to Ca2+ and Mg2+ in Aqueous Solution

Phosphate derivatives and their interaction with metal cations are involved in many important biological phenomena, so an accurate characterization of the phosphate-metal interaction is necessary to properly understand the role of phosphate-metal contacts in mediating biological function. Herein, we improved the standard 12-6 Lennard-Jones (LJ) potential via the usage of the 12-6-4 LJ model, which incorporates ion-induced dipole interactions. Via parameter scanning, we fine-tuned the 12-6-4 LJ polarizability values to obtain accurate absolute binding free energies for the phosphate anions H2PO4-, HPO42-, PO43- coordinating with Ca2+ and Mg2+. First, we modified the phosphate 12-6-4 LJ parameters to reproduce the solvation free energies of the series of phosphate anions using the thermodynamic integration (TI) method. Then, using the potential mean force (PMF) method, the polarizability of the metal-phosphate interaction was obtained. We show that the free energy profiles of phosphate ions coordinated to Ca2+ and Mg2+ generally show similar trends at longer metal-phosphate distances, while the absolute binding energy values increased with deprotonation. The resulting parameters demonstrate the flexibility of the 12-6-4 LJ-type nonbonded model and its usefulness in accurately describing cation-anion interactions.

Modeling Zinc Complexes Using Neural Networks

Understanding the energetic landscapes of large molecules is necessary for the study of chemical and biological systems. Recently, deep learning has greatly accelerated the development of models based on quantum chemistry, making it possible to build potential energy surfaces and explore chemical space. However, most of this work has focused on organic molecules due to the simplicity of their electronic structures as well as the availability of data sets. In this work, we build a deep learning architecture to model the energetics of zinc organometallic complexes. To achieve this, we have compiled a configurationally and conformationally diverse data set of zinc complexes using metadynamics to overcome the limitations of traditional sampling methods. In terms of the neural network potentials, our results indicate that for zinc complexes, partial charges play an important role in modeling the long-range interactions with a neural network. Our developed model outperforms semiempirical methods in predicting the relative energy of zinc conformers, yielding a mean absolute error (MAE) of 1.32 kcal/mol with reference to the double-hybrid PWPB95 method.

Substrate Conformational Switch Enables the Stereoselective Dimerization in P450 NascB: Insights from Molecular Dynamics Simulations and Quantum Mechanical/Molecular Mechanical Calculations

P450 NascB catalyzes the coupling of cyclo-(l-tryptophan-l-proline) (1) to generate (-)-naseseazine C (2) through intramolecular C-N bond formation and intermolecular C-C coupling. A thorough understanding of its catalytic mechanism is crucial for the engineering or design of P450-catalyzed C-N dimerization reactions. By employing MD simulations, QM/MM calculations, and enhanced sampling, we assessed various mechanisms from recent works. Our study demonstrates that the most favorable pathway entails the transfer of a hydrogen atom from N7-H to Cpd I. Subsequently, there is a conformational change in the substrate radical, shifting it from the Re-face to the Si-face of N7 in Substrate 1. The Si-face conformation of Substrate 1 is stabilized by the protein environment and the π-π stacking interaction between the indole ring and heme porphyrin. The subsequent intermolecular C3-C6' bond formation between Substrate 1 radical and Substrate 2 occurs via a radical attack mechanism. The conformational switch of the Substrate 1 radical not only lowers the barrier of the intermolecular C3-C6' bond formation but also yields the correct stereoselectivity observed in experiments. In addition, we evaluated the reactivity of the ferric-superoxide species, showing it is not reactive enough to initiate the hydrogen atom abstraction from the indole NH group of the substrate. Our simulation provides a comprehensive mechanistic insight into how the P450 enzyme precisely controls both the intramolecular C-N cyclization and intermolecular C-C coupling. The current findings align with the available experimental data, emphasizing the pivotal role of substrate dynamics in governing P450 catalysis.

DL_POLY Quantum 2.0: A modular general-purpose software for advanced path integral simulations

DL_POLY Quantum 2.0, a vastly expanded software based on DL_POLY Classic 1.10, is a highly parallelized computational suite written in FORTRAN77 with a modular structure for incorporating nuclear quantum effects into large-scale/long-time molecular dynamics simulations. This is achieved by presenting users with a wide selection of state-of-the-art dynamics methods that utilize the isomorphism between a classical ring polymer and Feynman's path integral formalism of quantum mechanics. The flexible and user-friendly input/output handling system allows the control of methodology, integration schemes, and thermostatting. DL_POLY Quantum is equipped with a module specifically assigned for calculating correlation functions and printing out the values for sought-after quantities, such as dipole moments and center-of-mass velocities, with packaged tools for calculating infrared absorption spectra and diffusion coefficients.

Multiscale Study on the Intramolecular C-S Bond Formation Catalyzed by P450 Monooxygenase CxnD Involved in the Biosynthesis of Chuangxinmycin: The Critical Roles of Noncrystal Water Molecule and Conformational Change

Cytochrome P450 monooxygenase CxnD catalyzes intramolecular C-S bond formation in the biosynthesis of chuangxinmycin, which is representative of the synthesis of sulfur-containing natural heterocyclic compounds. The intramolecular cyclization usually requires the activation of two reaction sites and a large conformational change; thus, illuminating its detailed reaction mechanism remains challengeable. Here, the reaction pathway of CxnD-catalyzed C-S bond formation was clarified by a series of calculations, including Gaussian accelerated molecular dynamics simulations and quantum mechanical-molecular mechanical calculations. Our results revealed that the C-S formation follows a diradical coupling mechanism. CxnD first employs Cpd I to abstract the hydrogen atom from the imino group of the indole ring, and then, the resulted Cpd II further extracts another hydrogen atom from the thiol group of the side chain to afford a diradical intermediate, in which a noncrystal water molecule entering into the active site after the formation of Cpd I was proved to play an indispensable role. Moreover, the diradical intermediate cannot directly perform the coupling reaction. It should first undergo a series of conformational changes leading to the proximity of two reaction sites. It is the flexibility of the active site of the enzyme and the side chain of the substrate that makes the diradical coupling to be successful.

System-Specific Parameter Optimization for Nonpolarizable and Polarizable Force Fields

The accuracy of classical force fields (FFs) has been shown to be limited for the simulation of cation-protein systems despite their importance in understanding the processes of life. Improvements can result from optimizing the parameters of classical FFs or by extending the FF formulation by terms describing charge transfer (CT) and polarization (POL) effects. In this work, we introduce our implementation of the CTPOL model in OpenMM, which extends the classical additive FF formula by adding CT and POL. Furthermore, we present an open-source parametrization tool, called FFAFFURR, that enables the (system-specific) parametrization of OPLS-AA and CTPOL models. The performance of our workflow was evaluated by its ability to reproduce quantum chemistry energies and by molecular dynamics simulations of a zinc-finger protein.

Development of a Fluctuating Charge Model for Zinc-Containing Metalloproteins

Metalloproteins widely exist in biology and play important roles in various processes. To accurately simulate metalloprotein systems, modeling polarization and charge transfer effects is vital. The fluctuating charge (FQ) model can efficiently generate atomic charges and simulate the charge transfer effect; it has been developed for a wide range of applications, but few models have been specifically tailored for metalloproteins. In this study, we present a fluctuating charge model specifically for zinc-containing metalloproteins based on the extended charge equilibration (EQeq) scheme. Our model was parametrized to reproduce CM5 charges instead of RESP/CHELPG charges because the former is less dependent on the conformation or basis set, does not suffer from unphysical charges for buried atoms, and is still being able to well reproduce the molecular dipoles. During our study, we found that adding the Pauling-bond-order-like term (referred to as the "+C term" in a previous study) between the zinc ion and ligating atoms significantly improves the model's performance. Although our model was trained for four-coordinated zinc sites only, our results indicated it can well describe the atomic charges in diverse zinc sites. Morever, our model was used to generate partial charges for the metal sites in three different zinc-containing metalloproteins (with four-, five-, and six-coordinated metal sites, respectively). These charges exhibited performance comparable to that of the RESP charges in molecular dynamics (MD) simulations. Additional tests indicated our model could also well reproduce the CM5 charges when geometric changes were involved. Those results indicate that our model can efficiently calculate the atomic charges for metal sites and well simulate the charge transfer effect, which marks an important step toward developing versatile polarizable force fields for metalloproteins.

Molecular Dynamics Simulation of an Iron(III) Binding Site on the Fc Domain of IgG1 Relevant for Visible Light-Induced Protein Fragmentation

Molecular dynamics simulations were employed to investigate the interaction between Fe(III) and an iron-binding site composed of THR259, ASP252, and GLU261 on the Fc domain of an IgG1. The goal was to provide microscopic mechanistic information for the photochemical, iron-dependent site-specific oxidative fragmentation of IgG1 at THR259 reported in our previous paper. The distance between Fe(III) and residues of interest as well as the binding pocket size was examined for both protonated and deprotonated THR259. The Fe(III) binding free energy (ΔG) was estimated by using an umbrella sampling approach. The pKa shift of the THR259 hydroxyl group caused by the presence of nearby Fe(III) was estimated based on a thermodynamic cycle. The simulation results show that Fe(III) resides inside the proposed binding pocket and profoundly changes the pocket configuration. The ΔG values indicate that the pocket possesses a strong binding affinity for Fe(III). Furthermore, Fe(III) profoundly lowers the pKa value of the THR259 hydroxyl group by 5.4 pKa units.

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

Exploring Ring Conformation in Uronate Monosaccharides: Insights from Ab Initio Calculations and Classical Molecular Dynamics Simulations

The study focuses on the conformational properties of biologically relevant monosaccharides belonging to the group of uronates: α-l-iduronate, O2-sulfated-α-l-iduronate, and O2-sulfated-α-l-guluronate, either unfunctionalized or O1-methylated. We applied the previously proposed two-step methodology, combining classical MD simulations and subsequent ab initio (QM) calculations, performed on a rationally subsampled set of molecular configurations. We found that, regardless of the number of molecular configurations considered, the level of theory, and the weighting scheme applied, none of the QM approaches is capable of predicting the correct conformational equilibrium of sulfated iduronates as long as the tight counterion binding is not considered. Multicenter, ring-shape-specific binding of either Na+ or Ca2+ ions drastically shifts the conformational equilibrium of the pyranose ring in sulfated iduronates toward 1C4 but does not significantly affect the conformation of non-sulfated compounds. A similar shift is observed upon the protonation of carboxyl groups in all iduronates. In addition, we report a set of average J-coupling constant values related to vicinal protons bound to the pyranose ring of iduronates and corresponding to each of the three main groups of ring conformers, i.e., 4C1, B/S (boat/skew boat), and 1C4. In combination with the conformational energies or with the experimental data, these values allowed the relative proportions of the ring conformers to be estimated and the Karplus-type equations linking the 3JHH-coupling constants to the torsion angles within the pyranose ring to be refined.

HTLV-1 reverse transcriptase homology model provides structural basis for sensitivity to existing nucleoside/nucleotide reverse transcriptase inhibitors

The human T-lymphotropic virus type 1 (HTLV-1) infects millions of people globally and is endemic to various resource-limited regions. Infections persist for life and are associated with increased susceptibility to opportunistic infections and severe diseases including adult T cell leukemia/lymphoma and HTLV-1-associated myelopathy-tropical spastic paraparesis. No HTLV-1-specific anti-retrovirals have been developed and it is unclear whether existing anti-retrovirals developed for treatment of human immunodeficiency virus (HIV) have efficacy against HTLV-1. To understand the structural basis for therapeutic binding, homology modelling and machine learning were used to develop a structural model of the HTLV-1 reverse transcriptase. With this, molecular docking experiments using a panel of FDA-approved inhibitors of viral reverse transcriptases to assess their capacity for binding, and in turn, inhibition. Importantly, nucleoside/nucleotide reverse transcriptase inhibitor but not non-nucleoside reverse transcriptase inhibitors were predicted to bind the HTLV-1 reverse transcriptase, with similar affinity to HIV-1 reverse transcriptase. By strengthening the rationale for clinical testing of therapies such as tenofovir alafenamide, zidovudine, lamivudine, and azvudine for treatment of HTLV-1, this study has demonstrated the power of in silico structural biology approaches in drug design and therapeutic testing.

Elucidating the Molecular Determinants of the Binding Modes of a Third-Generation HIV-1 Integrase Strand Transfer Inhibitor: The Importance of Side Chain and Solvent Reorganization

The first- and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, resistance to even the latest clinically used INSTIs is beginning to emerge. Developmental third-generation INSTIs, based on naphthyridine scaffolds, are promising candidates to combat drug-resistant viral variants. Among these novel INSTIs, compound 4f exhibits two distinct conformations when binding with intasomes from HIV-1 and the closely related prototype foamy virus (PFV) despite the high structural similarity of their INSTI binding pockets. The molecular mechanism and the key active site residues responsible for these differing binding modes in closely related intasomes remain elusive. To unravel the molecular determinants governing the two distinct binding modes, we applied a novel molecular dynamics-based free energy method that utilizes alchemical pathways to overcome the sampling challenges associated with transitioning between the two bound conformations of ligand 4f within the crowded environments of the INSTI binding pockets in these intasomes. The calculated conformational free energies successfully recapitulate the experimentally observed binding mode preferences in the two viral intasomes. Analysis of the simulated structures suggests that the observed binding mode preferences are caused by amino acid residue differences in both the front and the central catalytic sub-pocket of the INSTI binding site in HIV-1 and PFV. Additional free energy calculations on mutants of HIV-1 and PFV revealed that while both sub-pockets contribute to binding mode selection, the central sub-pocket plays a more important role. These results highlight the importance of both side chain and solvent reorganization, as well as the conformational entropy in determining the ligand binding mode, and will help inform the development of more effective INSTIs for combatting drug-resistant viral variants.

Deciphering Deoxynybomycin Biosynthesis Reveals Fe(II)/α-Ketoglutarate-Dependent Dioxygenase-Catalyzed Oxazoline Ring Formation and Decomposition

The antibacterial agents deoxynybomycin (DNM) and nybomycin (NM) have a unique tetracyclic structure featuring an angularly fused 4-oxazoline ring. Here, we report the identification of key enzymes responsible for forming the 4-oxazoline ring in Embleya hyalina NBRC 13850 by comparative bioinformatics analysis of the biosynthetic gene clusters encoding structurally similar natural products DNM, deoxynyboquinone (DNQ), and diazaquinomycins (DAQs). The N-methyltransferase DnmS plays a crucial role in catalyzing the N-dimethylation of a tricyclic precursor prenybomycin to generate NM D; subsequently, the Fe(II)/α-ketoglutarate-dependent dioxygenase (Fe/αKGD) DnmT catalyzes the formation of a 4-oxazoline ring from NM D to produce DNM; finally, a second Fe/αKGD DnmU catalyzes the C-12 hydroxylation of DNM to yield NM. Strikingly, DnmT is shown to display unexpected functions to also catalyze the decomposition of the 4-oxazoline ring and the N-demethylation, thereby converting DNM back to prenybomycin, to putatively serve as a manner to control the intracellular yield of DNM. Structure modeling, site-directed mutagenesis, and quantum mechanics calculations provide mechanistic insights into the DnmT-catalyzed reactions. This work expands our understanding of the functional diversity of Fe/αKGDs in natural product biosynthesis.

Binding of Per- and Polyfluoroalkyl Substances (PFAS) to the PPARγ/RXRα-DNA Complex

Nuclear receptors are the fundamental building blocks of gene expression regulation and the focus of many drug targets. While binding to DNA, nuclear receptors act as transcription factors, governing a multitude of functions in the human body. Peroxisome proliferator-activator receptor γ (PPARγ) and the retinoid X receptor α (RXRα) form heterodimers with unique properties and have a primordial role in insulin sensitization. This PPARγ/RXRα heterodimer has been shown to be impacted by per- and polyfluoroalkyl substances (PFAS) and linked to a variety of significant health conditions in humans. Herein, a selection of the most common PFAS (legacy and emerging) was studied utilizing molecular dynamics simulations for PPARγ/RXRα. The local and global structural effects of PFAS binding on the known ligand binding pockets of PPARγ and RXRα as well as the DNA binding domain (DBD) of RXRα were inspected. The binding free energies were predicted computationally and were compared between the different binding pockets. In addition, two electronic structure approaches were utilized to model the interaction of PFAS within the DNA binding domain, density functional theory (DFT) and domain-based pair natural orbital coupled cluster with perturbative triples (DLPNO-CCSD(T)) approaches, with implicit solvation. Residue decomposition and hydrogen-bonding analysis were also performed, detailing the role of prominent residues in molecular recognition. The role of l-carnitine is explored as a potential in vivo remediation strategy for PFAS interaction with the PPARγ/RXRα heterodimer. In this work, it was found that PFAS can bind and act as agonists for all of the investigated pockets. For the first time in the literature, PFAS are postulated to bind to the DNA binding domain in a nonspecific manner. In addition, for the PPARγ ligand binding domain, l-carnitine shows promise in replacing smaller PFAS from the pocket.

Density functional theory study of crown ether-magnesium complexes: from a solvated ion to an ion trap

Metal ion detection rests on host-guest recognition. We propose a theoretical protocol for designing an optimal trap for a desired metal cation. A host for magnesium ions was sought for among derivatives of crown ethers 12-crown-4, 15-crown-5, and 18-crown-6. Mg-crown complexes and their hydrated counterparts with water molecules bound to the cation were optimized using density functional theory. Based on specific geometric criteria, Interacting quantum atoms analysis and density functional theory-based molecular dynamics of Mg-crown complexes immersed in water, crown ethers for optimal accommodation of Mg2+ in aqueous solution were identified. Selectivity of the chosen crowns towards Na+, K+, and Ca2+ ions is addressed.

Elucidating the molecular determinants for binding modes of a third-generation HIV-1 integrase strand transfer inhibitor: Importance of side chain and solvent reorganization

The first and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, resistance to even the latest clinically used INSTIs is beginning to emerge. Developmental third-generation INSTIs, based on naphthyridine scaffold, are promising candidates to combat drug-resistant viral variants. Among these novel INSTIs, compound 4f exhibits two distinct conformations when binding to intasomes from HIV-1 and the closely related prototype foamy virus (PFV), despite the high structural similarity of their INSTI binding pockets. The molecular mechanism and the key active site residues responsible for these differing binding modes in closely related intasomes remain elusive. To unravel the molecular determinants governing the two distinct binding modes, we employ a novel molecular dynamics-based free energy approach that utilizes alchemical pathways to overcome the sampling challenges associated with transitioning between two ligand conformations within crowded environments along physical pathways. The calculated conformational free energies successfully recapitulate the experimentally observed binding mode preferences in the two viral intasomes. Analysis of the simulated structures suggests that the observed binding mode preferences are caused by amino acid residue differences in both the front and the central catalytic sub-pocket of the INSTI binding site in HIV-1 and PFV. Additional free energy calculations on mutants of HIV-1 and PFV revealed that while both sub-pockets contribute to the binding mode selection, the central sub-pocket plays a more important role. These results highlight the importance of both side chain and solvent reorganization, as well as the conformational entropy in determining the ligand binding mode and will help inform the development of more effective INSTIs for combatting drug-resistant viral variants.

Novel Computational Chemistry Infrastructure for Simulating Astatide in Water: From Basis Sets to Force Fields Using Particle Swarm Optimization

Using the example of astatine, the heaviest naturally occurring halogen whose isotope At-211 has promising medical applications, we propose a new infrastructure for large-scale computational models of heavy elements with strong relativistic effects. In particular, we focus on developing an accurate force field for At- in water based on reliable relativistic density functional theory (DFT) calculations. To ensure the reliability of such calculations, we design novel basis sets for relativistic DFT, via the particle swarm optimization algorithm to optimize the coefficients of the new basis sets and the polarization-consistent basis set idea's extension to heavy elements to eliminate the basis set error from DFT calculations. The resulting basis sets enable the well-grounded evaluation of relativistic DFT against "gold-standard" CCSD(T) results. Accounting for strong relativistic effects, including spin-orbit interaction, via our redesigned infrastructure, we elucidate a noticeable dissimilarity between At- and I- in halide-water force field parameters, radial distribution functions, diffusion coefficients, and hydration energies. This work establishes the framework for the systematic development of polarization-consistent basis sets for relativistic DFT and accurate force fields for molecular dynamics simulations to be used in large-scale models of complex molecular systems with elements from the bottom of the periodic table, including actinides and even superheavy elements.

Unraveling the Valence State and Reactivity of Copper Centers in Membrane-Bound Particulate Methane Monooxygenase

Particulate methane monooxygenase (pMMO) plays a critical role in catalyzing the conversion of methane to methanol, constituting the initial step in the C1 metabolic pathway within methanotrophic bacteria. However, the membrane-bound pMMO's structure and catalytic mechanism, notably the copper's valence state and genuine active site for methane oxidation, have remained elusive. Based on the recently characterized structure of membrane-bound pMMO, extensive computational studies were conducted to address these long-standing issues. A comprehensive analysis comparing the quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) simulated structures with cryo-EM data indicates that both the CuC and CuD sites tend to stay in the Cu(I) valence state within the membrane environment. Additionally, the concurrent presence of Cu(I) at both CuC and CuD sites leads to the significant reduction of the ligand-binding cavity situated between them, making it less likely to accommodate a reductant molecule such as durohydroquinone (DQH2). Subsequent QM/MM calculations reveal that the CuD(I) site is more reactive than the CuC(I) site in oxygen activation, en route to H2O2 formation and the generation of Cu(II)-O•- species. Finally, our simulations demonstrate that the natural reductant ubiquinol (CoQH2) assumes a productive binding conformation at the CuD(I) site but not at the CuC(I) site. This provides evidence that the true active site of membrane-bound pMMOs may be CuD rather than CuC. These findings clarify pMMO's catalytic mechanism and emphasize the membrane environment's pivotal role in modulating the coordination structure and the activity of copper centers within pMMO.

Free energies at QM accuracy from force fields via multimap targeted estimation

Accurate predictions of ligand binding affinities would greatly accelerate the first stages of drug discovery campaigns. However, using highly accurate interatomic potentials based on quantum mechanics (QM) in free energy methods has been so far largely unfeasible due to their prohibitive computational cost. Here, we present an efficient method to compute QM free energies from simulations using cheap reference potentials, such as force fields (FFs). This task has traditionally been out of reach due to the slow convergence of computing the correction from the FF to the QM potential. To overcome this bottleneck, we generalize targeted free energy methods to employ multiple maps-implemented with normalizing flow neural networks (NNs)-that maximize the overlap between the distributions. Critically, the method requires neither a separate expensive training phase for the NNs nor samples from the QM potential. We further propose a one-epoch learning policy to efficiently avoid overfitting, and we combine our approach with enhanced sampling strategies to overcome the pervasive problem of poor convergence due to slow degrees of freedom. On the drug-like molecules in the HiPen dataset, the method accelerates the calculation of the free energy difference of switching from an FF to a DFTB3 potential by three orders of magnitude compared to standard free energy perturbation and by a factor of eight compared to previously published nonequilibrium calculations. Our results suggest that our method, in combination with efficient QM/MM calculations, may be used in lead optimization campaigns in drug discovery and to study protein-ligand molecular recognition processes.

Preorganized Internal Electric Field Promotes a Double-Displacement Mechanism for the Adenine Excision Reaction by Adenine DNA Glycosylase

Adenine DNA glycosylase (MutY) is a monofunctional glycosylase, removing adenines (A) misinserted opposite 8-oxo-7,8-dihydroguanine (OG), a common product of oxidative damage to DNA. Through multiscale calculations, we decipher a detailed adenine excision mechanism of MutY that is consistent with all available experimental data, involving an initial protonation step and two nucleophilic displacement steps. During the first displacement step, N-glycosidic bond cleavage is accompanied by the attack of the carboxylate group of residue Asp144 at the anomeric carbon (C1'), forming a covalent glycosyl-enzyme intermediate to stabilize the fleeting oxocarbenium ion. After departure of the excised base, water nucleophiles can be recruited to displace Asp144, completing the catalytic cycle with retention of stereochemistry at the C1' position. The two displacement reactions are found to mostly involve the movement of the oxocarbenium ion, occurring with large charge reorganization and thus sensitive to the internal electric field (IEF) exerted by the polar protein environment. Intriguingly, we find that the negatively charged carboxylate group is a good nucleophile for the oxocarbenium ion, yet an unactivated water molecule is not, and that the electric field catalysis strategy is used by the enzyme to enable its unique double-displacement reaction mechanism. A strong IEF, pointing toward 5' direction of the substrate sugar ring, greatly facilitates the second displacement reaction at the expense of elevating the barrier of the first one, thereby allowing both reactions to occur. These findings not only increase our understanding of the strategies used by DNA glycosylases to repair DNA lesions, but also have important implications for how internal/external electric field can be applied to modulate chemical reactions.

Chitosan Polysaccharides from a Polarizable Multiscale Approach

We report simulations of chitosan polysaccharides in the aqueous phase, at infinite dilute conditions and zero ionic strength. Those simulations are performed by means of a polarizable multiscale modeling scheme that relies on a polarizable all atom force field to model solutes and on a polarizable solvent coarse grained approach. Force field parameters are assigned only from quantum chemistry ab initio data. We simulate chitosan monomer units, dimers and 50-long chains. Regarding the 50-long chains we simulate three sets of ten randomly built chain replica at three different pH conditions (corresponding to different chain protonation states, the chain degree of deacetylation is 85%). Our simulations show the persistence length of 50-long chitosan chains at strong acidic conditions (pH <5) to be 24 ± 2 nm (at weak/negligible ionic strength conditions), and to be 1 order of magnitude shorter at usual pH conditions. Our simulation data support the most recent simulation and experimental studies devoted to chitosan polysaccharides in the aqueous phase.

Interaction of Radiopharmaceuticals with Somatostatin Receptor 2 Revealed by Molecular Dynamics Simulations

The development of drugs targeting somatostatin receptor 2 (SSTR2), generally overexpressed in neuroendocrine tumors, is focus of intense research. A few molecules in conjugation with radionuclides are in clinical use for both diagnostic and therapeutic purposes. These radiopharmaceuticals are composed of a somatostatin analogue biovector conjugated to a chelator moiety bearing the radionuclide. To date, despite valuable efforts, a detailed molecular-level description of the interaction of radiopharmaceuticals in complex with SSTR2 has not yet been accomplished. Therefore, in this work, we carefully analyzed the key dynamical features and detailed molecular interactions of SSTR2 in complex with six radiopharmaceutical compounds selected among the few already in use (64Cu/68Ga-DOTATATE, 68Ga-DOTATOC, 64Cu-SARTATE) and some in clinical development (68Ga-DOTANOC, 64Cu-TETATATE). Through molecular dynamics simulations and exploiting recently available structures of SSTR2, we explored the influence of the different portions of the compounds (peptide, radionuclide, and chelator) in the interaction with the receptor. We identified the most stable binding modes and found distinct interaction patterns characterizing the six compounds. We thus unveiled detailed molecular interactions crucial for the recognition of this class of radiopharmaceuticals. The microscopically well-founded analysis presented in this study provides guidelines for the design of new potent ligands targeting SSTR2.

Molecular Dynamics Studies of the Ho(III) Aqua-tris(dibenzoylmethane) Complex: Role of Water Dynamics

The seven-coordinate Ho(III) aqua-tris(dibenzoylmethane)(DBM) complex, referred to as Ho-(DBM)₃·H₂O, was first reported in the late 1960s. It has a threefold symmetric structure, with Ho at the center of three dibenzoylmethane ligands and hydrogen-bonded water to ligands. It is considered that the hydrogen bonds between the water molecule and the ligands surrounding Ho play an important role in the formation of its symmetrical structure. In this work, we developed new force-field parameters for classical molecular dynamics (CMD) simulations to theoretically elucidate the structure and dynamics of Ho-(DBM)₃·H₂O. To develop the force field, structural optimization and molecular dynamics were performed on the basis of ab initio calculations using the plane-wave pseudopotential method. The force-field parameters for CMD were then optimized to reproduce the data obtained from ab initio calculations. Validation of the developed force field showed good agreement with the experimental crystalline structure and ab initio data. The vibrational properties of water in Ho-(DBM)₃·H₂O were investigated by comparison with bulk liquid water. The vibrational motion of water was found to have a characteristic mode originating from stationary rotational motion along the c-axis of Ho(III) aqua-tris(dibenzoylmethane). Contrary to expectations, the hydrogen-bond dynamics of water in Ho-(DBM)₃·H₂O were found to be almost equivalent to those of bulk liquid water except for librational motion. This development route for force-field parameters for CMD and the establishment of water dynamics can advance the understanding of water-coordinated metal complexes with high coordination numbers such as Ho-(DBM)₃·H₂O.

Comparison of force fields to study the zinc-finger containing protein NPL4, a target for disulfiram in cancer therapy

Molecular dynamics (MD) simulations are a powerful approach to studying the structure and dynamics of proteins related to health and disease. Advances in the MD field allow modeling proteins with high accuracy. However, modeling metal ions and their interactions with proteins is still challenging. NPL4 is a zinc-binding protein and works as a cofactor for p97 to regulate protein homeostasis. NPL4 is of biomedical importance and has been proposed as the target of disulfiram, a drug recently repurposed for cancer treatment. Experimental studies proposed that the disulfiram metabolites, bis-(diethyldithiocarbamate)‑copper and cupric ions, induce NPL4 misfolding and aggregation. However, the molecular details of their interactions with NPL4 and consequent structural effects are still elusive. Here, biomolecular simulations can help to shed light on the related structural details. To apply MD simulations to NPL4 and its interaction with copper the first important step is identifying a suitable force field to describe the protein in its zinc-bound states. We examined different sets of non-bonded parameters because we want to study the misfolding mechanism and cannot rule out that the zinc may detach from the protein during the process and copper replaces it. We investigated the force-field ability to model the coordination geometry of the metal ions by comparing the results from MD simulations with optimized geometries from quantum mechanics (QM) calculations using model systems of NPL4. Furthermore, we investigated the performance of a force field including bonded parameters to treat copper ions in NPL4 that we obtained based on QM calculations.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules. However, as important as they are, molecular dynamics studies focused on DNA repair pathways are still becoming more widespread. Currently, there are no review articles compiling the advancements made in molecular dynamics approaches applied to NER and discussing: (i) how this technique is currently employed in the field of DNA repair, focusing on NER proteins; (ii) which technical setups are being employed, their strengths and limitations; (iii) which insights or information are they providing to understand the NER pathway or NER-associated proteins; (iv) which open questions would be suited for this technique to answer; and (v) where can we go from here. These questions become even more crucial considering the numerous 3D structures published regarding the NER pathway's proteins in recent years. In this work, we tackle each one of these questions, revising and critically discussing the results published in the context of the NER pathway.

Bond clusters control rupture force limit in shear loaded histidine-Ni2+ metal-coordinated proteins

Dynamic noncovalent interactions are pivotal to the structure and function of biological proteins and have been used in bioinspired materials for similar roles. Metal-coordination bonds, in particular, are especially tunable and enable control over static and dynamic properties when incorporated into synthetic materials. Despite growing efforts to engineer metal-coordination bonds to produce strong, tough, and self-healing materials, the systematic characterization of the exact contribution of these bonds towards mechanical strength and the effect of geometric arrangements is missing, limiting the full design potential of these bonds. In this work, we engineer the cooperative rupture of metal-coordination bonds to increase the rupture strength of metal-coordinated peptide dimers. Utilizing all-atom steered molecular dynamics simulations on idealized bidentate histidine-Ni²⁺ coordinated peptides, we show that histidine-Ni²⁺ bonds can rupture cooperatively in groups of two to three bonds. We find that there is a strength limit, where adding additional coordination bonds does not contribute to the additional increase in the protein rupture strength, likely due to the highly heterogeneous rupture behavior exhibited by the coordination bonds. Further, we show that this coordination bond limit is also found natural metal-coordinated biological proteins. Using these insights, we quantitatively suggest how other proteins can be rationally designed with dynamic noncovalent interactions to exhibit cooperative bond breaking behavior. Altogether, this work provides a quantitative analysis of the cooperativity and intrinsic strength limit for metal-coordination bonds with the aim of advancing clear guiding molecular principles for the mechanical design of metal-coordinated materials.

Theoretical and computational methodologies for understanding coordination self-assembly complexes

This perspective highlights three theoretical and computational methods to capture the coordination self-assembly processes at the molecular level: quantum chemical modeling, molecular dynamics, and reaction network analysis. These methods cover the different scales from the metal-ligand bond to a more global aspect, and approaches that are best suited to understand the coordination self-assembly from different perspectives are introduced. Theoretical and numerical researches based on these methods are not merely ways of interpreting the experimental studies but complementary to them.

Machines on Genes through the Computational Microscope

Macromolecular machines acting on genes are at the core of life's fundamental processes, including DNA replication and repair, gene transcription and regulation, chromatin packaging, RNA splicing, and genome editing. Here, we report the increasing role of computational biophysics in characterizing the mechanisms of "machines on genes", focusing on innovative applications of computational methods and their integration with structural and biophysical experiments. We showcase how state-of-the-art computational methods, including classical and ab initio molecular dynamics to enhanced sampling techniques, and coarse-grained approaches are used for understanding and exploring gene machines for real-world applications. As this review unfolds, advanced computational methods describe the biophysical function that is unseen through experimental techniques, accomplishing the power of the "computational microscope", an expression coined by Klaus Schulten to highlight the extraordinary capability of computer simulations. Pushing the frontiers of computational biophysics toward a pragmatic representation of large multimegadalton biomolecular complexes is instrumental in bridging the gap between experimentally obtained macroscopic observables and the molecular principles playing at the microscopic level. This understanding will help harness molecular machines for medical, pharmaceutical, and biotechnological purposes.