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At least 307 records · Page 17

Surface distribution of heterogenous clathrin assemblies in resorbing osteoclasts

Highlights: • Platinum replica microscopy has revealed new structural data on the clathrins on the ventralmembrane of osteoclasts. • Various clathrins were visualized, suggesting that they followed variations in the surface topography of the apatite. • Most of the flat clathrins may participate in the adhesive and mechnosensory functions in co-operation with podosomes. • The present findings in osteoclast biology reveal potential novel drug targets or treatment regimens. Osteoclasts seeded on either glass coverslips or apatite pellets have at least two morphologically distinct substrate adhesion sites: actin-based adhesion structures including podosome belts and sealing zones, and adjacent clathrin sheets. Clathrin-coated structures are exclusively localized at the podosome belts and sealing zone, in both of which the plasma membrane forms a tight attachment to the substrate surface. When cultured on apatite osteoclasts can degrade the apatite leading to the formation of resorption lacunae. The sealing zone divides the ventral membrane into different domains, outside and inside of the sealing zones. The former facing the smooth-surfaced intact apatite contains relatively solitary or networks of larger flat clathrin structures; and the latter, facing the rough-surfaced degraded apatite in the resorption lacunae contain clathrin in various shapes and sizes. Clathrin assemblies on the membrane domain facing not only a resorption lacuna, or trails but also intact apatite indeed were observed to be heterogeneous in size and intensity, suggesting that they appeared to follow variations in the surface topography of the apatite surface. These results provide a detailed insight into the flat clathrin sheets that have been suggested to be the sites of adhesion and mechanosensing in co-operation with podosomes.

60 APPLIED LIFE SCIENCES↗

Differential Membrane Binding Mechanics of Synaptotagmin Isoforms Observed in Atomic Detail

Synaptotagmin (Syt) is a membrane-associated protein involved in vesicle fusion through the SNARE complex that is found throughout the human body in 17 different isoforms. These isoforms have two membrane-binding C2 domains, which sense Ca 2+ and thereby promote anionic membrane binding and lead to vesicle fusion. Through molecular dynamics simulations using the HMMM acclerated bilayer model, we have investigated how small protein sequence changes in the Ca 2+ binding loops of the C2 domains may give rise to the experimentally determined difference in binding kinetics between Syt-1 and Syt-7 isoforms. Syt-7 C2 domains are found to form more close contacts with anionic phospholipid head groups, particularly in Loop 1, where an additional positive charge in Syt-7 draws the loop closer to the membrane and causes the anchoring residue F167 to insert deeper into the bilayer than the corresponding methionine in Syt-1 (M173). By carrying out additional replica exchange umbrella sampling calculations, we demonstrate that these additional contacts increase the energetic cost of unbinding the Syt-7 C2 domains from the bilayer, causing them to unbind more slowly than their counterparts in Syt-1.

59 BASIC BIOLOGICAL SCIENCES↗

Simulating the Geological Fate of Terrestrial Organic Matter: Lignin vs Cellulose

While shale gas has become a major source of energy, a more sustainable recovery requires a better understanding of the gas/kerogen matrix interactions. Here, we use replica exchange molecular dynamics to investigate the geological conversion of two important classes of gas-forming constituents of the terrestrial organic matter: lignin and cellulose. In agreement with results from pyrolysis experiments, we show that lignin produces twice as much kerogen and 5 times more methane than cellulose. In addition, while ex-cellulose kerogen is relatively stiff and almost nonporous, ex-lignin kerogen, despite having a very similar composition and bonding, is an order of magnitude more compliant due to the presence of large micropores. The obtained results can potentially improve the nanoscale brick of bottom-up models of shale gas recovery.

58 GEOSCIENCES↗

Adaptive Ensemble Refinement of Protein Structures in High Resolution Electron Microscopy Density Maps with Radical Augmented Molecular Dynamics Flexible Fitting

Recent advances in cryo-electron microscopy (cryo-EM) have enabled modeling macromolecular complexes that are essential components of the cellular machinery. The density maps derived from cryo-EM experiments are often integrated with manual, knowledge or artificial intelligence driven, and physics-guided computational methods to build, fit, and refine molecular structures. Going beyond a single stationary- structure determination scheme, it is becoming more common to interpret the experimental data with an ensemble of models, which contributes to an average observation. Hence, there is a need to decide on the quality of an ensemble of protein structures on-the-fly, while refining them against the density maps. Here, we introduce such an adaptive decision making scheme during the molecular dynamics flexible fitting (MDFF) of biomolecules. Using RADICAL-Cybertools, and the new RADICAL augmented MDFF implementation (R-MDFF) is examined in high-performance computing environments for refinement of two protein systems, Adenylate Kinase and Carbon Monoxide Dehydrogenase. For the test cases, use of multiple replicas in flexible fitting with adaptive decision making in R-MDFF improves the overall correlation to the density by 40% relative to the refinements of the brute-force MDFF. The improvements are particularly significant at high, 2 - 3 Å, map resolutions. More importantly, the ensemble model captures key features of biologically relevant molecular dynamics that is inaccessible to a single-model interpretation. Finally, the pipeline is applicable to systems of growing sizes, which is demonstrated using ensemble refinement of capsid proteins from Chimpanzee adenovirus. The overhead for decision making remaining low and robust to computing environments. The software is publicly available on GitHub and includes a short user guide to install the R-MDFF on different computing environments, from local Linux based workstations to High Performance Computing (HPC) environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computing Relative Binding Affinity of Ligands to Receptor: An Effective Hybrid Single-Dual-Topology Free-Energy Perturbation Approach in NAMD

An effective hybrid single-dual-topology protocol is designed for the calculation of relative binding affinities of small ligands to a receptor. The protocol was developed as an extension of the NAMD molecular dynamics program, which exclusively supports a dual-topology framework for relative alchemical free-energy perturbation (FEP) calculations. Here, the alchemical end states are represented as two separate molecules sharing a common substructure identified through maximum structural mapping. Within the substructure, an atom-to-atom correspondence is established, and each pair of corresponding atoms is holonomically constrained to share identical coordinates at all time throughout the simulation. The forces are projected and combined at each step for propagation. Following this formulation, a set of illustrative calculations of reliable experiment/simulation data, including relative solvation free energies of small molecules and relative binding affinities of drug compounds to proteins, are presented. To enhance sampling of the dual-topology region, the FEP calculations were carried out within a replica-exchange MD scheme supported by the multiple-copy algorithm module of NAMD, with periodically attempted swapping of the thermodynamic coupling parameter lambda between neighboring states. The findings are consistent with experiments and benchmarks reported in the literature, lending support to the validity of the current protocol. In summary, this hybrid single-dual-topology approach combines the conceptual simplicity of the dual-topology paradigm with the advantageous sampling efficiency of the single-topology method, making it an ideal strategy for high-throughput in silico drug design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic Characterization of Gramicidin Channel Formation

We investigated gramicidin A (gA) subunit dimerization in lipid bilayers using microsecond-long replica-exchange umbrella sampling simulations, millisecond-long unbiased molecular dynamics simulations, and machine learning. Our simulations led to a dimer structure that is indistinguishable from the experimentally determined gA channel structures, with the two gA subunits joined by six hydrogen bonds (6HB). The simulations also uncovered two additional dimer structures, with different gA–gA stacking orientations that were stabilized by four or two hydrogen bonds (4HB or 2HB). When examining the temporal evolution of the dimerization, we found that two bilayer-inserted gA subunits can form the 6HB dimer directly, with no discernible intermediate states, as well as through paths that involve the 2HB and 4HB dimers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

36 MATERIALS SCIENCE↗

Characterization of Heparin’s Conformational Ensemble by Molecular Dynamics Simulations and Nuclear Magnetic Resonance Spectroscopy

Heparin is a highly charged, polysulfated polysaccharide and serves as an anticoagulant. Heparin binds to multiple proteins throughout the body, suggesting a large range of potential therapeutic applications. Although its function has been characterized in multiple physiological contexts, heparin’s solution conformational dynamics and structure–function relationships are not fully understood. Molecular dynamics (MD) simulations facilitate the analysis of a molecule’s underlying conformational ensemble, which then provides important information necessary for understanding structure–function relationships. However, for MD simulations to afford meaningful results, they must both provide adequate sampling and accurately represent the energy properties of a molecule. The aim of this study is to compare heparin’s conformational ensemble using two well-developed force fields for carbohydrates, known as GLYCAM06 and CHARMM36, using replica exchange molecular dynamics (REMD) simulations, and to validate these results with NMR experiments. In this work, the anticoagulant sequence, an ultra-low-molecular-weight heparin, known as Arixtra (fondaparinux, sodium), was simulated with both parameter sets. The results suggest that GLYCAM06 matches experimental nuclear magnetic resonance three-bond J-coupling values measured for Arixtra better than CHARMM36. In addition, NOESY and ROESY experiments suggest that Arixtra is very flexible in the sub-millisecond time scale and does not adopt a unique structure at 25 C. Moreover, GLYCAM06 affords a much more dynamic conformational ensemble for Arixtra than CHARMM36.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protein–Ligand Binding Free-Energy Calculations with ARROW–A Purely First-Principles Parameterized Polarizable Force Field

Protein–ligand binding free-energy calculations using molecular dynamics (MD) simulations have emerged as a powerful tool for in silico drug design. Here, we present results obtained with the ARROW force field (FF)–a multipolar polarizable and physics-based model with all parameters fitted entirely to high-level ab initio quantum mechanical (QM) calculations. ARROW has already proven its ability to determine solvation free energy of arbitrary neutral compounds with unprecedented accuracy. The ARROW FF parameterization is now extended to include coverage of all amino acids including charged groups, allowing molecular simulations of a series of protein–ligand systems and prediction of their relative binding free energies. We ensure adequate sampling by applying a novel technique that is based on coupling the Hamiltonian Replica exchange (HREX) with a conformation reservoir generated via potential softening and nonequilibrium MD. ARROW provides predictions with near chemical accuracy (mean absolute error of ~0.5 kcal/mol) for two of the three protein systems studied here (MCL1 and Thrombin). The third protein system (CDK2) reveals the difficulty in accurately describing dimer interaction energies involving polar and charged species. Overall, for all of the three protein systems studied here, ARROW FF predicts relative binding free energies of ligands with a similar accuracy level as leading nonpolarizable force fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Water freezing and ice melting

The generalized replica exchange method (gREM) is designed to sample states with coexisting phases and thereby to describe strong first order phase transitions. The isobaric MD version of the gREM is presented and applied to freezing of liquid water, and melting of hexagonal and cubic ice. It is confirmed that coexisting states are well sampled. The statistical temperature as a function of enthalpy, T S (H), is obtained. Hysteresis between freezing and melting is observed and discussed. The entropic analysis of phase transitions is applied and equilibrium transition temperatures, latent heats, and surface tensions are obtained for hexagonal ice↔liquid and cubic ice↔liquid, with excellent agreement with published values. A new method is given to assign water molecules among various symmetry types. As a result, pathways for water freezing, ultimately leading to hexagonal ice, are found to contain intermediate layered structures built from hexagonal and cubic ice.

36 MATERIALS SCIENCE↗

Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer

We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole–dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang–Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.

36 MATERIALS SCIENCE↗

Structure–Thermodynamic Relationship of a Polysaccharide Gel (Alginate) as a Function of Water Content and Counterion Type (Na vs Ca)

Biofilms are the predominant mode of microbial life on Earth, and so a deep understanding of microbial communities-and their impacts on environmental processes-requires a firm understanding of biofilm properties. Because of the importance of biofilms to their microbial inhabitants, microbes have evolved different ways of engineering and reconfiguring the matrix of extracellular polymeric substances (EPS) that constitute the main non-living component of biofilms. This ability makes it difficult to distinguish between the biotic and abiotic origins of biofilm properties. An important route toward establishing this distinction has been the study of simplified models of the EPS matrix. This study builds on such efforts by using atomistic simulations to predict the nanoscale (≤10 nm scale) structure of a model EPS matrix and the sensitivity of this structure to interpolymer interactions and water content. To accomplish this, we use replica exchange molecular dynamics (REMD) simulations to generate all-atom configurations of ten 3.4 kDa alginate polymers at a range of water contents and Ca–Na ratios. Simulated systems are solvated with explicitly modeled water molecules, which allows us to capture the discrete structure of the hydrating water and to examine the thermodynamic stability of water in the gels as they are progressively dehydrated. Our primary findings are that (i) the structure of the hydrogels is highly sensitive to the identity of the charge-compensating cations, (ii) the thermodynamics of water within the gels (specific enthalpy and free energy) are, surprisingly, only weakly sensitive to cation identity, and (iii) predictions of the differential enthalpy and free energy of hydration include a short-ranged enthalpic term that promotes hydration and a longer-ranged (presumably entropic) term that promotes dehydration, where short and long ranges refer to distances shorter or longer than ~0.6 nm between alginate strands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of Aβ Monomers through the Convergence of Ensemble Properties among Simulations with Multiple Force Fields

We found that amyloid β (Aβ) monomers represent a base state in the pathways of aggregation that result in the fibrils and oligomers implicated in the pathogenesis of Alzheimer’s disease (AD). The structural properties of these intrinsically disordered peptides remain unclear despite extensive experimental and computational investigations. Further, there are mutations within Aβ that change the way the peptide aggregates and are known to cause familial AD (FAD). Here, we analyze the ensembles of different isoforms (Aβ42 and Aβ40) and mutants (E22Δ, D23N, E22K, E22G, and A2T in Aβ40) of Aβ generated with all-atom replica exchange molecular dynamics (REMD) simulations on the μs/replica time scale. These were run using three different force field/water model combinations: OPLS-AA/L and TIP3P (“OPLS”), AMBER99sb-ILDN and TIP4P-Ew (“ILDN”), as well as CHARMM22* and TIP3SP (“CHARMM”). Despite fundamental changes in simulation parameters, we find that the resulting ensembles demonstrate a strong convergence in structural properties. In particular, antiparallel contacts between L17–A21 and A30–L34 are prevalent in ensembles of Aβ40, directly forming β sheets in the OPLS and ILDN combinations. A21–A30 commonly forms an interceding region that rarely interacts with the rest of the peptide. Further, Aβ42 contributes new β hairpin motifs involving V40–I41 in both OPLS and ILDN. However, the structural flexibility of the central region and the electrostatic interactions that characterize it are notably different between the different conditions. Further, for OPLS, each of the FAD mutations disrupts central bend character and increases the polymorphism of antiparallel contacts across the central region. However, the studied mutations in the ILDN set primarily encourage more global contacts involving the N-terminus and the central region, and promote the formation of new β topologies that may seed different aggregates involved in disease phenotypes. Furthermore, these differences aside, the large degree of agreement between simulation sets across multiple force fields provides a generalizable characterization of Aβ that is also consistent with experimental data and models.

59 BASIC BIOLOGICAL SCIENCES↗

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗

Equilibrium denaturation and preferential interactions of an RNA tetraloop with urea

Urea is an important organic cosolute with implications in maintaining osmotic stress in cells and differentially stabilizing ensembles of folded biomolecules. We report an equilibrium study of urea-induced denaturation of a hyperstable RNA tetraloop through unbiased replica exchange molecular dynamics. We find that, in addition to destabilizing the folded state, urea smooths the RNA free energy landscape by destabilizing specific configurations, and forming favorable interactions with RNA nucleobases. A linear concentration-dependence of the free energy (m-value) is observed, in agreement with the results of other RNA hairpins and proteins. Additionally, analysis of the hydrogen-bonding and stacking interactions within RNA primarily show temperature-dependence, while interactions between RNA and urea primarily show concentration-dependence. Lastly, our findings provide valuable insight into the effects of urea on RNA folding and describe the thermodynamics of a basic RNA hairpin as a function of solution chemistry.

59 BASIC BIOLOGICAL SCIENCES↗

Foldamer architectures of triazine-based sequence-defined polymers investigated with molecular dynamics simulations and enhanced sampling methods

Triazine-based sequence-defined polymers have recently been developed that are biomimetic and robust (Grate \latin{et al.} Angewandte Chemie 2016). In molecular dynamics (MD) simulations, the triazine polymers were shown to form linear nanorod foldamers through hydrogen bonding and $\pi$-$\pi$ interactions. The nanorod foldamers have motifs resembling those of DNA, $\alpha$-helices, and $\beta$-sheets, and have potential to be useful building blocks for new macromolecules and materials. To understand the formation of nanorod foldamers, we investigate how linker structures in the middle of the triazine polymers lead to folding using MD simulations. We found that a variety of linkers can participate in folding, but that specific linker structures are more favorable than others, depending on the polymer length. Folding of hexamers into well-defined nanorod foldamers was most favorable with pentanediamine and \emph{ortho}-xylenediamine linkers in the center of the polymers. Foldamers with \emph{ortho}-xylenediamine linkers in the center were investigated for longer polymers, i.e., octamers and decamers, using two different enhanced sampling methods, since regular MD simulations had failed to show any folding for these longer polymers. In particular, the recently developed concurrent adaptive sampling (CAS) algorithm (Ahn \latin{et al.} J. Chem. Phys. 2017) and replica exchange molecular dynamics (REMD) were used. We found that the two enhanced sampling methods did lead to the observation of foldamers, and that REMD revealed new foldamer architectures where \emph{cis}-\emph{trans} isomerizations had occurred. Foldamer formation, diversity, and the strengths and limitations of simulation techniques are discussed. These findings provide new insights into the diversity of foldamer architectures for a new type of biomimetic synthetic polymer.

Foldamers, Nanorods, Free energy landscapes, Molec↗

Surface Charge Effects on Fe(II) Sorption and Oxidation at (110) Goethite Surfaces

Iron(III) oxides and oxyhydroxides are among the most reactive minerals in the environment, with surfaces that become charged when immersed in water. The governing role of surface charge over interfacial processes such as metal sorption is well understood. However, its role in interfacial redox reactions, such as when metal sorption is coupled to interfacial electron transfer (ET), is not. This is mainly because surface charge affects not only the types and densities of surface complexes formed but also their respective driving forces for ET. An important case is Fe(II)-catalyzed recrystallization of Fe(III)-oxyhydroxides, in which Fe(II) sorption and interfacial ET are closely linked. We used replica-exchange constant-pH molecular dynamics simulations (Zarzycki, P.; Smith, D. M.; Rosso, K. M. J. Chem. Theory Comput. 2015, 11, 1715–1724) to calculate the distance-dependent electrostatic potential at charged (110) surfaces of goethite particles, assessing its effect on previously computed Fe(II) sorption and interfacial ET free energies (Zarzycki, P.; Kerisit, S.; Rosso, K. M. J. Phys. Chem. C 2015, 119, 3111–3123). We show that Fe(II) adsorbs preferentially as an inner-sphere complex on the negatively charged surface, and as an outer-sphere complex on the positively charged surface because of both electrostatic repulsion and high energy barriers that arise from ordered water layers at the interface. The separation distance between adsorbed Fe(II) and the surface largely dictates adiabatic versus nonadiabatic ET regimes for this interface. The findings help unravel the pH dependence of Fe(II)-catalyzed recrystallization of goethite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗