MD Modeling Research Articles

Cheminformatics-based analysis identified (Z)-2-(2,5-dimethoxy benzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one as an inhibitor of Marburg replication by interacting with NP

The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family, a non-segmented negative-strand RNA virus. This article represents the computer-aided drug design (CADD) approach for identifying drug-like compounds that prevent the MARV virus disease by inhibiting nucleoprotein, which is responsible for their replication. This study used a wide range of in silico drug design techniques to identify potential drugs. Out of 368 natural compounds, 202 compounds passed ADMET, and molecular docking identified the top two molecules (CID: 1804018 and 5280520) with a high binding affinity of −6.77 and −6.672 kcal/mol, respectively. Both compounds showed interactions with the common amino acid residues SER_216, ARG_215, TYR_135, CYS_195, and ILE_108, which indicates that lead compounds and control ligands interact in the common active site/catalytic site of the protein. The negative binding free energies of CID: 1804018 and 5280520 were −66.01 and −31.29 kcal/mol, respectively. Two lead compounds were re-evaluated using MD modeling techniques, which confirmed CID: 1804018 as the most stable when complexed with the target protein. PC3 of the (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) was 8.74 %, whereas PC3 of the 2′-Hydroxydaidzein (CID: 5280520) was 11.25 %. In this study, (Z)-2-(2,5-dimethoxybenzylidene)-6-(2-(4-methoxyphenyl)-2-oxoethoxy) benzofuran-3(2H)-one (CID: 1804018) unveiled the significant stability of the proteins' binding site in ADMET, Molecular docking, MM-GBSA and MD simulation analysis studies, which also showed a high negative binding free energy value, confirming as the best drug candidate which is found in Angelica archangelica which may potentially inhibit the replication of MARV nucleoprotein.

Density functional theory and ReaxFF MD study on steam-induced nitrogen migration mechanism during char gasification

The formation of nitrogen-containing species during char gasification is crucial for emission of nitrogenous pollutants. In this work, the detailed nitrogen migration mechanism during char gasification is studied. Density functional theory (DFT) coupled with ReaxFF MD methods are used to conduct an in-depth analysis on the intrinsic reaction mechanism during Char(N) and steam interaction. DFT results show that orbital electrons of carbon atoms on char surface are driven towards nitrogen atoms by nitrogen functional groups. The electron density of adjacent carbon atoms is weakened, which has a positive charge. Orbital electron properties show that the band energy gaps of three Char(N) models are 3.063 eV, 1.092 eV and 3.328 eV, indicating the reactivity order for three Char(N) models is as follows: Char(N)-2＞Char(N)-1＞Char(N)-3. DFT calculation indicates that the interaction between Char(N) and steam reduces unsaturated carbon atoms and lower the char decomposition activity, which will inhibit the yield of HCN. In contrast, through hydrogen transfer reactions, nitrogen atoms are easily combined with hydrogen atoms, which is more conducive to the formation of ammonia. ReaxFF MD modeling proves that HCN is the main product for Char(N) decomposition under inert atmosphere. Under steam atmosphere, nitrogen atoms in char are more likely to be converted into amino products. The induction of steam provides a large number of active hydrogen radicals, which is able to attack the nitrogen atoms of char and form N–H bonds, thus promoting the formation of ammonia.

Adsorption of Red 141 and methylene blue by cuttlebone: experimental and molecular dynamics study

AbstractThe current study explores the removal of two organic dyes: Reactive Red 141, an anionic dye, and Methylene Blue, a cationic one, via adsorption onto a novel animal-derived biomaterial known as Cuttlebone (Sepia Officinalis). Before conducting experiments, an analysis of the biomaterial was performed. Subsequently, a sequence of experiments was undertaken to investigate the impact of different parameters on adsorption capacity. These parameters included mass of the adsorbent, pH level, duration of contact, and initial concentration of the dye. Findings indicate that Cuttlebone exhibits a more pronounced adsorption affinity for the anionic dye Reactive Red 141 compared to the cationic dye Methylene Blue (MB). The examination of adsorption isotherms for the respective adsorbent/adsorbate systems reveals that the adsorption behavior differs. Specifically, the adsorption of Red 141 on Cuttlebone conforms to the Langmuir model, while the uptake of MB on Cuttlebone shows a superior agreement with the Freundlich model. A peak adsorption capacity of 129.87 mg/g was noted for Red 141, while for MB, it was observed to be 23.86 mg/g. To elucidate the mechanism, the adsorptive characteristics of Red 141 and MB were validated using various methods, including Monte Carlo simulation (MC) and Molecular Dynamics simulation (MD). The results of MC and MD modeling demonstrate that Red 141 is significantly adsorbed onto calcium carbonate via the chemisorption phenomenon. Graphical abstract

Multiscale Modeling and Characterization of Graphene Epoxy Nanocomposite.

This study aims to characterize graphene epoxy nanocomposite properties using multiscale modeling. Molecular dynamics was used to study the nanocomposite at the nanoscale and finite element analysis at the macroscale to complete the multiscale modeling. The coupling of these two scales was carried out using the Irving-Kirkwood averaging method. First, the functionalization of graphene was carried and 6% grafted graphene was selected based on Young's modulus and the tensile strength of the grafted graphene sheet. Functionalized graphene with weight fractions of 1.8, 3.7, and 5.6 wt.% were reinforced with epoxy polymer to form a graphene epoxy nanocomposite. The results showed that the graphene with 3.7 wt.% achieved the highest modulus. Subsequently, a functionalized graphene sheet with an epoxy matrix was developed to obtain the interphase properties using the MD modeling technique. The normal and shear forces at the interphase region of the graphene epoxy nanocomposite were investigated using a traction-separation test to analyze the mechanical properties including Young's modulus and traction forces. The mean stiffness of numerically tested samples with 1.8, 3.7, and 5.6 wt.% graphene and the stiffness obtained from experimental results from the literature were compared. The experimental results are lower than the multiscale model results because the experiments cannot replicate the molecular-scale behavior. However, a similar trend could be observed for the addition of up to 3.7 wt.% graphene. This demonstrated that the graphene with 3.7 wt.% shows improved interphase properties. The macroscale properties of the graphene epoxy nanocomposite models with 1.8 and 3.7 wt.% were comparatively higher.

In silico exploration of deep-sea fungal metabolites as inhibitor of Ebola and Marburg VP35 and VP40.

VP30 and VP40 proteins of Ebola and Marburg viruses have been recognized as potential targets for antiviral drug development due to their essential roles in the viral lifecycle. Targeting these proteins could disrupt key stages of the viral replication process, inhibiting the viruses' ability to propagate and cause disease. The current study aims to perform molecular docking and virtual screening on deep-sea fungal metabolites targeting Marburg virus VP40 Dimer, matrix protein VP40 from Ebola virus Sudan, Ebola VP35 Interferon Inhibitory Domain, and VP35 from Marburg virus. The top ten compounds for each protein target were chosen using the glide score. All the compounds obtained indicate a positive binding interaction. Furthermore, AdmetSAR was utilized to investigate the pharmacokinetics of the inhibitors chosen. Gliotoxin was used as a ligand with Marburg virus VP40 Dimer, Austinol with matrix protein VP40 from Ebola virus Sudan, Ozazino-cyclo-(2,3-dihydroxyl-trp-tyr) with Ebola VP35 Interferon Inhibitory Domain, and Dehydroaustinol with VP35 from Marburg virus. MD modeling and MMPBSA studies were used to provide a better understanding of binding behaviors. Pre-clinical experiments can assist validate our in-silico studies and assess whether the molecule can be employed as an anti-viral drug.

Using NMR diffusion data to validate MD models of disordered proteins: Test case of N-terminal tail of histone H4

MD simulations can provide uniquely detailed models of intrinsically disordered proteins (IDPs). However, these models need careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed field gradient NMR, offers a potentially useful piece of experimental information related to the compactness of the IDP’s conformational ensemble. Here, we investigate, both experimentally and via the MD modeling, the translational diffusion of a 25-residue N-terminal fragment from histone H4 (N-H4). We found that the predicted values of Dtr, as obtained from mean-square displacement of the peptide in the MD simulations, are largely determined by the viscosity of the MD water (which has been reinvestigated as a part of our study). Beyond that, our analysis of the diffusion data indicates that MD simulations of N-H4 in the TIP4P-Ew water give rise to an overly compact conformational ensemble for this peptide. In contrast, TIP4P-D and OPC simulations produce the ensembles that are consistent with the experimental Dtr result. These observations are supported by the analyses of the 15N spin relaxation rates. We also tested a number of empirical methods to predict Dtr based on IDP’s coordinates extracted from the MD snapshots. In particular, we show that the popular approach involving the program HYDROPRO can produce misleading results. This happens because HYDROPRO is not intended to predict the diffusion properties of highly flexible biopolymers such as IDPs. Likewise, recent empirical schemes that exploit the relationship between the small-angle x-ray scattering-informed conformational ensembles of IDPs and the respective experimental Dtr values also prove to be problematic. In this sense, the first-principle calculations of Dtr from the MD simulations, such as demonstrated in this work, should provide a useful benchmark for future efforts in this area.

Measurement and Modeling the Properties and Equilibrium of Fluid Systems Involving Carbon Dioxide and Hydrocarbons

On the basis of molecular dynamics modeling (MD modeling) and experimental data pVTx, a study was made of the dynamic and thermodynamic properties of a binary system based on light gases containing heavy oil (A-B). The solvent (A) used was carbon dioxide and n-alkanes (methane, ethane, and propane) in the supercritical fluid (SCF) state. Measurements of the pVTx properties were carried out in the temperature, density, and pressure ranges near the critical parameters of the light gas-heavy oil systems. Based on pVTx data and MD modeling in the A-B system, the diffusion coefficient (D) was determined near the critical parameters of the solvent. The values of D in the binary system SCF carbon dioxide or alkanes containing (methane, ethane and propane) heavy oil from the Siyazan field of Azerbaijan are calculated. The D SCF value of methane and ethane in the A-B system is higher than in a system containing SCF propane at given concentrations (c or x) of heavy oil and temperature. The value of D SCF of light gases in the A-B system increases with an increase in the concentration of heavy oil up to x = 2.5 wt. %. Diffusing molecules of SCF gases reduce the viscosity of heavy oil in the A-B system. Dependence D = f(c) tends to have an asymptotic value with increasing oil concentration. In the A-B system, the dependence of D SCF gases on pressure has a non-monotonic form. To calculate mixtures of light gases, the modified Peng-Robinson equation of state (PR EOS) was used. The isothermal dependence P-x of the carbon dioxide-methane binary system is approximated. The calculated P-x curves are consistent with the experimental ones in the temperature range 277-345 K.

Leveraging Molecular Dynamics to Improve Porous Electrode Theory Modeling Predictions of Lithium-Ion Battery Cells

Lithium-ion battery cell modeling using physics-based approaches such as porous electrode theory is a powerful tool for battery design and analysis. Performance metrics such as cell power and resistance can be quickly calculated in a pseudo-two-dimensional (P2D) framework and when coupled with thermal models, component level detail of heating and temperature rise can be evaluated1. For engineering of electric vehicle batteries, speed and fidelity of electrochemical models is paramount in a competitive landscape. Physics-based models allow for high fidelity but require detailed knowledge of the cell component material properties. Acquiring these material characteristics typically requires time-consuming and expensive experiments limiting the ability to quickly screen through cell designs. Therefore, engineering assumptions of the materials properties must be made based on prior tests or literature sources necessarily limiting model accuracy. One approach to improve model accuracy and circumvent costly experiments is to use atomistic modeling to calculate battery cell material properties such as kinetics, OCVs, and transport properties without the need of experiments2–4.In this contribution we use molecular dynamics to calculate electrolyte conductivity and lithium-ion diffusion coefficients for a commercial electrolyte. We first validate our MD modeling approach by reproducing experimental measures of electrolyte conductivity for several test systems. We then construct a porous electrode theory model using the computed electrolyte transport values for the commercial system. Using this model, cell resistance and power is calculated and compared to experimental values measured from small-format pouch cells using the same electrolyte. We show how the variability in the MD modeling impacts cell performance metrics and demonstrate the robustness of this approach to improve cell-level model accuracy.

Structure, Mutagenesis, and QM:MM Modeling of 3-Ketosteroid Δ1-Dehydrogenase from Sterolibacterium denitrificans─The Role of a New Putative Membrane-Associated Domain and Proton-Relay System in Catalysis.

3-Ketosteroid Δ1-dehydrogenases (KstD) are important microbial flavin enzymes that initiate the metabolism of steroid ring A and find application in the synthesis of steroid drugs. We present a structure of the KstD from Sterolibacterium denitrificans (AcmB), which contains a previously uncharacterized putative membrane-associated domain and extended proton-relay system. The experimental and theoretical studies show that the steroid Δ1-dehydrogenation proceeds according to the Ping-Pong bi-bi kinetics and a two-step base-assisted elimination (E2cB) mechanism. The mechanism is validated by evaluating the experimental and theoretical kinetic isotope effect for deuterium-substituted substrates. The role of the active-site residues is quantitatively assessed by point mutations, experimental activity assays, and QM/MM MD modeling of the reductive half-reaction (RHR). The pre-steady-state kinetics also reveals that the low pH (6.5) optimum of AcmB is dictated by the oxidative half-reaction (OHR), while the RHR exhibits a slight optimum at the pH usual for the KstD family of 8.5. The modeling confirms the origin of the enantioselectivity of C2-H activation and substrate specificity for Δ4-3-ketosteroids. Finally, the cholest-4-en-3-one turns out to be the best substrate of AcmB in terms of ΔG of binding and predicted rate of dehydrogenation.

Five and six membered heterocyclic rings endowed with azobenzene as dual EGFRT790M and VEGFR-2 inhibitors: design, synthesis, in silico ADMET profile, molecular docking, dynamic simulation and anticancer evaluations.

Novel azobenzene scaffold-joined heterocyclic isoxazole, pyrazole, triazole, and/or triazine moieties have been developed and synthesized utilizing microwave and traditional methods. Our compounds were tested for growth inhibition of A549, MCF-7, HCT-116, and HepG2 tumors by dual targeting the VEGFR-2 and EGFRT790M enzymes. The suggested compound's manner of binding with EGFRT790M and VEGFR-2 active sites was explored through molecular design and MD modeling. The information from the results of the biological screening and the docking studies was highly correlated. The A549 cell line was the one that responded to the novel compound's effects most effectively. Having IC50 values of 5.15, 6.37, 8.44 and 6.23 μM, respectively, 14 was the most effective derivative on the four A549, MCF-7, HCT116 and HepG2 cancer cells. It had greater activity than erlotinib and slightly inferior activities on the tested cell lines than sorafenib, respectively. The cytotoxicity of the most effective derivatives, 5, 6, 10 and 14, was evaluated against typical VERO cell lines. Having IC50 values ranging from 42.32 to 55.20 μM, the results showed that the investigated drugs have modest toxicity against VERO normal cells. Additionally all derivatives were assessed for their dual VEGFR-2 and EGFRT790M inhibitory effects. Among them, derivatives 14, 5 and 10 were established as the greatest inhibitors of VEGFR-2 at IC50 values of 0.95, 1.25 and 1.50 μM correspondingly. As well, derivatives 14, 6, 5 and 10 could inhibit EGFRT790M activity demonstrating strongest effects with IC50 = 0.25, 0.35, 0.40 and 0.50 μM respectively. Furthermore, the ADMET profile was evaluated for compounds 5, 6, 10 and 14 in contrast to reference drugs sorafenib and erlotinib.

Identification of molecular initiating events and key events leading to endocrine disrupting effects of PFOA: Integrated molecular dynamic, transcriptomic, and proteomic analyses

Perfluorooctanoic acid (PFOA) can rapidly activate signaling pathways independent of nuclear hormone receptors through membrane receptor regulation, which leads to endocrine disrupting effects. In the present work, the molecular initiating event (MIE) and the key events (KEs) which cause the endocrine disrupting effects of PFOA have been explored and determined based on molecular dynamics simulation (MD), fluorescence analysis, transcriptomics, and proteomics. MD modeling and fluorescence analysis proved that, on binding to the G protein-coupled estrogen receptor-1 (GPER), PFOA could induce a conformational change in the receptor, turning it into an active state. The results also indicated that the binding to GPER was the MIE that led to the adverse outcome (AO) of PFOA. In addition, the downstream signal transduction pathways of GPER, as regulated by PFOA, were further investigated through genomics and proteomics to identify the KEs leading to thr endocrine disrupting effects. Two pathways (Endocrine resistance, ERP and Estrogen signaling pathway, ESP) containing GPER were regulated by different concentration of PFOA and identified as the KEs. The knowledge of MIE, KEs, and AO of PFOA is necessary to understand the links between PFOA and the possible pathways that lead to its negative effects.

Diclofenac Ion Hydration: Experimental and Theoretical Search for Anion Pairs.

Self-assembly of organic ions in aqueous solutions is a hot topic at the present time, and substances that are well-soluble in water are usually studied. In this work, aqueous solutions of sodium diclofenac are investigated, which, like most medicinal compounds, is poorly soluble in water. Classical MD modeling of an aqueous solution of diclofenac sodium showed equilibrium between the hydrated anion and the hydrated dimer of the diclofenac anion. The assignment and interpretation of the bands in the UV, NIR, and IR spectra are based on DFT calculations in the discrete-continuum approximation. It has been shown that the combined use of spectroscopic methods in various frequency ranges with classical MD simulations and DFT calculations provides valuable information on the association processes of medical compounds in aqueous solutions. Additionally, such a combined application of experimental and calculation methods allowed us to put forward a hypothesis about the mechanism of the effect of diclofenac sodium in high dilutions on a solution of diclofenac sodium.

Benchmarking MD Models of Disordered Proteins using NMR Data on Translational Diffusion

MD trajectories can be viewed as “ultimate models” of disordered proteins. However, these models are in need of careful experimental validation. The coefficient of translational diffusion Dtr, measurable by pulsed-field gradient NMR, offers a measure of compactness for disordered proteins (especially useful for smaller proteins, where SAXS data are unavailable). Here we investigate, both experimentally and via MD modeling, the translational diffusion of 25-residue N-terminal fragment from histone H4 (N-H4).

All-Atom MD Modeling and Simulation of Mechanical Properties of Tropocollagen and Its Cross-Linked Structure

All-Atom MD Modeling and Simulation of Mechanical Properties of Tropocollagen and Its Cross-Linked Structure

Atomistic simulations of dislocation dynamics in δ-Pu-Ga alloys

Molecular dynamics with the modified embedded atom model (MEAM) for interatomic interaction is applied to direct simulations of dislocation dynamics in fcc δ-phase Pu-Ga alloys. First, parameters of the MEAM potential are fitted to accurately reproduce experimental phonon dispersion curves and phonon density of states at ambient conditions. Then the stress-velocity dependence for edge dislocations as well as Pierls stress are obtained in direct MD modeling of dislocation motion using the shear stress relaxation technique. The simulations are performed for different gallium concentrations and the dependence of static yield stress on Ga concentration derived demonstrates good agreement with experimental data. Finally, the influence of radiation defects (primary radiation defects, nano-pores, and radiogenic helium bubbles) on dislocation dynamics is investigated. It is demonstrated that uniformly distributed vacancies and nano-pores have little effect on dislocation dynamics in comparison with that of helium bubbles. The results of the MD simulations evidence that the accumulation of the radiogenic helium in the form of nanometer-sized bubbles is the main factor affecting strength properties during long-term storage. The calculated dependence of static yield stress on helium bubbles concentration for fcc Pu 1wt.% Ga is in good agreement with that obtained in experiments on accelerated aging. The developed technique of static yield stress evaluation is applicable to δ-phase Pu-Ga alloys with arbitrary Ga concentrations.

Interview with David A. Case: On force fields, biomolecular modeling, and NMR

AbstractProf. David Case is based in the Department of Chemistry and Chemical Biology at Rutgers University. In this interview he speaks about force field development and validation, predictive power of MD models, combining physics‐based force fields with empirical scoring functions, MD modeling of disordered proteins and RNA, synergies between MD simulations and NMR measurements, and chemical shift calculations. The video of this interview is available on the YouTube site (URL https://www.youtube.com/watch?v=bumGM1CWA7Y).

MD Modeling of Oxidative Folding in Peptides and Proteins

We are now at the dawn of the new era in protein modeling when it becomes possible to fold proteins in silico “from the first principles”, i.e. using unbiased MD simulations. We have developed an empirical protocol to include the process of disulfide bonding into conventional (unrestrained) MD models of protein folding. The protocol has been tested on 15-amino-acid peptide guanylin, containing four cysteine residues. The fifty guanylin trajectories recorded with GPU-enabled Amber 14 program under ff14SB force field produced thirty eight disulfide-bonded folds, with the isomer distribution that is broadly similar to the one observed experimentally. The PBSA/GBSA energy calculations performed on these MD models suggest that the isomer distribution is under kinetic rather than thermodynamic control. We have also used the new protocol to simulate disulfide bonding in the terminal guanylin segment within the 94-amino-acid prohormone proguanylin. It is envisaged that in future an efficient reactive force field can be constructed along these lines to model protein oxidative folding.

Dependence of the thermal stability of the interface states of d metals (Cu, Pd, Ti, Ni) and Al with graphene on the character of sorption and diffusion mobility in a contact zone

A comparative analysis is performed of the results from MD modeling for the thermal evolution of isolated clusters and interface nanosystems from 300 to 4000 K during contact between clusters and island films of d metals and Al taken for comparison with monolayer and bilayer graphene. It is revealed to what degree (in contrast with isolated clusters) the cohesion energy of contact metal-graphene layers, the initial type of their packing (one- or two-sided coating of graphene with metal films), electron band structure, and transfer properties determine the formation of the thermally stable atomic structure of interface systems.

MD modeling of screw dislocation influence upon initiation and mechanism of BCC-HCP polymorphous transition in iron

The present work is devoted to classical molecular dynamics investigation into microscopic mechanisms of the bcc-hcp transition in iron. The interatomic potential of EAM type used in the calculations was tested for the capability to reproduce ab initio data on energy evolution along the bcc-hcp transformation path (Burgers deformation + shuffe) and then used in the large-scale MD simulations. The large-scale simulations included constant volume deformation along the Burgers path to study the origin and nature of the plasticity, hydrostatic volume compression of defect free samples above the bcc to hcp transition threshold to observe the formation of new phase embryos, and the volume compression of samples containing screw dislocations to study the effect of the dislocations on the probability of the new phase critical embryo formation. The volume compression demonstrated high level of metastability. The transition starts at pressure much higher than the equilibrium one. Dislocations strongly affect the probability of the critical embryo formation and significantly reduce the onset pressure of transition. The dislocations affect also the resulting structure of the samples upon the transition. The formation of layered structure is typical for the samples containing the dislocations. The results of the simulations were compared with the in-situ experimental data on the mechanism of the bcc-hcp transition in iron.

Understanding the Li Disorder and Migration in Cubic Garnet Ionic Conductors through Diffraction Techniques and Computer Modeling

Solid-state lithium ionic conductors have received much attention recently as the issues associated with liquid electrolyte materials were increasingly recognized. Lithium garnet ionic conductors emerged as the most promising candidate in the oxide system owing to their high conductivity and good chemical and thermal stability [1, 2]. Majority of the research done on this family of compounds focused on the characterization of transport properties on a wide range of compositions with different doping strategy [3, 4], leaving a void of knowledge on the conduction mechanism. The limited number of structural studies [5, 6] typically employed a single technique. The lack of cross-check with other techniques left the findings vulnerable to challenges on the ground of limitations of individual technique.To understand local Li disorder and conduction pathway, we applied various diffraction and computational techniques to the lithium garnet oxides. The model material Li5La3Ta2O12 was picked because of its relative simplicity. Diffraction based techniques employed in this study include Rietveld refinement using time-of-flight neutron powder diffraction data, pair distribution analysis using total scattering data and maximum entropy analysis using constant wavelength neutron diffraction data. Static and dynamic structures were modeled with energy minimization method and molecular dynamics using conventional interatomic potentials. Rietveld refinement results revealed large anisotropic displacement factors on both tetrahedral and octahedral Li sites, suggesting strong positional disorder. Nuclear density map as calculated from maximum entropy analysis added more details to the lithium distribution. We adopted the iterative algorithm to minimize the structural biases. At low levels, the densities at the tetrahedral and octahedral sites connected, indicating the conduction pathway. This was confirmed by the modeled static structure where low energy state positions were represented by nuclear density maps obtained using a statistical approach. Pair distribution function analysis using reverse Monte Carlo modeling provided experimental evidence of the local structures and Li disorders. The positional disorders of both Li sites were further confirmed and the occupancies were in good agreement with Rietveld refinement results. Note that this is the first PDF analysis on garnet compounds so far and we proved that useful information can be extracted with this method despite the challenges as posed by the structural complexity and small scattering contribution from Li. Finally, the MD modeling simulated the conduction pathway of Li which is consistent with the indication of other techniques. To sum up, all the techniques tell one consistent story: positional disorders are so strong that the Li ions in Li-stuffed garnet compounds can be consider as composing an amorphous phase (i.e., having no symmetry at all) within a high symmetry framework; both tetrahedral and octahedral sites are involved in the conduction and the conduction pathway can be represented by connecting neighboring tetrahedral and octahedral Li sites. Figure 1. Nuclear density maps generated by (a) Rietveld refinement, (b) maximum entropy method, (c) energy minimization, (d) molecular dynamics; (e) experimental and fitted pair distribution functions.AcknowledgementThis work is supported by the Ceramics Program of National Science Foundation (DMR-1206356). We are grateful to Spallation Neutron Sourse at ORNL, Lujan Neutron Scattering Center at LANL and NIST Center for Neutron Research for making all facilities available. We wish to acknowledge the Michigan State University High Performance Computing Center and the Institute for Cyber-Enabled Research for access to their computing resources.