Unbiased Simulations Research Articles

Mechanistic insights into G-protein activation via phosphorylation mediated non-canonical pathway

Activation of heterotrimeric G-proteins (Gαβγ) downstream to receptor tyrosine kinases (RTKs) is a well-established crosstalk between the signaling pathways mediated by G-protein coupled receptors (GPCRs) and RTKs. While GPCR serves as a guanine exchange factor (GEF) in the canonical activation of Gα that facilitates the exchange of GDP for GTP, the mechanism through which RTK phosphorylations induce Gα activation remains unclear. Recent experimental studies revealed that the epidermal growth factor receptor (EGFR), a well-known RTK, phosphorylates the helical domain tyrosine residues Y154 and Y155 and accelerates the GDP release from the Gαi3, a subtype of Gα-protein. Using well-tempered metadynamics and extensive unbiased molecular dynamics simulations, we captured the GDP release event and identified the intermediates between bound and unbound states through Markov state models. In addition to weakened salt bridges at the domain interface, phosphorylations induced the unfolding of helix αF, which contributed to increased flexibility near the hinge region, facilitating a greater distance between domains in the phosphorylated Gαi3. Although the larger domain separation in the phosphorylated system provided an unobstructed path for the nucleotide, the accelerated release of GDP was attributed to increased fluctuations in several conserved regions like P-loop, switch 1, and switch 2. Overall, this study provides atomistic insights into the activation of G-proteins induced by RTK phosphorylations and identifies the specific structural motifs involved in the process. The knowledge gained from the study could establish a foundation for targeting non-canonical signaling pathways and developing therapeutic strategies against the ailments associated with dysregulated G-protein signaling.

Membrane-assisted tariquidar access and binding mechanisms of human ATP-binding cassette transporter P-glycoprotein.

The human multidrug transporter P-glycoprotein (P-gp) is physiologically essential and of key relevance to biomedicine. Recent structural studies have shed light on the mode of inhibition of the third-generation inhibitors for human P-gp, but the molecular mechanism by which these inhibitors enter the transmembrane sites remains poorly understood. In this study, we utilized all-atom molecular dynamics (MD) simulations to characterize human P-gp dynamics under a potent inhibitor, tariquidar, bound condition, as well as the atomic-level binding pathways in an explicit membrane/water environment. Extensive unbiased simulations show that human P-gp remains relatively stable in tariquidar-free and bound states, while exhibiting a high dynamic binding mode at either the drug-binding pocket or the regulatory site. Free energy estimations by partial nudged elastic band (PNEB) simulations and Molecular Mechanics Generalized Born Surface Area (MM/GBSA) method identify two energetically favorable binding pathways originating from the cytoplasmic gate with an extended tariquidar conformation. Interestingly, free tariquidar in the lipid membrane predominantly adopts extended conformations similar to those observed at the regulatory site. These results suggest that membrane lipids may preconfigure tariquidar into an active ligand conformation for efficient binding to the regulatory site. However, due to its conformational plasticity, tariquidar ultimately moves toward the drug-binding pocket in both pathways, explaining how it acts as a substrate at low concentrations. Our molecular findings propose a membrane-assisted mechanism for the access and binding of the third-generation inhibitors to the binding sites of human P-gp, and offer deeper insights into the molecule design of more potent inhibitors against P-gp-mediated drug resistance.

Peptide Self-Assembly into Amyloid Fibrils: Unbiased All-Atom Simulations.

Protein self-assembly plays an important role in biological systems, accounting for the formation of mesoscopic structures that can be highly symmetric as in the capsid of viruses or disordered as in molecular condensates or exhibit a one-dimensional fibrillar morphology as in amyloid fibrils. Deposits of the latter in tissues of individuals with degenerative diseases like Alzheimer's and Parkinson's has motivated extensive efforts to understand the sequence of molecular events accounting for their formation. These studies aim to identify on-pathway intermediates that may be the targets for therapeutic intervention. This detailed knowledge of fibril formation remains obscure, in part due to challenges with experimental analyses of these processes. However, important progress is being achieved for short amyloid peptides due to advances in our ability to perform completely unbiased all-atom simulations of the self-assembly process. This perspective discusses recent developments, their implications, and the hurdles that still need to be overcome to further advance the field.

Molecular Mechanisms Underlying Medium-Chain Free Fatty Acid-Regulated Activity of the Phospholipase PlaF from Pseudomonas aeruginosa.

PlaF is a membrane-bound phospholipase A1 from Pseudomonas aeruginosa that is involved in remodeling membrane glycerophospholipids (GPLs) and modulating virulence-associated signaling and metabolic pathways. Previously, we identified the role of medium-chain free fatty acids (FFAs) in inhibiting PlaF activity and promoting homodimerization, yet the underlying molecular mechanism remained elusive. Here, we used unbiased and biased molecular dynamics simulations and free energy computations to assess how PlaF interacts with FFAs localized in the water milieu surrounding the bilayer or within the bilayer and how these interactions regulate PlaF activity. Medium-chain FFAs localized in the upper bilayer leaflet can stabilize inactive dimeric PlaF, likely through interactions with charged surface residues, as has been experimentally validated. Potential of mean force (PMF) computations indicate that membrane-bound FFAs may facilitate the activation of monomeric PlaF by lowering the activation barrier for changing into a tilted, active configuration. We estimated that the coupled equilibria of PlaF monomerization-dimerization and tilting at the physiological concentration of PlaF lead to the majority of PlaF forming inactive dimers when in a cell membrane loaded with decanoic acid (C10). This is in agreement with a suggested in vivo product feedback loop and gas chromatography-mass spectrometry profiling results, indicating that PlaF catalyzes the release of C10 from P. aeruginosa membranes. Additionally, we found that C10 in the water milieu can access the catalytic site of active monomeric PlaF, contributing to the competitive component of C10-mediated PlaF inhibition. Our study provides mechanistic insights into how medium-chain FFAs may regulate the activity of PlaF, a potential bacterial drug target.

Structural and Dynamic Analyses of Pathogenic Variants in PIK3R1 Reveal a Shared Mechanism Associated among Cancer, Undergrowth, and Overgrowth Syndromes.

The PI3K enzymes modify phospholipids to regulate cell growth and differentiation. Somatic variants in PI3K are recurrent in cancer and drive a proliferative phenotype. Somatic mosaicism of PIK3R1 and PIK3CA are associated with vascular anomalies and overgrowth syndromes. Germline PIK3R1 variants are associated with varying phenotypes, including immunodeficiency or facial dysmorphism with growth delay, lipoatrophy, and insulin resistance associated with SHORT syndrome. There has been limited study of the molecular mechanism to unify our understanding of how variants in PIK3R1 drive both undergrowth and overgrowth phenotypes. Thus, we compiled genomic variants from cancer and rare vascular anomalies and sought to interpret their effects using an unbiased physics-based simulation approach for the protein complex. We applied molecular dynamics simulations to mechanistically understand how genetic variants affect PIK3R1 and its interactions with PIK3CA. Notably, iSH2 genetic variants associated with undergrowth destabilize molecular interactions with the PIK3CA receptor binding domain in simulations, which is expected to decrease activity. On the other hand, overgrowth and cancer variants lead to loss of inhibitory interactions in simulations, which is expected to increase activity. We find that all disease variants display dysfunctions on either structural characteristics or intermolecular interaction energy. Thus, this comprehensive characterization of novel mosaic somatic variants associated with two opposing phenotypes has mechanistic importance and biomedical relevance and may aid in future therapeutic developments.

Free energy profile of the substrate-induced occlusion of the human serotonin transporter.

The serotonin transporter (SERT) is a member of the Solute Carrier 6 (SLC6) family and is responsible for maintaining the appropriate level of serotonin in the brain. Dysfunction of SERT has been linked to several neuropsychiatric disorders, including depression, anxiety and obsessive-compulsive disorder. Therefore, an in-depth understanding of the mechanism on an atomistic level, coupled with a quantification of transporter dynamics and the associated free energies is required. Here, we constructed Markov state models (MSMs) from extensive unbiased molecular dynamics simulations to quantify the free energy profile of serotonin (5HT) triggered SERT occlusion and explored the driving forces of the mechanism of occlusion. Our results reveal that SERT occludes via multiple intermediate conformations and show that the motion of occlusion is energetically downhill for the 5HT-bound transporter. Force distribution analyses show that the interactions of 5HT with the bundle domain are crucial. During occlusion, attractive forces steadily increase and pull on the bundle domain, which leads to SERT occlusion. Some interactions become repulsive upon full occlusion, suggesting that SERT creates pressure on 5HT to promote its movement towards the cytosol.

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG-PLGA Polymer Nanoparticles.

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.

Fouling behavior of protein in mixed solvent systems: A combined experimental and simulation study

Membrane fouling in organic solvent environments remains poorly explored despite its significance in chemical and pharmaceutical industries. This study uses molecular dynamics (MD) simulations and experiments to explore lysozyme fouling in water, as well as four organic solvent environments, namely, 30 % v/v and 50 % v/v isopropyl alcohol (IPA), and 30 % v/v and 50 % v/v dimethyl sulfoxide (DMSO). Experimentally, flux declines were least with IPA and worst with DMSO. Biased simulations indicate the worst fouling in DMSO is tied to the most attractive lysozyme-membrane energy in the presence of DMSO. However, the relative attractive energies for IPA and water do not agree with the relative flux declines, indicating other factors are more influential when the interaction energies are similar. To understand the gentler flux decline for IPA despite the more attractive lysozyme-membrane energy, radial distribution functions (RDFs) were obtained from unbiased simulations. Analyses of the water and solvent films around both the membrane and the lysozyme molecule reveal that the denser water film around both entities induced by the presence of IPA serves as a barrier for fouling and thus leads to less flux decline. The results underscore the complexity of fouling in organic solvent systems, cautioning against direct use of the understanding based on aqueous systems.

Interaction between Permeation Enhancers and Lipid Bilayers.

Permeation enhancers (PEs) are a class of molecules that interact with the epithelial membrane and transiently increase its transcellular permeability. Although there have been few clinical trials of PE coformulated drugs, the mechanism of action of PEs remains elusive. In this paper, the interaction between two archetypes of PEs [salcaprozate sodium (SNAC) and sodium caprate (C10)] and membranes is investigated with extensive all-atom molecular dynamics simulations. The simulations show that (1) the association between the neutral PEs and membranes is favored in free energy, (2) the propensity of neutral PE aggregation is larger in aqueous solution than in lipid bilayers, (3) the equilibrium distribution of neutral PEs in membranes is fast, e.g., accessible with unbiased MD simulations, and (4) the micelle of neutral PEs formed in aqueous solution does not rupture the membranes (e.g., not forming pores or breaking up the membrane) under simulation conditions. All results combined, this study indicates that PEs insert into the membranes in an equilibrium or near equilibrium process. This study lays the foundation for future investigations of how PEs impact the free energy of permeation for small molecules.

Transfer learning of hyperparameters for fast construction of anisotropic GPR models: design and application to the machine-learned force field FFLUX.

The polarisable machine-learned force field FFLUX requires pre-trained anisotropic Gaussian process regression (GPR) models of atomic energies and multipole moments to propagate unbiased molecular dynamics simulations. The outcome of FFLUX simulations is highly dependent on the predictive accuracy of the underlying models whose training entails determining the optimal set of model hyperparameters. Unfortunately, traditional direct learning (DL) procedures do not scale well on this task, especially when the hyperparameter search is initiated from a (set of) random guess solution(s). Additionally, the complexity of the hyperparameter space (HS) increases with the number of geometrical input features, at least for anisotropic kernels, making the optimization of hyperparameters even more challenging. In this study, we propose a transfer learning (TL) protocol that accelerates the training process of anisotropic GPR models by facilitating access to promising regions of the HS. The protocol is based on a seeding-relaxation mechanism in which an excellent guess solution is identified by rapidly building one or several small source models over a subset of the target training set before readjusting the previous guess over the entire set. We demonstrate the performance of this protocol by building and assessing the performance of DL and TL models of atomic energies and charges in various conformations of benzene, ethanol, formic acid dimer and the drug fomepizole. Our experiments suggest that TL models can be built one order of magnitude faster while preserving the quality of their DL analogs. Most importantly, when deployed in FFLUX simulations, TL models compete with or even outperform their DL analogs when it comes to performing FFLUX geometry optimization and computing harmonic vibrational modes.

Resolving heterogeneous particle mobility in deeply quenched liquid iron: an ultra-fast assembly-free two-step nucleation mechanism.

Despite intensive research, little is known about the intermediate state of phase transforming materials, which may form the missing link between e.g. liquids and solids on the nanoscale. The unraveling of the nanoscale interplay between the structure and dynamics of the intermediate state of phase transformations (through which e.g. crystal nucleation proceeds) is one of the biggest challenges and unsolved problems of materials science. Here we show using unbiased molecular dynamics simulations and spatially resolved atomic displacement maps (d-maps) that upon deep quenching the solidification of undercooled liquid iron proceeds through the formation of metastable pre-nucleation clusters (PNCs). We also reveal that the hitherto hidden PNCs are nearly immobile (dynamically arrested) and the related heterogeneity in atomic mobilities becomes clearly visible on atomic displacement-maps (d-maps) when atomic jumps are referenced to the final crystalline positions. However, this is in contrast to PNCs found in molecular solutions, in which PNCs tend to aggregate, move and crystallize via an activated process. Coordination filtered d-maps resolved in real space directly demonstrate that previously unseen highly ramified intermediate atomic clusters with a short lifetime emerge after incubation of undercooled liquid iron. The supercooled liquid iron is neither a spinodal system nor a liquid and undergoes a transition into a specific state called a quasi-liquid state within the temperature regime of 700-1250 K (0.5Tm > 0.7Tm, where the melting point is Tm ≈ 1811 K). Below 700 K the supercooled system is spinodal-like and above 1300 K it behaves like an ordinary liquid with long incubation times. A two-step process is proposed to explain the anomalous drop in the incubation time in the temperature regime of 700-1250 K. The 1st step is activated aggregation of small atomic clusters followed by assembly-free nearly barrierless ultrafast growth of early ramified prenucleation clusters called germs. The display and characterization of the hidden PNCs in computer simulations could provide new perspectives on the deeper understanding of the long-standing problem of precursor development during crystal nucleation following deep quenching.

The density-threshold affinity:Calculating lipid binding affinities from unbiased coarse-grained molecular dynamics simulations.

Many membrane proteins are sensitive to their local lipid environment. As structural methods for membrane proteins have improved, there is growing evidence of direct, specific binding of lipids to protein surfaces. Unfortunately the workhorse of understanding protein-small molecule interactions, the binding affinity for a given site, is experimentally inaccessible for these systems. Coarse-grained molecular dynamics simulations can be used to bridge this gap, and are relatively straightforward to learn. Such simulations allow users to observe spontaneous binding of lipids to membrane proteins and quantify localized densities of individual lipids or lipid fragments. In this chapter we outline a protocol for extracting binding affinities from these localized distributions, known as the "density threshold affinity." The density threshold affinity uses an adaptive and flexible definition of site occupancy that alleviates the need to distinguish between "bound'' lipids and bulk lipids that are simply diffusing through the site. Furthermore, the method allows "bead-level" resolution that is suitable for the case where lipids share binding sites, and circumvents ambiguities about a relevant reference state. This approach provides a convenient and straightforward method for comparing affinities of a single lipid species for multiple sites, multiple lipids for a single site, and/or a single lipid species modeled using multiple forcefields.

Structures of Th4+ aqueous solutions: insights from AIMD and metadynamics simulations.

Solution chemistry of actinide ions is critical to understanding the solvation behaviors and hydrolysis process. Using tetravalent thorium ion Th4+ as a representative example, we investigate the local structures and dynamic behaviors of hydrated Th4+ ions by ab initio molecular dynamics (AIMD) simulations using the recently developed norm-conserving pseudopotentials and basis sets optimized for actinides (J.-B. Lu et al., J. Chem. Theory Comput. 2021, 17, 3360-3371). AIMD simulations reveal two distinct solvation shells, with the first shell comprising 9 water molecules at approximately rTh-O = 2.50 Å and exhibiting a tricapped trigonal prism geometry. These conclusions are confirmed through metadynamics simulations and further structural analysis. AIMD simulations also show the slight effect of temperature and counterions on the structure of the solution. The structured solvation shells of the highly charged Th4+ ion with the specific geometry, distinct from the structure of liquid water, lead to corresponding structural changes in the hydrogen bond network in water. Additionally, beyond the solvent-shared ion pair (SIP) state observed in the unbiased AIMD simulations, the metadynamics simulations reconstruct a two-dimensional free energy surface that clearly indicates the potential stability of the contact ion pair (CIP) state in the system with Cl- as a counterion. The findings in this work provide insights into the solution chemistry of actinides and serve as a reference for studying other actinide solution systems.

Binding of Cholesterol to the N-Terminal Domain of the NPC1L1 Transporter: Analysis of the Epimerization-Related Binding Selectivity and Loop Mutations.

Cholesterol is a fat-like substance with a pivotal physiological relevance in humans, and its homeostasis is tightly regulated by various cellular processes, including the import in the small intestine and the reabsorption in the biliary ducts by the Niemann-Pick C1 Like 1 (NPC1L1) importer. NPC1L1 can mediate the absorption of a variety of sterols but strikingly exhibits a large sensitivity to cholesterol epimerization. This study examines the molecular basis of the epimerization-related selective binding of cholesterol by combining extended unbiased molecular dynamics simulations of the apo and holo species of the N-terminal domain of wild-type NPC1L1, in conjunction with relative binding free energy, umbrella sampling, and well-tempered metadynamics calculations. The analysis of the results discloses the existence of two distinct binding modes for cholesterol and epi-cholesterol. The former binds deeper in the cavity, forming key hydrogen-bond interactions with Q95, S56, and a water molecule. In contrast, epi-cholesterol is shifted ca. 3 Å to the mouth of the cavity and the transition to the Q95 site is prevented by an energetic barrier of 4.1 kcal·mol-1. Thus, the configuration of the hydroxyl group of cholesterol, together with the presence of a structural water molecule, is a key feature for effective absorption. Finally, whereas these findings may seemingly be challenged by single-point mutations that impair cholesterol transport but have a mild impact on the binding of cholesterol to the Q95 binding site, our results reveal that they have a drastic influence on the conformational landscape of the α8/β7 loop in the apo species compared to the wild-type protein. Overall, the results give support to the functional role played by the α8/β7 loop in regulating the access of ligands to NPC1L1, and hence to interpreting the impact of these mutations on diseases related to disruption of sterol absorption, paving the way to understanding certain physiological dysfunctions.

Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations.

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Deciphering insights into the binding mechanism and plasticity of Telacebec with M. tuberculosis cytochrome bcc-aa3 supercomplex through an unbiased molecular dynamics simulation, free-energy analysis, and DFT study

The cytochrome bcc-aa3 supercomplex, a key component in the electron transport chain pathway involved in bacterial energy production and homeostasis, is a clinically validated target for tuberculosis (TB), leading to Telacebec (Q203). Telacebec is a potent candidate drug under Phase II clinical development for the treatment of drug-sensitive and drug-resistant TB. Recently, the cryo-electron microscopy structure of this supercomplex from Mycobacterium tuberculosis (Mtb) complexed with Q203 was resolved at 6.9 Å resolution (PDB ID: 7E1W). To understand the binding site (QP site) flexibility and Q203’s stability at the QP site of the Mtb cytochrome bcc complex, we conducted molecular dynamics (MD) simulation and free energy analysis on this complex in an explicit hydrated lipid bilayer environment for 500 ns. Through this study, the persistence of a range of direct and indirect interactions was observed over the course of the simulation. The significance of the interactions with His375, Tyr161, Ala178, Ala179, Ile183, His355, Leu356, and Thr313 is underlined. Electrostatic energy was the primary source of the net binding free energy, regardless of the important interacting residues. The overall binding free energy for Q203 was −112.84 ± 7.73 kcal/mol, of which the electrostatic and lipophilic energy contributions were −116.31 ± 1.14 and −21.32 ± 2.35 kcal/mol, respectively. Meanwhile, DFT calculations were utilized to elucidate Q203’s molecular properties. Overall, this study deciphers key insights into the cytochrome bcc-aa3 supercomplex with Q203 on the ground of molecular mechanics and quantum mechanics that may facilitate structure-based drug design and optimization for the discovery of the next-generation antitubercular drug(s). Communicated by Ramaswamy H. Sarma

Dynamics behavior of PE and PET oligomers in lipid bilayer simulations

In recent years many investigators have been concerned about the toxicity and potential health hazards of micro- and nanoplastics. However, we are still lacking a good understanding of the methods of their transport into the human body and subsequently within cells. This is especially true at the lower nanometer scale; these particles are potentially more dangerous than their micrometer counterparts due to their easier permeation into cells. In this study we used both unbiased molecular dynamics simulations and steered umbrella sampling simulations to explore the interactions of polyethylene terephthalate (PET) and polyethylene (PE) oligomers in phospholipid bilayers. Our simulations revealed that the bilayers did not represent significant energy barriers to the small oligomers; not only did they readily enter the cell membrane but they also became concentrated into specific parts of the membrane. The larger PET tetramers exhibited a strong aggregation in water but were the least likely to permeate through or into the membranes. It is possible that PE monomers and tetramers can become concentrated into membranes while PET monomers are more likely to pass through or concentrate just inside the membrane surface. Passive transport of microplastics into cells is, however, likely limited to particles of a few nanometers in diameter.

A stochastic interpretation of the parametrix method

UDC 519.21 We revisit, in a didactic manner and by using stochastic analysis, the parametrix method and its application to unbiased simulation. We consider, in particular, the case of one-dimensional diffusions without drift.

Effect of Framework Composition and NH3 on the Diffusion of Cu+ in Cu-CHA Catalysts Predicted by Machine-Learning Accelerated Molecular Dynamics.

Cu-exchanged zeolites rely on mobile solvated Cu+ cations for their catalytic activity, but the role of the framework composition in transport is not fully understood. Ab initio molecular dynamics simulations can provide quantitative atomistic insight but are too computationally expensive to explore large length and time scales or diverse compositions. We report a machine-learning interatomic potential that accurately reproduces ab initio results and effectively generalizes to allow multinanosecond simulations of large supercells and diverse chemical compositions. Biased and unbiased simulations of [Cu(NH3)2]+ mobility show that aluminum pairing in eight-membered rings accelerates local hopping and demonstrate that increased NH3 concentration enhances long-range diffusion. The probability of finding two [Cu(NH3)2]+ complexes in the same cage, which is key for SCR-NOx reaction, increases with Cu content and Al content but does not correlate with the long-range mobility of Cu+. Supporting experimental evidence was obtained from reactivity tests of Cu-CHA catalysts with a controlled chemical composition.

Passive permeability controls synthesis for the allelochemical sorgoleone in sorghum root exudate

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce multiple small molecules that are released via root exudates into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a quinone analog and interferes with photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential to exude sorgoleone efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico assessment for sorgoleone and its precursors to passively permeate biological membranes. To facilitate accurate simulation, CHARMM parameters were newly optimized for sorgoleone and its precursors. These parameters were used to conduct 1 μs of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, suggesting that the precursor molecules may remain in the same leaflet for access by biosynthetic P450 enzymes. Since no sorgoleone was extracted during unbiased simulations, we compute a permeability coefficient using the inhomogeneous solubility diffusion model. The requisite free energy and diffusivity profiles for sorgoleone through a sorghum membrane model were determined through Replica Exchange Umbrella Sampling (REUS) simulations. The REUS calculations highlight that any soluble sorgoleone would quickly insert into a lipid bilayer, and would readily transit. When sorgoleone forms aggregates in root exudate as indicated by our equilibrium simulations, aggregate formation would lower the effective concentration in aqueous solution, creating a concentration gradient that would facilitate passive transport. This suggests that sorgoleone synthesis occurs within sorghum root cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein once the extracellular sorgoleone aggregate is formed.