The effect of polymer coating on nanoparticles' interaction with lipid membranes studied by coarse-grained molecular dynamics simulations.

Nanoparticles' (NPs) permeation through cell membranes, whether it happens via passive or active transport, is an essential initial step for their cellular internalization. The NPs' surface coating impacts the way they translocate through the lipid bilayer and the spontaneity of the process. Understanding the molecular details of NPs' interaction with cell membranes allows the design of nanosystems with optimal characteristics for crossing the lipid bilayer: computer simulations are a powerful tool for this purpose. In this work, we have performed coarse-grained molecular dynamics simulations and free energy calculations on spherical titanium dioxide NPs conjugated with polymer chains of different chemical compositions. We have demonstrated that the hydrophobic/hydrophilic character of the chains, more than the nature of their terminal group, plays a crucial role in determining the NPs' interaction with the lipid bilayer and the thermodynamic spontaneity of NPs' translocation from water to the membrane. We envision that this computational work will be helpful to the experimental community in terms of the rational design of NPs for efficient cell membrane permeation.

Click-free imaging of carbohydrate trafficking in live cells using an azido photothermal probe.

Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.

Flexibility of Binding Site is Essential to the Ca2+ Selectivity in EF-Hand Calcium-Binding Proteins.

High binding affinity and selectivity of metal ions are essential to the function of metalloproteins. Thus, understanding the factors that determine these binding characteristics is of major interest for both fundamental mechanistic investigations and guiding of the design of novel metalloproteins. In this work, we perform QM cluster model calculations and quantum mechanics/molecular mechanics (QM/MM) free energy simulations to understand the binding selectivity of Ca2+ and Mg2+ in the wild-type carp parvalbumin and its mutant. While a nonpolarizable MM model (CHARMM36) does not lead to the correct experimental trend, treatment of the metal binding site with the DFTB3 model in a QM/MM framework leads to relative binding free energies (ΔΔGbind) comparable with experimental data. For the wild-type (WT) protein, the calculated ΔΔGbind is ∼6.6 kcal/mol in comparison with the experimental value of 5.6 kcal/mol. The good agreement highlights the value of a QM description of the metal binding site and supports the role of electronic polarization and charge transfer to metal binding selectivity. For the D51A/E101D/F102W mutant, different binding site models lead to considerable variations in computed binding affinities. With a coordination number of seven for Ca2+, which is shown by QM/MM metadynamics simulations to be the dominant coordination number for the mutant, the calculated relative binding affinity is ∼4.8 kcal/mol, in fair agreement with the experimental value of 1.6 kcal/mol. The WT protein is observed to feature a flexible binding site that accommodates a range of coordination numbers for Ca2+, which is essential to the high binding selectivity for Ca2+ over Mg2+. In the mutant, the E101D mutation reduces the flexibility of the binding site and limits the dominant coordination number of Ca2+ to be seven, thereby leading to reduced binding selectivity against Mg2+. Our results highlight that the binding selectivity of metal ions depends on both the structural and dynamical properties of the protein binding site.

The catalytic mechanism of the RNA methyltransferase METTL3.

The complex of methyltransferase-like proteins 3 and 14 (METTL3-14) is the major enzyme that deposits N6-methyladenosine (m6A) modifications on messenger RNA (mRNA) in humans. METTL3-14 plays key roles in various biological processes through its methyltransferase (MTase) activity. However, little is known about its substrate recognition and methyl transfer mechanism from its cofactor and methyl donor S-adenosylmethionine (SAM). Here, we study the MTase mechanism of METTL3-14 by a combined experimental and multiscale simulation approach using bisubstrate analogues (BAs), conjugates of a SAM-like moiety connected to the N6-atom of adenosine. Molecular dynamics simulations based on crystal structures of METTL3-14 with BAs suggest that the Y406 side chain of METTL3 is involved in the recruitment of adenosine and release of m6A. A crystal structure with a BA representing the transition state of methyl transfer shows a direct involvement of the METTL3 side chains E481 and K513 in adenosine binding which is supported by mutational analysis. Quantum mechanics/molecular mechanics (QM/MM) free energy calculations indicate that methyl transfer occurs without prior deprotonation of adenosine-N6. Furthermore, the QM/MM calculations provide further support for the role of electrostatic contributions of E481 and K513 to catalysis. The multidisciplinary approach used here sheds light on the (co)substrate binding mechanism, catalytic step, and (co)product release, and suggests that the latter step is rate-limiting for METTL3. The atomistic information on the substrate binding and methyl transfer reaction of METTL3 can be useful for understanding the mechanisms of other RNA MTases and for the design of transition state analogues as their inhibitors.

24-hour average PM2.5 concentration caused by aircraft in Chinese airports from Jan. 2006 to Dec. 2023.

Since 2006, the rapid development of China's aviation industry has been accompanied by a significant increase in one of its emissions, namely, PM2.5, which poses a substantial threat to human health. However, little data is describing the PM2.5 concentration caused by aircraft activities. This study addresses this gap by initially computing the monthly PM2.5 emissions of the landing-take-off (LTO) stage from Jan. 2006 to Dec. 2023 for 175 Chinese airports, employing the modified BFFM2-FOA-FPM method. Subsequently, the study uses the Gaussian diffusion model to measure the 24-hour average PM2.5 concentration resulting from flight activities at each airport. This study mainly draws the following conclusions: Between 2006 and 2023, the highest recorded PM2.5 concentration data at all airports was observed in 2018, reaching 5.7985 micrograms per cubic meter, while the lowest point was recorded in 2022, at 2.0574 micrograms per cubic meter. Moreover, airports with higher emissions are predominantly located in densely populated and economically vibrant regions such as Beijing, Shanghai, Guangzhou, Chengdu, and Shenzhen.

Sequence Sensitivity in Membrane Remodeling by Polyampholyte Condensates.

Intrinsically disordered peptides (IDPs) have been found to undergo liquid-liquid phase separation (LLPS) and produce complex coacervates that play numerous regulatory roles in the cell. Recent experimental studies have discovered that LLPS at or near the membrane surface helps in the biomolecular organization during signaling events and can significantly alter the membrane morphology. However, the molecular mechanism and microscopic details of such processes still remain unclear. Here we study the effect of polyampholyte and polyelectrolyte condensation on two different anionic membranes, as they represent a majority of naturally occurring IDPs. The polyampholytes are fifty-residue polymers, made of glutamate(E) and lysine(K) with different charge patterns. The polyelectrolytes are separate chains of E25 and K25. We first calibrate the MARTINI v3.0 force field and then perform long-time-scale coarse-grained molecular dynamics simulations. We find that condensates formed by all the polyampholytes get adsorbed on the membrane. However, the strong polyampholytes (i.e., blocky sequences) can remodel the membranes more prominently than the weaker ones (i.e., scrambled sequences). Condensates formed by the blocky sequences induce a significant negative curvature (∼0.1 nm-1) and local demixing of lipids, whereas those by the scrambled sequences tend to wet the membrane to a greater extent without generating significant curvature or demixing. We perform several microscopic analyses to characterize the nature of the interaction between membranes and these condensates. Our analyses of interaction energetics reveal that membrane remodeling and/or wetting are favored by enhanced interactions between polyampholytes with lipids and the counterions.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields.

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

The juxtamembrane linker of synaptotagmin 1 regulates Ca2+ binding via liquid-liquid phase separation.

Synaptotagmin (syt) 1, a Ca2+ sensor for synaptic vesicle exocytosis, functions in vivo as a multimer. Syt1 senses Ca2+ via tandem C2-domains that are connected to a single transmembrane domain via a juxtamembrane linker. Here, we show that this linker segment harbors a lysine-rich, intrinsically disordered region that is necessary and sufficient to mediate liquid-liquid phase separation (LLPS). Interestingly, condensate formation negatively regulates the Ca2+-sensitivity of syt1. Moreover, Ca2+ and anionic phospholipids facilitate the observed phase separation, and increases in [Ca2+]i promote the fusion of syt1 droplets in living cells. Together, these observations suggest a condensate-mediated feedback loop that serves to fine-tune the ability of syt1 to trigger release, via alterations in Ca2+ binding activity and potentially through the impact of LLPS on membrane curvature during fusion reactions. In summary, the juxtamembrane linker of syt1 emerges as a regulator of syt1 function by driving self-association via LLPS.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR.

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of cooperativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semiquantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different rescuabilities observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same noninducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscores the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions and therefore provides quantitative guidance to allostery modulation for therapeutic and engineering applications.

The impact of Chinese airport infrastructure on airline pollutant emissions: A hybrid stochastic-neural network approach based on utility functions.

With China being the world's largest emitter of greenhouse gases and its aviation sector burgeoning, the environmental performance of Chinese airlines has global significance. Amidst rising demands for eco-friendly practices from both customers and regulators, the interplay between airport infrastructure and environmental performance becomes pivotal. This research offers an innovative methodology to gauge the environmental performance of Chinese airlines, emphasizing the distance traveled between airports using weighted additive utility functions. Leveraging neural networks, the study investigates the impact of various airport infrastructural characteristics on environmental performance. Noteworthy findings indicate that ground control measures, automatic information services at origin airports, surface concrete on runways at both ends, and a centerline lighting system in destination airports positively influence environmental performance. In contrast, longer and wider runways at origin airports, increased distances to control towers, and asphalt runways at destination airports adversely affect it. These insights not only underscore the importance of strategic infrastructure enhancements for reducing carbon footprints but also hold profound policy implications. As global climate change remains at the forefront, fostering sustainable airport infrastructure in China can significantly contribute to worldwide mitigation efforts.

A parametrized two-domain thermodynamic model explains diverse mutational effects on protein allostery.

New experimental findings continue to challenge our understanding of protein allostery. Recent deep mutational scanning study showed that allosteric hotspots in the tetracycline repressor (TetR) and its homologous transcriptional factors are broadly distributed rather than spanning well-defined structural pathways as often assumed. Moreover, hotspot mutation-induced allostery loss was rescued by distributed additional mutations in a degenerate fashion. Here, we develop a two-domain thermodynamic model for TetR, which readily rationalizes these intriguing observations. The model accurately captures the in vivo activities of various mutants with changes in physically transparent parameters, allowing the data-based quantification of mutational effects using statistical inference. Our analysis reveals the intrinsic connection of intra- and inter-domain properties for allosteric regulation and illustrate epistatic interactions that are consistent with structural features of the protein. The insights gained from this study into the nature of two-domain allostery are expected to have broader implications for other multidomain allosteric proteins.

B56δ long-disordered arms form a dynamic PP2A regulation interface coupled with global allostery and Jordan's syndrome mutations.

Intrinsically disordered regions (IDR) and short linear motifs (SLiMs) play pivotal roles in the intricate signaling networks governed by phosphatases and kinases. B56δ (encoded by PPP2R5D) is a regulatory subunit of protein phosphatase 2A (PP2A) with long IDRs that harbor a substrate-mimicking SLiM and multiple phosphorylation sites. De novo missense mutations in PPP2R5D cause intellectual disabilities (ID), macrocephaly, Parkinsonism, and a broad range of neurological symptoms. Our single-particle cryo-EM structures of the PP2A-B56δ holoenzyme reveal that the long, disordered arms at the B56δ termini fold against each other and the holoenzyme core. This architecture suppresses both the phosphatase active site and the substrate-binding protein groove, thereby stabilizing the enzyme in a closed latent form with dual autoinhibition. The resulting interface spans over 190 Šand harbors unfavorable contacts, activation phosphorylation sites, and nearly all residues with ID-associated mutations. Our studies suggest that this dynamic interface is coupled to an allosteric network responsive to phosphorylation and altered globally by mutations. Furthermore, we found that ID mutations increase the holoenzyme activity and perturb the phosphorylation rates, and the severe variants significantly increase the mitotic duration and error rates compared to the normal variant.

Synaptotagmin-7 outperforms synaptotagmin-1 to promote the formation of large, stable fusion pores via robust membrane penetration.

Synaptotagmin-1 and synaptotagmin-7 are two prominent calcium sensors that regulate exocytosis in neuronal and neuroendocrine cells. Upon binding calcium, both proteins partially penetrate lipid bilayers that bear anionic phospholipids, but the specific underlying mechanisms that enable them to trigger exocytosis remain controversial. Here, we examine the biophysical properties of these two synaptotagmin isoforms and compare their interactions with phospholipid membranes. We discover that synaptotagmin-1-membrane interactions are greatly influenced by membrane order; tight packing of phosphatidylserine inhibits binding due to impaired membrane penetration. In contrast, synaptotagmin-7 exhibits robust membrane binding and penetration activity regardless of phospholipid acyl chain structure. Thus, synaptotagmin-7 is a super-penetrator. We exploit these observations to specifically isolate and examine the role of membrane penetration in synaptotagmin function. Using nanodisc-black lipid membrane electrophysiology, we demonstrate that membrane penetration is a critical component that underlies how synaptotagmin proteins regulate reconstituted, exocytic fusion pores in response to calcium.

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method.

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

Modulation of Allostery with Multiple Mechanisms by Hotspot Mutations in TetR.

Modulating allosteric coupling offers unique opportunities for biomedical applications. Such efforts can benefit from efficient prediction and evaluation of allostery hotspot residues that dictate the degree of co-operativity between distant sites. We demonstrate that effects of allostery hotspot mutations can be evaluated qualitatively and semi-quantitatively by molecular dynamics simulations in a bacterial tetracycline repressor (TetR). The simulations recapitulate the effects of these mutations on abolishing the induction function of TetR and provide a rationale for the different degrees of rescuability observed to restore allosteric coupling of the hotspot mutations. We demonstrate that the same non-inducible phenotype could be the result of perturbations in distinct structural and energetic properties of TetR. Our work underscore the value of explicitly computing the functional free energy landscapes to effectively evaluate and rank hotspot mutations despite the prevalence of compensatory interactions, and therefore provide quantitative guidance to allostery modulation for therapeutic and engineering applications.

The catalytic mechanism of the RNA methyltransferase METTL3.

The complex of methyltransferase-like proteins 3 and 14 (METTL3-14) is the major enzyme that deposits N6-methyladenosine (m6A) modifications on mRNA in humans. METTL3-14 plays key roles in various biological processes through its methyltransferase (MTase) activity. However, little is known about its substrate recognition and methyl transfer mechanism from its cofactor and methyl donor S-adenosylmethionine (SAM). Here, we study the MTase mechanism of METTL3-14 by a combined experimental and multiscale simulation approach using bisubstrate analogues (BAs), conjugates of a SAM-like moiety connected to the N6-atom of adenosine. Molecular dynamics simulations based on crystal structures of METTL3-14 with BAs suggest that the Y406 side chain of METTL3 is involved in the recruitment of adenosine and release of m6A. A crystal structure with a bisubstrate analogue representing the transition state of methyl transfer shows a direct involvement of the METTL3 side chains E481 and K513 in adenosine binding which is supported by mutational analysis. Quantum mechanics/molecular mechanics (QM/MM) free energy calculations indicate that methyl transfer occurs without prior deprotonation of adenosine-N6. Furthermore, the QM/MM calculations provide further support for the role of electrostatic contributions of E481 and K513 to catalysis. The multidisciplinary approach used here sheds light on the (co)substrate binding mechanism, catalytic step, and (co)product release catalysed by METTL3, and suggests that the latter step is rate-limiting. The atomistic information on the substrate binding and methyl transfer reaction of METTL3 can be useful for understanding the mechanisms of other RNA MTases and for the design of transition state analogues as their inhibitors.

The juxtamembrane linker of synaptotagmin 1 regulates Ca2+ binding via liquid-liquid phase separation.

Synaptotagmin (syt) 1, a Ca2+ sensor for synaptic vesicle exocytosis, functions in vivo as a multimer. Syt1 senses Ca2+ via tandem C2-domains that are connected to a single transmembrane domain via a juxtamembrane linker. Here, we show that this linker segment harbors a lysine-rich, intrinsically disordered region that is necessary and sufficient to mediate liquid-liquid phase separation (LLPS). Interestingly, condensate formation negatively regulates the Ca2+-sensitivity of syt1. Moreover, Ca2+ and anionic phospholipids facilitate the observed phase separation, and increases in [Ca2+]i promote the fusion of syt1 droplets in living cells. Together, these observations suggest a condensate-mediated feedback loop that serves to fine-tune the ability of syt1 to trigger release, via alterations in Ca2+ binding activity and potentially through the impact of LLPS on membrane curvature during fusion reactions. In summary, the juxtamembrane linker of syt1 emerges as a regulator of syt1 function by driving self-association via LLPS.

Accurate and Efficient Multilevel Free Energy Simulations with Neural Network-Assisted Enhanced Sampling.

Free energy differences (ΔF) are essential to quantitative characterization and understanding of chemical and biological processes. Their direct estimation with an accurate quantum mechanical potential is of great interest and yet impractical due to high computational cost and incompatibility with typical alchemical free energy protocols. One promising solution is the multilevel free energy simulation in which the estimate of ΔF at an inexpensive low level of theory is combined with the correction toward a higher level of theory. The poor configurational overlap generally expected between the two levels of theory, however, presents a major challenge. We overcome this challenge by using a deep neural network model and enhanced sampling simulations. An adversarial autoencoder is used to identify a low-dimensional (latent) space that compactly represents the degrees of freedom that encode the distinct distributions at the two levels of theory. Enhanced sampling in this latent space is then used to drive the sampling of configurations that predominantly contribute to the free energy correction. Results for both gas phase and condensed phase systems demonstrate that this data-driven approach offers high accuracy and efficiency with great potential for scalability to complex systems.

Non-equilibrium transport of nanoparticles across the lipid membrane.

Development of effective strategies for the internalization of nanoparticles is essential in many applications, such as drug delivery. Most, if not all, previous studies are based on equilibrium considerations. In this work, inspired by the recent development of a pro-drug delivery strategy based on reversible esterification, we consider a non-equilibrium transport mechanism for nanoparticles of a 6 nm diameter across the lipid membrane. We divide the transport process into insertion and ejection steps, which are studied with coarse-grained models using free energy and reactive Monte Carlo simulations, respectively. The simulations show that the non-equilibrium transport efficiency is relatively insensitive to the fraction of reactive surface ligands once a modest threshold is surpassed, while the distribution pattern of different (hydrophilic, reactive and permanent hydrophobic) ligands on the nanoparticle surface has a notable impact on both the insertion and ejection steps. Our study thus supports a novel avenue for designing nanoparticles that are able to be efficiently internalized and provides a set of relevant guidelines for surface functionalization.

Coacervation-Induced Remodeling of Nanovesicles.

Intrinsically disordered peptides can form biomolecular condensates through liquid-liquid phase separation. These condensates play diverse roles in cells, including inducing large-scale changes in membrane morphology. Here we employ coarse-grained molecular dynamics simulations to identify the most salient physical principles that govern membrane remodeling by condensates. By systematically varying the interaction strengths among the polymers and lipids in our coarse-grained model, we are able to recapitulate various membrane transformations observed in different experiments. Endocytosis and exocytosis of the condensate are observed when the interpolymeric attraction is stronger than polymer-lipid interaction. We find a critical size of the condensate required to exhibit successful endocytosis. Multilamellarity and local gelation are observed when the polymer-lipid attraction is significantly stronger than the interpolymeric attraction. Our insights provide essential guidance to the design of (bio)polymers for the manipulation of membrane morphology in various applications such as drug delivery and synthetic biology.