Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models

Coupling the role of lipids to the conformational dynamics of the ABC transporter P-glycoprotein

The ATP-binding cassette transporter P-glycoprotein (P-gp) is a multidrug efflux pump that is overexpressed in a variety of cancers and associated with the drug-resistance phenomenon. P-gp structures were previously determined in detergent and in nanodiscs, in which different transmembrane helix conformations were found, "straight" and "kinked," respectively, indicating a possible role of the lipid environment on the P-gp structural ensemble. Here, we investigate the dynamic conformational ensembles and protein-lipid interactions of two human P-gp inward-open conformers, straight and kinked, employing all-atom molecular dynamics (MD) simulations in asymmetric multicomponent lipid bilayers that mimic the highly specialized hepatocyte membrane in which P-gp is expressed. The two conformers are found to differ in terms of the accessibility of the substrate cavity. The MD simulations show how cholesterol and different lipid species wedge, snorkel, and partially enter into the cavity of the straight P-gp conformer solved in detergent. However, access to the cavity of the kinked P-gp conformer solved in nanodiscs is restricted. Furthermore, the volume and dynamic fluctuations of the substrate cavity largely differ between the two P-gp conformers and are modulated by the presence (or absence) of cholesterol in the membrane and/or of ATP. From the mechanistic perspective, the findings indicate that the straight conformer likely precedes the kinked conformer in the functional working cycle of P-gp, with the latter conformation representing a post substrate-bound state. The inaccessibility of the main transmembrane cavity in the kinked conformer might be crucial in preventing substrate disengagement and transport withdrawal. Remarkably, in our unbiased MD simulations, one transmembrane helix (TM10) of the straight conformer underwent a spontaneous transition to a kinked conformation, underlining the relevance of both conformations in a native phospholipid environment and revealing structural descriptors defining the transition between the two P-gp conformers.

Exploring the Ligand Binding and Conformational Dynamics of the Substrate-Binding Domain 1 of the ABC Transporter GlnPQ

The adenosine triphosphate (ATP)-binding cassette (ABC) importer GlnPQ from Lactococcus lactis has two sequential covalently linked substrate-binding domains (SBDs), which capture the substrates and deliver them to the translocon. The two SBDs differ in their ligand specificities, binding affinities and the distance to the transmembrane domain; interestingly, both SBDs can bind their ligands simultaneously without affecting each other. In this work, we studied the binding of ligands to both SBDs using X-ray crystallography and molecular dynamics simulations. We report three high-resolution structures of SBD1, namely, the wild-type SBD1 with bound asparagine or arginine, and E184D SBD1 with glutamine bound. Molecular dynamics (MD) simulations provide a detailed insight into the dynamics associated with open-closed transitions of the SBDs.

Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.

Insertion and Anchoring of HIV-1 Fusion Peptide into Complex Membrane Mimicking Human T-cell

A fundamental understanding of how HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a 9-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow timescale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

ezAlign: A Tool for Converting Coarse-Grained Molecular Dynamics Structures to Atomistic Resolution for Multiscale Modeling

Soft condensed matter is challenging to study due to the vast time and length scales that are necessary to accurately represent complex systems and capture their underlying physics. Multiscale simulations are necessary to study processes that have disparate time and/or length scales, which abound throughout biology and other complex systems. Herein we present ezAlign, an open-source software for converting coarse-grained molecular dynamics structures to atomistic representation, allowing multiscale modeling of biomolecular systems. The ezAlign v1.1 software package is publicly available for download at github.com/LLNL/ezAlign. Its underlying methodology is based on a simple alignment of an atomistic template molecule, followed by position-restraint energy minimization, which forces the atomistic molecule to adopt a conformation consistent with the coarse-grained molecule. The molecules are then combined, solvated, minimized, and equilibrated with position restraints. Validation of the process was conducted on a pure POPC membrane and compared with other popular methods to construct atomistic membranes. Additional examples, including surfactant self-assembly, membrane proteins, and more complex bacterial and human plasma membrane models, are also presented. By providing these examples, parameter files, code, and an easy-to-follow recipe to add new molecules, this work will aid future multiscale modeling efforts.

BCL-2 and BOK regulate apoptosis by interaction of their C-terminal transmembrane domains

The Bcl-2 family controls apoptosis by direct interactions of pro- and anti-apoptotic proteins. The principle mechanism is binding of the BH3 domain of pro-apoptotic proteins to the hydrophobic groove of anti-apoptotic siblings, which is therapeutically exploited by approved BH3-mimetic anti-cancer drugs. Evidence suggests that also the transmembrane domain (TMD) of Bcl-2 proteins can mediate Bcl-2 interactions. We developed a highly-specific split luciferase assay enabling the analysis of TMD interactions of pore-forming apoptosis effectors BAX, BAK, and BOK with anti-apoptotic Bcl-2 proteins in living cells. We confirm homotypic interaction of the BAX-TMD, but also newly identify interaction of the TMD of anti-apoptotic BCL-2 with the TMD of BOK, a peculiar pro-apoptotic Bcl-2 protein. BOK-TMD and BCL-2-TMD interact at the endoplasmic reticulum. Molecular dynamics simulations confirm dynamic BOK-TMD and BCL-2-TMD dimers and stable heterotetramers. Mutation of BCL-2-TMD at predicted key residues abolishes interaction with BOK-TMD. Also, inhibition of BOK-induced apoptosis by BCL-2 depends specifically on their TMDs. Thus, TMDs of Bcl-2 proteins are a relevant interaction interface for apoptosis regulation and provide a novel potential drug target.

Lipid Organization by the Caveolin-1 Complex

Caveolins are lipid-binding proteins that can organize membrane remodeling and oligomerize into the 8S-complex. The CAV1 8S-complex comprises a disk-like structure, about 15nm in diameter, with a central beta barrel. Further oligomerization of 8S-complexes remodels the membrane into caveolae vessels, with a dependence on cholesterol concentration. However, the molecular mechanisms behind membrane remodeling and cholesterol filtering are still not understood. Performing atomistic Molecular Dynamics simulations in combination with advanced sampling techniques, we describe how the CAV1-8S complex bends the membrane and accumulates cholesterol. Here, our simulations show an enhancing effect by the palmitoylations of CAV1, and we predict that the CAV1-8S complex can extract cholesterol molecules from the lipid bilayer and accommodate them in its beta barrel. Through backmapping to the all-atom level we also conclude that the Martini v2 coarse-grained forcefield overestimates membrane bending, as the atomistic simulations exhibit only very localized bending.

Dynamics and Activation of Membrane-Bound B Cell Receptor Assembly

B-cell receptor complexes (BCR) are expressed on the surface of a B-cell and are the critical regulators of adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation of antibody-producing B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structure of the human B-cell antigen receptor of the IgM isotype was published. Given the new asymmetric BCR complex, we have carried out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane. We identified two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding caused increased flexibility in regions distal to the antigen binding site. Second, this increased flexibility led to the rearrangement of helices in transmembrane helices, including the relative interaction of Igα/Igβ, which has been responsible for intracellular signaling. Further, these transmembrane rearrangements led to changes in localized lipid composition. Even though the simulations considered only a single BCR complex, our work indirectly supports the dissociation activation model.

Molecular Dynamics Simulations Help Determine the Molecular Mechanisms of Lasioglossin-III and Its Variant Peptides' Membrane Interfacial Interactions

Lasioglossin-III (LL-III) is a potent broad-spectrum antimicrobial peptide used in diverse antimicrobial applications. In this work, coarse-grained and all-atom molecular dynamics simulation strategies were used in tandem to interpret the molecular mechanisms involved in the interfacial dynamics of LL-III and its recombinant variants during interactions with diverse cell membrane systems. Our results indicate that the membrane charges act as the driving force for initiating the membrane-peptide interactions, while the hydrophobic or van der Waals forces help to reinforce the membrane-peptide bindings. The optimized charge-hydrophobicity ratio of the LL-III peptides helps ensure their high specificity toward bacterial membranes compared to mammalian membrane systems, which also helps explain our experimental observations. Overall, we hope that our work gives new insight into the antimicrobial action of LL-III peptides and that the adopted simulation strategy will help other scientists and engineers extract maximal information from complex molecular simulations using minimal computational power.

There and back again: bridging meso- and nano-scales to understand lipid vesicle patterning

We describe a complete methodology to bridge the scales between nanoscale molecular dynamics and (micrometer) mesoscale Monte Carlo simulations in lipid membranes and vesicles undergoing phase separation, in which curving molecular species are furthermore embedded. To go from the molecular to the mesoscale, we notably appeal to physical renormalization arguments enabling us to rigorously infer the mesoscale interaction parameters from its molecular counterpart. We also explain how to deal with the physical timescales at stake at the mesoscale. Simulating the as-obtained mesoscale system enables us to equilibrate the long wavelengths of the vesicles of interest, up to the vesicle size. Conversely, we then backmap from the meso- to the nano-scale, which enables us to equilibrate in turn the short wavelengths down to the molecular length-scales. By applying our approach to the specific situation of patterning a vesicle membrane, we show that macroscopic membranes can thus be equilibrated at all length-scales in achievable computational time offering an original strategy to address the fundamental challenge of timescale in simulations of large bio-membrane systems.

A Practical Guide to All-Atom and Coarse-Grained Molecular Dynamics Simulations Using Amber and Gromacs: A Case Study of Disulfide-Bond Impact on the Intrinsically Disordered Amyloid Beta

Intrinsically disordered proteins (IDPs) pose challenges to conventional experimental techniques due to their large-scale conformational fluctuations and transient structural elements. This work presents computational methods for studying IDPs at various resolutions using the Amber and Gromacs packages with both all-atom (Amber ff19SB with the OPC water model) and coarse-grained (Martini 3 and SIRAH) approaches. The effectiveness of these methodologies is demonstrated by examining the monomeric form of amyloid-β (Aβ42), an IDP, with and without disulfide bonds at different resolutions. Our results clearly show that the addition of a disulfide bond decreases the β-content of Aβ42; however, it increases the tendency of the monomeric Aβ42 to form fibril-like conformations, explaining the various aggregation rates observed in experiments. Moreover, analysis of the monomeric Aβ42 compactness, secondary structure content, and comparison between calculated and experimental chemical shifts demonstrates that all three methods provide a reasonable choice to study IDPs; however, coarse-grained approaches may lack some atomistic details, such as secondary structure recognition, due to the simplifications used. In general, this study not only explains the role of disulfide bonds in Aβ42 but also provides a step-by-step protocol for setting up, conducting, and analyzing molecular dynamics (MD) simulations, which is adaptable for studying other biomacromolecules, including folded and disordered proteins and peptides.

Unveiling the crucial role of betaine: modulation of GABA homeostasis via SLC6A1 transporter (GAT1)

Betaine is an endogenous osmolyte that exhibits therapeutic potential by mitigating various neurological disorders. However, the underlying cellular and molecular mechanisms responsible for its neuroprotective effects remain puzzling.In this study, we describe a possible mechanism behind the positive impact of betaine in preserving neurons from excitotoxicity. Here we demonstrate that betaine at low concentration modulates the GABA uptake by GAT1 (slc6a1), the predominant GABA transporter in the central nervous system. This modulation occurs through the temporal inhibition of the transporter, wherein prolonged occupancy by betaine impedes the swift transition of the transporter to the inward conformation. Importantly, the modulatory effect of betaine on GAT1 is reversible, as the blocking of GAT1 disappears with increased extracellular GABA. Using electrophysiology, mass spectroscopy, radiolabelled cellular assay, and molecular dynamics simulation we demonstrate that betaine has a dual role in GAT1: at mM concentration acts as a slow substrate, and at µM as a temporal blocker of GABA, when it is below its K0.5. Given this unique modulatory characteristic and lack of any harmful side effects, betaine emerges as a promising neuromodulator of the inhibitory pathways improving GABA homeostasis via GAT1, thereby conferring neuroprotection against excitotoxicity.

Scrutinising the Conformational Ensemble of the Intrinsically Mixed-Folded Protein Galectin-3

Galectin-3 is a protein involved in many intra- and extra-cellular processes. It has been identified as a diagnostic or prognostic biomarker for certain types of heart disease, kidney disease and cancer. Galectin-3 comprises a carbohydrate recognition domain (CRD) and an N-terminal domain (NTD), which is unstructured and contains eight collagen-like Pro-Gly-rich tandem repeats. While the structure of the CRD has been solved using protein crystallography, current knowledge about conformations of full-length galectin-3 is limited. To fill in this knowledge gap, we performed molecular dynamics (MD) simulations of full-length galectin-3. We systematically re-scaled the solute-solvent interactions in the Martini 3 force field to obtain the best possible agreement between available data from SAXS experiments and the ensemble of conformations generated in the MD simulations. The simulation conformations were found to be very diverse, as reflected, e.g., by (i) large fluctuations in the radius of gyration, ranging from about 2 to 5 nm, and (ii) multiple transient contacts made by amino acid residues in the NTD. Consistent with evidence from NMR experiments, contacts between the CRD and NTD were observed to not involve the carbohydrate-binding site on the CRD surface. Contacts within the NTD were found to be made most frequently by aromatic residues. Formation of fuzzy complexes with unspecific stoichiometry was observed to be mediated mostly by the NTD. Taken together, we offer a detailed picture of the conformational ensemble of full-length galectin-3, which will be important for explaining the biological functions of this protein at the molecular level.

Molecular interactions of the Omicron, Kappa, and Delta SARS-CoV-2 spike proteins with quantum dots of graphene oxide

CONTEXT

The Omicron, Kappa, and Delta variants are different strains of the SARS-CoV-2 virus. Graphene oxide quantum dots (GOQDs) represent a burgeoning class of oxygen-enriched, zero-dimensional materials characterized by their sub-20-nm dimensions. Exhibiting pronounced quantum confinement and edge effects, GOQDs manifest exceptional physical-chemical attributes. This study delves into the potential of graphene oxide quantum dots, elucidating their inherent properties pertinent to the surface structures of SARS-CoV-2, employing an integrated computational approach for the repositioning of inhibitory agents.

METHODS

Following rigorous adjustment tests, a spectrum of divergent bonding conformations emerged, with particular emphasis placed on identifying the conformation exhibiting optimal adjustment scores and interactions. The investigation employed molecular docking simulations integrating affinity energy evaluations, electrostatic potential clouds, molecular dynamics encompassing average square root calculations, and the computation of Gibbs-free energy. These values quantify the strength of interaction between GOQDs and SARS-CoV-2 spike protein variants. The receptor structures were optimized using the CHARM-GUI server employing force field AMBERFF14SB. The algorithm embedded in CHARMM offers an efficient interpolation scheme and automatic step size selection, enhancing the efficiency of the optimization process. The 3D structures of the ligands are constructed and optimized with density functional theory (DFT) method based on the most stable conformer of each binder. Autodock Vina Software (ADV) was utilized, where essential parameters were specified. Electrostatic potential maps (MEPs) provide a visual depiction of molecules' charge distributions and related properties. After this, molecular dynamics simulations employing the CHARM36 force field in Gromacs 2022.2 were conducted to investigate GOs' interactions with surface macromolecules of SARS-CoV-2 in an explicit aqueous environment. Furthermore, our investigation suggests that lower values indicate stronger binding. Notably, GO-E consistently showed the most negative values across interactions with different variants, suggesting a higher affinity compared to other GOQDs (GO-A to GO-D).

The structure, self-assembly and dynamics of lipid nanodiscs revealed by computational approaches

Nanodisc technology is increasingly being used in structural, biochemical and biophysical studies of membrane proteins. The computational approaches have revealed many important features of nanodisc assembly, structures and dynamics. Therefore, we reviewed the application of computational approaches, especially molecular modeling and molecular dyncamics (MD) simulations, to characterize nanodiscs, including the structural models, assembly and disassembly, protocols for modeling, structural properties and dynamics, and protein-lipid interactions in nanodiscs. More amazing computational studies about nanodiscs are looked forward to in the future.

Rigorous Progress in Coarse-Graining

Low-resolution coarse-grained (CG) models provide remarkable computational and conceptual advantages for simulating soft materials. In principle, bottom-up CG models can reproduce all structural and thermodynamic properties of atomically detailed models that can be observed at the resolution of the CG model. This review discusses recent progress in developing theory and computational methods for achieving this promise. We first briefly review variational approaches for parameterizing interaction potentials and their relationship to machine learning methods. We then discuss recent approaches for simultaneously improving both the transferability and thermodynamic properties of bottom-up models by rigorously addressing the density and temperature dependence of these potentials. We also briefly discuss exciting progress in modeling high-resolution observables with low-resolution CG models. More generally, we highlight the essential role of the bottom-up framework not only for fundamentally understanding the limitations of prior CG models but also for developing robust computational methods that resolve these limitations in practice.

Spontaneous Dimerization and Distinct Packing Modes of Transmembrane Domains in Receptor Tyrosine Kinases

The insulin receptor (IR) and the insulin-like growth factor-1 receptor (IGF1R) are homodimeric transmembrane glycoproteins that transduce signals across the membrane on binding of extracellular peptide ligands. The structures of IR/IGF1R fragments in apo and liganded states have revealed that the extracellular subunits of these receptors adopt Λ-shaped configurations to which are connected the intracellular tyrosine kinase (TK) domains. The binding of peptide ligands induces structural transitions in the extracellular subunits leading to potential dimerization of transmembrane domains (TMDs) and autophosphorylation in TKs. However, the activation mechanisms of IR/IGF1R, especially the role of TMDs in coordinating signal-inducing structural transitions, remain poorly understood, in part due to the lack of structures of full-length receptors in apo or liganded states. While atomistic simulations of IR/IGF1R TMDs showed that these domains can dimerize in single component membranes, spontaneous unbiased dimerization in a plasma membrane having physiologically representative lipid composition has not been observed. We address this limitation by employing coarse-grained (CG) molecular dynamics simulations to probe the dimerization propensity of IR/IGF1R TMDs. We observed that TMDs in both receptors spontaneously dimerized independent of their initial orientations in their dissociated states, signifying their natural propensity for dimerization. In the dimeric state, IR TMDs predominantly adopted X-shaped configurations with asymmetric helical packing and significant tilt relative to the membrane normal, while IGF1R TMDs adopted symmetric V-shaped or parallel configurations with either no tilt or a small tilt relative to the membrane normal. Our results suggest that IR/IGF1R TMDs spontaneously dimerize and adopt distinct dimerized configurations.

An atomistic characterization of high-density lipoproteins and the conserved "LN" region of apoA-I

The physicochemical characteristics of the various subpopulations of high-density lipoproteins (HDLs) and, in particular, their surface properties determine their ability to scavenge lipids and interact with specific receptors and peptides. Five representative spheroidal HDL subpopulation models were mapped from a previously reported equilibrated coarse-grained (CG) description to an atomistic representation for subsequent molecular dynamics simulation. For each HDL model a range of finer-level analyses was undertaken, including the component-wise characterization of HDL surfaces, the average size and composition of hydrophobic surface patches, dynamic protein secondary structure monitoring, and the proclivity for solvent exposure of the proposed β-amyloid (Aβ) binding region of apolipoprotein A-I (apoA-I), "LN." This study reveals that previously characterized ellipsoidal HDL3a and HDL2a models revert to a more spherical geometry in an atomistic representation due to the enhanced conformational flexibility afforded to the apoA-I protein secondary structure, allowing for enhanced surface lipid packing and lower overall surface hydrophobicity. Indeed, the proportional surface hydrophobicity and apoA-I exposure reduced with increasing HDL size, consistent with previous characterizations. Furthermore, solvent exposure of the "LN" region of apoA-I was exclusively limited to the smallest HDL3c model within the timescale of the simulations, and typically corresponded to a distinct loss in secondary structure across the "LN" region to form part of a significant contiguous hydrophobic patch on the HDL surface. Taken together, these findings provide preliminary evidence for a subpopulation-specific interaction between HDL3c particles and circulating hydrophobic species such as Aβ via the exposed "LN" region of apoA-I.

Reverse Mapping of Coarse Grained Polyglutamine Conformations from PRIME20 Sampling

An inverse coarse-graining protocol is presented for generating and validating atomistic structures of large (bio-) molecules from conformations obtained via a coarse-grained sampling method. Specifically, the protocol is implemented and tested based on the (coarse-grained) PRIME20 protein model (P20/SAMC), and the resulting all-atom conformations are simulated using conventional biomolecular force fields. The phase space sampling at the coarse-grained level is performed with a stochastical approximation Monte Carlo approach. The method is applied to a series of polypeptides, specifically dimers of polyglutamine with varying chain length in aqueous solution. The majority (>70 %) of the conformations obtained from the coarse-grained peptide model can successfully be mapped back to atomistic structures that remain conformationally stable during 10 ns of molecular dynamics simulations. This work can be seen as the first step towards the overarching goal of improving our understanding of protein aggregation phenomena through simulation methods.

Thrombin activation of the factor XI dimer is a multistaged process for each subunit

BACKGROUND

Factor (F)XI can be activated by proteases, including thrombin and FXIIa. The interactions of these enzymes with FXI are transient in nature and therefore difficult to study.

OBJECTIVES

To identify the binding interface between thrombin and FXI and understand the dynamics underlying FXI activation.

METHODS

Crosslinking mass spectrometry was used to localize the binding interface of thrombin on FXI. Molecular dynamics simulations were applied to investigate conformational changes enabling thrombin-mediated FXI activation after binding. The proposed trajectory of activation was examined with nanobody 1C10, which was previously shown to inhibit thrombin-mediated activation of FXI.

RESULTS

We identified a binding interface of thrombin located on the light chain of FXI involving residue Pro520. After this initial interaction, FXI undergoes conformational changes driven by binding of thrombin to the apple 1 domain in a secondary step to allow migration toward the FXI cleavage site. The 1C10 binding site on the apple 1 domain supports this proposed trajectory of thrombin. We validated the results with known mutation sites on FXI. As Pro520 is conserved in prekallikrein (PK), we hypothesized and showed that thrombin can bind PK, even though it cannot activate PK.

CONCLUSION

Our investigations show that the activation of FXI is a multistaged procedure. Thrombin first binds to Pro520 in FXI; thereafter, it migrates toward the activation site by engaging the apple 1 domain. This detailed analysis of the interaction between thrombin and FXI paves a way for future interventions for bleeding or thrombosis.

Identification of the potassium-binding site in serotonin transporter

Clearance of serotonin (5-hydroxytryptamine, 5-HT) from the synaptic cleft after neuronal signaling is mediated by serotonin transporter (SERT), which couples this process to the movement of a Na+ ion down its chemical gradient. After release of 5-HT and Na+ into the cytoplasm, the transporter faces a rate-limiting challenge of resetting its conformation to be primed again for 5-HT and Na+ binding. Early studies of vesicles containing native SERT revealed that K+ gradients can provide an additional driving force, via K+ antiport. Moreover, under appropriate conditions, a H+ ion can replace K+. Intracellular K+ accelerates the resetting step. Structural studies of SERT have identified two binding sites for Na+ ions, but the K+ site remains enigmatic. Here, we show that K+ antiport can drive substrate accumulation into vesicles containing SERT extracted from a heterologous expression system, allowing us to study the residues responsible for K+ binding. To identify candidate binding residues, we examine many cation binding configurations using molecular dynamics simulations, predicting that K+ binds to the so-called Na2 site. Site-directed mutagenesis of residues in this site can eliminate the ability of both K+ and H+ to drive 5-HT accumulation into vesicles and, in patch clamp recordings, prevent the acceleration of turnover rates and the formation of a channel-like state by K+ or H+. In conclusion, the Na2 site plays a pivotal role in orchestrating the sequential binding of Na+ and then K+ (or H+) ions to facilitate 5-HT uptake in SERT.

Computational Insights into the Conformational Dynamics of HIV-1 Vpr in a Lipid Bilayer for Ion Channel Modeling

HIV-1 Vpr is a multifunctional accessory protein consisting of 96 amino acids that play a critical role in viral pathogenesis. Among its diverse range of activities, Vpr can create a cation-selective ion channel within the plasma membrane. However, the oligomeric state of this channel has not yet been elucidated. In this study, we investigated the conformational dynamics of Vpr helices to model the ion channel topology. First, we employed a series of multiscale simulations to investigate the specific structure of monomeric Vpr in a membrane model. During the lipid bilayer self-assembly coarse grain simulation, the C-terminal helix (residues 56-77) effectively formed the transmembrane region, while the N-terminal helix exhibited an amphipathic nature by associating horizontally with a single leaflet. All-atom molecular dynamics (MD) simulations of full-length Vpr inside a phospholipid bilayer show that the C-terminal helix remains very stable inside the bilayer core in a vertical orientation. Subsequently, using the predicted C-terminal helix orientation and conformation, various oligomeric states (ranging from tetramer to heptamer) possibly forming the Vpr ion channel were built and further evaluated. Among these models, the pentameric form exhibited consistent stability in MD simulations and displayed a compatible conformation for a water-assisted ion transport mechanism. This study provides structural insights into the ion channel activity of the Vpr protein and the foundation for developing therapeutics against HIV-1 Vpr-related conditions.

Electron videography of a lipid-protein tango

Biological phenomena, from enzymatic catalysis to synaptic transmission, originate in the structural transformations of biomolecules and biomolecular assemblies in liquid water. However, directly imaging these nanoscopic dynamics without probes or labels has been a fundamental methodological challenge. Here, we developed an approach for "electron videography"-combining liquid phase electron microscopy with molecular modeling-with which we filmed the nanoscale structural fluctuations of individual, suspended, and unlabeled membrane protein nanodiscs in liquid. Systematic comparisons with biochemical data and simulation indicate the graphene encapsulation involved can afford sufficiently reduced effects of the illuminating electron beam for these observations to yield quantitative fingerprints of nanoscale lipid-protein interactions. Our results suggest that lipid-protein interactions delineate dynamically modified membrane domains across unexpectedly long ranges. Moreover, they contribute to the molecular mechanics of the nanodisc as a whole in a manner specific to the protein within. Overall, this work illustrates an experimental approach to film, quantify, and understand biomolecular dynamics at the nanometer scale.

Overcoming Endosomal Escape Barriers in Gene Drug Delivery Using De Novo Designed pH-Responsive Peptides

A major challenge in using nanocarriers for intracellular drug delivery is their restricted capacity to escape from endosomes into the cytosol. Here, we significantly enhance the drug delivery efficiency by accurately predicting and regulating the transition pH (pH0) of peptides to modulate their endosomal escape capability. Moreover, by inverting the chirality of the peptide carriers, we could further enhance their ability to deliver nucleic acid drugs as well as antitumor drugs. The resulting peptide carriers exhibit versatility in transfecting various cell types with a high efficiency of up to 90% by using siRNA, pDNA, and mRNA. In vivo antitumor experiments demonstrate a tumor growth inhibition of 83.4% using the peptide. This research offers a potent method for the rapid development of peptide vectors with exceptional transfection efficiencies for diverse pathophysiological indications.

Building complex membranes with Martini 3

The Martini model is a popular force field for coarse-grained simulations. Membranes have always been at the center of its development, with the latest version, Martini 3, showing great promise in capturing more and more realistic behavior. In this chapter we provide a step-by-step tutorial on how to construct starting configurations, run initial simulations and perform dedicated analysis for membrane-based systems of increasing complexity, including leaflet asymmetry, curvature gradients and embedding of membrane proteins.

Micropolarity governs the structural organization of biomolecular condensates

Membraneless organelles within cells have unique microenvironments that play a critical role in their functions. However, how microenvironments of biomolecular condensates affect their structure and function remains unknown. In this study, we investigated the micropolarity and microviscosity of model biomolecular condensates by fluorescence lifetime imaging coupling with environmentally sensitive fluorophores. Using both in vitro and in cellulo systems, we demonstrated that sufficient micropolarity difference is key to forming multilayered condensates, where the shells present more polar microenvironments than the cores. Furthermore, micropolarity changes were shown to be accompanied by conversions of the layered structures. Decreased micropolarities of the granular components, accompanied by the increased micropolarities of the dense fibrillar components, result in the relocation of different nucleolus subcompartments in transcription-stalled conditions. Our results demonstrate the central role of the previously overlooked micropolarity in the regulation of structures and functions of membraneless organelles.

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.

Physics-Informed Deep Learning Approach for Reintroducing Atomic Detail in Coarse-Grained Configurations of Multiple Poly(lactic acid) Stereoisomers

Multiscale modeling of complex molecular systems, such as macromolecules, encompasses methods that combine information from fine and coarse representations of molecules to capture material properties over a wide range of spatiotemporal scales. Being able to exchange information between different levels of resolution is essential for the effective transfer of this information. The inverse problem of reintroducing atomistic degrees of freedom in coarse-grained (CG) molecular configurations is particularly challenging as, from a mathematical point of view, it is an ill-posed problem; the forward mapping from the atomistic to the CG description is typically defined via a deterministic operator ("one-to-one" problem), whereas the reversed mapping from the CG to the atomistic model refers to creating one representative configuration out of many possible ones ("one-to-many" problem). Most of the backmapping methods proposed so far balance accuracy, efficiency, and general applicability. This is particularly important for macromolecular systems with different types of isomers, i.e., molecules that have the same molecular formula and sequence of bonded atoms (constitution) but differ in the three-dimensional configurations of their atoms in space. Here, we introduce a versatile deep learning approach for backmapping multicomponent CG macromolecules with chiral centers, trained to learn structural correlations between polymer configurations at the atomistic level and their corresponding CG descriptions. This method is intended to be simple and flexible while presenting a generic solution for resolution transformation. In addition, the method is aimed to respect the structural features of the molecule, such as local packing, capturing therefore the physical properties of the material. As an illustrative example, we apply the model on linear poly(lactic acid) (PLA) in melt, which is one of the most popular biodegradable polymers. The framework is tested on a number of model systems starting from homopolymer stereoisomers of PLA to copolymers with randomly placed chiral centers. The results demonstrate the efficiency and efficacy of the new approach.

Multiscale, Multiresolution Coarse-Grained Model via a Hybrid Approach: Solvation, Structure, and Self-Assembly of Aromatic Tripeptides

Short aromatic peptides have been observed to assemble into diverse nanostructures, including fibers, tubes, and vesicles, using computational techniques. However, the computational studies have employed top-down coarse-grained (CG) models, which are unable to capture the assembly along with the conformation, packing, and organization of the peptides within the aggregates in a manner that is consistent with the all atom (AA) representation of the molecules. In this study, a hybrid structure- and force-based approach is adapted to develop a bottom-up CG force field of triphenylalanine using reference data from AA trajectories. This approach follows a flexible methodology to approximate the chemical complexity of the underlying AA representation with the chosen CG representation. Two CG models are developed with distinct representations of the aromatic side chains. The first uses a simple single-bead representation, while the second uses a three-bead representation to more accurately represent the planarity of the ring. The one-bead model yields nanorods, while the three-bead model results in nanospheres. The role of different chemical groups in the assembly of nanostructures is identified, along with the importance of steric effects on the packing of the peptides within assemblies.

Improved Protein Dynamics and Hydration in the Martini3 Coarse-Grain Model

The Martini coarse-grain force-field has emerged as an important framework to probe cellular processes at experimentally relevant time- and length-scales. However, the recently developed version, the Martini3 force-field with the implemented Go̅ model (Martini3Go̅), as well as previous variants of the Martini model have not been benchmarked and rigorously tested for globular proteins. In this study, we consider three globular proteins, ubiquitin, lysozyme, and cofilin, and compare protein dynamics and hydration with observables from experiments and all-atom simulations. We show that the Martini3Go̅ model is able to accurately model the structural and dynamic features of small globular proteins. Overall, the structural integrity of the proteins is maintained, as validated by contact maps, radii of gyration (Rg), and SAXS profiles. The chemical shifts predicted from the ensemble sampled in the simulations are consistent with the experimental data. Further, a good match is observed in the protein-water interaction energetics, and the hydration levels of the residues are similar to atomistic simulations. However, the protein-water interaction dynamics is not accurately represented and appears to depend on the protein structural complexity, residue specificity, and water dynamics. Our work is a step toward testing and assessing the Martini3Go̅ model and provides insights into future efforts to refine Martini models with improved solvation effects and better correspondence to the underlying all-atom systems.

Aggregation, structure and water permeability of membrane-embedded helical Aβ oligomers

It is widely recognized that membranes can facilitate the aggregation of amyloid-β (Aβ) peptides, while Aβ can in turn cause membrane damage. Many studies focus on the peptide-membrane interactions of Aβ oligomers with β-rich structures. However, the exact aggregation and toxicity mechanism of the membrane-embedded helical Aβ oligomers remain ambiguous. Herein, the molecular dynamics simulations were performed on membrane-embedded helical Aβ42 peptides. Initiated by eight Aβ42 monomers embedded in a lipid bilayer, the monomers aggregate into oligomers with stable transmembrane helix structures. With the aggregation of peptides, the membrane perturbations caused by Aβ aggregates decrease. The molecular architectures of oligomers were characterized and a helix-rich octamer stabilized by an annular network of hydrogen bonds was observed. The oligomers demonstrate the capability to assist transmembrane water transport. Our study may provide new insights for the investigation of transmembrane Aβ oligomers.

Multiscale Modeling of Macromolecular Interactions between Tau-Amylin Oligomers and Asymmetric Lipid Nanodomains That Link Alzheimer's and Diabetic Diseases

The molecular events of protein misfolding and self-aggregation of tau and amylin are associated with the progression of Alzheimer's and diabetes, respectively. Recent studies suggest that tau and amylin can form hetero-tau-amylin oligomers. Those hetero-oligomers are more neurotoxic than homo-tau oligomers. So far, the detailed interactions between the hetero-oligomers and the neuronal membrane are unknown. Using multiscale MD simulations, the lipid binding and protein folding behaviors of hetero-oligomers on asymmetric lipid nanodomains or raft membranes were examined. Our raft membranes contain phase-separated phosphatidylcholine (PC), cholesterol, and anionic phosphatidylserine (PS) or ganglioside (GM1) in one leaflet of the lipid bilayer. The hetero-oligomers bound more strongly to the PS and GM1 than other lipids via the hydrophobic and hydrophilic interactions, respectively, in the raft membranes. The hetero-tetramer disrupted the acyl chain orders of both PC and PS in the PS-containing raft membrane, but only the GM1 in the GM1-containing raft membrane as effectively as the homo-tau-tetramer. We discovered that the alpha-helical content in the heterodimer was greater than the sum of alpha-helical contents from isolated tau and amylin monomers on both raft membranes, indicative of a synergetic effect of tau-amylin interactions in surface-induced protein folding. Our results provide new molecular insights into understanding the cross-talk between Alzheimer's and diabetes.

Reconciling ASPP-p53 binding mode discrepancies through an ensemble binding framework that bridges crystallography and NMR data

ASPP2 and iASPP bind to p53 through their conserved ANK-SH3 domains to respectively promote and inhibit p53-dependent cell apoptosis. While crystallography has indicated that these two proteins employ distinct surfaces of their ANK-SH3 domains to bind to p53, solution NMR data has suggested similar surfaces. In this study, we employed multi-scale molecular dynamics (MD) simulations combined with free energy calculations to reconcile the discrepancy in the binding modes. We demonstrated that the binding mode based solely on a single crystal structure does not enable iASPP's RT loop to engage with p53's C-terminal linker-a verified interaction. Instead, an ensemble of simulated iASPP-p53 complexes facilitates this interaction. We showed that the ensemble-average inter-protein contacting residues and NMR-detected interfacial residues qualitatively overlap on ASPP proteins, and the ensemble-average binding free energies better match experimental KD values compared to single crystallgarphy-determined binding mode. For iASPP, the sampled ensemble complexes can be grouped into two classes, resembling the binding modes determined by crystallography and solution NMR. We thus propose that crystal packing shifts the equilibrium of binding modes towards the crystallography-determined one. Lastly, we showed that the ensemble binding complexes are sensitive to p53's intrinsically disordered regions (IDRs), attesting to experimental observations that these IDRs contribute to biological functions. Our results provide a dynamic and ensemble perspective for scrutinizing these important cancer-related protein-protein interactions (PPIs).

Distilling coarse-grained representations of molecular electronic structure with continuously gated message passing

Bottom-up methods for coarse-grained (CG) molecular modeling are critically needed to establish rigorous links between atomistic reference data and reduced molecular representations. For a target molecule, the ideal reduced CG representation is a function of both the conformational ensemble of the system and the target physical observable(s) to be reproduced at the CG resolution. However, there is an absence of algorithms for selecting CG representations of molecules from which complex properties, including molecular electronic structure, can be accurately modeled. We introduce continuously gated message passing (CGMP), a graph neural network (GNN) method for atomically decomposing molecular electronic structure sampled over conformational ensembles. CGMP integrates 3D-invariant GNNs and a novel gated message passing system to continuously reduce the atomic degrees of freedom accessible for electronic predictions, resulting in a one-shot importance ranking of atoms contributing to a target molecular property. Moreover, CGMP provides the first approach by which to quantify the degeneracy of "good" CG representations conditioned on specific prediction targets, facilitating the development of more transferable CG representations. We further show how CGMP can be used to highlight multiatom correlations, illuminating a path to developing CG electronic Hamiltonians in terms of interpretable collective variables for arbitrarily complex molecules.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors

The presynaptic serotonin transporter (SERT) clears extracellular serotonin following vesicular release to ensure temporal and spatial regulation of serotonergic signalling and neurotransmitter homeostasis. Prescription drugs used to treat neurobehavioral disorders, including depression, anxiety, and obsessive-compulsive disorder, trap SERT by blocking the transport cycle. In contrast, illicit drugs of abuse like amphetamines reverse SERT directionality, causing serotonin efflux. Both processes result in increased extracellular serotonin levels. By combining molecular dynamics simulations with biochemical experiments and using a homologous series of serotonin analogues, we uncovered the coupling mechanism between the substrate and the transporter, which triggers the uptake of serotonin. Free energy analysis showed that only scaffold-bound substrates could initiate SERT occlusion through attractive long-range electrostatic interactions acting on the bundle domain. The associated spatial requirements define substrate and inhibitor properties, enabling additional possibilities for rational drug design approaches.

Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities

The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.

One bead per residue can describe all-atom protein structures

Atomistic resolution is the standard for high-resolution biomolecular structures, but experimental structural data are often at lower resolution. Coarse-grained models are also used extensively in computational studies to reach biologically relevant spatial and temporal scales. This study explores the use of advanced machine learning networks for reconstructing atomistic models from reduced representations. The main finding is that a single bead per amino acid residue allows construction of accurate and stereochemically realistic all-atom structures with minimal loss of information. This suggests that lower resolution representations of proteins may be sufficient for many applications when combined with a machine learning framework that encodes knowledge from known structures. Practical applications include the rapid addition of atomistic detail to low-resolution structures from experiment or computational coarse-grained models. The application of rapid, deterministic all-atom reconstruction within multi-scale frameworks is further demonstrated with a rapid protocol for the generation of accurate models from cryo-EM densities close to experimental structures.

Probing binding and occlusion of substrate in the human creatine transporter-1 by computation and mutagenesis

In chordates, energy buffering is achieved in part through phosphocreatine, which requires cellular uptake of creatine by the membrane-embedded creatine transporter (CRT1/SLC6A8). Mutations in human slc6a8 lead to creatine transporter deficiency syndrome, for which there is only limited treatment. Here, we used a combined homology modeling, molecular dynamics, and experimental approach to generate a structural model of CRT1. Our observations support the following conclusions: contrary to previous proposals, C144, a key residue in the substrate binding site, is not present in a charged state. Similarly, the side chain D458 must be present in a protonated form to maintain the structural integrity of CRT1. Finally, we identified that the interaction chain Y148-creatine-Na+ is essential to the process of occlusion, which occurs via a "hold-and-pull" mechanism. The model should be useful to study the impact of disease-associated point mutations on the folding of CRT1 and identify approaches which correct folding-deficient mutants.

Molecular dynamics simulation of apolipoprotein E3 lipid nanodiscs

Nanodiscs are binary discoidal complexes of a phospholipid bilayer circumscribed by belt-like helical scaffold proteins. Using coarse-grained and all-atom molecular dynamics simulations, we explore the stability, size, and structure of nanodiscs formed between the N-terminal domain of apolipoprotein E3 (apoE3-NT) and variable number of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) molecules. We study both parallel and antiparallel double-belt configurations, consisting of four proteins per nanodisc. Our simulations predict nanodiscs containing between 240 and 420 DMPC molecules to be stable. The antiparallel configurations exhibit an average of 1.6 times more amino acid interactions between protein chains and 2 times more ionic contacts, compared to the parallel configuration. With one exception, DMPC order parameters are consistently larger in the antiparallel configuration than in the parallel one. In most cases, the root mean square deviation of the positions of the protein backbone atoms is smaller in the antiparallel configuration. We further report nanodisc size, thickness, radius of gyration, and solvent accessible surface area. Combining all investigated parameters, we hypothesize the antiparallel protein configuration leading to more stable and more rigid nanodiscs than the parallel one.

Design of light-responsive amphiphilic self-assemblies: A novel application of the photosensitive diazirine moiety

Diazirine is one of the smallest photo-sensitive moieties discovered to date. When incorporated in the structure of phospholipids, its minimal size has a low impact on the morphology of the resultant liposomes. A DMPC-diazirine analogue was designed and subsequently used to generate liposomes with a lower permeability and a lower phase-transition temperature compared to control DMPC liposomes. Contrary to control liposomes, in the absence of light, the photosensitive nanoparticles retained the cargo (calcein) for at least 10 days. However, upon irradiation, diazirine's conversion triggered the fluorophore release within minutes. The kinetics of the release could be tuned by the power and duration of the irradiation process. The same approach can be used on other nanomaterials, with the final goal of discovering a release profile appropriate not only for therapeutic applications, but also for agrochemicals delivery or cosmoceutics.

Assessing the interaction between hemoglobin and the receptor binding domain of SARS-CoV-2 spike protein through MARTINI coarse-grained molecular dynamics

The emergence of different coronavirus-related diseases in the 2000's (SARS, MERS, and Covid-19) warrants the need of a complete understanding of the pathological, biological, and biochemical behavior of this class of pathogens. Great attention has been paid to the SARS-CoV-2 Spike protein, and its interaction with the human ACE2 has been thoroughly investigated. Recent findings suggested that the SARS-CoV-2 components may interact with different human proteins, and hemoglobin has very recently been demonstrated as a potential target for the Spike protein. Here we have investigated the interaction between either adult or fetal hemoglobin and the receptor binding domain of the Spike protein at molecular level through advanced molecular dynamics techniques and proposed rational binding modes and energy estimations. Our results agree with biochemical data previously reported in literature. We also demonstrated that co-incubation of pulmonary epithelial cells with hemoglobin strongly reduces the pro-inflammatory effects exerted by the concomitant administration of Spike protein.

Liquid-Liquid Phase Separation of the Intrinsically Disordered Domain of the Fused in Sarcoma Protein Results in Substantial Slowing of Hydration Dynamics

Formation of liquid condensates plays a critical role in biology via localization of different components or via altered hydrodynamic transport, yet the hydrogen-bonding environment within condensates, pivotal for solvation, has remained elusive. We explore the hydrogen-bond dynamics within condensates formed by the low-complexity domain of the fused in sarcoma protein. Probing the hydrogen-bond dynamics sensed by condensate proteins using two-dimensional infrared spectroscopy of the protein amide I vibrations, we find that frequency-frequency correlations of the amide I vibration decay on a picosecond time scale. Interestingly, these dynamics are markedly slower for proteins in the condensate than in a homogeneous protein solution, indicative of different hydration dynamics. All-atom molecular dynamics simulations confirm that lifetimes of hydrogen-bonds between water and the protein are longer in the condensates than in the protein in solution. Altered hydrogen-bonding dynamics may contribute to unique solvation and reaction dynamics in such condensates.

Nonuniversal impact of cholesterol on membranes mobility, curvature sensing and elasticity

Biological membranes, composed mainly of phospholipids and cholesterol, play a vital role as cellular barriers. They undergo localized reshaping in response to environmental cues and protein interactions, with the energetics of deformations crucial for exerting biological functions. This study investigates the non-universal role of cholesterol on the structure and elasticity of saturated and unsaturated lipid membranes. Our study uncovers a highly cooperative relationship between thermal membrane bending and local cholesterol redistribution, with cholesterol showing a strong preference for the compressed membrane leaflet. Remarkably, in unsaturated membranes, increased cholesterol mobility enhances cooperativity, resulting in membrane softening despite membrane thickening and lipid compression caused by cholesterol. These findings elucidate the intricate interplay between thermodynamic forces and local molecular interactions that govern collective properties of membranes.

Eukaryotic Kv channel Shaker inactivates through selectivity filter dilation rather than collapse

Eukaryotic voltage-gated K+ channels have been extensively studied, but the structural bases for some of their most salient functional features remain to be established. C-type inactivation, for example, is an auto-inhibitory mechanism that confers temporal resolution to their signal-firing activity. In a recent breakthrough, studies of a mutant of Shaker that is prone to inactivate indicated that this process entails a dilation of the selectivity filter, the narrowest part of the ion conduction pathway. Here, we report an atomic-resolution cryo-electron microscopy structure that demonstrates that the wild-type channel can also adopt this dilated state. All-atom simulations corroborate this conformation is congruent with the electrophysiological characteristics of the C-type inactivated state, namely, residual K+ conductance and altered ion specificity, and help rationalize why inactivation is accelerated or impeded by certain mutations. In summary, this study establishes the molecular basis for an important self-regulatory mechanism in eukaryotic K+ channels, laying a solid foundation for further studies.

Docking for EP4R antagonists active against inflammatory pain

The lipid prostaglandin E2 (PGE2) mediates inflammatory pain by activating G protein-coupled receptors, including the prostaglandin E2 receptor 4 (EP4R). Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce nociception by inhibiting prostaglandin synthesis, however, the disruption of upstream prostanoid biosynthesis can lead to pleiotropic effects including gastrointestinal bleeding and cardiac complications. In contrast, by acting downstream, EP4R antagonists may act specifically as anti-inflammatory agents and, to date, no selective EP4R antagonists have been approved for human use. In this work, seeking to diversify EP4R antagonist scaffolds, we computationally dock over 400 million compounds against an EP4R crystal structure and experimentally validate 71 highly ranked, de novo synthesized molecules. Further, we show how structure-based optimization of initial docking hits identifies a potent and selective antagonist with 16 nanomolar potency. Finally, we demonstrate favorable pharmacokinetics for the discovered compound as well as anti-allodynic and anti-inflammatory activity in several preclinical pain models in mice.

Backmapping with Mapping and Isomeric Information

I present a powerful and flexible backmapping tool named Multiscale Simulation Tool (mstool) that converts a coarse-grained (CG) system into all-atom (AA) resolution and only requires AA to CG mapping and isomeric information (cis/trans/dihedral/chiral). The backmapping procedure includes two simple steps: (a) AA atoms are randomly placed near the corresponding CG beads according to the provided mapping scheme. (b) Energy minimization is performed with two modifications in the AA force field (FF). First, nonbonded interactions are replaced with cosine functions to ensure the numerical stability. Second, additional torsions are imposed to maintain the molecules' isomeric properties. To test the simplicity and robustness of the tool, I backmapped multiple membrane and protein CG structures into AA resolution, including a four-bead CG lipid model (resolution increased by a factor of 34) without using intermediate resolution. The tool is freely available at github.com/ksy141/mstool.

Dimerization mechanism of an inverted-topology ion channel in membranes

Many ion channels are multisubunit complexes where oligomerization is an obligatory requirement for function as the binding axis forms the charged permeation pathway. However, the mechanisms of in-membrane assembly of thermodynamically stable channels are largely unknown. Here, we demonstrate a key advance by reporting the dimerization equilibrium reaction of an inverted-topology, homodimeric fluoride channel Fluc in lipid bilayers. While the wild-type channel is a long-lived dimer, we leverage a known mutation, N43S, that weakens Na+ binding in a buried site at the interface, thereby unlocking the complex for reversible association in lipid bilayers. Single-channel recordings show that Na+ binding is required for fluoride conduction while single-molecule microscopy experiments demonstrate that N43S Fluc exists in a dynamic monomer-dimer equilibrium in the membrane, even following removal of Na+. Quantifying the thermodynamic stability while titrating Na+ indicates that dimerization occurs first, providing a membrane-embedded binding site where Na+ binding weakly stabilizes the complex. To understand how these subunits form stable assemblies while presenting charged surfaces to the membrane, we carried out molecular dynamics simulations, which show the formation of a thinned membrane defect around the exposed dimerization interface. In simulations where subunits are permitted to encounter each other while preventing protein contacts, we observe spontaneous and selective association at the native interface, where stability is achieved by mitigation of the membrane defect. These results suggest a model wherein membrane-associated forces drive channel assembly in the native orientation while subsequent factors, such as Na+ binding, result in channel activation.

Identification of inhibitors targeting the energy-coupling factor (ECF) transporters

The energy-coupling factor (ECF) transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. The central role of vitamin transport in the metabolism of bacteria and absence from humans make the ECF transporters an attractive target for inhibition with selective chemical probes. Here, we report on the identification of a promising class of inhibitors of the ECF transporters. We used coarse-grained molecular dynamics simulations on Lactobacillus delbrueckii ECF-FolT2 and ECF-PanT to profile the binding mode and mechanism of inhibition of this novel chemotype. The results corroborate the postulated mechanism of transport and pave the way for further drug-discovery efforts.

DiAMoNDBack: Diffusion-Denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces

Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long time scales, such as aggregation and folding. The reduced resolution realizes computational accelerations, but an atomistic representation can be vital for a complete understanding of mechanistic details. Backmapping is the process of restoring all-atom resolution to coarse-grained molecular models. In this work, we report DiAMoNDBack (Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping) as an autoregressive denoising diffusion probability model to restore all-atom details to coarse-grained protein representations retaining only Cα coordinates. The autoregressive generation process proceeds from the protein N-terminus to C-terminus in a residue-by-residue fashion conditioned on the Cα trace and previously backmapped backbone and side-chain atoms within the local neighborhood. The local and autoregressive nature of our model makes it transferable between proteins. The stochastic nature of the denoising diffusion process means that the model generates a realistic ensemble of backbone and side-chain all-atom configurations consistent with the coarse-grained Cα trace. We train DiAMoNDBack over 65k+ structures from the Protein Data Bank (PDB) and validate it in applications to a hold-out PDB test set, intrinsically disordered protein structures from the Protein Ensemble Database (PED), molecular dynamics simulations of fast-folding mini-proteins from DE Shaw Research, and coarse-grained simulation data. We achieve state-of-the-art reconstruction performance in terms of correct bond formation, avoidance of side-chain clashes, and the diversity of the generated side-chain configurational states. We make the DiAMoNDBack model publicly available as a free and open-source Python package.