CG2AT2: an Enhanced Fragment-Based Approach for Serial Multi-scale Molecular Dynamics Simulations

Mapping structural and dynamic divergence across the MBOAT family

Membrane-bound O-acyltransferases (MBOATs) are membrane-embedded enzymes that catalyze acyl chain transfer to a diverse group of substrates, including lipids, small molecules, and proteins. MBOATs share a conserved structural core, despite wide-ranging functional specificity across both prokaryotes and eukaryotes. The structural basis of catalytic specificity, regulation and interactions with the surrounding environment remain uncertain. Here, we combine comparative molecular dynamics (MD) simulations with bioinformatics to assess molecular and interactional divergence across the family. In simulations, MBOATs differentially distort the bilayer depending on their substrate type. Additionally, we identify lipid binding sites surrounding reactant gates in the surrounding membrane. Complementary bioinformatic analyses reveal a conserved role for re-entrant loop-2 in MBOAT fold stabilization and a key hydrogen bond bridging DGAT1 dimerization. Finally, we predict differences in MBOAT solvation and water gating properties. These data are pertinent to the design of MBOAT-specific inhibitors that encompass dynamic information within cellular mimetic environments.

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.

Molecular dynamics simulations of lipid-protein interactions in SLC4 proteins

The SLC4 family of secondary bicarbonate transporters is responsible for the transport of HCO3-, CO32-, Cl-, Na+, K+, NH3, and H+, which are necessary for regulation of pH and ion homeostasis. They are widely expressed in numerous tissues throughout the body and function in different cell types with different membrane properties. Potential lipid roles in SLC4 function have been reported in experimental studies, focusing mostly on two members of the family: AE1 (Cl-/HCO3- exchanger) and NBCe1 (Na+-CO32-cotransporter). Previous computational studies of the outward-facing state of AE1 with model lipid membranes revealed enhanced protein-lipid interactions between cholesterol (CHOL) and phosphatidylinositol bisphosphate (PIP2). However, the protein-lipid interactions in other members of the family and other conformation states are still poorly understood and this precludes the detailed studies of a potential regulatory role for lipids in the SLC4 family. In this work, we performed coarse-grained and atomistic molecular dynamics simulations on three members of the SLC4 family with different transport modes: AE1, NBCe1, and NDCBE (an Na+-CO32-/Cl- exchanger), in model HEK293 membranes consisting of CHOL, PIP2, phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, and sphingomyelin. The recently resolved inward-facing state of AE1 was also included in the simulations. Lipid-protein contact analysis of the simulated trajectories was performed with the ProLint server, which provides a multitude of visualization tools for illustration of areas of enhanced lipid-protein contact and identification of putative lipid binding sites within the protein matrix. We observed enrichment of CHOL and PIP2 around all proteins with subtle differences in their distribution depending on the protein type and conformation state. Putative binding sites were identified for CHOL, PIP2, phosphatidylcholine, and sphingomyelin in the three studied proteins, and their potential roles in the SLC4 transport function, conformational transition, and protein dimerization are discussed.

State-dependent binding of cholesterol and an anionic lipid to the muscle-type Torpedo nicotinic acetylcholine receptor

The ability of the Torpedo nicotinic acetylcholine receptor (nAChR) to undergo agonist-induced conformational transitions requires the presence of cholesterol and/or anionic lipids. Here we use recently solved structures along with multiscale molecular dynamics simulations to examine lipid binding to the nAChR in bilayers that have defined effects on nAChR function. We examine how phosphatidic acid and cholesterol, lipids that support conformational transitions, individually compete for binding with phosphatidylcholine, a lipid that does not. We also examine how the two lipids work synergistically to stabilize an agonist-responsive nAChR. We identify rapidly exchanging lipid binding sites, including both phospholipid sites with a high affinity for phosphatidic acid and promiscuous cholesterol binding sites in the grooves between adjacent transmembrane α-helices. A high affinity cholesterol site is confirmed in the inner leaflet framed by a key tryptophan residue on the MX α-helix. Our data provide insight into the dynamic nature of lipid-nAChR interactions and set the stage for a detailed understanding of the mechanisms by which lipids facilitate nAChR function at the neuromuscular junction.

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.

Synthesis of lipid-linked precursors of the bacterial cell wall is governed by a feedback control mechanism in Pseudomonas aeruginosa

Many bacterial surface glycans such as the peptidoglycan (PG) cell wall are built from monomeric units linked to a polyprenyl lipid carrier. How this limiting carrier is distributed among competing pathways has remained unclear. Here we describe the isolation of hyperactive variants of Pseudomonas aeruginosa MraY, the enzyme that forms the first lipid-linked PG precursor. These variants result in the elevated production of the final PG precursor lipid II in cells and are hyperactive in vitro. The activated MraY variants have substitutions that map to a cavity on the extracellular side of the dimer interface, far from the active site. Our structural and molecular dynamics results suggest that this cavity is a binding site for externalized lipid II. Overall, our results support a model in which excess externalized lipid II allosterically inhibits MraY, providing a feedback mechanism that prevents the sequestration of lipid carrier in the PG biogenesis pathway.

Recovery from desensitization in GluA2 AMPA receptors is affected by a single mutation in the N-terminal domain interface

AMPA-type ionotropic glutamate receptors (AMPARs) are central to various neurological processes, including memory and learning. They assemble as homo- or heterotetramers of GluA1, GluA2, GluA3, and GluA4 subunits, each consisting of an N-terminal domain (NTD), a ligand-binding domain, a transmembrane domain, and a C-terminal domain. While AMPAR gating is primarily controlled by reconfiguration in the ligand-binding domain layer, our study focuses on the NTDs, which also influence gating, yet the underlying mechanism remains enigmatic. In this investigation, we employ molecular dynamics simulations to evaluate the NTD interface strength in GluA1, GluA2, and NTD mutants GluA2-H229N and GluA1-N222H. Our findings reveal that GluA1 has a significantly weaker NTD interface than GluA2. The NTD interface of GluA2 can be weakened by a single point mutation in the NTD dimer-of-dimer interface, namely H229N, which renders GluA2 more GluA1-like. Electrophysiology recordings demonstrate that this mutation also leads to slower recovery from desensitization. Moreover, we observe that lowering the pH induces more splayed NTD states and enhances desensitization in GluA2. We hypothesized that H229 was responsible for this pH sensitivity; however, GluA2-H229N was also affected by pH, meaning that H229 is not solely responsible and that protons exert their effect across multiple domains of the AMPAR. In summary, our work unveils an allosteric connection between the NTD interface strength and AMPAR desensitization.

Mechanism and cellular function of direct membrane binding by the ESCRT and ERES-associated Ca2+-sensor ALG-2

Apoptosis linked Gene-2 (ALG-2) is a multifunctional intracellular Ca2+ sensor and the archetypal member of the penta-EF hand protein family. ALG-2 functions in the repair of damage to both the plasma and lysosome membranes and in COPII-dependent budding at endoplasmic reticulum exit sites (ERES). In the presence of Ca2+, ALG-2 binds to ESCRT-I and ALIX in membrane repair and to SEC31A at ERES. ALG-2 also binds directly to acidic membranes in the presence of Ca2+ by a combination of electrostatic and hydrophobic interactions. By combining giant unilamellar vesicle-based experiments and molecular dynamics simulations, we show that charge-reversed mutants of ALG-2 at these locations disrupt membrane recruitment. ALG-2 membrane binding mutants have reduced or abrogated ERES localization in response to Thapsigargin-induced Ca2+ release but still localize to lysosomes following lysosomal Ca2+ release. In vitro reconstitution shows that the ALG-2 membrane-binding defect can be rescued by binding to ESCRT-I. These data thus reveal the nature of direct Ca2+-dependent membrane binding and its interplay with Ca2+-dependent protein binding in the cellular functions of ALG-2.

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.

Three-step docking by WIPI2, ATG16L1, and ATG3 delivers LC3 to the phagophore

The covalent attachment of ubiquitin-like LC3 proteins (microtubule-associated proteins 1A/1B light chain 3) prepares the autophagic membrane for cargo recruitment. We resolve key steps in LC3 lipidation by combining molecular dynamics simulations and experiments in vitro and in cellulo. We show how the E3-like ligaseautophagy-related 12 (ATG12)-ATG5-ATG16L1 in complex with the E2-like conjugase ATG3 docks LC3 onto the membrane in three steps by (i) the phosphatidylinositol 3-phosphate effector protein WD repeat domain phosphoinositide-interacting protein 2 (WIPI2), (ii) helix α2 of ATG16L1, and (iii) a membrane-interacting surface of ATG3. Phosphatidylethanolamine (PE) lipids concentrate in a region around the thioester bond between ATG3 and LC3, highlighting residues with a possible role in the catalytic transfer of LC3 to PE, including two conserved histidines. In a near-complete pathway from the initial membrane recruitment to the LC3 lipidation reaction, the three-step targeting of the ATG12-ATG5-ATG16L1 machinery establishes a high level of regulatory control.

Palmitoylation of the Glucagon-like Peptide-1 Receptor Modulates Cholesterol Interactions at the Receptor-Lipid Microenvironment

The G protein-coupled receptor (GPCR) superfamily of cell surface receptors has been shown to be functionally modulated by post-translational modifications. The glucagon-like peptide receptor-1 (GLP-1R), which is a drug target in diabetes and obesity, undergoes agonist-dependent palmitoyl tail conjugation. The palmitoylation in the C-terminal domain of GLP-1R has been suggested to modulate the receptor-lipid microenvironment. In this work, we have performed coarse-grain molecular dynamics simulations of palmitoylated and nonpalmitoylated GLP-1R to analyze the differential receptor-lipid interactions. Interestingly, the placement and dynamics of the C-terminal domain of GLP-1R are found to be directly dependent on the palmitoyl tail. We observe that both cholesterol and phospholipids interact with the receptor but display differential interactions in the presence and absence of the palmitoyl tail. We characterize important cholesterol-binding sites and validate sites that have been previously reported in experimentally resolved structures of the receptor. We show that the receptor acts like a conduit for cholesterol flip-flop by stabilizing cholesterol in the membrane core. Taken together, our work represents an important step in understanding the molecular effects of lipid modifications in GPCRs.

Martini 3 Force Field Parameters for Protein Lipidation Post-Translational Modifications

Protein lipidations are vital co/post-translational modifications that tether lipid tails to specific protein amino acids, allowing them to anchor to biological membranes, switch their subcellular localization, and modulate association with other proteins. Such lipidations are thus crucial for multiple biological processes including signal transduction, protein trafficking, and membrane localization and are implicated in various diseases as well. Examples of lipid-anchored proteins include the Ras family of proteins that undergo farnesylation; actin and gelsolin that are myristoylated; phospholipase D that is palmitoylated; glycosylphosphatidylinositol-anchored proteins; and others. Here, we develop parameters for cysteine-targeting farnesylation, geranylgeranylation, and palmitoylation, as well as glycine-targeting myristoylation for the latest version of the Martini 3 coarse-grained force field. The parameters are developed using the CHARMM36m all-atom force field parameters as reference. The behavior of the coarse-grained models is consistent with that of the all-atom force field for all lipidations and reproduces key dynamical and structural features of lipid-anchored peptides, such as the solvent-accessible surface area, bilayer penetration depth, and representative conformations of the anchors. The parameters are also validated in simulations of the lipid-anchored peripheral membrane proteins Rheb and Arf1, after comparison with independent all-atom simulations. The parameters, along with mapping schemes for the popular martinize2 tool, are available for download at 10.5281/zenodo.7849262 and also as supporting information.

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.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Electronic Polarizability Tunes the Function of the Human Bestrophin 1 Cl - Channel

Mechanisms of anion permeation within ion channels and nanopores remain poorly understood. Recent cryo-electron microscopy structures of the human bestrophin 1 chloride channel (hBest1) provide an opportunity to evaluate ion interactions predicted by molecular dynamics (MD) simulations against experimental observations. We implement the fully polarizable forcefield AMOEBA in MD simulations of open and partially-open states of the hBest1. The AMOEBA forcefield models multipole moments up to the quadrupole; therefore, it captures induced dipole and anion- π interactions. By including polarization we demonstrate the key role that aromatic residues play in ion permeation and the functional advantages of pore asymmetry within the highly conserved hydrophobic neck of the pore. We establish that these only arise when electronic polarization is included in the molecular models. We also show that Cl - permeation in this region can be achieved through hydrophobic solvation concomitant with partial ion dehydration, which is compensated for by the formation of contacts with the edge of the phenylalanine ring. Furthermore, we demonstrate how polarizable simulations can help determine the identity of ion-like densities within high-resolution cryo-EM structures. Crucially, neglecting polarization in simulation of these systems results in the localization of Cl - at positions that do not correspond with their experimentally resolved location. Overall, our results demonstrate the importance of including electronic polarization in realistic and physically accurate models of biological systems.

Statement of Significance

Ion channels are nanoscale protein pores that enable the selective passage of charged ions across cell membranes. Understanding the underlying mechanisms for selective anion permeation through such pores remains a challenge. To simulate their behavior efficiently in silico , fixed charge models are typically employed. However, this approach is insufficient for the study of anions. Here, we use simulations with explicit treatment of electrostatics to investigate the interactions of chloride ions in the human bestrophin 1 channel. We find that electronic polarization tunes the state of the channel and affects the interactions of chloride ions thereby revealing a mechanism for permeation. Furthermore, these simulations can be used to resolve experimental ambiguity in ion-like densities from cryo-EM structures.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Mechanism and cellular function of direct membrane binding by the ESCRT and ERES-associated Ca2+-sensor ALG-2

Apoptosis Linked Gene-2 (ALG-2) is a multifunctional intracellular Ca2+ sensor and the archetypal member of the penta-EF hand protein family. ALG-2 functions in the repair of damage to both the plasma and lysosome membranes and in COPII-dependent budding at endoplasmic reticulum exit sites (ERES). In the presence of Ca2+, ALG-2 binds to ESCRT-I and ALIX in membrane repair and to SEC31A at ERES. ALG-2 also binds directly to acidic membranes in the presence of Ca2+ by a combination of electrostatic and hydrophobic interactions. By combining GUV-based experiments and molecular dynamics simulations, we show that charge-reversed mutants of ALG-2 at these locations disrupt membrane recruitment. ALG-2 membrane binding mutants have reduced or abrogated ERES localization in response to Thapsigargin-induced Ca2+ release but still localize to lysosomes following lysosomal Ca2+ release. In vitro reconstitution shows that the ALG-2 membrane-binding defect can be rescued by binding to ESCRT-I. These data thus reveal the nature of direct Ca2+-dependent membrane binding and its interplay with Ca2+-dependent protein binding in the cellular functions of ALG-2.

Structural basis of peptidoglycan synthesis by E. coli RodA-PBP2 complex

Peptidoglycan (PG) is an essential structural component of the bacterial cell wall that is synthetized during cell division and elongation. PG forms an extracellular polymer crucial for cellular viability, the synthesis of which is the target of many antibiotics. PG assembly requires a glycosyltransferase (GT) to generate a glycan polymer using a Lipid II substrate, which is then crosslinked to the existing PG via a transpeptidase (TP) reaction. A Shape, Elongation, Division and Sporulation (SEDS) GT enzyme and a Class B Penicillin Binding Protein (PBP) form the core of the multi-protein complex required for PG assembly. Here we used single particle cryo-electron microscopy to determine the structure of a cell elongation-specific E. coli RodA-PBP2 complex. We combine this information with biochemical, genetic, spectroscopic, and computational analyses to identify the Lipid II binding sites and propose a mechanism for Lipid II polymerization. Our data suggest a hypothesis for the movement of the glycan strand from the Lipid II polymerization site of RodA towards the TP site of PBP2, functionally linking these two central enzymatic activities required for cell wall peptidoglycan biosynthesis.

The solute carrier SPNS2 recruits PI(4,5)P2 to synergistically regulate transport of sphingosine-1-phosphate

Solute carrier spinster homolog 2 (SPNS2), one of only four known major facilitator superfamily (MFS) lysolipid transporters in humans, exports sphingosine-1-phosphate (S1P) across cell membranes. Here, we explore the synergistic effects of lipid binding and conformational dynamics on SPNS2's transport mechanism. Using mass spectrometry, we discovered that SPNS2 interacts preferentially with PI(4,5)P2. Together with functional studies and molecular dynamics (MD) simulations, we identified potential PI(4,5)P2 binding sites. Mutagenesis of proposed lipid binding sites and inhibition of PI(4,5)P2 synthesis reduce S1P transport, whereas the absence of the N terminus renders the transporter essentially inactive. Probing the conformational dynamics of SPNS2, we show how synergistic binding of PI(4,5)P2 and S1P facilitates transport, increases dynamics of the extracellular gate, and stabilizes the intracellular gate. Given that SPNS2 transports a key signaling lipid, our results have implications for therapeutic targeting and also illustrate a regulatory mechanism for MFS transporters.

A feedback control mechanism governs the synthesis of lipid-linked precursors of the bacterial cell wall

Many bacterial surface glycans such as the peptidoglycan (PG) cell wall, O-antigens, and capsules are built from monomeric units linked to a polyprenyl lipid carrier. How this limiting lipid carrier is effectively distributed among competing pathways has remained unclear for some time. Here, we describe the isolation and characterization of hyperactive variants of Pseudomonas aeruginosa MraY, the essential and conserved enzyme catalyzing the formation of the first lipid-linked PG precursor called lipid I. These variants result in the elevated production of the final PG precursor lipid II in cells and are hyperactive in a purified system. Amino acid substitutions within the activated MraY variants unexpectedly map to a cavity on the extracellular side of the dimer interface, far from the active site. Our structural evidence and molecular dynamics simulations suggest that the cavity is a binding site for lipid II molecules that have been transported to the outer leaflet of the membrane. Overall, our results support a model in which excess externalized lipid II allosterically inhibits MraY, providing a feedback mechanism to prevent the sequestration of lipid carrier in the PG biogenesis pathway. MraY belongs to the broadly distributed polyprenyl-phosphate N-acetylhexosamine 1-phosphate transferase (PNPT) superfamily of enzymes. We therefore propose that similar feedback mechanisms may be widely employed to coordinate precursor supply with demand by polymerases, thereby optimizing the partitioning of lipid carriers between competing glycan biogenesis pathways.

PLSCR1 is a cell-autonomous defence factor against SARS-CoV-2 infection

Understanding protective immunity to COVID-19 facilitates preparedness for future pandemics and combats new SARS-CoV-2 variants emerging in the human population. Neutralizing antibodies have been widely studied; however, on the basis of large-scale exome sequencing of protected versus severely ill patients with COVID-19, local cell-autonomous defence is also crucial1-4. Here we identify phospholipid scramblase 1 (PLSCR1) as a potent cell-autonomous restriction factor against live SARS-CoV-2 infection in parallel genome-wide CRISPR-Cas9 screens of human lung epithelia and hepatocytes before and after stimulation with interferon-γ (IFNγ). IFNγ-induced PLSCR1 not only restricted SARS-CoV-2 USA-WA1/2020, but was also effective against the Delta B.1.617.2 and Omicron BA.1 lineages. Its robust activity extended to other highly pathogenic coronaviruses, was functionally conserved in bats and mice, and interfered with the uptake of SARS-CoV-2 in both the endocytic and the TMPRSS2-dependent fusion routes. Whole-cell 4Pi single-molecule switching nanoscopy together with bipartite nano-reporter assays found that PLSCR1 directly targeted SARS-CoV-2-containing vesicles to prevent spike-mediated fusion and viral escape. A PLSCR1 C-terminal β-barrel domain-but not lipid scramblase activity-was essential for this fusogenic blockade. Our mechanistic studies, together with reports that COVID-associated PLSCR1 mutations are found in some susceptible people3,4, identify an anti-coronavirus protein that interferes at a late entry step before viral RNA is released into the host-cell cytosol.

Transmembrane dimers of type 1 receptors sample alternate configurations: MD simulations using coarse grain Martini 3 versus AlphaFold2 Multimer

Structures and dynamics of transmembrane (TM) receptor regions are key to understanding their signaling mechanism across membranes. Here we examine configurations of TM region dimers, assembled using the recent Martini 3 force field for coarse-grain (CG) molecular dynamics simulations. At first glance, our results show only a reasonable agreement with ab initio predictions using PREDDIMER and AlphaFold2 Multimer and with nuclear magnetic resonance (NMR)-derived structures. 5 of 11 CG TM structures are similar to the NMR structures (within <3.5 Å root-mean-square deviation [RMSD]) compared with 10 and 9 using PREDDIMER and AlphaFold2, respectively (with 8 structures of the later within 1.5 Å). Surprisingly, AlphaFold2 predictions are closer to NMR structures when the 2001 instead of 2020 database is used for training. The CG simulations reveal that alternative configurations of TM dimers readily interconvert with a predominant population. The implications for transmembrane signaling are discussed, including for the development of peptide-based pharmaceuticals.

Nonlocal Effects of Antibiotic-Resistance-Causing Mutations Reveal an Alternative Region for Targeting on FtsW-Penicillin-Binding Protein 3 Complex of Haemophilus influenzae

Currently prescribed antibiotics target the catalytic sites of wild-type bacterial proteins; however, bacteria adopt mutations at this site, eventually leading to the emergence of resistance. Therefore, the identification of alternative drug binding sites is crucial, which requires knowledge of the dynamics of the mutant protein. Here, we set out to investigate the impact of a high-resistance-causing triple mutation (S385T + L389F + N526K) on the dynamics of a prioritized resistant pathogen, Haemophilus influenzae, using computational techniques. We studied penicillin-binding protein 3 (PBP3) and its complex with FtsW, which display resistance toward β-lactam antibiotics. We showed that mutations displayed local and nonlocal effects. In terms of the former, the orientation of the β-sheet, which surrounds the active site of PBP3, was impacted and the catalytic site was exposed to the periplasmic region. In addition, the flexibility of the β3-β4 loop, which modulates the catalysis of the enzyme, increased in the mutant FtsW-PBP3 complex. As for nonlocal effects, the dynamics of the pedestal domain (N-terminal periplasmic modulus (N-t)), i.e., the opening of the fork, was different between the wild-type and mutant enzymes. We showed the closed fork caused a greater number of residues to participate in the hypothesized allosteric communication network connecting N-t to the transpeptidase domain in the mutant enzyme. Finally, we demonstrated that the closed fork results in more favorable binding with β-lactam antibiotics, particularly cefixime, suggesting that small therapeutics that can stabilize the closed fork of mutant PBP3 may lead to the development of more effective molecules to combat resistant bacteria.

The Role of C2 Domains in Two Different Phosphatases: PTEN and SHIP2

Phosphatase and tensin homologue (PTEN) and SH2-containing inositol 5'-phosphatase 2 (SHIP2) are structurally and functionally similar. They both consist of a phosphatase (Ptase) domain and an adjacent C2 domain, and both proteins dephosphorylate phosphoinositol-tri(3,4,5)phosphate, PI(3,4,5)P₃; PTEN at the 3-phophate and SHIP2 at the 5-phosphate. Therefore, they play pivotal roles in the PI3K/Akt pathway. Here, we investigate the role of the C2 domain in membrane interactions of PTEN and SHIP2, using molecular dynamics simulations and free energy calculations. It is generally accepted that for PTEN, the C2 domain interacts strongly with anionic lipids and therefore significantly contributes to membrane recruitment. In contrast, for the C2 domain in SHIP2, we previously found much weaker binding affinity for anionic membranes. Our simulations confirm the membrane anchor role of the C2 domain in PTEN, as well as its necessity for the Ptase domain in gaining its productive membrane-binding conformation. In contrast, we identified that the C2 domain in SHIP2 undertakes neither of these roles, which are generally proposed for C2 domains. Our data support a model in which the main role of the C2 domain in SHIP2 is to introduce allosteric interdomain changes that enhance catalytic activity of the Ptase domain.

Integrating Machine Learning in the Coarse-Grained Molecular Simulation of Polymers

Machine learning (ML) is having an increasing impact on the physical sciences, engineering, and technology and its integration into molecular simulation frameworks holds great potential to expand their scope of applicability to complex materials and facilitate fundamental knowledge and reliable property predictions, contributing to the development of efficient materials design routes. The application of ML in materials informatics in general, and polymer informatics in particular, has led to interesting results, however great untapped potential lies in the integration of ML techniques into the multiscale molecular simulation methods for the study of macromolecular systems, specifically in the context of Coarse Grained (CG) simulations. In this Perspective, we aim at presenting the pioneering recent research efforts in this direction and discussing how these new ML-based techniques can contribute to critical aspects of the development of multiscale molecular simulation methods for bulk complex chemical systems, especially polymers. Prerequisites for the implementation of such ML-integrated methods and open challenges that need to be met toward the development of general systematic ML-based coarse graining schemes for polymers are discussed.

Facilitating CG Simulations with MAD: The MArtini Database Server

The MArtini Database (MAD - https://mad.ibcp.fr) is a web server designed for the sharing of structures and topologies of molecules parametrized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids, etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems, and deliver all files necessary to start simulations in the GROMACS MD engine.

Molecular dynamics simulation of an entire cell

The ultimate microscope, directed at a cell, would reveal the dynamics of all the cell's components with atomic resolution. In contrast to their real-world counterparts, computational microscopes are currently on the brink of meeting this challenge. In this perspective, we show how an integrative approach can be employed to model an entire cell, the minimal cell, JCVI-syn3A, at full complexity. This step opens the way to interrogate the cell's spatio-temporal evolution with molecular dynamics simulations, an approach that can be extended to other cell types in the near future.

Multiscale molecular dynamics simulations predict arachidonic acid binding sites in human ASIC1a and ASIC3 transmembrane domains

Acid-sensing ion channels (ASICs) play important roles in inflammatory pathways by conducting ions across the neuronal membrane in response to proton binding under acidic conditions. Recent studies have shown that ASICs can be modulated by arachidonic acid (AA), and, in the case of the ASIC3 subtype, even activated by AA at physiological pH. However, the mechanism by which these fatty acids act on the channel is still unknown. Here, we have used multiscale molecular dynamics simulations to predict a putative, general binding region of AA to models of the human ASIC protein. We have identified, in agreement with recent studies, residues in the outer leaflet transmembrane region which interact with AA. In addition, despite their similar modulation, we observe subtle differences in the AA interaction pattern between human ASIC1a and human ASIC3, which can be reversed by mutating three key residues at the outer leaflet portion of TM1. We further probed interactions with these residues in hASIC3 using atomistic simulations and identified possible AA coordinating interactions; salt bridge interactions of AA with R65hASIC3 and R68hASIC3 and AA tail interactions with the Y58hASIC3 aromatic ring. We have shown that longer fatty acid tails with more double bonds have increased relative occupancy in this region of the channel, a finding supported by recent functional studies. We further proposed that the modulatory effect of AA on ASIC does not result from changes in local membrane curvature. Rather, we speculate that it may occur through structural changes to the ion channel upon AA binding.

Membrane curvature sensing and stabilization by the autophagic LC3 lipidation machinery

How the highly curved phagophore membrane is stabilized during autophagy initiation is a major open question in autophagosome biogenesis. Here, we use in vitro reconstitution on membrane nanotubes and molecular dynamics simulations to investigate how core autophagy proteins in the LC3 (Microtubule-associated proteins 1A/1B light chain 3) lipidation cascade interact with curved membranes, providing insight into their possible roles in regulating membrane shape during autophagosome biogenesis. ATG12(Autophagy-related 12)-ATG5-ATG16L1 was up to 100-fold enriched on highly curved nanotubes relative to flat membranes. At high surface density, ATG12-ATG5-ATG16L1 binding increased the curvature of the nanotubes. While WIPI2 (WD repeat domain phosphoinositide-interacting protein 2) binding directs membrane recruitment, the amphipathic helix α2 of ATG16L1 is responsible for curvature sensitivity. Molecular dynamics simulations revealed that helix α2 of ATG16L1 inserts shallowly into the membrane, explaining its curvature-sensitive binding to the membrane. These observations show how the binding of the ATG12-ATG5-ATG16L1 complex to the early phagophore rim could stabilize membrane curvature and facilitate autophagosome growth.

Cardiolipin, and not monolysocardiolipin, preferentially binds to the interface of complexes III and IV

The mitochondrial electron transport chain comprises a series of protein complexes embedded in the inner mitochondrial membrane that generate a proton motive force via oxidative phosphorylation, ultimately generating ATP. These protein complexes can oligomerize to form larger structures called supercomplexes. Cardiolipin (CL), a conical lipid, unique within eukaryotes to the inner mitochondrial membrane, has proven essential in maintaining the stability and function of supercomplexes. Monolysocardiolipin (MLCL) is a CL variant that accumulates in people with Barth syndrome (BTHS). BTHS is caused by defects in CL biosynthesis and characterised by abnormal mitochondrial bioenergetics and destabilised supercomplexes. However, the mechanisms by which MLCL causes pathogenesis remain unclear. Here, multiscale molecular dynamics characterise the interactions of CL and MLCL with yeast and mammalian mitochondrial supercomplexes containing complex III (CIII) and complex IV (CIV). Coarse-grained simulations reveal that both CL and MLCL bind to sites at the interface between CIII and CIV of the supercomplex. Free energy perturbation calculations show that MLCL interaction is weaker than that of CL and suggest that interaction with CIV drives this difference. Atomistic contact analyses show that, although interaction with CIII is similar for CL and MLCL, CIV makes more contacts with CL than MLCL, demonstrating that CL is a more successful "glue" between the two complexes. Simulations of the human CIII₂CIV supercomplex show that this interface site is maintained between species. Our study suggests that MLCL accumulation in people with BTHS disrupts supercomplex stability by formation of relatively weak interactions at the interface lipid binding site.

Deep convolutional neural networks for generating atomistic configurations of multi-component macromolecules from coarse-grained models

Despite the modern advances in the available computational resources, the length and time scales of the physical systems that can be studied in full atomic detail, via molecular simulations, are still limited. To overcome such limitations, coarse-grained (CG) models have been developed to reduce the dimensionality of the physical system under study. However, to study such systems at the atomic level, it is necessary to re-introduce the atomistic details into the CG description. Such an ill-posed mathematical problem is typically treated via numerical algorithms, which need to balance accuracy, efficiency, and general applicability. Here, we introduce an efficient and versatile method for backmapping multi-component CG macromolecules of arbitrary microstructures. By utilizing deep learning algorithms, we train a convolutional neural network to learn structural correlations between polymer configurations at the atomistic and their corresponding CG descriptions, obtained from atomistic simulations. The trained model is then utilized to get predictions of atomistic structures from input CG configurations. As an illustrative example, we apply the convolutional neural network to polybutadiene copolymers of various microstructures, in which each monomer microstructure (i.e., cis-1,4, trans-1,4, and vinyl-1,2) is represented as a different CG particle type. The proposed methodology is transferable over molecular weight and various microstructures. Moreover, starting from a specific single CG configuration with a given microstructure, we show that by modifying its chemistry (i.e., CG particle types), we are able to obtain a set of well equilibrated polymer configurations of different microstructures (chemistry) than the one of the original CG configuration.

An N-glycan on the C2 domain of JAGGED1 is important for Notch activation

The canonical members of the Jagged/Serrate and Delta families of transmembrane ligands have an extracellular, amino-terminal C2 domain that binds to phospholipids and is required for optimal activation of the Notch receptor. Somatic mutations that cause amino substitutions in the C2 domain in human JAGGED1 (JAG1) have been identified in tumors. We found in reporter cell assays that mutations affecting an N-glycosylation site reduced the ligand's ability to activate Notch. This N-glycosylation site located in the C2 domain is conserved in the Jagged/Serrate family but is lacking in the Delta family. Site-specific glycan analysis of the JAG1 amino terminus demonstrated that occupancy of this site by either a complex-type or high-mannose N-glycan was required for full Notch activation in reporter cell assays. Similarly to JAG1 variants with defects in Notch binding, N-glycan removal, either by mutagenesis of the glycosylation site or by endoglycosidase treatment, reduced receptor activation. The N-glycan variants also reduced receptor activation in a Notch signaling-dependent vascular smooth muscle cell differentiation assay. Loss of the C2 N-glycan reduced JAG1 binding to liposomes to a similar extent as the loss of the entire C2 domain. Molecular dynamics simulations suggested that the presence of the N-glycan limits the orientation of JAG1 relative to the membrane, thus facilitating Notch binding. These data are consistent with a critical role for the N-glycan in promoting a lipid-binding conformation that is required to orient Jagged at the cell membrane for full Notch activation.

Bottom-up Coarse-Graining: Principles and Perspectives

Large-scale computational molecular models provide scientists a means to investigate the effect of microscopic details on emergent mesoscopic behavior. Elucidating the relationship between variations on the molecular scale and macroscopic observable properties facilitates an understanding of the molecular interactions driving the properties of real world materials and complex systems (e.g., those found in biology, chemistry, and materials science). As a result, discovering an explicit, systematic connection between microscopic nature and emergent mesoscopic behavior is a fundamental goal for this type of investigation. The molecular forces critical to driving the behavior of complex heterogeneous systems are often unclear. More problematically, simulations of representative model systems are often prohibitively expensive from both spatial and temporal perspectives, impeding straightforward investigations over possible hypotheses characterizing molecular behavior. While the reduction in resolution of a study, such as moving from an atomistic simulation to that of the resolution of large coarse-grained (CG) groups of atoms, can partially ameliorate the cost of individual simulations, the relationship between the proposed microscopic details and this intermediate resolution is nontrivial and presents new obstacles to study. Small portions of these complex systems can be realistically simulated. Alone, these smaller simulations likely do not provide insight into collectively emergent behavior. However, by proposing that the driving forces in both smaller and larger systems (containing many related copies of the smaller system) have an explicit connection, systematic bottom-up CG techniques can be used to transfer CG hypotheses discovered using a smaller scale system to a larger system of primary interest. The proposed connection between different CG systems is prescribed by (i) the CG representation (mapping) and (ii) the functional form and parameters used to represent the CG energetics, which approximate potentials of mean force (PMFs). As a result, the design of CG methods that facilitate a variety of physically relevant representations, approximations, and force fields is critical to moving the frontier of systematic CG forward. Crucially, the proposed connection between the system used for parametrization and the system of interest is orthogonal to the optimization used to approximate the potential of mean force present in all systematic CG methods. The empirical efficacy of machine learning techniques on a variety of tasks provides strong motivation to consider these approaches for approximating the PMF and analyzing these approximations.

Towards Molecular Understanding of the Functional Role of UbiJ-UbiK2 Complex in Ubiquinone Biosynthesis by Multiscale Molecular Modelling Studies

Ubiquinone (UQ) is a polyisoprenoid lipid found in the membranes of bacteria and eukaryotes. UQ has important roles, notably in respiratory metabolisms which sustain cellular bioenergetics. Most steps of UQ biosynthesis take place in the cytosol of E. coli within a multiprotein complex called the Ubi metabolon, that contains five enzymes and two accessory proteins, UbiJ and UbiK. The SCP2 domain of UbiJ was proposed to bind the hydrophobic polyisoprenoid tail of UQ biosynthetic intermediates in the Ubi metabolon. How the newly synthesised UQ might be released in the membrane is currently unknown. In this paper, we focused on better understanding the role of the UbiJ-UbiK₂ heterotrimer forming part of the metabolon. Given the difficulties to gain functional insights using biophysical techniques, we applied a multiscale molecular modelling approach to study the UbiJ-UbiK₂ heterotrimer. Our data show that UbiJ-UbiK₂ interacts closely with the membrane and suggests possible pathways to enable the release of UQ into the membrane. This study highlights the UbiJ-UbiK₂ complex as the likely interface between the membrane and the enzymes of the Ubi metabolon and supports that the heterotrimer is key to the biosynthesis of UQ₈ and its release into the membrane of E. coli.

Molecular Dynamics Simulations of Curved Lipid Membranes

Eukaryotic cells contain membranes with various curvatures, from the near-plane plasma membrane to the highly curved membranes of organelles, vesicles, and membrane protrusions. These curvatures are generated and sustained by curvature-inducing proteins, peptides, and lipids, and describing these mechanisms is an important scientific challenge. In addition to that, some molecules can sense membrane curvature and thereby be trafficked to specific locations. The description of curvature sensing is another fundamental challenge. Curved lipid membranes and their interplay with membrane-associated proteins can be investigated with molecular dynamics (MD) simulations. Various methods for simulating curved membranes with MD are discussed here, including tools for setting up simulation of vesicles and methods for sustaining membrane curvature. The latter are divided into methods that exploit scaffolding virtual beads, methods that use curvature-inducing molecules, and methods applying virtual forces. The variety of simulation tools allow researcher to closely match the conditions of experimental studies of membrane curvatures.

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.

Specific interactions of peripheral membrane proteins with lipids: what can molecular simulations show us?

Peripheral membrane proteins (PMPs) can reversibly and specifically bind to biological membranes to carry out functions such as cell signalling, enzymatic activity, or membrane remodelling. Structures of these proteins and of their lipid-binding domains are typically solved in a soluble form, sometimes with a lipid or lipid headgroup at the binding site. To provide a detailed molecular view of PMP interactions with the membrane, computational methods such as molecular dynamics (MD) simulations can be applied. Here, we outline recent attempts to characterise these binding interactions, focusing on both intracellular proteins, such as phosphatidylinositol phosphate (PIP)-binding domains, and extracellular proteins such as glycolipid-binding bacterial exotoxins. We compare methods used to identify and analyse lipid-binding sites from simulation data and highlight recent work characterising the energetics of these interactions using free energy calculations. We describe how improvements in methodologies and computing power will help MD simulations to continue to contribute to this field in the future.

Peptidoglycan biosynthesis is driven by lipid transfer along enzyme-substrate affinity gradients

Maintenance of bacterial cell shape and resistance to osmotic stress by the peptidoglycan (PG) renders PG biosynthetic enzymes and precursors attractive targets for combating bacterial infections. Here, by applying native mass spectrometry, we elucidate the effects of lipid substrates on the PG membrane enzymes MraY, MurG, and MurJ. We show that dimerization of MraY is coupled with binding of the carrier lipid substrate undecaprenyl phosphate (C₅₅-P). Further, we demonstrate the use of native MS for biosynthetic reaction monitoring and find that the passage of substrates and products is controlled by the relative binding affinities of the different membrane enzymes. Overall, we provide a molecular view of how PG membrane enzymes convey lipid precursors through favourable binding events and highlight possible opportunities for intervention.

Bacterial cell wall enzymes and their precursors are critical targets for antibiotic development. Here, the authors investigate several biosynthetic enzymes with their substrates and show that the passage of substrates and products in the pathway is controlled by their relative binding affinities.

Correction Schemes for Absolute Binding Free Energies Involving Lipid Bilayers

Absolute binding free-energy (ABFE) calculations are playing an increasing role in drug design, especially as they can be performed on a range of disparate compounds and direct comparisons between them can be made. It is, however, especially important to ensure that they are as accurate as possible, as unlike relative binding free-energy (RBFE) calculations, one does not benefit as much from a cancellation of errors during the calculations. In most modern implementations of ABFE calculations, a particle mesh Ewald scheme is typically used to treat the electrostatic contribution to the free energy. A central requirement of such schemes is that the box preserves neutrality throughout the calculation. There are many ways to deal with this problem that have been discussed over the years ranging from a neutralizing plasma with a post hoc correction term through to a simple co-alchemical ion within the same box. The post hoc correction approach is the most widespread. However, the vast majority of these studies have been applied to a soluble protein in a homogeneous solvent (water or salt solution). In this work, we explore which of the more common approaches would be the most suitable for a simulation box with a lipid bilayer within it. We further develop the idea of the so-called Rocklin correction for lipid-bilayer systems and show how such a correction could work. However, we also show that it will be difficult to make this generalizable in a practical way and thus we conclude that the use of a “co-alchemical ion” is the most useful approach for simulations involving lipid membrane systems.

PyLipID: A Python Package for Analysis of Protein-Lipid Interactions from Molecular Dynamics Simulations

Lipids play important modulatory and structural roles for membrane proteins. Molecular dynamics simulations are frequently used to provide insights into the nature of these protein-lipid interactions. Systematic comparative analysis requires tools that provide algorithms for objective assessment of such interactions. We introduce PyLipID, a Python package for the identification and characterization of specific lipid interactions and binding sites on membrane proteins from molecular dynamics simulations. PyLipID uses a community analysis approach for binding site detection, calculating lipid residence times for both the individual protein residues and the detected binding sites. To assist structural analysis, PyLipID produces representative bound lipid poses from simulation data, using a density-based scoring function. To estimate residue contacts robustly, PyLipID uses a dual-cutoff scheme to differentiate between lipid conformational rearrangements while bound from full dissociation events. In addition to the characterization of protein-lipid interactions, PyLipID is applicable to analysis of the interactions of membrane proteins with other ligands. By combining automated analysis, efficient algorithms, and open-source distribution, PyLipID facilitates the systematic analysis of lipid interactions from large simulation data sets of multiple species of membrane proteins.

Structure, mechanism, and inhibition of Hedgehog acyltransferase

The Sonic Hedgehog (SHH) morphogen pathway is fundamental for embryonic development and stem cell maintenance and is implicated in various cancers. A key step in signaling is transfer of a palmitate group to the SHH N terminus, catalyzed by the multi-pass transmembrane enzyme Hedgehog acyltransferase (HHAT). We present the high-resolution cryo-EM structure of HHAT bound to substrate analog palmityl-coenzyme A and a SHH-mimetic megabody, revealing a heme group bound to HHAT that is essential for HHAT function. A structure of HHAT bound to potent small-molecule inhibitor IMP-1575 revealed conformational changes in the active site that occlude substrate binding. Our multidisciplinary analysis provides a detailed view of the mechanism by which HHAT adapts the membrane environment to transfer an acyl chain across the endoplasmic reticulum membrane. This structure of a membrane-bound O-acyltransferase (MBOAT) superfamily member provides a blueprint for other protein-substrate MBOATs and a template for future drug discovery.

GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling

We describe a general approach to transforming molecular models between different levels of resolution, based on machine learning methods. The approach uses a matched set of models at both levels of resolution for training, but requires only the coordinates of their particles and no side information (e.g., templates for substructures, defined mappings, or molecular mechanics force fields). Once trained, the approach can transform further molecular models of the system between the two levels of resolution in either direction with equal facility.

Mechanism of lipid droplet formation by the yeast Sei1/Ldb16 Seipin complex

Lipid droplets (LDs) are universal lipid storage organelles with a core of neutral lipids, such as triacylglycerols, surrounded by a phospholipid monolayer. This unique architecture is generated during LD biogenesis at endoplasmic reticulum (ER) sites marked by Seipin, a conserved membrane protein mutated in lipodystrophy. Here structural, biochemical and molecular dynamics simulation approaches reveal the mechanism of LD formation by the yeast Seipin Sei1 and its membrane partner Ldb16. We show that Sei1 luminal domain assembles a homooligomeric ring, which, in contrast to other Seipins, is unable to concentrate triacylglycerol. Instead, Sei1 positions Ldb16, which concentrates triacylglycerol within the Sei1 ring through critical hydroxyl residues. Triacylglycerol recruitment to the complex is further promoted by Sei1 transmembrane segments, which also control Ldb16 stability. Thus, we propose that LD assembly by the Sei1/Ldb16 complex, and likely other Seipins, requires sequential triacylglycerol-concentrating steps via distinct elements in the ER membrane and lumen.

Membrane-binding mechanism of the EEA1 FYVE domain revealed by multi-scale molecular dynamics simulations

Early Endosomal Antigen 1 (EEA1) is a key protein in endosomal trafficking and is implicated in both autoimmune and neurological diseases. The C-terminal FYVE domain of EEA1 binds endosomal membranes, which contain phosphatidylinositol-3-phosphate (PI(3)P). Although it is known that FYVE binds PI(3)P specifically, it has not previously been described of how FYVE attaches and binds to endosomal membranes. In this study, we employed both coarse-grained (CG) and atomistic (AT) molecular dynamics (MD) simulations to determine how FYVE binds to PI(3)P-containing membranes. CG-MD showed that the dominant membrane binding mode resembles the crystal structure of EEA1 FYVE domain in complex with inositol-1,3-diphospate (PDB ID 1JOC). FYVE, which is a homodimer, binds the membrane via a hinge mechanism, where the C-terminus of one monomer first attaches to the membrane, followed by the C-terminus of the other monomer. The estimated total binding energy is ~70 kJ/mol, of which 50-60 kJ/mol stems from specific PI(3)P-interactions. By AT-MD, we could partition the binding mode into two types: (i) adhesion by electrostatic FYVE-PI(3)P interaction, and (ii) insertion of amphipathic loops. The AT simulations also demonstrated flexibility within the FYVE homodimer between the C-terminal heads and coiled-coil stem. This leads to a dynamic model whereby the 200 nm long coiled coil attached to the FYVE domain dimer can amplify local hinge-bending motions such that the Rab5-binding domain at the other end of the coiled coil can explore an area of 0.1 μm2 in the search for a second endosome with which to interact.