Multiscale Computational Study of the Conformation of the Full-Length Intrinsically Disordered Protein MeCP2.

The malfunction of the methyl-CpG binding protein 2 (MeCP2) is associated with the Rett syndrome, one of the most common causes of cognitive impairment in females. MeCP2 is an intrinsically disordered protein (IDP), making its experimental characterization a challenge. There is currently no structure available for the full-length MeCP2 in any of the databases, and only the structure of its MBD domain has been solved. We used this structure to build a full-length model of MeCP2 by completing the rest of the protein via ab initio modeling. Using a combination of all-atom and coarse-grained simulations, we characterized its structure and dynamics as well as the conformational space sampled by the ID and transcriptional repression domain (TRD) domains in the absence of the rest of the protein. The present work is the first computational study of the full-length protein. Two main conformations were sampled in the coarse-grained simulations: a globular structure similar to the one observed in the all-atom force field and a two-globule conformation. Our all-atom model is in good agreement with the available experimental data, predicting amino acid W104 to be buried, amino acids R111 and R133 to be solvent-accessible, and having a 4.1% α-helix content, compared to the 4% found experimentally. Finally, we compared the model predicted by AlphaFold to our Modeller model. The model was not stable in water and underwent further folding. Together, these simulations provide a detailed (if perhaps incomplete) conformational ensemble of the full-length MeCP2, which is compatible with experimental data and can be the basis of further studies, e.g., on mutants of the protein or its interactions with its biological partners.

Binding of divalent cations to acetate: molecular simulations guided by Raman spectroscopy.

In spite of the biological importance of the binding of Zn2+, Ca2+, and Mg2+ to the carboxylate group, cation-acetate binding affinities and binding modes remain actively debated. Here, we report the first use of Raman multivariate curve resolution (Raman-MCR) vibrational spectroscopy to obtain self-consistent free and bound metal acetate spectra and one-to-one binding constants, without the need to invoke any a priori assumptions regarding the shapes of the corresponding vibrational bands. The experimental results, combined with classical molecular dynamics simulations with a force field effectively accounting for electronic polarization via charge scaling and ab initio simulations, indicate that the measured binding constants pertain to direct (as opposed to water separated) ion pairing. The resulting binding constants do not scale with cation size, as the binding constant to Zn2+ is significantly larger than that to either Mg2+ or Ca2+, although Zn2+ and Mg2+ have similar radii that are about 25% smaller than Ca2+. Remaining uncertainties in the metal acetate binding free energies are linked to fundamental ambiguities associated with identifying the range of structures pertaining to non-covalently bound species.

Scalable molecular dynamics on CPU and GPU architectures with NAMD.

NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

A Novel Bifunctional Alkylphenol Anesthetic Allows Characterization of γ-Aminobutyric Acid, Type A (GABAA), Receptor Subunit Binding Selectivity in Synaptosomes.

Propofol, an intravenous anesthetic, is a positive modulator of the GABAA receptor, but the mechanistic details, including the relevant binding sites and alternative targets, remain disputed. Here we undertook an in-depth study of alkylphenol-based anesthetic binding to synaptic membranes. We designed, synthesized, and characterized a chemically active alkylphenol anesthetic (2-((prop-2-yn-1-yloxy)methyl)-5-(3-(trifluoromethyl)-3H-diazirin-3-yl)phenol, AziPm-click (1)), for affinity-based protein profiling (ABPP) of propofol-binding proteins in their native state within mouse synaptosomes. The ABPP strategy captured ∼4% of the synaptosomal proteome, including the unbiased capture of five α or ß GABAA receptor subunits. Lack of γ2 subunit capture was not due to low abundance. Consistent with this, independent molecular dynamics simulations with alchemical free energy perturbation calculations predicted selective propofol binding to interfacial sites, with higher affinities for α/ß than γ-containing interfaces. The simulations indicated hydrogen bonding is a key component leading to propofol-selective binding within GABAA receptor subunit interfaces, with stable hydrogen bonds observed between propofol and α/ß cavity residues but not γ cavity residues. We confirmed this by introducing a hydrogen bond-null propofol analogue as a protecting ligand for targeted-ABPP and observed a lack of GABAA receptor subunit protection. This investigation demonstrates striking interfacial GABAA receptor subunit selectivity in the native milieu, suggesting that asymmetric occupancy of heteropentameric ion channels by alkylphenol-based anesthetics is sufficient to induce modulation of activity.

Type VI secretion and bacteriophage tail tubes share a common assembly pathway.

The Type VI secretion system (T6SS) is a widespread macromolecular structure that delivers protein effectors to both eukaryotic and prokaryotic recipient cells. The current model describes the T6SS as an inverted phage tail composed of a sheath-like structure wrapped around a tube assembled by stacked Hcp hexamers. Although recent progress has been made to understand T6SS sheath assembly and dynamics, there is no evidence that Hcp forms tubes in vivo. Here we show that Hcp interacts with TssB, a component of the T6SS sheath. Using a cysteine substitution approach, we demonstrate that Hcp hexamers assemble tubes in an ordered manner with a head-to-tail stacking that are used as a scaffold for polymerization of the TssB/C sheath-like structure. Finally, we show that VgrG but not TssB/C controls the proper assembly of the Hcp tubular structure. These results highlight the conservation in the assembly mechanisms between the T6SS and the bacteriophage tail tube/sheath.

Membrane Protein Structure, Function, and Dynamics: a Perspective from Experiments and Theory.

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

A predicted binding site for cholesterol on the GABAA receptor.

Modulation of the GABA type A receptor (GABAAR) function by cholesterol and other steroids is documented at the functional level, yet its structural basis is largely unknown. Current data on structurally related modulators suggest that cholesterol binds to subunit interfaces between transmembrane domains of the GABAAR. We construct homology models of a human GABAAR based on the structure of the glutamate-gated chloride channel GluCl of Caenorhabditis elegans. The models show the possibility of previously unreported disulfide bridges linking the M1 and M3 transmembrane helices in the α and γ subunits. We discuss the biological relevance of such disulfide bridges. Using our models, we investigate cholesterol binding to intersubunit cavities of the GABAAR transmembrane domain. We find that very similar binding modes are predicted independently by three approaches: analogy with ivermectin in the GluCl crystal structure, automated docking by AutoDock, and spontaneous rebinding events in unbiased molecular dynamics simulations. Taken together, the models and atomistic simulations suggest a somewhat flexible binding mode, with several possible orientations. Finally, we explore the possibility that cholesterol promotes pore opening through a wedge mechanism.

Lipid concentration and molar ratio boundaries for the use of isotropic bicelles.

Bicelles are model membranes generally made of long-chain dimyristoylphosphatidylcholine (DMPC) and short-chain dihexanoyl-PC (DHPC). They are extensively used in the study of membrane interactions and structure determination of membrane-associated peptides, since their composition and morphology mimic the widespread PC-rich natural eukaryotic membranes. At low DMPC/DHPC (q) molar ratios, fast-tumbling bicelles are formed in which the DMPC bilayer is stabilized by DHPC molecules in the high-curvature rim region. Experimental constraints imposed by techniques such as circular dichroism, dynamic light scattering, or microscopy may require the use of bicelles at high dilutions. Studies have shown that such conditions induce the formation of small aggregates and alter the lipid-to-detergent ratio of the bicelle assemblies. The objectives of this work were to determine the exact composition of those DMPC/DHPC isotropic bicelles and study the lipid miscibility. This was done using (31)P nuclear magnetic resonance (NMR) and exploring a wide range of lipid concentrations (2-400 mM) and q ratios (0.15-2). Our data demonstrate how dilution modifies the actual DMPC/DHPC molar ratio in the bicelles. Care must be taken for samples with a total lipid concentration ≤250 mM and especially at q ∼ 1.5-2, since moderate dilutions could lead to the formation of large and slow-tumbling lipid structures that could hinder the use of solution NMR methods, circular dichroism or dynamic light scattering studies. Our results, supported by infrared spectroscopy and molecular dynamics simulations, also show that phospholipids in bicelles are largely segregated only when q > 1. Boundaries are presented within which control of the bicelles' q ratio is possible. This work, thus, intends to guide the choice of q ratio and total phospholipid concentration when using isotropic bicelles.

Lambda-ABF: Simplified, Portable, Accurate, and Cost-Effective Alchemical Free-Energy Computation.

We introduce the lambda-Adaptive Biasing Force (lambda-ABF) method for the computation of alchemical free-energy differences. We propose a software implementation and showcase it on biomolecular systems. The method arises from coupling multiple-walker adaptive biasing force with λ-dynamics. The sampling of the alchemical variable is continuous and converges toward a uniform distribution, making manual optimization of the λ schedule unnecessary. Contrary to most other approaches, alchemical free-energy estimates are obtained immediately without any postprocessing. Free diffusion of λ improves orthogonal relaxation compared to fixed-λ thermodynamic integration or free-energy perturbation. Furthermore, multiple walkers provide generic orthogonal space coverage with minimal user input and negligible computational overhead. We show that our high-performance implementations coupling the Colvars library with NAMD and Tinker-HP can address real-world cases including ligand-receptor binding with both fixed-charge and polarizable models, with a demonstrably richer sampling than fixed-λ methods. The implementation is fully open-source, publicly available, and readily usable by practitioners of current alchemical methods. Thanks to the portable Colvars library, lambda-ABF presents a unified user interface regardless of the back-end (NAMD, Tinker-HP, or any software to be interfaced in the future), sparing users the effort of learning multiple interfaces. Finally, the Colvars Dashboard extension of the visual molecular dynamics (VMD) software provides an interactive monitoring and diagnostic tool for lambda-ABF simulations.

General anesthetics predicted to block the GLIC pore with micromolar affinity.

Although general anesthetics are known to modulate the activity of ligand-gated ion channels in the Cys-loop superfamily, there is at present neither consensus on the underlying mechanisms, nor predictive models of this modulation. Viable models need to offer quantitative assessment of the relative importance of several identified anesthetic binding sites. However, to date, precise affinity data for individual sites has been challenging to obtain by biophysical means. Here, the likely role of pore block inhibition by the general anesthetics isoflurane and propofol of the prokaryotic pentameric channel GLIC is investigated by molecular simulations. Microscopic affinities are calculated for both single and double occupancy binding of isoflurane and propofol to the GLIC pore. Computations are carried out for an open-pore conformation in which the pore is restrained to crystallographic radius, and a closed-pore conformation that results from unrestrained molecular dynamics equilibration of the structure. The GLIC pore is predicted to be blocked at the micromolar concentrations for which inhibition by isofluorane and propofol is observed experimentally. Calculated affinities suggest that pore block by propofol occurs at signifcantly lower concentrations than those for which inhibition is observed: we argue that this discrepancy may result from binding of propofol to an allosteric site recently identified by X-ray crystallography, which may cause a competing gain-of-function effect. Affinities of isoflurane and propofol to the allosteric site are also calculated, and shown to be 3 mM for isoflurane and 10 µM for propofol; both anesthetics have a lower affinity for the allosteric site than for the unoccupied pore.

Multiple binding sites for the general anesthetic isoflurane identified in the nicotinic acetylcholine receptor transmembrane domain.

An extensive search for isoflurane binding sites in the nicotinic acetylcholine receptor (nAChR) and the proton gated ion channel from Gloebacter violaceus (GLIC) has been carried out based on molecular dynamics (MD) simulations in fully hydrated lipid membrane environments. Isoflurane introduced into the aqueous phase readily partitions into the lipid membrane and the membrane-bound protein. Specifically, isoflurane binds persistently to three classes of sites in the nAChR transmembrane domain: (i) An isoflurane dimer occludes the pore, contacting residues identified by previous mutagenesis studies; analogous behavior is observed in GLIC. (ii) Several nAChR subunit interfaces are also occupied, in a site suggested by photoaffinity labeling and thought to positively modulate the receptor; these sites are not occupied in GLIC. (iii) Isoflurane binds to the subunit centers of both nAChR alpha chains and one of the GLIC chains, in a site that has had little experimental targeting. Interpreted in the context of existing structural and physiological data, the present MD results support a multisite model for the mechanism of receptor-channel modulation by anesthetics.

Unwrapping NPT Simulations to Calculate Diffusion Coefficients.

In molecular dynamics simulations in the NPT ensemble at constant pressure, the size and shape of the periodic simulation box fluctuate with time. For particle images far from the origin, the rescaling of the box by the barostat results in unbounded position displacements. Special care is thus required when a particle trajectory is unwrapped from a projection into the central box under periodic boundary conditions to a trajectory in full three-dimensional space, e.g., for the calculation of translational diffusion coefficients. Here, we review and compare different schemes in use for trajectory unwrapping. We also specify the corresponding rewrapping schemes to put an unwrapped trajectory back into the central box. On this basis, we then identify a scheme for the calculation of diffusion coefficients from NPT simulations, which is a primary application of trajectory unwrapping. In this scheme, the wrapped and unwrapped trajectory are mutually consistent and their statistical properties are preserved. We conclude with advice on best practice for the consistent unwrapping of constant-pressure simulation trajectories and the calculation of accurate translational diffusion coefficients.

Molecular determinants of inhibition of UCP1-mediated respiratory uncoupling.

Brown adipose tissue expresses uncoupling protein 1 (UCP1), which dissipates energy as heat, making it a target for treating metabolic disorders. Here, we investigate how purine nucleotides inhibit respiration uncoupling by UCP1. Our molecular simulations predict that GDP and GTP bind UCP1 in the common substrate binding site in an upright orientation, where the base moiety interacts with conserved residues R92 and E191. We identify a triplet of uncharged residues, F88/I187/W281, forming hydrophobic contacts with nucleotides. In yeast spheroplast respiration assays, both I187A and W281A mutants increase the fatty acid-induced uncoupling activity of UCP1 and partially suppress the inhibition of UCP1 activity by nucleotides. The F88A/I187A/W281A triple mutant is overactivated by fatty acids even at high concentrations of purine nucleotides. In simulations, E191 and W281 interact with purine but not pyrimidine bases. These results provide a molecular understanding of the selective inhibition of UCP1 by purine nucleotides.

Alchemical Free Energy Calculations on Membrane-Associated Proteins.

Membrane proteins have diverse functions within cells and are well-established drug targets. The advances in membrane protein structural biology have revealed drug and lipid binding sites on membrane proteins, while computational methods such as molecular simulations can resolve the thermodynamic basis of these interactions. Particularly, alchemical free energy calculations have shown promise in the calculation of reliable and reproducible binding free energies of protein-ligand and protein-lipid complexes in membrane-associated systems. In this review, we present an overview of representative alchemical free energy studies on G-protein-coupled receptors, ion channels, transporters as well as protein-lipid interactions, with emphasis on best practices and critical aspects of running these simulations. Additionally, we analyze challenges and successes when running alchemical free energy calculations on membrane-associated proteins. Finally, we highlight the value of alchemical free energy calculations calculations in drug discovery and their applicability in the pharmaceutical industry.

Symmetry-Adapted Restraints for Binding Free Energy Calculations.

Binding free energy calculations rely critically on a precise definition of the bound state and well-designed ligand restraints to ensure that binding free energy calculations converge rapidly and yield estimates of well-defined thermodynamic quantities. The distance-to-bound-configuration (DBC) is a single variable that can precisely delineate the bound state of a ligand including translational, rotational and conformational degrees of freedom and has been successfully used to capture binding modes with complex geometries. DBC is defined as the root-mean-square deviation (RMSD) of ligand coordinates in the frame of reference of the binding site. In the special case where the ligand features symmetry-equivalent atoms, a standard RMSD arbitrarily distinguishes equivalent poses, mixing equivalent and nonequivalent degrees of freedom, and preventing the precise delineation of the bound state ensemble, which negates the benefits of defining a flat-bottom binding restraint. To remedy this, we introduce a symmetry-adapted DBC coordinate where the RMSD is minimized over permutations of equivalent ligand atoms. This coordinate is implemented in a portable software library, the Collective Variables Module. We tested the approach by computing the absolute binding free energy of benzene to the engineered site of a mutant lysozyme (L99A/M102H) using alchemical free energy perturbation. We found that the symmetry-adapted restraint leads to well-behaved convergence of both the decoupling free energy in the binding site and the restrained free energy in the gas phase, recovering the affinity computed using a classic center-of-mass restraint. Thus, symmetry-adapted DBC seamlessly generalizes the benefits of DBC restraints to the case of symmetric ligands. The underlying symmetric RMSD coordinate can also be used for analyzing or biasing simulations in other contexts than affinity predictions.

Human Learning for Molecular Simulations: The Collective Variables Dashboard in VMD.

The Collective Variables Dashboard is a software tool for real-time, seamless exploration of molecular structures and trajectories in a customizable space of collective variables. The Dashboard arises from the integration of the Collective Variables Module (also known as Colvars) with the visualization software VMD, augmented with a fully discoverable graphical interface offering interactive workflows for the design and analysis of collective variables. Typical use cases include a priori design of collective variables for enhanced sampling and free energy simulations as well as analysis of any type of simulation or collection of structures in a collective variable space. A combination of those cases commonly occurs when preliminary simulations, biased or unbiased, reveal that an optimized set of collective variables is necessary to improve sampling in further simulations. Then the Dashboard provides an efficient way to intuitively explore the space of likely collective variables, validate them on existing data, and use the resulting collective variable definitions directly in further biased simulations using the Collective Variables Module. Visualization of biasing energies and forces is proposed to help analyze or plan biased simulations. We illustrate the use of the Dashboard on two applications: discovering coordinates to describe ligand unbinding from a protein binding site and designing volume-based variables to bias the hydration of a transmembrane pore.

Consistent Picture of Phosphate-Divalent Cation Binding from Models with Implicit and Explicit Electronic Polarization.

The binding of divalent cations to the ubiquitous phosphate group is essential for a number of key biological processes, such as DNA compaction, RNA folding, or interactions of some proteins with membranes. Yet, probing their binding sites, modes, and associated binding free energy is a challenge for both experiments and simulations. In simulations, standard force fields strongly overestimate the interaction between phosphate groups and divalent cations. Here, we examine how different strategies to include electronic polarization effects in force fields─implicitly, through the use of scaled charges or pair-specific Lennard-Jones parameters, or explicitly, with the polarizable force fields Drude and AMOEBA─capture the interactions of a model phosphate compound, dimethyl phosphate, with calcium and magnesium divalent cations. We show that both implicit and explicit approaches, when carefully parameterized, are successful in capturing the overall binding free energy and that common trends emerge from the comparison of different simulation approaches. Overall, the binding is very moderate, slightly weaker for Ca2+ than Mg2+, and the solvent-shared ion pair is slightly more stable than the contact monodentate ion pair. The bidentate ion pair is higher in energy (or even fully unstable for Mg2+). Our results thus suggest practical ways to capture the divalent cations with biomolecular phosphate groups in complex biochemical systems. In particular, the computational efficiency of implicit models makes them ideally suited for large-scale simulations of biological assemblies, with improved accuracy compared to state-of-the-art fixed-charge force fields.

Open-channel structure of a pentameric ligand-gated ion channel reveals a mechanism of leaflet-specific phospholipid modulation.

Pentameric ligand-gated ion channels (pLGICs) mediate synaptic transmission and are sensitive to their lipid environment. The mechanism of phospholipid modulation of any pLGIC is not well understood. We demonstrate that the model pLGIC, ELIC (Erwinia ligand-gated ion channel), is positively modulated by the anionic phospholipid, phosphatidylglycerol, from the outer leaflet of the membrane. To explore the mechanism of phosphatidylglycerol modulation, we determine a structure of ELIC in an open-channel conformation. The structure shows a bound phospholipid in an outer leaflet site, and structural changes in the phospholipid binding site unique to the open-channel. In combination with streamlined alchemical free energy perturbation calculations and functional measurements in asymmetric liposomes, the data support a mechanism by which an anionic phospholipid stabilizes the activated, open-channel state of a pLGIC by specific, state-dependent binding to this site.

Embedded cholesterol in the nicotinic acetylcholine receptor.

The nicotinic acetylcholine receptor (nAChR) is a cation-selective channel central to both neuronal and muscular processes and is considered the prototype for ligand-gated ion channels, motivating a structural determination effort that spanned several decades [Unwin N (2005) Refined structure of the nicotinic acetylcholine receptor at 4 A resolution. J Mol Biol 346:967-989]. Purified nAChR must be reconstituted in a mixture containing cholesterol to function. Proposed modes of interaction between cholesterol and the protein range from specific binding to indirect membrane-mediated mechanisms. However, the underlying cause of nAChR sensitivity to cholesterol remains controversial, in part because the vast majority of functional studies were conducted before a medium resolution structure was reported. We show that the nAChR contains internal sites capable of containing cholesterol, whose occupation stabilizes the protein structure. We detect sites at the protein-lipid interface as conventionally predicted from functional data, as well as deeply buried sites that are not usually considered. Molecular dynamics simulations reveal that occupation of both superficial and deeply buried sites most effectively preserves the experimental structure; the structure collapses in the absence of bound cholesterol. In particular, we find that bound cholesterol directly supports contacts between the agonist-binding domain and the pore that are thought to be essential for activation of the receptor. These results likely apply to those other ion channels within the Cys-loop superfamily that depend on cholesterol, such as the GABA receptor.

Fast and Accurate Multidimensional Free Energy Integration.

Enhanced sampling and free energy calculation algorithms of the thermodynamic integration family (such as the adaptive biasing force (ABF) method) are not based on the direct computation of a free energy surface but rather of its gradient. Integrating the free energy surface is nontrivial in dimensions higher than one. Here, the author introduces a flexible, portable implementation of a Poisson equation formalism to integrate free energy surfaces from estimated gradients in dimensions 2 and 3 using any combination of periodic and nonperiodic (Neumann) boundary conditions. The algorithm is implemented in portable C++ and provided as a standalone tool that can be used to integrate multidimensional gradient fields estimated on a grid using any algorithm, such as umbrella integration as a post-treatment of umbrella sampling simulations. It is also included in the implementation of ABF (and its extended-system variant eABF) in the Collective Variables Module, enabling the seamless computation of multidimensional free energy surfaces within ABF and eABF simulations. A Python-based analysis toolchain is provided to easily plot and analyze multidimensional ABF simulation results, including metrics to assess their convergence. The Poisson integration algorithm can also be used to perform Helmholtz decomposition of noisy gradient estimates on the fly, resulting in an efficient implementation of the projected ABF (pABF) method proposed by Leliévre and co-workers. In numerical tests, pABF is found to lead to faster convergence with respect to ABF in simple cases of low intrinsic dimension but seems detrimental to convergence in a more realistic case involving degenerate coordinates and hidden barriers due to slower exploration. This suggests that variance reduction schemes do not always yield convergence improvements when applied to enhanced sampling methods.