Tuning Potential Functions to Host-Guest Binding Data.

Software to more rapidly and accurately predict protein-ligand binding affinities is of high interest for early-stage drug discovery, and physics-based methods are among the most widely used technologies for this purpose. The accuracy of these methods depends critically on the accuracy of the potential functions that they use. Potential functions are typically trained against a combination of quantum chemical and experimental data. However, although binding affinities are among the most important quantities to predict, experimental binding affinities have not to date been integrated into the experimental data set used to train potential functions. In recent years, the use of host-guest complexes as simple and tractable models of binding thermodynamics has gained popularity due to their small size and simplicity, relative to protein-ligand systems. Host-guest complexes can also avoid ambiguities that arise in protein-ligand systems such as uncertain protonation states. Thus, experimental host-guest binding data are an appealing additional data type to integrate into the experimental data set used to optimize potential functions. Here, we report the extension of the Open Force Field Evaluator framework to enable the systematic calculation of host-guest binding free energies and their gradients with respect to force field parameters, coupled with the curation of 126 host-guest complexes with available experimental binding free energies. As an initial application of this novel infrastructure, we optimized generalized Born (GB) cavity radii for the OBC2 GB implicit solvent model against experimental data for 36 host-guest systems. This refitting led to a dramatic improvement in accuracy for both the training set and a separate test set with 90 additional host-guest systems. The optimized radii also showed encouraging transferability from host-guest systems to 59 protein-ligand systems. However, the new radii are significantly smaller than the baseline radii and lead to excessively favorable hydration free energies (HFEs). Thus, users of the OBC2 GB model currently may choose between GB cavity radii that yield more accurate binding affinities and GB cavity radii that yield more accurate HFEs. We suspect that achieving good accuracy on both will require more far-reaching adjustments to the GB model. We note that binding free-energy calculations using the OBC2 model in OpenMM gain about a 10× speedup relative to corresponding explicit solvent calculations, suggesting a future role for implicit solvent absolute binding free-energy (ABFE) calculations in virtual compound screening. This study proves the principle of using host-guest systems to train potential functions that are transferrable to protein-ligand systems and provides an infrastructure that enables a range of applications.

Divalent cations bind to phosphoinositides to induce ion and isomer specific propensities for nano-cluster initiation in bilayer membranes.

We report all-atom molecular dynamics simulations of asymmetric bilayers containing phosphoinositides in the presence of monovalent and divalent cations. We have characterized the molecular mechanism by which these divalent cations interact with phosphoinositides. Ca2+ desolvates more readily, consistent with single-molecule calculations, and forms a network of ionic-like bonds that serve as a 'molecular glue' that allows a single ion to coordinate with up to three phosphatidylinositol-(4,5)-bisphosphate (PI(4, 5)P2) lipids. The phosphatidylinositol-(3,5)-bisphosphate isomer shows no such effect and neither does PI(4, 5)P2 in the presence of Mg2+. The resulting network of Ca2+-mediated lipid-lipid bonds grows to span the entire simulation space and therefore has implications for the lateral distribution of phosophoinositides in the bilayer. We observe context-specific differences in lipid diffusion rates, lipid surface densities and bilayer structure. The molecular-scale delineation of ion-lipid arrangements reported here provides insight into similar nanocluster formation induced by peripheral proteins to regulate the formation of functional signalling complexes on the membrane.

The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.

Approaches for computing small molecule binding free energies based on molecular simulations are now regularly being employed by academic and industry practitioners to study receptor-ligand systems and prioritize the synthesis of small molecules for ligand design. Given the variety of methods and implementations available, it is natural to ask how the convergence rates and final predictions of these methods compare. In this study, we describe the concept and results for the SAMPL6 SAMPLing challenge, the first challenge from the SAMPL series focusing on the assessment of convergence properties and reproducibility of binding free energy methodologies. We provided parameter files, partial charges, and multiple initial geometries for two octa-acid (OA) and one cucurbit[8]uril (CB8) host-guest systems. Participants submitted binding free energy predictions as a function of the number of force and energy evaluations for seven different alchemical and physical-pathway (i.e., potential of mean force and weighted ensemble of trajectories) methodologies implemented with the GROMACS, AMBER, NAMD, or OpenMM simulation engines. To rank the methods, we developed an efficiency statistic based on bias and variance of the free energy estimates. For the two small OA binders, the free energy estimates computed with alchemical and potential of mean force approaches show relatively similar variance and bias as a function of the number of energy/force evaluations, with the attach-pull-release (APR), GROMACS expanded ensemble, and NAMD double decoupling submissions obtaining the greatest efficiency. The differences between the methods increase when analyzing the CB8-quinine system, where both the guest size and correlation times for system dynamics are greater. For this system, nonequilibrium switching (GROMACS/NS-DS/SB) obtained the overall highest efficiency. Surprisingly, the results suggest that specifying force field parameters and partial charges is insufficient to generally ensure reproducibility, and we observe differences between seemingly converged predictions ranging approximately from 0.3 to 1.0 kcal/mol, even with almost identical simulations parameters and system setup (e.g., Lennard-Jones cutoff, ionic composition). Further work will be required to completely identify the exact source of these discrepancies. Among the conclusions emerging from the data, we found that Hamiltonian replica exchange-while displaying very small variance-can be affected by a slowly-decaying bias that depends on the initial population of the replicas, that bidirectional estimators are significantly more efficient than unidirectional estimators for nonequilibrium free energy calculations for systems considered, and that the Berendsen barostat introduces non-negligible artifacts in expanded ensemble simulations.

Binding Thermodynamics of Host-Guest Systems with SMIRNOFF99Frosst 1.0.5 from the Open Force Field Initiative.

Designing ligands that bind their target biomolecules with high affinity and specificity is a key step in small-molecule drug discovery, but accurately predicting protein-ligand binding free energies remains challenging. Key sources of errors in the calculations include inadequate sampling of conformational space, ambiguous protonation states, and errors in force fields. Noncovalent complexes between a host molecule with a binding cavity and a druglike guest molecule have emerged as powerful model systems. As model systems, host-guest complexes reduce many of the errors in more complex protein-ligand binding systems, as their small size greatly facilitates conformational sampling, and one can choose systems that avoid ambiguities in protonation states. These features, combined with their ease of experimental characterization, make host-guest systems ideal model systems to test and ultimately optimize force fields in the context of binding thermodynamics calculations. The Open Force Field Initiative aims to create a modern, open software infrastructure for automatically generating and assessing force fields using data sets. The first force field to arise out of this effort, named SMIRNOFF99Frosst, has approximately one tenth the number of parameters, in version 1.0.5, compared to typical general small molecule force fields, such as GAFF. Here, we evaluate the accuracy of this initial force field, using free energy calculations of 43 α and ß-cyclodextrin host-guest pairs for which experimental thermodynamic data are available, and compare with matched calculations using two versions of GAFF. For all three force fields, we used TIP3P water and AM1-BCC charges. The calculations are performed using the attach-pull-release (APR) method as implemented in the open source package, pAPRika. For binding free energies, the root-mean-square error of the SMIRNOFF99Frosst calculations relative to experiment is 0.9 [0.7, 1.1] kcal/mol, while the corresponding results for GAFF 1.7 and GAFF 2.1 are 0.9 [0.7, 1.1] kcal/mol and 1.7 [1.5, 1.9] kcal/mol, respectively, with 95% confidence ranges in brackets. These results suggest that SMIRNOFF99Frosst performs competitively with existing small molecule force fields and is a parsimonious starting point for optimization.

Open collaborative writing with Manubot.

Open, collaborative research is a powerful paradigm that can immensely strengthen the scientific process by integrating broad and diverse expertise. However, traditional research and multi-author writing processes break down at scale. We present new software named Manubot, available at https://manubot.org, to address the challenges of open scholarly writing. Manubot adopts the contribution workflow used by many large-scale open source software projects to enable collaborative authoring of scholarly manuscripts. With Manubot, manuscripts are written in Markdown and stored in a Git repository to precisely track changes over time. By hosting manuscript repositories publicly, such as on GitHub, multiple authors can simultaneously propose and review changes. A cloud service automatically evaluates proposed changes to catch errors. Publication with Manubot is continuous: When a manuscript's source changes, the rendered outputs are rebuilt and republished to a web page. Manubot automates bibliographic tasks by implementing citation by identifier, where users cite persistent identifiers (e.g. DOIs, PubMed IDs, ISBNs, URLs), whose metadata is then retrieved and converted to a user-specified style. Manubot modernizes publishing to align with the ideals of open science by making it transparent, reproducible, immediate, versioned, collaborative, and free of charge.

Escaping Atom Types in Force Fields Using Direct Chemical Perception.

Traditional approaches to specifying a molecular mechanics force field encode all the information needed to assign force field parameters to a given molecule into a discrete set of atom types. This is equivalent to a representation consisting of a molecular graph comprising a set of vertices, which represent atoms labeled by atom type, and unlabeled edges, which represent chemical bonds. Bond stretch, angle bend, and dihedral parameters are then assigned by looking up bonded pairs, triplets, and quartets of atom types in parameter tables to assign valence terms and using the atom types themselves to assign nonbonded parameters. This approach, which we call indirect chemical perception because it operates on the intermediate graph of atom-typed nodes, creates a number of technical problems. For example, atom types must be sufficiently complex to encode all necessary information about the molecular environment, making it difficult to extend force fields encoded this way. Atom typing also results in a proliferation of redundant parameters applied to chemically equivalent classes of valence terms, needlessly increasing force field complexity. Here, we describe a new approach to assigning force field parameters via direct chemical perception. Rather than working through the intermediary of the atom-typed graph, direct chemical perception operates directly on the unmodified chemical graph of the molecule to assign parameters. In particular, parameters are assigned to each type of force field term (e.g., bond stretch, angle bend, torsion, and Lennard-Jones) based on standard chemical substructure queries implemented via the industry-standard SMARTS chemical perception language, using SMIRKS extensions that permit labeling of specific atoms within a chemical pattern. We use this to implement a new force field format, called the SMIRKS Native Open Force Field (SMIRNOFF) format. We demonstrate the power and generality of this approach using examples of specific molecules that pose problems for indirect chemical perception and construct and validate a minimalist yet very general force field, SMIRNOFF99Frosst. We find that a parameter definition file only ∼300 lines long provides coverage of all but <0.02% of a 5 million molecule drug-like test set. Despite its simplicity, the accuracy of SMIRNOFF99Frosst for small molecule hydration free energies and selected properties of pure organic liquids is similar to that of the General Amber Force Field, whose specification requires thousands of parameters. This force field provides a starting point for further optimization and refitting work to follow.

Motor-like Properties of Nonmotor Enzymes.

Molecular motors are thought to generate force and directional motion via nonequilibrium switching between energy surfaces. Because all enzymes can undergo such switching, we hypothesized that the ability to generate rotary motion and torque is not unique to highly adapted biological motor proteins but is instead a common feature of enzymes. We used molecular dynamics simulations to compute energy surfaces for hundreds of torsions in three enzymes-adenosine kinase, protein kinase A, and HIV-1 protease-and used these energy surfaces within a kinetic model that accounts for intersurface switching and intrasurface probability flows. When substrate is out of equilibrium with product, we find computed torsion rotation rates up ∼140 cycles s-1, with stall torques up to ∼2 kcal mol-1 cycle-1, and power outputs up to ∼50 kcal mol-1 s-1. We argue that these enzymes are instances of a general phenomenon of directional probability flows on asymmetric energy surfaces for systems out of equilibrium. Thus, we conjecture that cyclic probability fluxes, corresponding to rotations of torsions and higher-order collective variables, exist in any chiral molecule driven between states in a nonequilibrium manner; we call this the "Asymmetry-Directionality" conjecture. This is expected to apply as well to synthetic chiral molecules switched in a nonequilibrium manner between energy surfaces by light, redox chemistry, or catalysis.

The SAMPL5 host-guest challenge: computing binding free energies and enthalpies from explicit solvent simulations by the attach-pull-release (APR) method.

The absolute binding free energies and binding enthalpies of twelve host-guest systems in the SAMPL5 blind challenge were computed using our attach-pull-release (APR) approach. This method has previously shown good correlations between experimental and calculated binding data in retrospective studies of cucurbit[7]uril (CB7) and ß-cyclodextrin (ßCD) systems. In the present work, the computed binding free energies for host octa acid (OA or OAH) and tetra-endo-methyl octa-acid (TEMOA or OAMe) with guests are in good agreement with prospective experimental data, with a coefficient of determination (R2) of 0.8 and root-mean-squared error of 1.7 kcal/mol using the TIP3P water model. The binding enthalpy calculations achieve moderate correlations, with R2 of 0.5 and RMSE of 2.5 kcal/mol, for TIP3P water. Calculations using the newly developed OPC water model also show good performance. Furthermore, the present calculations semi-quantitatively capture the experimental trend of enthalpy-entropy compensation observed, and successfully predict guests with the strongest and weakest binding affinity. The most populated binding poses of all twelve systems, based on clustering analysis of 750 ns molecular dynamics (MD) trajectories, were extracted and analyzed. Computational methods using MD simulations and explicit solvent models in a rigorous statistical thermodynamic framework, like APR, can generate reasonable predictions of binding thermodynamics. Especially with continuing improvement in simulation force fields, such methods hold the promise of making substantial contributions to hit identification and lead optimization in the drug discovery process.

Overview of the SAMPL5 host-guest challenge: Are we doing better?

The ability to computationally predict protein-small molecule binding affinities with high accuracy would accelerate drug discovery and reduce its cost by eliminating rounds of trial-and-error synthesis and experimental evaluation of candidate ligands. As academic and industrial groups work toward this capability, there is an ongoing need for datasets that can be used to rigorously test new computational methods. Although protein-ligand data are clearly important for this purpose, their size and complexity make it difficult to obtain well-converged results and to troubleshoot computational methods. Host-guest systems offer a valuable alternative class of test cases, as they exemplify noncovalent molecular recognition but are far smaller and simpler. As a consequence, host-guest systems have been part of the prior two rounds of SAMPL prediction exercises, and they also figure in the present SAMPL5 round. In addition to being blinded, and thus avoiding biases that may arise in retrospective studies, the SAMPL challenges have the merit of focusing multiple researchers on a common set of molecular systems, so that methods may be compared and ideas exchanged. The present paper provides an overview of the host-guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution. A range of methods were applied, including electronic structure calculations with implicit solvent models; methods that combine empirical force fields with implicit solvent models; and explicit solvent free energy simulations. The most reliable methods tend to fall in the latter class, consistent with results in prior SAMPL rounds, but the level of accuracy is still below that sought for reliable computer-aided drug design. Advances in force field accuracy, modeling of protonation equilibria, electronic structure methods, and solvent models, hold promise for future improvements.

Salmon-derived thrombin inhibits development of chronic pain through an endothelial barrier protective mechanism dependent on APC.

Many neurological disorders are initiated by blood-brain barrier breakdown, which potentiates spinal neuroinflammation and neurodegeneration. Peripheral neuropathic injuries are known to disrupt the blood-spinal cord barrier (BSCB) and to potentiate inflammation. But, it is not known whether BSCB breakdown facilitates pain development. In this study, a neural compression model in the rat was used to evaluate relationships among BSCB permeability, inflammation and pain-related behaviors. BSCB permeability increases transiently only after injury that induces mechanical hyperalgesia, which correlates with serum concentrations of pro-inflammatory cytokines, IL-7, IL-12, IL-1α and TNF-α. Mammalian thrombin dually regulates vascular permeability through PAR1 and activated protein C (APC). Since thrombin protects vascular integrity through APC, directing its affinity towards protein C, while still promoting coagulation, might be an ideal treatment for BSCB-disrupting disorders. Salmon thrombin, which prevents the development of mechanical allodynia, also prevents BSCB breakdown after neural injury and actively inhibits TNF-α-induced endothelial permeability in vitro, which is not evident the case for human thrombin. Salmon thrombin's production of APC faster than human thrombin is confirmed using a fluorogenic assay and APC is shown to inhibit BSCB breakdown and pain-related behaviors similar to salmon thrombin. Together, these studies highlight the impact of BSCB on pain and establish salmon thrombin as an effective blocker of BSCB, and resulting nociception, through its preferential affinity for protein C.

Physical chemistry and membrane properties of two phosphatidylinositol bisphosphate isomers.

The most highly charged phospholipids, polyphosphoinositides, are often involved in signaling pathways that originate at cell-cell and cell-matrix contacts, and different isomers of polyphosphoinositides have distinct biological functions that cannot be explained by separate highly specific protein ligand binding sites [Lemmon, Nat. Rev. Mol. Cell Biol., 2008, 9, 99-111]. PtdIns(3,5)P2 is a low abundance phosphoinositide localized to cytoplasmic-facing membrane surfaces, with relatively few known ligands, yet PtdIns(3,5)P2 plays a key role in controlling membrane trafficking events and cellular stress responses that cannot be duplicated by other phosphoinositides [Dove et al., Nature, 1997, 390, 187-192; Michell, FEBS J., 2013, 280, 6281-6294]. Here we show that PtdIns(3,5)P2 is structurally distinct from PtdIns(4,5)P2 and other more common phospholipids, with unique physical chemistry. Using multiscale molecular dynamics techniques on the quantum level, single molecule, and in bilayer settings, we found that the negative charge of PtdIns(3,5)P2 is spread over a larger area, compared to PtdIns(4,5)P2, leading to a decreased ability to bind divalent ions. Additionally, our results match well with experimental data characterizing the cluster forming potential of these isomers in the presence of Ca(2+) [Wang et al., J. Am. Chem. Soc., 2012, 134, 3387-3395; van den Bogaart et al., Nature, 2011, 479, 552-555]. Our results demonstrate that the different cellular roles of PtdIns(4,5)P2 and PtdIns(3,5)P2in vivo are not simply determined by their localization by enzymes that produce or degrade them, but also by their molecular size, ability to chelate ions, and the partial dehydration of those ions, which might affect the ability of PtdIns(3,5)P2 and PtdIns(4,5)P2 to form phosphoinositide-rich clusters in vitro and in vivo.

Polyelectrolyte properties of filamentous biopolymers and their consequences in biological fluids.

Anionic polyelectrolyte filaments are common in biological cells. DNA, RNA, the cytoskeletal filaments F-actin, microtubules, and intermediate filaments, and polysaccharides such as hyaluronan that form the pericellular matrix all have large net negative charge densities distributed over their surfaces. Several filamentous viruses with diameters and stiffnesses similar to those of cytoskeletal polymers also have similar negative charge densities. Extracellular protein filaments such collagen, fibrin and elastin, in contrast, have notably smaller charge densities and do not behave as highly charged polyelectrolytes in solution. This review summarizes data that demonstrate generic counterion-mediated effects on four structurally unrelated biopolymers of similar charge density: F-actin, vimentin, Pf1 virus, and DNA, and explores the possible biological and pathophysiological consequences of the polyelectrolyte properties of biological filaments.

Counterion-mediated pattern formation in membranes containing anionic lipids.

Most lipid components of cell membranes are either neutral, like cholesterol, or zwitterionic, like phosphatidylcholine and sphingomyelin. Very few lipids, such as sphingosine, are cationic at physiological pH. These generally interact only transiently with the lipid bilayer, and their synthetic analogs are often designed to destabilize the membrane for drug or DNA delivery. However, anionic lipids are common in both eukaryotic and prokaryotic cell membranes. The net charge per anionic phospholipid ranges from -1 for the most abundant anionic lipids such as phosphatidylserine, to near -7 for phosphatidylinositol 3,4,5 trisphosphate, although the effective charge depends on many environmental factors. Anionic phospholipids and other negatively charged lipids such as lipopolysaccharides are not randomly distributed in the lipid bilayer, but are highly restricted to specific leaflets of the bilayer and to regions near transmembrane proteins or other organized structures within the plane of the membrane. This review highlights some recent evidence that counterions, in the form of monovalent or divalent metal ions, polyamines, or cationic protein domains, have a large influence on the lateral distribution of anionic lipids within the membrane, and that lateral demixing of anionic lipids has effects on membrane curvature and protein function that are important for biological control.

Counterion-mediated cluster formation by polyphosphoinositides.

Polyphosphoinositides (PPI) and in particular PI(4,5)P2, are among the most highly charged molecules in cell membranes, are important in many cellular signaling pathways, and are frequently targeted by peripheral polybasic proteins for anchoring through electrostatic interactions. Such interactions between PIP2 and proteins containing polybasic stretches depend on the physical state and the lateral distribution of PIP2 within the inner leaflet of the cell's lipid bilayer. The physical and chemical properties of PIP2 such as pH-dependent changes in headgroup ionization and area per molecule as determined by experiments together with molecular simulations that predict headgroup conformations at various ionization states have revealed the electrostatic properties and phase behavior of PIP2-containing membranes. This review focuses on recent experimental and computational developments in defining the physical chemistry of PIP2 and its interactions with counterions. Ca(2+)-induced changes in PIP2 charge, conformation, and lateral structure within the membrane are documented by numerous experimental and computational studies. A simplified electrostatic model successfully predicts the Ca(2+)-driven formation of PIP2 clusters but cannot account for the different effects of Ca(2+) and Mg(2+) on PIP2-containing membranes. A more recent computational study is able to see the difference between Ca(2+) and Mg(2+) binding to PIP2 in the absence of a membrane and without cluster formation. Spectroscopic studies suggest that divalent cation- and multivalent polyamine-induced changes in the PIP2 lateral distribution in model membrane are also different, and not simply related to the net charge of the counterion. Among these differences is the capacity of Ca(2+) but not other polycations to induce nm scale clusters of PIP2 in fluid membranes. Recent super resolution optical studies show that PIP2 forms nanoclusters in the inner leaflet of a plasma membrane with a similar size distribution as those induced by Ca(2+) in model membranes. The mechanisms by which PIP2 forms nanoclusters and other structures inside a cell remain to be determined, but the unique electrostatic properties of PIP2 and its interactions with multivalent counterions might have particular physiological relevance.

Quantum and all-atom molecular dynamics simulations of protonation and divalent ion binding to phosphatidylinositol 4,5-bisphosphate (PIP2).

Molecular dynamics calculations have been used to determine the structure of phosphatidylinositol 4,5 bisphosphate (PIP2) at the quantum level and to quantify the propensity for PIP2 to bind two physiologically relevant divalent cations, Mg(2+) and Ca(2+). We performed a geometry optimization at the Hartree-Fock 6-31+G(d) level of theory in vacuum and with a polarized continuum dielectric to determine the conformation of the phospholipid headgroup in the presence of water and its partial charge distribution. The angle between the headgroup and the acyl chains is nearly perpendicular, suggesting that in the absence of other interactions the inositol ring would lie flat along the cytoplasmic surface of the plasma membrane. Next, we employed hybrid quantum mechanics/molecular mechanics (QM/MM) simulations to investigate the protonation state of PIP2 and its interactions with magnesium or calcium. We test the hypothesis suggested by prior experiments that binding of magnesium to PIP2 is mediated by a water molecule that is absent when calcium binds. These results may explain the selective ability of calcium to induce the formation of PIP2 clusters and phase separation from other lipids.

Optimization of coded aperture radioscintigraphy for sentinel lymph node mapping.

PURPOSE: Radioscintigraphic imaging during sentinel lymph node (SLN) mapping could potentially improve localization; however, parallel-hole collimators have certain limitations. In this study, we explored the use of coded aperture (CA) collimators. PROCEDURES: Equations were derived for the six major dependent variables of CA collimators (i.e., masks) as a function of the ten major independent variables, and an optimized mask was fabricated. After validation, dual-modality CA and near-infrared (NIR) fluorescence SLN mapping were performed in pigs. RESULTS: Mask optimization required the judicious balance of competing dependent variables, resulting in sensitivity of 0.35%, XY resolution of 2.0 mm, and Z resolution of 4.2 mm at an 11.5-cm field of view. The findings in pigs suggested that NIR fluorescence imaging and CA radioscintigraphy could be complementary, but present difficult technical challenges. CONCLUSIONS: This study lays the foundation for using CA collimation for SLN mapping, and also exposes several problems that require further investigation.

Transmembrane orientation and possible role of the fusogenic peptide from parainfluenza virus 5 (PIV5) in promoting fusion.

Membrane fusion is required for diverse biological functions ranging from viral infection to neurotransmitter release. Fusogenic proteins increase the intrinsically slow rate of fusion by coupling energetically downhill conformational changes of the protein to kinetically unfavorable fusion of the membrane-phospholipid bilayers. Class I viral fusogenic proteins have an N-terminal hydrophobic fusion peptide (FP) domain, important for interaction with the target membrane, plus a C-terminal transmembrane (C-term-TM) helical membrane anchor. The role of the water-soluble regions of fusogenic proteins has been extensively studied, but the contributions of the membrane-interacting FP and C-term-TM peptides are less well characterized. Typically, FPs are thought to bind to membranes at an angle that allows helix penetration but not traversal of the lipid bilayer. Here, we show that the FP from the paramyxovirus parainfluenza virus 5 fusogenic protein, F, forms an N-terminal TM helix, which self-associates into a hexameric bundle. This FP also interacts strongly with the C-term-TM helix. Thus, the fusogenic F protein resembles SNARE proteins involved in vesicle fusion by having water-soluble coiled coils that zipper during fusion and TM helices in both membranes. By analogy to mechanosensitive channels, the force associated with zippering of the water-soluble coiled-coil domain is expected to lead to tilting of the FP helices, promoting interaction with the C-term-TM helices. The energetically unfavorable dehydration of lipid headgroups of opposing bilayers is compensated by thermodynamically favorable interactions between the FP and C-term-TM helices as the coiled coils zipper into the membrane phase, leading to a pore lined by both lipid and protein.