Folding Simulations of the Transmembrane Helix of Virus Protein U in an Implicit Membrane Model

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Dimerization energetics of the G-protein coupled bile acid receptor TGR5 from all-atom simulations

We describe the first extensive energetic evaluation of GPCR dimerization on the atomistic level by means of potential of mean force (PMF) computations and implicit solvent/implicit membrane end-point free energy calculations (MM-PBSA approach). Free energies of association computed from the PMFs show that the formation of both the 1/8 and 4/5 interface is energetically favorable for TGR5, the first GPCR known to be activated by hydrophobic bile acids and neurosteroids. Furthermore, formation of the 1/8 interface is favored over that of the 4/5 interface. Both results are in line with our previous FRET experiments in live cells. Differences in lipid-protein interactions are identified to contribute to the observed differences in free energies of association. A per-residue decomposition of the MM-PBSA effective binding energy reveals hot spot residues specific for both interfaces that form clusters. This knowledge may be used to guide the design of dimerization inhibitors or perform mutational studies to explore physiological consequences of distorted TGR5 association. Finally, we characterized the role of Y111, located in the conserved (D/E)RY motif, as a facilitator of TGR5 interactions. The types of computations performed here should be transferable to other transmembrane proteins that form dimers or higher oligomers as long as good structural models of the dimeric or oligomeric states are available. Such computations may help to overcome current restrictions due to an imperfect energetic representation of protein association at the coarse-grained level. © 2019 Wiley Periodicals, Inc.

Molecular Dynamics Simulations Are Redefining Our View of Peptides Interacting with Biological Membranes

Ever since the first molecular mechanics computer simulations of biological molecules became possible, there has been the dream to study all complex biological phenomena in silico, simply bypassing the enormous experimental challenges and their associated costs. For this, two inherent requirements need to be met: First, the time scales achievable in simulations must reach up to the millisecond range and even longer. Second, the computational model must accurately reproduce what is measured experimentally. Despite some recent successes, the general consensus in the field to date has been that neither of these conditions have yet been met and that the dream will be realized, if at all, only in the distant future. In this Account, we show that this view is wrong; instead, we are actually in the middle of the in silico molecular dynamics (MD) revolution, which is reshaping how we think about protein function. The example explored in this Account is a recent advance in the field of membrane-active peptides (MAPs). MD simulations have succeeded in accurately capturing the process of peptide binding, folding, and partitioning into lipid bilayers as well as revealing how channels form spontaneously from polypeptide fragments and conduct ionic and other cargo across membranes, all at atomic resolution. These game-changing advances have been made possible by a combination of steadily advancing computational power, more efficient algorithms and techniques, clever accelerated sampling schemes, and thorough experimental verifications. The great advantage of MD is the spatial and temporal resolution, directly providing a molecular movie of a protein undergoing folding and cycling through a functional process. This is especially important for proteins with transitory functional states, such as pore-forming MAPs. Recent successes are demonstrated here for the large class of antimicrobial peptides (AMPs). These short peptides are an essential part of the nonadaptive immune system for many organisms, ubiquitous in nature, and of particular interest to the pharmaceutical industry in the age of rising bacterial resistance to conventional antibiotic treatments. Unlike integral membrane proteins, AMPs are sufficiently small to allow converged sampling with the unbiased high-temperature sampling methodology outlined here and are relatively easy to handle experimentally. At the same time, AMPs exhibit a wealth of complex and poorly understood interactions with lipid bilayers, which allow not only tuning and validation of the simulation methodology but also advancement of our knowledge of protein-lipid interactions at a fundamental level. Space constraints limit our discussion to AMPs, but the MD methodologies outlined here can be applied to all phenomena involving peptides in membranes, including cell-penetrating peptides, signaling peptides, viral channel forming peptides, and fusion peptides, as well as ab initio membrane protein folding and assembly. For these systems, the promise of MD simulations to predict the structure of channels and to provide complete-atomic-detail trajectories of the mechanistic processes underlying their biological functions appears to rapidly become a reality. The current challenge is to design joint experimental and computational benchmarks to verify and tune MD force fields. With this, MD will finally fulfill its promise to become an inexpensive, powerful, and easy-to-use tool providing atomic-detail insights to researchers as part of their investigations into membrane biophysics and beyond.

A Finite Element Solution of Lateral Periodic Poisson-Boltzmann Model for Membrane Channel Proteins

Membrane channel proteins control the diffusion of ions across biological membranes. They are closely related to the processes of various organizational mechanisms, such as: cardiac impulse, muscle contraction and hormone secretion. Introducing a membrane region into implicit solvation models extends the ability of the Poisson–Boltzmann (PB) equation to handle membrane proteins. The use of lateral periodic boundary conditions can properly simulate the discrete distribution of membrane proteins on the membrane plane and avoid boundary effects, which are caused by the finite box size in the traditional PB calculations. In this work, we: (1) develop a first finite element solver (FEPB) to solve the PB equation with a two-dimensional periodicity for membrane channel proteins, with different numerical treatments of the singular charges distributions in the channel protein; (2) add the membrane as a dielectric slab in the PB model, and use an improved mesh construction method to automatically identify the membrane channel/pore region even with a tilt angle relative to the z-axis; and (3) add a non-polar solvation energy term to complete the estimation of the total solvation energy of a membrane protein. A mesh resolution of about 0.25 Å (cubic grid space)/0.36 Å (tetrahedron edge length) is found to be most accurate in linear finite element calculation of the PB solvation energy. Computational studies are performed on a few exemplary molecules. The results indicate that all factors, the membrane thickness, the length of periodic box, membrane dielectric constant, pore region dielectric constant, and ionic strength, have individually considerable influence on the solvation energy of a channel protein. This demonstrates the necessity to treat all of those effects in the PB model for membrane protein simulations.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Membrane/Toxin Interaction Energetics via Serial Multiscale Molecular Dynamics Simulations

Computing free energies of complex biomolecular systems via atomistic (AT) molecular dynamics (MD) simulations remains a challenge due to the need for adequate sampling and convergence. Recent coarse-grained (CG) methodology allows simulations of significantly larger systems (∼10(6) to 10(8) atoms) over longer (μs/ms) time scales. Such CG models appear to be capable of making semiquantitative predictions. However, their ability to reproduce accurate thermodynamic quantities remains uncertain. We have recently used CG MD simulations to compute the potential of mean force (PMF) or free energy profile of a small peptide toxin interacting with a lipid bilayer along a 1D reaction coordinate. The toxin studied was VSTx1 (Voltage Sensor Toxin 1) from spider venom which inhibits the archeabacterial voltage-gated potassium (Kv) channel KvAP by binding to the voltage-sensor (VS) domains. Here, we re-estimate this PMF profile using (i) AT MD simulations with explicit membrane and solvent and (ii) an implicit membrane and solvent (generalized Born; GBIM) model where only the peptide was explicit. We used the CG MD free energy simulations to guide the setup of the corresponding AT MD simulations. The aim was to avoid local minima in the AT simulations which would be difficult over shorter AT time scales. A cross-comparison of the PMF profiles revealed a conserved topology, although there were differences in the magnitude of the free energies. The CG and AT simulations predicted a membrane/water interface free energy well of -27 and -23 kcal/mol, respectively (with respect to water). The GBIM model, however, gave a reduced interfacial free energy well (-12 kcal/mol). In addition, the CG and GBIM models predicted a free energy barrier of +61 and +96 kcal/mol, respectively, for positioning the toxin at the center of the bilayer, which was considerably smaller in the AT simulations (+26 kcal/mol). Thus, we present a framework for serially combining CG and AT simulations to estimate the free energy of peptide/membrane interactions. Such approaches for combining simulations at different levels of granularity will become increasingly important in future studies of complex membrane/protein systems.

United Atom Lipid Parameters for Combination with the Optimized Potentials for Liquid Simulations All-Atom Force Field

We have developed a new united-atom set of lipid force field parameters for dipalmitoylphosphatidylcholine (DPPC) lipid bilayers that can be combined with the all-atom optimized potentials for liquid simulations (OPLS-AA) protein force field. For this, all torsions have been refitted for a nonbonded 1-4 scale factor of 0.5, which is the standard in OPLS-AA. Improved van der Waals parameters have been obtained for the acyl lipid tails by matching simulation results of bulk pentadecane against recently improved experimental measurements. The charge set has been adjusted from previous lipid force fields to allow for an identical treatment of the alkoxy ester groups. This reduces the amount of parameters required for the model. Simulation of DPPC bilayers in the tension-free NPT ensemble at 50 °C gives the correct area per lipid of 62.9 ± 0.1 Å(2), which compares well with the recently refined experimental value of 63.0 Å(2). Electron density profiles and deuterium order parameters are similarly well reproduced. The new parameters will allow for improved simulation results in microsecond scale peptide partitioning simulations, which have proved problematic with prior parametrizations.

Applications of MMPBSA to Membrane Proteins I: Efficient Numerical Solutions of Periodic Poisson-Boltzmann Equation

Continuum solvent models have been widely used in biomolecular modeling applications. Recently much attention has been given to inclusion of implicit membranes into existing continuum Poisson-Boltzmann solvent models to extend their applications to membrane systems. Inclusion of an implicit membrane complicates numerical solutions of the underlining Poisson-Boltzmann equation due to the dielectric inhomogeneity on the boundary surfaces of a computation grid. This can be alleviated by the use of the periodic boundary condition, a common practice in electrostatic computations in particle simulations. The conjugate gradient and successive over-relaxation methods are relatively straightforward to be adapted to periodic calculations, but their convergence rates are quite low, limiting their applications to free energy simulations that require a large number of conformations to be processed. To accelerate convergence, the Incomplete Cholesky preconditioning and the geometric multigrid methods have been extended to incorporate periodicity for biomolecular applications. Impressive convergence behaviors were found as in the previous applications of these numerical methods to tested biomolecules and MMPBSA calculations.

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.

Molecular dynamics simulations reveal the HIV-1 Vpu transmembrane protein to form stable pentamers

The human immunodeficiency virus type I (HIV-1) Vpu protein is 81 residues long and has two cytoplasmic and one transmembrane (TM) helical domains. The TM domain oligomerizes to form a monovalent cation selective ion channel and facilitates viral release from host cells. Exactly how many TM domains oligomerize to form the pore is still not understood, with experimental studies indicating the existence of a variety of oligomerization states. In this study, molecular dynamics (MD) simulations were performed to investigate the propensity of the Vpu TM domain to exist in tetrameric, pentameric, and hexameric forms. Starting with an idealized α-helical representation of the TM domain, a thorough search for the possible orientations of the monomer units within each oligomeric form was carried out using replica-exchange MD simulations in an implicit membrane environment. Extensive simulations in a fully hydrated lipid bilayer environment on representative structures obtained from the above approach showed the pentamer to be the most stable oligomeric state, with interhelical van der Waals interactions being critical for stability of the pentamer. Atomic details of the factors responsible for stable pentamer structures are presented. The structural features of the pentamer models are consistent with existing experimental information on the ion channel activity, existence of a kink around the Ile17, and the location of tetherin binding residues. Ser23 is proposed to play an important role in ion channel activity of Vpu and possibly in virus propagation.

Characterization of the interface of the bone marrow stromal cell antigen 2-Vpu protein complex via computational chemistry

Bone marrow stromal cell antigen 2 (BST-2) inhibits the release of enveloped viruses from the cell surface. Various viral counter measures have been discovered, which allow viruses to escape BST-2 restriction. Human immunodeficiency virus type 1 (HIV-1) encodes viral protein U (Vpu) that interacts with BST-2 through their transmembrane domains and causes the downregulation of cell surface BST-2. In this study, we used a computer modeling method to establish a molecular model to investigate the binding interface of the transmembrane domains of BST-2 and Vpu. The model predicts that the interface is composed of Vpu residues I6, A10, A14, A18, V25, and W22 and BST-2 residues L23, I26, V30, I34, V35, L41, I42, and T45. Introduction of mutations that have been previously reported to disrupt the Vpu-BST-2 interaction led to a calculated higher binding free energy (MMGBSA), which supports our molecular model. A pharmacophore was also generated on the basis of this model. Our results provide a precise model that predicts the detailed interaction occurring between the transmembrane domains of Vpu and BST-2 and should facilitate the design of anti-HIV agents that are able to disrupt this interaction.

In silico partitioning and transmembrane insertion of hydrophobic peptides under equilibrium conditions

Nascent transmembrane (TM) polypeptide segments are recognized and inserted into the lipid bilayer by the cellular translocon machinery. The recognition rules, described by a biological hydrophobicity scale, correlate strongly with physical hydrophobicity scales that describe the free energy of insertion of TM helices from water. However, the exact relationship between the physical and biological scales is unknown, because solubility problems limit our ability to measure experimentally the direct partitioning of hydrophobic peptides across lipid membranes. Here we use microsecond molecular dynamics (MD) simulations in which monomeric polyleucine segments of different lengths are allowed to partition spontaneously into and out of lipid bilayers. This approach directly reveals all states populated at equilibrium. For the hydrophobic peptides studied here, only surface-bound and transmembrane-inserted helices are found. The free energy of insertion is directly obtained from the relative occupancy of these states. A water-soluble state was not observed, consistent with the general insolubility of hydrophobic peptides. The approach further allows determination of the partitioning pathways and kinetics. Surprisingly, the transfer free energy appears to be independent of temperature, which implies that surface-to-bilayer peptide insertion is a zero-entropy process. We find that the partitioning free energy of the polyleucine segments correlates strongly with values from translocon experiments but reveals a systematic shift favoring shorter peptides, suggesting that translocon-to-bilayer partitioning is not equivalent but related to spontaneous surface-to-bilayer partitioning.

Viral channel forming proteins - modeling the target

The cellular and subcellular membranes encounter an important playground for the activity of membrane proteins encoded by viruses. Viral membrane proteins, similar to their host companions, can be integral or attached to the membrane. They are involved in directing the cellular and viral reproduction, the fusion and budding processes. This review focuses especially on those integral viral membrane proteins which form channels or pores, the classification to be so, modeling by in silico methods and potential drug candidates. The sequence of an isolate of Vpu from HIV-1 is aligned with host ion channels and a toxin. The focus is on the alignment of the transmembrane domains. The results of the alignment are mapped onto the 3D structures of the respective channels and toxin. The results of the mapping support the idea of a 'channel-pore dualism' for Vpu.

Oligomerization state and supramolecular structure of the HIV-1 Vpu protein transmembrane segment in phospholipid bilayers

HIV-1 Vpu is an 81-residue protein with a single N-terminal transmembrane (TM) helical segment that is involved in the release of new virions from host cell membranes. Vpu and its TM segment form ion channels in phospholipid bilayers, presumably by oligomerization of TM helices into a pore-like structure. We describe measurements that provide new constraints on the oligomerization state and supramolecular structure of residues 1-40 of Vpu (Vpu(1-40)), including analytical ultracentrifugation measurements to investigate oligomerization in detergent micelles, photo-induced crosslinking experiments to investigate oligomerization in bilayers, and solid-state nuclear magnetic resonance measurements to obtain constraints on intermolecular contacts between and orientations of TM helices in bilayers. From these data, we develop molecular models for Vpu TM oligomers. The data indicate that a variety of oligomers coexist in phospholipid bilayers, so that a unique supramolecular structure can not be defined. Nonetheless, since oligomers of various sizes have similar intermolecular contacts and orientations, molecular models developed from our data are most likely representative of Vpu TM oligomers that exist in host cell membranes.

Determining peptide partitioning properties via computer simulation

The transfer of polypeptide segments into lipid bilayers to form transmembrane helices represents the crucial first step in cellular membrane protein folding and assembly. This process is driven by complex and poorly understood atomic interactions of peptides with the lipid bilayer environment. The lack of suitable experimental techniques that can resolve these processes both at atomic resolution and nanosecond timescales has spurred the development of computational techniques. In this review, we summarize the significant progress achieved in the last few years in elucidating the partitioning of peptides into lipid bilayer membranes using atomic detail molecular dynamics simulations. Indeed, partitioning simulations can now provide a wealth of structural and dynamic information. Furthermore, we show that peptide-induced bilayer distortions, insertion pathways, transfer free energies, and kinetic insertion barriers are now accurate enough to complement experiments. Further advances in simulation methods and force field parameter accuracy promise to turn molecular dynamics simulations into a powerful tool for investigating a wide range of membrane active peptide phenomena.

Conformational preferences of a 14-residue fibrillogenic peptide from acetylcholinesterase

A 14-residue fragment from near the C-terminus of the enzyme acetylcholinesterase (AChE) is believed to have a neurotoxic/neurotrophic effect acting via an unknown pathway. While the peptide is α-helical in the full-length enzyme, the structure and association mechanism of the fragment are unknown. Using multiple molecular dynamics simulations, starting from a tetrameric complex of the association domain of AChE and systematically disassembled subsets that include the peptide fragment, we show that the fragment is incapable of retaining its helicity in solution. Extensive replica exchange Monte Carlo folding and unfolding simulations in implicit solvent with capped and uncapped termini failed to converge to any consistent cluster of structures, suggesting that the fragment remains largely unstructured in solution under the conditions considered. Furthermore, extended molecular dynamics simulations of two steric zipper models show that the peptide is likely to form a zipper with antiparallel sheets and that peptides with mutations known to prevent fibril formation likely do so by interfering with this packing. The results demonstrate how the local environment of a peptide can stabilize a particular conformation.

Viral channel-forming proteins

Channel-forming proteins are found in a number of viral genomes. In some cases, their role in the viral life cycle is well understood, in some cases it needs still to be elucidated. A common theme is that their mode of action involves a change of electrochemical or proton gradient across the lipid membrane which modulates the viral or cellular activity. Blocking these proteins can be a suitable therapeutic strategy as for some viruses this may be "lethal." Besides the many biological relevant questions still to be answered, there are also many open questions concerning the biophysical side as well as structural information and the mechanism of function on a molecular level. The immanent biophysical issues are addressed and the work in the field is summarized.

Methods for Monte Carlo simulations of biomacromolecules

The state-of-the-art for Monte Carlo (MC) simulations of biomacromolecules is reviewed. Available methodologies for sampling conformational equilibria and associations of biomacromolecules in the canonical ensemble, given a continuum description of the solvent environment, are reviewed. Detailed sections are provided dealing with the choice of degrees of freedom, the efficiencies of MC algorithms and algorithmic peculiarities, as well as the optimization of simple movesets. The issue of introducing correlations into elementary MC moves, and the applicability of such methods to simulations of biomacromolecules is discussed. A brief discussion of multicanonical methods and an overview of recent simulation work highlighting the potential of MC methods are also provided. It is argued that MC simulations, while underutilized biomacromolecular simulation community, hold promise for simulations of complex systems and phenomena that span multiple length scales, especially when used in conjunction with implicit solvation models or other coarse graining strategies.

Self-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channel

The transmembrane (TM) domain of the M2 channel protein from influenza A is a homotetrameric bundle of alpha-helices and provides a model system for computational approaches to self-assembly of membrane proteins. Coarse-grained molecular dynamics (CG-MD) simulations have been used to explore partitioning into a membrane of M2 TM helices during bilayer self-assembly from lipids. CG-MD is also used to explore tetramerization of preinserted M2 TM helices. The M2 helix monomer adopts a membrane spanning orientation in a lipid (DPPC) bilayer. Multiple extended CG-MD simulations (5 x 5 micros) were used to study the tetramerization of inserted M2 helices. The resultant tetramers were evaluated in terms of the most populated conformations and the dynamics of their interconversion. This analysis reveals that the M2 tetramer has 2x rotationally symmetrical packing of the helices. The helices form a left-handed bundle, with a helix tilt angle of approximately 16 degrees. The M2 helix bundle generated by CG-MD was converted to an atomistic model. Simulations of this model reveal that the bundle's stability depends on the assumed protonation state of the H37 side chains. These simulations alongside comparison with recent x-ray (3BKD) and NMR (2RLF) structures of the M2 bundle suggest that the model yielded by CG-MD may correspond to a closed state of the channel.