Calculations of pH-dependent binding of proteins to biological membranes

Challenges of Protein-Protein Docking of the Membrane Proteins

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes.

Simulations suggest a scaffolding mechanism of membrane deformation by the caveolin 8S complex

Caveolins form complexes of various sizes that deform membranes into polyhedral shapes. However, the recent structure of the 8S complex was disk-like with a flat membrane-binding surface. How can a flat complex deform membranes into nonplanar structures? Molecular dynamics simulations revealed that the 8S complex rapidly takes the form of a suction cup. Simulations on implicit membrane vesicles determined that binding is stronger when E140 gets protonated. In that case, the complex binds much more strongly to 5- and 10-nm-radius vesicles. A concave membrane-binding surface readily explains the membrane-deforming ability of caveolins by direct scaffolding. We propose that the 8S complex sits at the vertices of the caveolar polyhedra, rather than at the center of the polyhedral faces.

Relevance of the protein macrodipole in the membrane-binding process. Interactions of fatty-acid binding proteins with cationic lipid membranes

The fatty acid-binding proteins L-BABP and Rep1-NCXSQ bind to anionic lipid membranes by electrostatic interactions. According to Molecular Dynamics (MD) simulations, the interaction of the protein macrodipole with the membrane electric field is a driving force for protein binding and orientation in the interface. To further explore this hypothesis, we studied the interactions of these proteins with cationic lipid membranes. As in the case of anionic lipid membranes, we found that both proteins, carrying a negative as well as a positive net charge, were bound to the positively charged membrane. Their major axis, those connecting the bottom of the β-barrel with the α-helix portal domain, were rotated about 180 degrees as compared with their orientations in the anionic lipid membranes. Fourier transform infrared (FTIR) spectroscopy of the proteins showed that the positively charged membranes were also able to induce conformational changes with a reduction of the β-strand proportion and an increase in α-helix secondary structure. Fatty acid-binding proteins (FABPs) are involved in several cell processes, such as maintaining lipid homeostasis in cells. They transport hydrophobic molecules in aqueous medium and deliver them into lipid membranes. Therefore, the interfacial orientation and conformation, both shown herein to be electrostatically determined, have a strong correlation with the specific mechanism by which each particular FABP exerts its biological function.

Free Energy Calculations for the Peripheral Binding of Proteins/Peptides to an Anionic Membrane. 1. Implicit Membrane Models

The binding of peptides and proteins to the surface of complex lipid membranes is important in many biological processes such as cell signaling and membrane remodeling. Computational studies can aid experiments by identifying physical interactions and structural motifs that determine the binding affinity and specificity. However, previous studies focused on either qualitative behaviors of protein/membrane interactions or the binding affinity of small peptides. Motivated by this observation, we set out to develop computational protocols for bimolecular binding to charged membranes that are applicable to both peptides and large proteins. In this work, we explore a method based on an implicit membrane/solvent model (generalized Born with a simple switching in combination with the Gouy-Chapman-Stern model for a charged interface), which we expect to lead to useful results when the binding does not implicate significant membrane deformation and local demixing of lipids. We show that the binding free energy can be efficiently computed following a thermodynamic cycle similar to protein-ligand binding calculations, especially when a Bennett acceptance ratio based protocol is used to consider both the membrane bound and solution conformational ensembles. Test calculations on a series of peptides show that our computational approach leads to binding affinities in encouraging agreement with experimental data, including for the challenging example of the bringing of flexible MARCKS-ED peptides to membranes. The calculations highlight that for a membrane with a significant fraction of anionic lipids, it is essential to include the effect of ion adsorption using the Stern model, which significantly modifies the effective surface charge. This implicit membrane model based computational protocol helps lay the groundwork for more systematic analysis of protein/peptide binding to membranes of complex shape and composition.

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.

Spectroscopic investigation of fluorinated phenols as pH-sensitive probes in mixed liposomal systems

The pK_a values of three fluorinated phenols, 2,4,6-trifluorophenol (3FP), 2,3,5,6-tetrafluorophenol (4FP) and 2,3,4,5,6-pentafluorophenol (5FP) have been measured by using UV-vis and ¹⁹F-NMR spectroscopy at 25 °C in water and in the presence of pure POPC, pure DDAB and mixed POPC–DDAB liposomes.

Transmembrane helix association affinity can be modulated by flanking and noninterfacial residues

The GxxxG sequence motif mediates the association of transmembrane (TM) helices by providing a site of close contact between them. However, it is not sufficient for strong association. For example, both bacteriophage M13 major coat protein (MCP) and human erythrocyte protein glycophorin A (GpA) contain a GxxxG motif in their TM domains and form a homodimer, but the association affinity of MCP, measured by the ToxCAT in vivo assay, is dramatically weaker than that of GpA. Even when all interfacial residues of MCP were substituted for those of GpA (MCP-GpA), association remained significantly weaker than in GpA. Here we provide an explanation for these experimental observations using molecular dynamics simulations in an implicit membrane (IMM1-GC). The association free energies of GpA29 (GpA with 29 residues all from the wild-type sequence), GpA15p11 (GpA with 15 residues from the wild-type sequence plus 11 flanking residues from the ToxCAT construct), MCP, and MCP-GpA TM helices were calculated and compared. MCP and MCP-GpA have the same flanking residues used in the ToxCAT assay as those in GpA15p11, but the position of the flanking residues relative to the GxxxG motif is different. The calculated association free energies follow experimental observations: the association affinity of MCP-GpA falls between those of GpA15p11 and MCP wild-type. MCP exhibits an equally strong interhelical interaction in the TM domain. A major reason for the weaker association of MCP in the calculations was the noninterfacial residue Lys-40, which in the dimer structure is forced to be buried in the membrane interior. To alleviate the desolvation cost, in MCP and MCP-GpA dimers, Lys-40 gets deprotonated. A second factor that modulates association affinity is the flanking residues. Thanks to them, GpA15p11 exhibits a much stronger association affinity than GpA29. The positioning of the flanking residues is also important, as evidenced by the difference in association affinity between MCP and MCP-GpA on one hand and GpA15p11 on the other. Thus, residues outside the contact interface can exert a significant influence on transmembrane helix association affinity.

CHARMM: the biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983.

Membrane-bound structure and energetics of alpha-synuclein

Aggregation and fibrillation of alpha-synuclein bound to membranes are believed to be involved in Parkinson's and other neurodegenerative diseases. On SDS micelles, the N-terminus of alpha-synuclein forms two curved helices linked by a short loop. However, its structure on lipid bilayers has not been experimentally resolved. Using MD simulations with an implicit membrane model we show here that, on a planar mixed membrane, the truncated alpha-synuclein (residues 1-95) forms a bent helix. Bending of the helix is not due to the protein sequence or membrane binding, but to collective motions of the long helix. The backbone of the helix is approximately 2.5 A above the membrane surface, with some residues partially inserted in the membrane core. The helix periodicity is 11/3 (11 residues complete three full turns) as opposed to 18/5 periodicity of an ideal alpha-helix, with hydrophobic residues towards the membrane, negatively charged residues towards the solvent and lysines on the polar/nonpolar interface. A series of threonines, which are characteristic for alpha-synuclein and perhaps a phosphorylation site, is also located at the hydrophobic/hydrophilic interface with their side chain often hydrogen bonded to the main-chain atom. The calculations show that the energy penalty for change in periodicity from the 18/5 to 11/3 on the anionic membrane is overcome by favorable solvation energy. The binding of truncated alpha-synuclein to membranes is weak. It prefers anionic membranes but it also binds marginally to a neutral membrane, via its C-terminus. Dimerization of helical monomers on the mixed membrane is energetically favorable. However, it slightly interferes with membrane binding. This might promote lateral diffusion of the protein on the membrane surface and facilitate assembly of oligomers that precede fibrillation.

Modeling fatty acid delivery from intestinal fatty acid binding protein to a membrane

Intestinal fatty acid binding protein (IFABP) interacts with biological membranes and delivers fatty acid (FA) into them via a collisional mechanism. However, the membrane-bound structure of the protein and the pathway of FA transfer are not precisely known. We used molecular dynamics (MD) simulations with an implicit membrane model to determine the optimal orientation of apo- and holo-IFABP (bound with palmitate) on an anionic membrane. In this orientation, the helical portal region, delimited by the alphaII helix and the betaC-betaD and betaE-betaF turns, is oriented toward the membrane whereas the putative beta-strand portal, delimited by the betaB-betaC, betaF-betaG, betaH-betaI turns and the N terminus, is exposed to solvent. Starting from the MD structure of holo-IFABP in the optimal orientation relative to the membrane, we examined the release of palmitate via both pathways. Although the domains can widen enough to allow the passage of palmitate, fatty acid release through the helical portal region incurs smaller conformational changes and a lower energetic cost.

Configuration of influenza hemagglutinin fusion peptide monomers and oligomers in membranes

The 20 N-terminal residues of the HA2 subunit of influenza hemagglutinin (HA), known as the fusion peptide, play a crucial role in membrane fusion. Molecular dynamics simulations with implicit solvation are employed here to study the structure and orientation of the fusion peptide in membranes. As a monomer the alpha-helical peptide adopts a shallow, slightly tilted orientation along the lipid tail-head group interface. The average angle of the peptide with respect to membrane plane is 12.4 degrees . We find that the kinked structure proposed on the basis of NMR data is not stable in our model because of the high energy cost related to the membrane insertion of polar groups. Because hemagglutinin-mediated membrane fusion is promoted by low pH, we examined the effect of protonation of the Glu and Asp residues. The configurations of the protonated peptides were slightly deeper in the membrane but at similar angles. Finally, because HA is a trimer, we modeled helical fusion peptide trimers. We find that oligomerization affects the insertion depth of the peptide and its orientation with respect to the membrane: a trimer exhibits equally favorable configurations in which some or all of the helices in the bundle insert obliquely deep into the membrane.