Solvation models and computational prediction of orientations of peptides and proteins in membranes

Antimicrobial peptide interactions with bacterial cell membranes

Antimicrobial peptides (AMPs) are potential alternatives for common antibiotics because of their greater activity and efficiency against a broad range of viruses, bacteria, fungi, and parasites. In this project, two antimicrobial peptides including magainin 2 and protegrin 1 with α-helix and β-sheet secondary structures were selected to investigate their interactions with different lipid bilayers such as 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine (POPS), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), POPC/POPG (7:3), POPC/POPS (7:3), POPG/POPE(1:3), and POPG/POPE(3:1). The obtained structures of the AMPs illustrated that protegrin 1 cannot maintain its secondary structure in the solution phase in contrast to magainin 2. The head groups of the lipid units play a key role in the stability of the lipid bilayers. The head parts of the lipid membranes by increasing the internal H-bond contribute to membrane compactness. The POPG and POPS units inside the POPC/POPG and POPC/POPS membranes increase the order of the POPC units. The cationic residues of the AMPs form remarkable electrostatic interactions with the negatively charged membrane surfaces, which play a key role in the stabilization process of the peptide secondary structures. The Arg residues of protegrin 1 and the Gly1, Lys4, Lys10, Lys11, Lys14, and Glu19 of the magainin 2 have the most important roles in the complexation process. The values of Gibbs binding energies (ΔG) indicate that the complexation process between AMPs and different bacterial membranes is favorable from the thermodynamic viewpoint and AMPs could form stable complexes with the lipid bilayers. As a result of ΔG values, protegrin 1 forms a more stable complex with POPG/POPE(3:1), while the α-helix has more affinity to the POPG/POPE(1:3) bacterial membranes. Therefore, it can be considered that β-sheet and α-helix AMPs are more effective against gram-positive and gram-negative bacteria, respectively. The results of this study can provide useful details about the antimicrobial peptide interactions with the bacterial cell, which can be employed for designing new antimicrobial materials with greater efficiency.Communicated by Ramaswamy H. Sarma.

BRANEart: Identify Stability Strength and Weakness Regions in Membrane Proteins

Understanding the role of stability strengths and weaknesses in proteins is a key objective for rationalizing their dynamical and functional properties such as conformational changes, catalytic activity, and protein-protein and protein-ligand interactions. We present BRANEart, a new, fast and accurate method to evaluate the per-residue contributions to the overall stability of membrane proteins. It is based on an extended set of recently introduced statistical potentials derived from membrane protein structures, which better describe the stability properties of this class of proteins than standard potentials derived from globular proteins. We defined a per-residue membrane propensity index from combinations of these potentials, which can be used to identify residues which strongly contribute to the stability of the transmembrane region or which would, on the contrary, be more stable in extramembrane regions, or vice versa. Large-scale application to membrane and globular proteins sets and application to tests cases show excellent agreement with experimental data. BRANEart thus appears as a useful instrument to analyze in detail the overall stability properties of a target membrane protein, to position it relative to the lipid bilayer, and to rationally modify its biophysical characteristics and function. BRANEart can be freely accessed from http://babylone.3bio.ulb.ac.be/BRANEart.

Getting to know each other: PPIMem, a novel approach for predicting transmembrane protein-protein complexes

Because of their considerable number and diversity, membrane proteins and their macromolecular complexes represent the functional units of cells. Their quaternary structure may be stabilized by interactions between the α-helices of different proteins in the hydrophobic region of the cell membrane. Membrane proteins equally represent potential pharmacological targets par excellence for various diseases. Unfortunately, their experimental 3D structure and that of their complexes with other intramembrane protein partners are scarce due to technical difficulties. To overcome this key problem, we devised PPIMem, a computational approach for the specific prediction of higher-order structures of α-helical transmembrane proteins. The novel approach involves proper identification of the amino acid residues at the interface of molecular complexes with a 3D structure. The identified residues compose then nonlinear interaction motifs that are conveniently expressed as mathematical regular expressions. These are efficiently implemented for motif search in amino acid sequence databases, and for the accurate prediction of intramembrane protein-protein complexes. Our template interface-based approach predicted 21,544 binary complexes between 1,504 eukaryotic plasma membrane proteins across 39 species. We compare our predictions to experimental datasets of protein-protein interactions as a first validation method. The online database that results from the PPIMem algorithm with the annotated predicted interactions are implemented as a web server and can be accessed directly at https://transint.univ-evry.fr.

Accelerated molecular dynamics simulation analysis of MSI-594 in a lipid bilayer

Multidrug resistance against the existing antibiotics is one of the most challenging threats across the globe. Antimicrobial peptides (AMPs), in this regard, are considered to be one of the effective alternatives that can overcome bacterial resistance. MSI-594, a 24-residue linear alpha-helical cationic AMP, has been shown to function via the carpet mechanism to disrupt bacterial membrane systems. To better understand the role of lipid composition in the function of MSI-594, in the present study, eight different model membrane systems have been studied using accelerated molecular dynamics (aMD) simulations. The simulated results are helpful in discriminating the particular effects of cationic MSI-594 against zwitterionic POPC, anionic POPG and POPS, and neutral POPE lipid moieties. Additionally, the effects of various heterogeneous POPC/POPG (7 : 3), POPC/POPS (7 : 3), and POPG/POPE (1 : 3 and 3 : 1) bilayer systems on the dynamic interaction of MSI-594 have also been investigated. The effect on the lipid bilayer due to the interaction with the peptide is characterized by lipid acyl-chain order, membrane thickness, and acyl-chain dynamics. Our simulation results show that the lipid composition affects the membrane interaction of MSI-594, suggesting that membrane selectivity is crucial to its mechanism of action. The results reported in this study are helpful to obtain accurate atomistic-level information governing MSI-594 and its membrane disruptive antimicrobial mechanism of action, and to design next generation potent antimicrobial peptides.

Ligand and membrane-binding behavior of the phosphatidylinositol transfer proteins PITPα and PITPβ

Phosphatidylinositol transfer proteins (PITPs) are believed to be lipid transfer proteins because of their ability to transfer either phosphatidylinositol (PI) or phosphatidylcholine (PC) between membrane compartments, in vitro. However, the detailed mechanism of this transfer process is not fully established. To further understand the transfer mechanism of PITPs we examined the interaction of PITPs with membranes using dual polarization interferometry (DPI), which measures protein binding affinity on a flat immobilized lipid surface. In addition, a fluorescence resonance energy transfer (FRET)-based assay was also employed to monitor how quickly PITPs transfer their ligands to lipid vesicles. DPI analysis revealed that PITPβ had a higher affinity to membranes compared with PITPα. Furthermore, the FRET-based transfer assay revealed that PITPβ has a higher ligand transfer rate compared with PITPα. However, both PITPα and PITPβ demonstrated a preference for highly curved membrane surfaces during ligand transfer. In other words, ligand transfer rate was higher when the accepting vesicles were highly curved.

Biological applications of classical electrostatics methods

Continuum electrostatics modeling of solvation based on the Poisson–Boltzmann (PB) equation has gained wide acceptance in biomolecular applications such as energetic analysis and structural visualization. Successful application of the PB solvent models requires careful calibration of the solvation parameters. Extensive testing and validation is also important to ensure accuracy in their applications. Limitation in the continuum modeling of solvation is also a known issue in certain biomolecular applications. Growing interest in membrane systems has further spurred developmental efforts to allow inclusion of membrane in the PB solvent models. Despite their past successes due to careful parameterization, algorithm development and parallel implementation, there is still much to be done to improve their transferability from the small molecular systems upon which they were developed and validated to complex macromolecular systems as advances in technology continue to push forward, providing ever greater computational resources to researchers to study more interesting biological systems of higher complexity.