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Cell-penetrating peptides (CPPs) have recently attracted much interest due to their apparent ability to penetrate cell membranes in an energy-independent manner. Here molecular-dynamics simulation techniques were used to study the interaction of two CPPs: penetratin and the TAT peptide with 1,2-Dipaimitoyl-sn-glycero-3-phosphocholine (DPPC) and 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) phospolipid bilayers shed light on alternative mechanisms by which these peptides might cross biological membranes. In contrast to previous simulation studies of charged peptides interacting with lipid bilayers, no spontaneous formation of transmembrane pores was observed. Instead, the simulations suggest that the peptides may enter the cell by micro-pinocytosis, whereby the peptides induce curvature in the membrane, ultimately leading to the formation of small vesicles within the cell that encapsulate the peptides. Specifically, multiple peptides were observed to induce large deformations in the lipid bilayer that persisted throughout the timescale of the simulations (hundreds of nanoseconds). Pore formation could be induced in simulations in which an external potential was used to pull a single penetratin or TAT peptide into the membrane. With the use of umbrella-sampling techniques, the free energy of inserting a single penetratin peptide into a DPPC bilayer was estimated to be similar to 75 kJmol(-1), which suggests that the spontaneous penetration of single peptides would require a timescale of at least seconds to minutes. This work also illustrates the extent to which the results of such simulations can depend on the initial conditions, the extent of equilibration, the size of the system, and the conditions under which the simulations are performed. The implications of this with respect to the current systems and to simulations of membrane-peptide interactions in general are discussed.

Structural, dynamic and energetic properties of proteins in solution can be studied in atomic detail by molecular dynamics computer simulation. Protein unfolding can be caused by a variety of driving forces induced in different ways: increased temperature or pressure, change of solvent composition, or protein amino acid mutation. The stability and unfolding of four different proteins (bovine pancreatic trypsin inhibitor, hen egg white lysozyme, the surfactant protein C and the DNA-binding domain of the 434 repressor) have been studied by applying the afore-mentioned driving forces and also to some artificial forces. The results give a picture of protein (in)stability and possible unfolding pathways, and are compared to experimental data where possible.

Many quantities that are standardly used to characterize a chemical system are related to free-energy differences between particular states of the system. By statistical mechanics, free-energy differences may be expressed in terms of averages over ensembles of atomic configurations for the molecular system of interest. Here, we review the most useful formulae to calculate free-energy differences from ensembles generated by molecular simulation, illustrate a number of recent developments, and highlight practical aspects of such calculations with examples selected from the literature.

Venom peptides that bind to ion channels have attracted much interest as potential lead molecules for pharmaceutical development. However, experiments to determine the structure of large peptide-channel complexes are challenging. Instead, structural models are often derived by combining experimental information with restraint-driven docking. The question is how reliable are such models and what is the most effective use of available experimental data. Also, structures obtained from docking are often assessed using geometric criteria, which might of limited use to an experimentalist aiming to identify the interactions at the binding interface for lead optimization. Using the complex formed by the venom peptide PcTx1 and the acid sensing ion channel 1 as a case study, we to examined the likelihood of using restraint-driven docking to find a structure that can be used to identify interfacial residues and to predict specific pairwise peptide-channel interactions.For this, we have analysed over 240’000 docked structures of the PcTx1-ASIC1a complex, produced using HADDOCK [1]. This showed that when using information on residues involved in binding for both the peptide and the channel, there is a ∼60% chance of predicting a structure with an interface-RMSD < 4A compared to the PcTx1-ASIC1a co-crystal structure. The likelihood of correctly identifying specific pairwise peptide-channel interactions was ∼30%. Furthermore, we will show how the effect of variability between docking runs should be considered when carrying out restraint-driven docking of peptide-channel complexes. Finally, we reflect on the limitations of relying on geometric criteria such as RMSD to assess the accuracy of docking procedures for lead optimization.1. Dominguez, C.; Boelens, R.; Bonvin, A. M., J. Am. Chem. Soc. 2003.

In order to investigate the dependence of the viscosity on the mass of the molecules in a liquid, and thus check the validity of Stokes' law for molecules, several molecular dynamics simulations of `water' molecules with different mass and different molecular mass distributions were performed. The viscosity is shown to be sensitive to the mass but less sensitive to the mass distribution. The product of diffusion coefficient and viscosity, which according to Stokes' law should be independent of the mass, varies. We may therefore conclude that Stokes' law is not valid for small molecules.

The binding of a set of 10 triphenoxypyridine derivatives to two serine proteases, factor Xa and trypsin, has been used to analyze factors related to sampling and convergence in free energy calculations based on molecular dynamics simulation techniques. The inhibitors investigated were initially proposed as part of the Critical Assessment of Techniques for Free Energy Evaluation (CATFEE) project for which no experimental results nor any assessment of the predictions submitted by various groups have ever been published. The inhibitors studied represent a severe challenge for explicit free energy calculations. The mutations from one compound to another involve up to 19 atoms, the creation and annihilation of net charge and several alternate binding modes. Nevertheless, we demonstrate that it is possible to obtain highly converged results (+/- 5-10 kJ/mol) even for such complex multi-atom mutations by simulating on a nanosecond time scale. This is achieved by using soft-core potentials to facilitate the creation and deletion of atoms and by a careful choice of mutation pathway. The results show that given modest computational resources, explicit free energy calculations can be successfully applied to realistic problems in drug design.

Several simulation methods are currently in use to study peptide and protein folding. They can be classified in three groups depending on how the solvent is treated. At the simplest level, the solvent is ignored. At a second level, solvent effects are implicitly represented in the atomic interaction function. At the third level, solvent degrees of freedom are treated explicitly. We have performed molecular dynamics simulations in vacuum, stochastic dynamics simulations, and molecular dynamics simulations in methanol of the folding of a β-heptapeptide to test these different levels of approximation. The results clearly show that the solvent cannot be ignored in folding simulations, and highlight the difficulties of implicitly modelling solvent effects in an atomic interaction function for a solute.

Highly optimized and well-validated parameters have been developed for structure refinement and computer simulation of biomolecules. However, the force fields for most drug and drug-like ligand molecules are not properly validated. Out of ∼100,000 X-ray crystal structures in the Protein Data Bank (2014), >25,000 structures contain at least one of >17,000 chemically diverse ligand molecules. In addition, there is over a million ligand molecules of interest in databases such as NCI and Pubchem. Understanding interatomic interactions of a given ligand with its target acceptor is crucial in molecular modelling and the lack of precise force field parameters for small heteromolecules may result in failure of drug design efforts.A web accessible Automated force field Topology Builder (ATB; http://compbio.biosci.uq.edu.au/atb/) and Repository was developed to facilitate the generation of force field parameters for chemically diverse ligand molecules. The ATB performs quantum mechanical calculations combined with a knowledge-based approach to ensure compatibility with a biomolecular force field. The topologies and parameters created can be used in simulations, computational drug design and X-ray refinement.Most importantly, a fully automated validation of the force field parameters has been incorporated into the ATB methodology. Recent work on the validation of parameters against structural and thermodynamic data as well as the outcome of participating in the SAMPL4 community challenge for the prediction of hydration free energy of drug-like molecules will be presented. Further refinement strategies to improve the parameters by scaling of the van der Waals and electrostatic interactions will be discussed as well.

A wide range of peptides is known to modulate the behavior of lipid membranes, in particular to be able to destabilize the normal lamellar state. Here we compare the various ways in which a lipid membrane can be distorted due to the presence of such peptides, using molecular dynamics simulations. In particular we show examples of membrane poration by antimicrobial peptides, micropinocytosis by cell penetrating peptides, and the formation of cubic phases by fusion peptides (see figure).View Large Image | View Hi-Res Image | Download PowerPoint SlideSnapshot of a single diamond cubic phase induced by the Influenze HA fusion peptide. The helical parts of the peptides are shown as red rods, the lipid/water interface as a green surface. Lipid tail beads are shown in gray. This particular cubic phase is special as it combines both pores (the white gaps) and stalks (filled with lipid tails) in one phase. The peptides stabilize this stalk/pore structure.