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We present a new sampling and analysis scheme for calculating the potential of mean force (PMF) of systems studied by steered molecular dynamics simulations. This scheme, which we call the bin-passing method, is based on the forward-reverse (FR) method (due to I. Kosztin and co-workers, Kosztin et al. J. Chem. Phys. 2006, 124(6), 064106) and arguments based on the second law of thermodynamics. Applying the bin-passing method results in enhanced sampling, better separation of the reversible and irreversible work distributions, and faster convergence to the underlying PMF of the system under study. Post-simulation analysis is performed using a purpose-built software that we have made publicly available at https://github.com/1particle/bin-passing_analyzer under the terms of the GNU General Public License (version 3). Three examples are provided, for systems of varying sizes and complexities, to demonstrate the efficiency of this method and the quality of the results: for the dissociation PMF of NaCl in water, the bin-passing method obtains PMFs in excellent agreement with that obtained for the same system and using the same force-field through static (equilibrium) methods. The bin-passing method gives a very symmetric PMF for passage of a single water molecule through a DPPC bilayer, and the resultant PMF leads to permeability values in better agreement with experiments than those obtained through previous simulation studies. Finally, we consider the interaction of the antimicrobial peptide HHC-36 with two model membranes and employ the bin-passing method to obtain the PMFs for peptide adsorption to the membranes. The characteristics of these PMFs are consistent with the qualities established for the HHC-36 peptide through in vivo and in vitro experiments, as a non-toxic strong antimicrobial agent.

Cationic antimicrobial peptides are promising sources for novel therapeutic agents against multi-drug-resistant bacteria. HHC-36 (KRWWKWWRR) is a simple but effective antimicrobial peptide with similar or superior activity compared with several conventional antibiotics. In this biophysical study, unique conformational properties of this peptide and some of its analogs as well as its interaction with lipid membranes are investigated in detail. Circular dichroism (CD) and molecular dynamics modeling studies of HHC-36 in different environments reveal a dynamic amphipathic structure composed of competing turn conformations with free energies lower than that of the unfolded state, implying a strong influence of tryptophan interactions in formation of the turns. CD spectra and gel electrophoresis also show strong evidence of self-association of this peptide in aqueous milieu and interaction with both neutrally and negatively charged lipid membrane systems. Isothermal titration calorimetry and acrylamide fluorescence quenching experiments emphasize the preference of HHC-36 for negatively charged vesicles. In addition, dye leakage experiments suggest that this peptide functions through a surface-associated mechanism with weak lytic activity against bacterial model membranes.

Use of harmonic guiding potentials is the most commonly adopted method for implementing steered molecular dynamics (SMD) simulations, performed to obtain potentials of mean force (PMFs) using Jarzynski's equality and other nonequilibrium work (NEW) theorems. The stiff spring approximation (SSA) of Schulten and co-workers enables calculation of the PMF by using the work performed along many SMD trajectories in NEW theorems. We discuss and demonstrate how a high spring constant, k, required for the validity of the SSA can violate another requirement of SSA, the validity of Brownian dynamics in the system under study. These result in skewed work distributions with their width increasing with k. The skew and broadening of work distributions result in biased estimation (through invoking NEW theorems) of the PMF. Remarkably, the skewness and the broadening of work distributions are independent of the average drift velocity and physical asymmetries and can only be attributed to using too-stiff springs. We discuss the proper upper limit for k such that the inertial effects are minimized. In the presence of inertial effects, using the peak value (rather than the statistical mean) of the work distributions vastly reduces the bias in the calculated PMFs and improves the accuracy.

HHC-36 is an antimicrobial peptide, designed through neural network algorithms. It has been tested in vivo and in vitro, and has proved to be strongly effective against strains of multidrug-resistant P. aeruginosa, methicillin-resistant Staphylococcus aureus, and a few other ‘superbugs’ (Cherkasov et al., ACS Chem. Biol., 2009, 4 (1), pp 65-74). The peptide has also been observed through in vivo tests to be greatly pathogen-specific, hence proving to be a great candidate for developing future antibiotics.To understand the mechanism of activity of this peptide against bacterial membranes, we have performed a number of all-atom simulations, together with a series of circular dichroism spectroscopy (CD) and isothermal titration calorimetry (ITC) experiments. The small size (9 amino acids) and great charge density of HHC-36 make it problematic (if not unreliable) to find the structure of HHC-36 through conventional spectroscopy and/or crystallography methods. We have thus performed microsecond-scale molecular dynamics simulations, starting from an unfolded structure of the peptide, to find its folded structure. An amphipathic turn structure has been obtained, which was observed to be very stable over few hundred nanosecond timescales of simulation. This result has been compared to circular dichroism spectroscopy results, and the presence of the turn structure has been verified. To assess the stability of the observed structure, we have also performed temperature-dependent simulations and CD measurements, which have shown the stability of the turn structure at close-to-physiological temperatures.The obtained structure is then used in peptide-membrane simulations with a few different membrane compositions mimicking both bacterial and animal cell membranes. Profiles of the potential of mean force have been obtained, and the relevant binding parameters extracted from these simulations are then compared with the binding free energies obtained from ITC experiments.

The increasing demand for antibiotics has contributed to the investigation of possible novel antibiotics by many researchers. For this purpose, experimental and theoretical studies have been carried out to draw scientists' attention to antimicrobial peptides and their interaction with the surface of bacterial membranes. Their ability to disrupt the functioning of bacterial membranes has been probed from different perspectives. The best possible choice of antimicrobial peptides are those which do not harm plant or animals' membranes but which disrupt bacterial membranes. It has been found that some cationic antimicrobial peptides (CAPs) satisfy these requirements. CAPs interacting with the outer membrane of gram-negative bacteria and the membrane of gram-positive bacteria has been studied recently.We conduct a MD simulation study of peptide-peptide interactions in the physiological solutions and investigate the mechanism of CAPs aggregation, since aggregation of the peptides usually precedes formation of a pore in the membrane. Different algorithms will be applied to calculate the potential mean force of the aggregation process of peptides to select the most efficient one. Also, we have run CD spectroscopy and Calorimetry experiments to predict the structure of the peptide and measure the peptide-peptide binding enthalpy, and we compare the results with our simulation data.The particular CAP studied is HHC-10, a peptide designed by the Hancock group, which has 9 amino acid residues and charge +4.

We present a method that enables the use of the forward-reverse (FR) method of Kosztin et al. on a broader range of problems in soft matter physics. Our method, which we call the oscillating forward-reverse (OFR) method, adds an oscillatory steering potential to the constant velocity steering potential of the FR method. This enables the calculation of the potential of mean force (PMF) in a single unidirectional oscillatory drift, rather than multiple drifts in both directions as required by the FR method. By following small forward perturbations with small reverse perturbations, the OFR method is able to generate a piecewise reverse path that follows the piecewise forward path much more closely than any practical set of paths used in the FR method. We calculate the PMF for four different systems: a dragged Brownian oscillator, a pair of atoms in a Lennard-Jones liquid, a Na${}^{+}$-Cl${}^{\ensuremath{-}}$ ion pair in an aqueous solution, and a deca-alanine molecule being stretched in an implicit solvent. In all cases, the PMF results are in good agreement with those published previously using various other methods, and, to our knowledge, we give for the first time PMFs calculated by nonequilibrium methods for the Lennard-Jones and Na${}^{+}$-Cl${}^{\ensuremath{-}}$ systems.