Computational and analytical modeling of cationic lipid-DNA complexes

We present a theoretical study of the physical properties of cationic lipid-DNA (CL-DNA) complexes--a promising synthetically based nonviral carrier of DNA for gene therapy. The study is based on a coarse-grained molecular model, which is used in Monte Carlo simulations of mesoscopically large systems over timescales long enough to address experimental reality. In the present work, we focus on the statistical-mechanical behavior of lamellar complexes, which in Monte Carlo simulations self-assemble spontaneously from a disordered random initial state. We measure the DNA-interaxial spacing, d(DNA), and the local cationic area charge density, sigma(M), for a wide range of values of the parameter (c) representing the fraction of cationic lipids. For weakly charged complexes (low values of (c)), we find that d(DNA) has a linear dependence on (c)(-1), which is in excellent agreement with x-ray diffraction experimental data. We also observe, in qualitative agreement with previous Poisson-Boltzmann calculations of the system, large fluctuations in the local area charge density with a pronounced minimum of sigma(M) halfway between adjacent DNA molecules. For highly-charged complexes (large (c)), we find moderate charge density fluctuations and observe deviations from linear dependence of d(DNA) on (c)(-1). This last result, together with other findings such as the decrease in the effective stretching modulus of the complex and the increased rate at which pores are formed in the complex membranes, are indicative of the gradual loss of mechanical stability of the complex, which occurs when (c) becomes large. We suggest that this may be the origin of the recently observed enhanced transfection efficiency of lamellar CL-DNA complexes at high charge densities, because the completion of the transfection process requires the disassembly of the complex and the release of the DNA into the cytoplasm. Some of the structural properties of the system are also predicted by a continuum free energy minimization. The analysis, which semiquantitatively agrees with the computational results, shows that that mesoscale physical behavior of CL-DNA complexes is governed by interplay among electrostatic, elastic, and mixing free energies.     

Atomic Level Rendering of DNA-Drug Encounter

Computer simulations have been demonstrated to be important for unraveling atomic mechanisms in biological systems. In this study, we show how combining unbiased molecular dynamic simulations with appropriate analysis tools can successfully describe metal-based drug interactions with DNA. To elucidate the noncovalent affinity of cisplatin’s family to DNA, we performed extensive all-atom molecular dynamics simulations (3.7 μs total simulation length). The results show that the parent drug, cisplatin, has less affinity to form noncovalent adducts in the major groove than its aquo complexes. Furthermore, the relative position in which the drugs enter the major groove is dependent on the compound’s net charge. Based on the simulations, we estimated noncovalent binding free energies through the use of Markov state models. In addition, and to overcome the lack of experimental information, we employed two additional methods: Molecular Mechanics Poisson-Boltzmann Surface Area (MMPB-SA) and steered molecular dynamics with the Jarzynski estimator, with an overall good agreement between the three methods. All complexes show interaction energies below 3 kcal/mol with DNA but the charged hydrolysis products have slightly more favorable binding free energies than the parent drug. Moreover, this study sets the precedent for future unbiased DNA-ligand simulations of more complex binders.     

Molecular simulation of size-selective gas adsorption in idealised carbon nanotubes

Molecular simulations were used to examine the adsorption of diatomic molecules (nitrogen and oxygen) and similarly sized gases (argon and methane) in pores with van der Waals diameters similar in size to the gas diameters. Idealised carbon nanotubes were used to model generic pores, to better understand the effect of pore diameter on guest adsorption in the absence of defects, specific adsorption sites, or variations in pore diameter that often complicate studies of gas adsorption in other porous materials. Molecular dynamics simulations of open nanotubes show that argon and methane are able to enter tubes whose diameters are slightly smaller than the gas diameters. Diatomic gases are able to enter tubes that are significantly smaller than their kinetic diameters with the molecular axis aligned parallel to the nanotube. The results indicate that size-selective adsorption of these gases is theoretically possible, although differences in pore diameters of only a few tenths of an Angstrom are required. Grand canonical Monte Carlo simulations of a 3.38 Å nanotube indicate significant uptake by argon and oxygen, but not nitrogen or methane. The adsorption of nitrogen and methane gradually increases as the nanotube diameter approaches 4.07 Å, and all gases fully saturate a 4.54 Å nanotube. Of the nanotubes studied, the largest adsorption enthalpy for any gas corresponds to the 4.54 Å nanotube, with significantly lower enthalpies seen in the 5.07 Å nanotube. These results suggest an ideal pore diameter for each gas based on the gas–pore van der Waals interaction energies. Trends in the ideal diameter correlate with the minimum tube diameter accessible to each gas.     

Insight into why pyrrolidinyl peptide nucleic acid binding to DNA is more stable than the DNA x DNA duplex

Molecular dynamics (MD) simulations and experimental measurements of the stability of a novel pyrrolidinyl PNA binding to DNA (PNA·DNA) in both parallel and antiparallel configurations were carried out. For comparison, simulations were also performed for the DNA·DNA duplex. The conformations of the three simulated systems were found to retain well-defined base pairing and base stacking as their starting B-like structure. A large gas-phase energy repulsion of the two negatively charged sugar-phosphate backbones of the DNA strands was found to reduce the stability of the DNA·DNA duplex significantly compared with that of the PNA·DNA complexes, especially in the antiparallel binding configuration. In addition, the antiparallel PNA·DNA was observed to be less solvated than that of the other two systems. The simulated binding free energies and the experimental melting temperatures for the three investigated systems are in good agreement, indicating that the antiparallel PNA·DNA is the most stable duplex.     

Equilibria for the adsorption of antibiotics onto neutral polymeric sorbents: Experimental and modeling studies

The objective of this work was to study the equilibria for adsorption of three antibiotics (penicillin V, tetracycline, and cephalosporin C) from water onto commercially available neutral polymeric sorbents. The pH was observed to be an important factor in adsorption as our results suggest that the neutral forms of penicillin V and cephalosporin C are preferentially adsorbed onto the neutral sorbents. Also, sorbent surface chemistry was observed to be important for adsorption, as the antibiotics adsorbed more favorably (both in terms of affinities and enthalpies) onto the aromatic sorbent as compared to the aliphatic ester sorbent. In addition to these thermodynamic measurements, molecular modeling studies and Monte Carlo simulations suggest that adsorption onto aromatic sorbents may involve specific interactions between the planar regions of the antibiotic molecules and the phenyl rings of the aromatic sorbent. The interaction energies predicted from Monte Carlo simulations were observed to provide qualitative agreement with experimentally determined adsorption affinities. (c) 1995 John Wiley & Sons, Inc.     

Axis Curvature and Ligand Induced Bending in the CAP-DNA Oligomers

The origin of DNA axis curvature in complexes of the catabolite activator protein with DNA is studied using multiple molecular dynamics (MD) simulations of the free and protein-bound forms of the DNA. The results are compared to available solution and crystal structure data. The MD simulations reproduce the experimentally observed bend in DNA and indicate that ∼40% of the bending observed in the complex is intrinsic to the DNA sequence, whereas ∼60% is induced on protein binding. The MD provides a model for the dynamical structure of the DNA free in solution and for ligand-induced bending.     

Molecular Modeling for a Comparative Analysis of Interactions Between 2LTRZFP and 2-LTR-Circle Junctions

In eukaryotes, one of the most often noticed DNA-binding motifs are Cys2His2 zinc finger proteins which have been extensively utilized as a framework for designing novel DNA-binding proteins. In this study, the conformational change, and binding stability, affinity and interactions of the 2LTRZFP–HIV-1 2-LTR-circle junction complexes were successfully reproduced with MD simulations, MM-PBSA/GBSA and binding mode analyses. The binding free energies were obtained, and it was found that the calculated binding free energy of Zif1 is lower than Zif2 and together with pharmacophore modeling, these binding results indicate strong affinity of 2LTRZFP for the DNA. Mutants of 2LTRZFP were analyzed. The computed energies provided proof for a relationship between the binding free energy and total electrostatic interaction energy. The mutation in a key amino acid (Glu81Tyr) of the finger 3 in position 6 showed increased binding energy to the DNA. The result agrees with our previous study which showed that the HIV-1 IN may be hindered by the 2LTRZFP. The obtained results may assist in the design of ZFPs depended on the 2-LTR-circle junctions inhibition mechanism.

     

Model for radial dependence of frequency distributions for energy imparted in nanometer volumes from HZE particles

This paper develops a deterministic model of frequency distributions for energy imparted (total energy deposition) in small volumes similar to DNA molecules from high-energy ions of interest for space radiation protection and cancer therapy. Frequency distributions for energy imparted are useful for considering radiation quality and for modeling biological damage produced by ionizing radiation. For high-energy ions, secondary electron (delta-ray) tracks originating from a primary ion track make dominant contributions to energy deposition events in small volumes. Our method uses the distribution of electrons produced about an ion's path and incorporates results from Monte Carlo simulation of electron tracks to predict frequency distributions for ions, including their dependence on radial distance. The contribution from primary ion events is treated using an impact parameter formalism of spatially restricted linear energy transfer (LET) and energy-transfer straggling. We validate our model by comparing it directly to results from Monte Carlo simulations for proton and alpha-particle tracks. We show for the first time frequency distributions of energy imparted in DNA structures by several high-energy ions such as cosmic-ray iron ions. Our comparison with results from Monte Carlo simulations at low energies indicates the accuracy of the method.     

Self-consistent reaction field computation of the reactive characteristics of DNA bases in water

The effect of the solvent in the molecular properties of DNA bases has been explored by using a self-consistent reaction field (SCRF) method based on the AM1 (Austin Model 1) Hamiltonian and a modified version of the high level Miertus–Scrocco–Tomasi (MST) algorithm. MST/AM1 estimates of free energies of hydration compare qualitatively well with the available experimental data, as well as with the results obtained from molecular dynamic simulations. Furthermore, the changes in the dipole predicted by the MST/AM1 method are in good agreement with Monte Carlo/quantum mechanical data, as well as with AM1-SM2 (Soluation Model 2) estimates. AM1/MST calculations of Mulliken, and electrostatic charges, dipoles, molecular electrostatic potentials and molecular interaction potentials in both vacuum and solution allowed us to quantify the effect of the water on the reactive characteristics of the DNA bases. This effect is large and complex, and cannot be neglected in theoretical calculations where an accurate representation of the DNA bases is needed. The possibility of including the polarization effect of the water into force-field simulations of DNA structures is discussed. © 1993 John Wiley & Sons, Inc.     

Atomic solvation parameters in the analysis of protein-protein docking results.

Several sets of amino acid surface areas and transfer free energies were used to derive a total of nine sets of atomic solvation parameters (ASPs). We tested the accuracy of each of these sets of parameters in predicting the experimentally determined transfer free energies of the amino acid derivatives from which the parameters were derived. In all cases, the calculated and experimental values correlated well. We then chose three parameter sets and examined the effect of adding an energetic correction for desolvation based on these three parameter sets to the simple potential function used in our multiple start Monte Carlo docking method. A variety of protein-protein interactions and docking results were examined. In the docking simulations studied, the desolvation correction was only applied during the final energy calculation of each simulation. For most of the docking results we analyzed, the use of an octanol-water-based ASP set marginally improved the energetic ranking of the low-energy dockings, whereas the other ASP sets we tested disturbed the ranking of the low-energy dockings in many of the same systems. We also examined the correlation between the experimental free energies of association and our calculated interaction energies for a series of proteinase-inhibitor complexes. Again, the octanol-water-based ASP set was compatible with our standard potential function, whereas ASP sets derived from other solvent systems were not.     

Computational binding studies of human pp60c-src SH2 domain with a series of nonpeptide, phosphophenyl-containing ligands

Monte Carlo/free energy perturbation (MC/FEP) simulations were performed on a series of nonpeptide ligands of the human pp60c-src SH2 domain in order to calculate relative free energies of binding for each compound and to understand the structural requirements for high affinity binding. The amido compound, exhibiting the highest experimental affinity, takes advantage of an interaction with a previously unobserved structural water.     

Protein surface roughness accounts for binding free energy of Plasmepsin II‐ligand complexes

The calculation of absolute binding affinities for protein‐inhibitor complexes remains as one of the main challenges in computational structure‐based ligand design. The present work explored the calculations of surface fractal dimension (as a measure of surface roughness) and the relationship with experimental binding free energies of Plasmepsin II complexes. Plasmepsin II is an attractive target for novel therapeutic compounds to treat malaria. However, the structural flexibility of this enzyme is a drawback when searching for specific inhibitors. Concerning that, we performed separate explicitly solvated molecular dynamics simulations using the available high‐resolution crystal structures of different Plasmepsin II complexes. Molecular dynamics simulations allowed a better approximation to systems dynamics and, therefore, a more reliable estimation of surface roughness. This constitutes a novel approximation in order to obtain more realistic values of fractal dimension, because previous works considered only x‐ray structures. Binding site fractal dimension was calculated considering the ensemble of structures generated at different simulation times. A linear relationship between binding site fractal dimension and experimental binding free energies of the complexes was observed within 20 ns. Previous studies of the subject did not uncover this relationship. Regression model, coined FD model, was built to estimate binding free energies from binding site fractal dimension values. Leave‐one‐out cross‐validation showed that our model reproduced accurately the absolute binding free energies for our training set (R² = 0.76; <|error|> =0.55 kcal/mol; SD_error = 0.19 kcal/mol). The fact that such a simple model may be applied raises some questions that are addressed in the article.     

A Monte Carlo simulation study of protein-induced heat capacity changes and lipid-induced protein clustering.

Monte Carlo simulations were used to describe the interaction of peripheral and integral proteins with lipids in terms of heat capacity profiles and protein distribution. The simulations were based on a two-state model for the lipid, representing the lipid state as being either gel or fluid. The interaction between neighboring lipids has been taken into account through an unlike nearest neighbor free energy term delta omega, which is a measure of the cooperativity of the lipid transition. Lipid/protein interaction was considered using the experimental observation that the transition midpoints of lipid membranes are shifted upon protein binding, a thermodynamic consequence of different binding constants of protein with fluid or gel lipids. The difference of the binding free energies was used as an additional parameter to describe lipid-protein interaction. The heat capacity profiles of lipid/protein complexes could be well described for both peripheral and integral proteins. Binding of proteins results in a shift and an asymmetric broadening of the melting profile. The model results in a coexistence of gel and fluid lipid domains in the proximity of the thermotropic transition. As a consequence, bound peripheral proteins aggregate in the temperature range of the lipid transition. Integral proteins induce calorimetric melting curves that are qualitatively different from that of peripheral proteins and aggregate in either gel or liquid crystalline lipid phase. The results presented here are in good agreement with calorimetric experiments on lipid-protein complexes and have implementations for the functional control of proteins.     

The effect of internucleosomal interaction on folding of the chromatin fiber

The folding of the nucleosome chain into a chromatin fiber modulates DNA accessibility and is therefore an important factor for the control of gene expression. The fiber conformation depends crucially on the interaction between individual nucleosomes. However, this parameter has not been accurately determined experimentally, and it is affected by posttranslational histone modifications and binding of chromosomal proteins. Here, the effect of different internucleosomal interaction strengths on the fiber conformation was investigated by Monte Carlo computer simulations. The fiber geometry was modeled to fit that of chicken erythrocyte chromatin, which has been examined in numerous experimental studies. In the Monte Carlo simulation, the nucleosome shape was described as an oblate spherocylinder, and a replica exchange protocol was developed to reach thermal equilibrium for a broad range of internucleosomal interaction energies. The simulations revealed the large impact of the nucleosome geometry and the nucleosome repeat length on the compaction of the chromatin fiber. At high internucleosomal interaction energies, a lateral self-association of distant fiber parts and an interdigitation of nucleosomes were apparent. These results identify key factors for the control of the compaction and higher order folding of the chromatin fiber.     

MC-PHS: A Monte Carlo Implementation of the Primary Hydration Shell for Protein Folding and Design

A primary hydration shell (PHS) approach is developed for Monte Carlo simulations of conformationally rich macromolecular systems in an environment that efficiently captures principal solvation effects. It has been previously demonstrated that molecular dynamics using PHS is an efficient method to study peptide structure and dynamics in aqueous solution. Here, we extend the PHS approach to Monte Carlo simulations, whereby a stable shell of water molecules is maintained with a flexible, nonspherical, half-harmonic potential, tuned to maintain a constant restraining energy, with the difference between the restraint and shell energies used to dynamically adjust the shell radius. Examination of the shell and system size dependence of the restraining potential reveals its robustness. Moreover, its suitability for biomolecular simulations is evaluated using small spheres of water, hydration properties of small biological molecules, and configurational sampling of β-hairpin pentapeptide YPGDV. This method, termed MC-PHS, appears to provide efficient representation of dominant solvation effects and should prove useful in the study of protein folding and design.     

Molecular simulation on the interaction of Ethinylestradiol (EE2) with polymer membranes in wastewater purification

Molecular dynamics (MD) simulations are performed to study the adsorption of solute organic molecules (Ethinylestradiol (EE2) and testosterone) with different polymer membranes such as polyether sulfone (PES), polyvinylidene fluoride (PVDF). The equilibrium MD simulations results for the membrane solution interface system show that the interaction of EE2 with PES is specific and strong, whereas the interaction is weak and non-specific for PVDF. The binding free energies, the non-bonded short range interaction energies and mobility are also consistent with the interaction behaviour found in experiments. The adsorption of testosterone onto PES and PVDF is considered as control system. The result shows that binding free energies of PES and PVDF interacting with organic solute are consistent with experimental result in the order as; PES-EE2 > PES-Testosterone > PVDF-EE2 > PVDF-Testosterone. The formation hydrogen bonds and π–π interactions are observed between the EE2 and PES. In addition, adsorption of EE2 onto polyamide 6-12 (PA612) and polystyrene (PS) membranes are predicted. This simulation study provides molecular insights on the experimental observations and helps as a computational methodology to screen the membrane materials for EE2 removal from wastewater.     

Application of the multiensemble sampling to the equilibrium folding of proteins

MOTIVATION: Conventional Monte Carlo and molecular dynamics simulations of proteins in the canonical ensemble are of little use, because they tend to get trapped in states of energy local minima at low temperatures. One way to surmount this difficulty is to use a non-Boltzmann sampling method in which conformations are sampled upon a general weighting function instead of the conventional Boltzmann weighting function. The multiensemble sampling (MES) method is a non-Boltzmann sampling method that was originally developed to estimate free energy differences between systems with different potential energies and/or at different thermodynamic states. The method has not yet been applied to studies of complex molecular systems such as proteins. RESULTS: MES Monte Carlo simulations of small proteins have been carried out using a united-residue force field. The proteins at several temperatures from the unfolded to the folded states were simulated in a single MC run at a time and their equilibrium thermodynamic properties were calculated correctly. The distributions of sampled conformations clearly indicate that, when going through states of energy local minima, the MES simulation did not get trapped in them but escaped from them so quickly that all the relevant parts of conformation space could be sampled properly. A two-step folding process consisting of a collapse transition followed by a folding transition is observed. This study demonstrates that the use of MES alleviates the multiple-minima problem greatly. AVAILABILITY: Available on request from the authors.