Bacterial Membranes Are More Perturbed by the Asymmetric Versus Symmetric Loading of Amphiphilic Molecules.

Characterizing the biophysical properties of bacterial membranes is critical for understanding the protective nature of the microbial envelope, interaction of biological membranes with exogenous materials, and designing new antibacterial agents. Presented here are molecular dynamics simulations for two cationic quaternary ammonium compounds, and the anionic and nonionic form of a fatty acid molecule interacting with a Staphylococcus aureus bacterial inner membrane. The effect of the tested materials on the properties of the model membranes are evaluated with respect to various structural properties such as the lateral pressure profile, lipid tail order parameter, and the bilayer's electrostatic potential. Conducting asymmetric loading of molecules in only one leaflet, it was observed that anionic and cationic amphiphiles have a large impact on the Staphylococcus aureus membrane's electrostatic potential and lateral pressure profile as compared to a symmetric distribution. Nonintuitively, we find that the cationic and anionic molecules induce a similar change in the electrostatic potential, which points to the complexity of membrane interfaces, and how asymmetry can induce biophysical consequences. Finally, we link changes in membrane structure to the rate of electroporation for the membranes, and again find a crucial impact of introducing asymmetry to the system. Understanding these physical mechanisms provides critical insights and viable pathways for the rational design of membrane-active molecules, where controlling the localization is key.

Computational Methods and Tools in Antimicrobial Peptide Research.

The evolution of antibiotic-resistant bacteria is an ongoing and troubling development that has increased the number of diseases and infections that risk going untreated. There is an urgent need to develop alternative strategies and treatments to address this issue. One class of molecules that is attracting significant interest is that of antimicrobial peptides (AMPs). Their design and development has been aided considerably by the applications of molecular models, and we review these here. These methods include the use of tools to explore the relationships between their structures, dynamics, and functions and the increasing application of machine learning and molecular dynamics simulations. This review compiles resources such as AMP databases, AMP-related web servers, and commonly used techniques, together aimed at aiding researchers in the area toward complementing experimental studies with computational approaches.

Quantum scale biomimicry of low dimensional growth: An unusual complex amorphous precursor route to TiO2 band confinement by shape adaptive biopolymer-like flexibility for energy applications.

Crystallization via an amorphous pathway is often preferred by biologically driven processes enabling living species to better regulate activation energies to crystal formation that are intrinsically linked to shape and size of dynamically evolving morphologies. Templated ordering of 3-dimensional space around amorphous embedded non-equilibrium phases at heterogeneous polymer─metal interfaces signify important routes for the genesis of low-dimensional materials under stress-induced polymer confinement. We report the surface induced catalytic loss of P=O ligands to bond activated aromatization of C-C C=C and Ti=N resulting in confinement of porphyrin-TiO2 within polymer nanocages via particle attachment. Restricted growth nucleation of TiO2 to the quantum scale (≤2 nm) is synthetically assisted by nitrogen, phosphine and hydrocarbon polymer chemistry via self-assembly. Here, the amorphous arrest phase of TiO2 is reminiscent of biogenic amorphous crystal growth patterns and polymer coordination has both a chemical and biomimetic significance arising from quantum scale confinement which is atomically challenging. The relative ease in adaptability of non-equilibrium phases renders host structures more shape compliant to congruent guests increasing the possibility of geometrical confinement. Here, we provide evidence for synthetic biomimicry akin to bio-polymerization mechanisms to steer disorder-to-order transitions via solvent plasticization-like behaviour. This challenges the rationale of quantum driven confinement processes by conventional processes. Further, we show the change in optoelectronic properties under quantum confinement is intrinsically related to size that affects their optical absorption band energy range in DSSC.

Characterization of Hydration Properties in Structural Ensembles of Biomolecules.

Solute-solvent interactions are critical for biomolecular stability and recognition. Explicit solvent molecular dynamics (MD) simulations are routinely used to probe such interactions. However, detailed analyses and interpretation of the hydration patterns seen in MD simulations can be both complex and time-consuming. A variety of approaches/tools to compute and interrogate hydration properties in structural ensembles of proteins, nucleic acids, or in general any molecule are available and are complemented here with a new and free software package ("JAL"). Central to "JAL" is an intuitive atom centric approach of computing hydration properties. In addition to the standard metrics commonly used to understand hydration, "JAL" introduces two nonstandard utilities: a program to rapidly compute buried waters in an MD trajectory and a new method to compute multiwater bridges around a solute. We demonstrate the utility of the package by probing the hydration characteristics of the tumor suppressor protein p53 and the translation initiation factor eif4E. "JAL" is hosted online and can be accessed for free at http://mspc.bii.a-star.edu.sg/minhn/jal.html .

Exploring Gatekeeper Mutations in EGFR through Computer Simulations.

The emergence of resistance against drugs that inhibit a particular protein is a major problem in targeted therapy. There is a clear need for rigorous methods to predict the likelihood of specific drug-resistance mutations arising in response to the binding of a drug. In this work we attempt to develop a robust computational protocol for predicting drug resistant mutations at the gatekeeper position (T790) in EGFR. We explore how mutations at this site affects interactions with ATP and three drugs that are currently used in clinics. We found, as expected, that certain mutations are not tolerated structurally, while some other mutations interfere with the natural substrate and hence are unlikely to be selected for. However, we found five possible mutations that are well tolerated structurally and energetically. Two of these mutations were predicted to have increased affinity for the drugs over ATP, as has been reported earlier. By reproducing the trends in the experimental binding affinities of the data, the methods chosen here are able to correctly predict the effects of these mutations on the binding affinities of the drugs. However, the increased affinity does not always translate into increased efficacy, because the efficacy is affected by several other factors such as binding kinetics, competition with ATP, and residence times. The computational methods used in the current study are able to reproduce or predict the effects of mutations on the binding affinities. However, a different set of methods is required to predict the kinetics of drug binding.

Conformational Transitions of Melittin between Aqueous and Lipid Phases: Comparison of Simulations with Experiments.

Peptides are promising drug candidates with advantageous therapeutic properties. However, their inherent flexibility makes the development of structure-activity relationships difficult. Molecular dynamics simulations have been widely used to study peptide conformations, but they are limited by force field parameters. We explore the ability of nine combinations of commonly used protein, lipid, and water force field models (ff99/tip3p, ff14SB/tip3p, c22/tip3p, c22/tips3p, c36/tip3p, c36/tips3p, c36m/tip3p, c36m/tips3p, and g53a6/spc) in capturing the conformational dynamics of the antimicrobial peptide melittin between the aqueous and model membrane environments. Circular dichroism experiments of melittin displayed a structural transition from a random coil in an aqueous solution to a helix in the presence of a model membrane. Of the protein/lipid/water models that we examined, c22 with the tips3p water model correctly recapitulated the experimentally observed disordered conformations in an aqueous solution and helical conformations in the presence of the model membrane, followed by c36/tips3p. Hydration analysis revealed that the tips3p water model leads to stronger peptide-water interactions, which, in turn, better describe the solvation and its effects on conformational distributions in aqueous and membrane environments. The results of this study reveal the secondary structure preferences of various force fields and emphasize the role of hydration and microenvironment in modulating peptide conformations.

Large scale ab initio modeling of structurally uncharacterized antimicrobial peptides reveals known and novel folds.

Antimicrobial resistance within a wide range of infectious agents is a severe and growing public health threat. Antimicrobial peptides (AMPs) are among the leading alternatives to current antibiotics, exhibiting broad spectrum activity. Their activity is determined by numerous properties such as cationic charge, amphipathicity, size, and amino acid composition. Currently, only around 10% of known AMP sequences have experimentally solved structures. To improve our understanding of the AMP structural universe we have carried out large scale ab initio 3D modeling of structurally uncharacterized AMPs that revealed similarities between predicted folds of the modeled sequences and structures of characterized AMPs. Two of the peptides whose models matched known folds are Lebocin Peptide 1A (LP1A) and Odorranain M, predicted to form ß-hairpins but, interestingly, to lack the intramolecular disulfide bonds, cation-π or aromatic interactions that generally stabilize such AMP structures. Other examples include Ponericin Q42, Latarcin 4a, Kassinatuerin 1, Ceratotoxin D, and CPF-B1 peptide, which have α-helical folds, as well as mixed αß folds of human Histatin 2 peptide and Garvicin A which are, to the best of our knowledge, the first linear αßß fold AMPs lacking intramolecular disulfide bonds. In addition to fold matches to experimentally derived structures, unique folds were also obtained, namely for Microcin M and Ipomicin. These results help in understanding the range of protein scaffolds that naturally bear antimicrobial activity and may facilitate protein design efforts towards better AMPs.

Comparison of Charge Derivation Methods Applied to Amino Acid Parameterization.

When using non-natural amino acids in computational simulations of proteins, it is necessary to ensure appropriate parameterization of the new amino acids toward the creation of appropriate input files. In particular, the charges on the atoms may have to be derived de novo and ad hoc for the new species. As there are many variables in the charge derivation process, an investigation was devised to compare different approaches and determine their effect on simulations. This was done with the purpose to identify the methods which produced results compatible with the existing parameters. It was found in this study that all analyzed charge derivation methods reproduce with sufficient accuracy the literature values and can be used with confidence when parameterizing novel species.

X-ray crystallographic and EPR spectroscopic analysis of HydG, a maturase in [FeFe]-hydrogenase H-cluster assembly.

Hydrogenases use complex metal cofactors to catalyze the reversible formation of hydrogen. In [FeFe]-hydrogenases, the H-cluster cofactor includes a diiron subcluster containing azadithiolate, three CO, and two CN(-) ligands. During the assembly of the H cluster, the radical S-adenosyl methionine (SAM) enzyme HydG lyses the substrate tyrosine to yield the diatomic ligands. These diatomic products form an enzyme-bound Fe(CO)x(CN)y synthon that serves as a precursor for eventual H-cluster assembly. To further elucidate the mechanism of this complex reaction, we report the crystal structure and EPR analysis of HydG. At one end of the HydG (ßα)8 triosephosphate isomerase (TIM) barrel, a canonical [4Fe-4S] cluster binds SAM in close proximity to the proposed tyrosine binding site. At the opposite end of the active-site cavity, the structure reveals the auxiliary Fe-S cluster in two states: one monomer contains a [4Fe-5S] cluster, and the other monomer contains a [5Fe-5S] cluster consisting of a [4Fe-4S] cubane bridged by a µ2-sulfide ion to a mononuclear Fe(2+) center. This fifth iron is held in place by a single highly conserved protein-derived ligand: histidine 265. EPR analysis confirms the presence of the [5Fe-5S] cluster, which on incubation with cyanide, undergoes loss of the labile iron to yield a [4Fe-4S] cluster. We hypothesize that the labile iron of the [5Fe-5S] cluster is the site of Fe(CO)x(CN)y synthon formation and that the limited bonding between this iron and HydG may facilitate transfer of the intact synthon to its cognate acceptor for subsequent H-cluster assembly.

A computational study of vicinal fluorination in 2,3-difluorobutane: implications for conformational control in alkane chains.

A comprehensive conformational analysis of both 2,3-difluorobutane diastereomers is presented based on density functional theory calculations in vacuum and in solution, as well as NMR experiments in solution. While for 1,2-difluoroethane the fluorine gauche effect is clearly the dominant effect determining its conformation, it was found that for 2,3-difluorobutane there is a complex interplay of several effects, which are of similar magnitude but often of opposite sign. As a result, unexpected deviations in dihedral angles, relative conformational energies and populations are observed which cannot be rationalised only by chemical intuition. Furthermore, it was found that it is important to consider the free energies of the various conformers, as these lead to qualitatively different results both in vacuum and in solvent, when compared to calculations based only on the electronic energies. In contrast to expectations, it was found that vicinal syn-difluoride introduction in the butane and by extension, longer hydrocarbon chains, is not expected to lead to an effective stabilisation of the linear conformation. Our findings have implications for the use of the vicinal difluoride motif for conformational control.

Density functional theory calculations on entire proteins for free energies of binding: application to a model polar binding site.

In drug optimization calculations, the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method can be used to compute free energies of binding of ligands to proteins. The method involves the evaluation of the energy of configurations in an implicit solvent model. One source of errors is the force field used, which can potentially lead to large errors due to the restrictions in accuracy imposed by its empirical nature. To assess the effect of the force field on the calculation of binding energies, in this article we use large-scale density functional theory (DFT) calculations as an alternative method to evaluate the energies of the configurations in a "QM-PBSA" approach. Our DFT calculations are performed with a near-complete basis set and a minimal parameter implicit solvent model, within the self-consistent calculation, using the ONETEP program on protein-ligand complexes containing more than 2600 atoms. We apply this approach to the T4-lysozyme double mutant L99A/M102Q protein, which is a well-studied model of a polar binding site, using a set of eight small aromatic ligands. We observe that there is very good correlation between the MM and QM binding energies in vacuum but less so in the solvent. The relative binding free energies from DFT are more accurate than the ones from the MM calculations, and give markedly better agreement with experiment for six of the eight ligands. Furthermore, in contrast to MM-PBSA, QM-PBSA is able to correctly predict a nonbinder.

Structures of lipoyl synthase reveal a compact active site for controlling sequential sulfur insertion reactions.

Lipoyl cofactors are essential for living organisms and are produced by the insertion of two sulfur atoms into the relatively unreactive C-H bonds of an octanoyl substrate. This reaction requires lipoyl synthase, a member of the radical S-adenosylmethionine (SAM) enzyme superfamily. In the present study, we solved crystal structures of lipoyl synthase with two [4Fe-4S] clusters bound at opposite ends of the TIM barrel, the usual fold of the radical SAM superfamily. The cluster required for reductive SAM cleavage conserves the features of the radical SAM superfamily, but the auxiliary cluster is bound by a CX4CX5C motif unique to lipoyl synthase. The fourth ligand to the auxiliary cluster is an extremely unusual serine residue. Site-directed mutants show this conserved serine ligand is essential for the sulfur insertion steps. One crystallized lipoyl synthase (LipA) complex contains 5'-methylthioadenosine (MTA), a breakdown product of SAM, bound in the likely SAM-binding site. Modelling has identified an 18 Å (1 Å=0.1 nm) deep channel, well-proportioned to accommodate an octanoyl substrate. These results suggest that the auxiliary cluster is the likely sulfur donor, but access to a sulfide ion for the second sulfur insertion reaction requires the loss of an iron atom from the auxiliary cluster, which the serine ligand may enable.

Free energies of binding from large-scale first-principles quantum mechanical calculations: application to ligand hydration energies.

Schemes of increasing sophistication for obtaining free energies of binding have been developed over the years, where configurational sampling is used to include the all-important entropic contributions to the free energies. However, the quality of the results will also depend on the accuracy with which the intermolecular interactions are computed at each molecular configuration. In this context, the energy change associated with the rearrangement of electrons (electronic polarization and charge transfer) upon binding is a very important effect. Classical molecular mechanics force fields do not take this effect into account explicitly, and polarizable force fields and semiempirical quantum or hybrid quantum-classical (QM/MM) calculations are increasingly employed (at higher computational cost) to compute intermolecular interactions in free-energy schemes. In this work, we investigate the use of large-scale quantum mechanical calculations from first-principles as a way of fully taking into account electronic effects in free-energy calculations. We employ a one-step free-energy perturbation (FEP) scheme from a molecular mechanical (MM) potential to a quantum mechanical (QM) potential as a correction to thermodynamic integration calculations within the MM potential. We use this approach to calculate relative free energies of hydration of small aromatic molecules. Our quantum calculations are performed on multiple configurations from classical molecular dynamics simulations. The quantum energy of each configuration is obtained from density functional theory calculations with a near-complete psinc basis set on over 600 atoms using the ONETEP program.

Electrostatic embedding in large-scale first principles quantum mechanical calculations on biomolecules.

Biomolecular simulations with atomistic detail are often required to describe interactions with chemical accuracy for applications such as the calculation of free energies of binding or chemical reactions in enzymes. Force fields are typically used for this task but these rely on extensive parameterisation which in cases can lead to limited accuracy and transferability, for example for ligands with unusual functional groups. These limitations can be overcome with first principles calculations with methods such as density functional theory (DFT) but at a much higher computational cost. The use of electrostatic embedding can significantly reduce this cost by representing a portion of the simulated system in terms of highly localised charge distributions. These classical charge distributions are electrostatically coupled with the quantum system and represent the effect of the environment in which the quantum system is embedded. In this paper we describe and evaluate such an embedding scheme in which the polarisation of the electronic density by the embedding charges occurs self-consistently during the calculation of the density. We have implemented this scheme in a linear-scaling DFT program as our aim is to treat with DFT entire biomolecules (such as proteins) and large portions of the solvent. We test this approach in the calculation of interaction energies of ligands with biomolecules and solvent and investigate under what conditions these can be obtained with the same level of accuracy as when the entire system is described by DFT, for a variety of neutral and charged species.