Molecular mechanism of action of tyrocidine antimicrobial peptides using NMR spectroscopy and computational techniques

Includes abstract.Includes bibliographical references.The need to come up with new and novel antibiotics that utilize unique mechanisms, to which bacteria cannot generate resistance, was the main motivation of this study. Tyrocidine peptides are non-selective antibiotics that have such properties. However, very limited information is available about their mechanism of action. The aim of this study was to determine the mechanism of action of tyrocidine peptides, tyrocidine A, tyrocidine B and tyrocidine C

Roles of cosolvents on protein stability

The function of a protein is determined by its three-dimensional structure which emerges from the delicate balance of forces involving atoms of the protein and the solvent. This balance can be perturbed by changing temperature, pressure, pH and by adding organic molecules known as cosolvents to the solution. Despite the wide use of cosolvents to perturb protein structures in the lab and in living systems, their molecular mechanisms are still not well established. Understanding these mechanisms is a problem of substantial interest, with potential application to the design of new drugs to target proteins. In this dissertation, we probe the role of two major cosolvents, urea and trimethylamine N-oxide (TMAO) at atomic level. Urea is widely used as a denaturant in the lab to destabilize native protein conformations. However, the atomic mechanism of this molecule remains a question of debate. To unravel its molecular mechanism, explicit all-atom molecular dynamics simulations of unrestrained and extended poly-alanine and poly-leucine dimers are performed. Consistent with experimental results, we find that the large non-polar side chain of leucine is affected by urea whereas backbone atoms and alanine’s side chain are not. Urea is found to occupy positions between leucine’s side chains that are not accessible to water. This accounts for extra Lennard-Jones bonds between urea and side chains that favors the unfolded state. These bonds compete with urea-solvent interactions that favor the folded state. The sum of these two energetic terms provides the enthalpic driving force for unfolding. It is shown here that this enthalpy correlates with the potential of mean force of poly-leucine dimers. To provide insights into the stabilizing mechanisms TMAO on protein structures, microsecond all-atom molecular dynamics simulations of peptides and replica exchange molecular dynamics simulations (REMD) of the Trp-cage miniprotein are performed. Most previous studies have focused on the effect of this osmolyte on protein backbone. Our results are consistent with these studies as we show that TMAO induces the backbone to adopt compact conformations. However, it is shown that effects of TMAO on the backbone are not dominant. In particular, TMAO\u27s effect on the backbone is overcompensated by its destabilizing effect on the hydrophobic core: non-polar peptides and residues forming the hydrophobic core of the Trp-cage protein adopt more extended conformations in solutions containing TMAO. It is found that a main interaction that can stabilize folded proteins are charge-charge interactions. In light of these results, we propose that competing effects of TMAO on hydrophobic and charge-charge interactions account for its net stabilizing role on proteins

Accelerating Membrane Simulations with Hydrogen Mass Repartitioning

The time step of atomistic molecular dynamics (MD) simulations is determined by the fastest motions in the system and is typically limited to 2 fs. An increasingly popular approach is to increase the mass of the hydrogen atoms to ~3 amu and decrease the mass of the parent atom by an equivalent amount. This approach, known as hydrogen-mass repartitioning (HMR), permits time steps up to 4 fs with reasonable simulation stability. While HMR has been applied in many published studies to date, it has not been extensively tested for membrane-containing systems. Here, we compare the results of simulations of a variety of membranes and membrane–protein systems run using a 2 fs time step and a 4 fs time step with HMR. For pure membrane systems, we find almost no difference in structural properties, such as area-per-lipid, electron density profiles, and order parameters, although there are differences in kinetic properties such as the diffusion constant. Conductance through a porin in an applied field, partitioning of a small peptide, hydrogen-bond dynamics, and membrane mixing show very little dependence on HMR and the time step. We also tested a 9 Å cutoff as compared to the standard CHARMM cutoff of 12 Å, finding significant deviations in many properties tested. We conclude that HMR is a valid approach for membrane systems, but a 9 Å cutoff is not

The energetics of protein-lipid interactions as viewed by molecular simulations

Membranes are formed from a bilayer containing diverse lipid species with which membrane proteins interact. Thus, integral membrane proteins are embedded in a bilayer, where they interact with lipids from their surroundings, whilst peripheral membrane proteins bind to lipids at the surface of membranes. Lipid interactions can influence the function of membrane proteins, either directly or allosterically. Both experimental (structural) and computational approaches can reveal lipid binding sites on membrane proteins. It is therefore important to understand the free energies of these interactions. This affords a more complete view of the engagement of a particular protein with the biological membrane surrounding it. Here, we describe a number of computational approaches currently in use for this purpose, including recent advances using both free energy and unbiased simulation methods. In particular we focus on interactions of integral membrane proteins with cholesterol, and with anionic lipids such as phosphatidylinositol 4,5-bisphosphate and cardiolipin. Peripheral membrane proteins are exemplified via interactions of PH domains with phosphoinositide-containing membranes. We summarise the current state of the field and provide an outlook on likely future directions of investigation

Lipid bilayer phase separations, cholesterol, and their effect on the amyloid precursor protein C99

The Amyloid Cascade hypothesis provides a molecular-level mechanism for the etiology of Alzheimer’s Disease (AD) and proposes a central role for the genesis and aggregation of Aβ protein. Aβ protein is the product of cleavage of the amyloid precursor protein (APP), a single pass transmembrane protein, by secretases and is found in a variety of isoforms, with longer isoforms being linked to the early onset of AD. The isoform distribution is dependent on membrane environment, mutations, and post-translational modifications. Lipid rafts are characterized by lipids induced into the liquid ordered phase by cholesterol, enhancing membrane thickness and lateral lipid density. Protein preference for rafts can control protein kinetics, and has been implicated in determining whether APP is processed by α– or β-secretase in the plasma membrane. In addition to inducing lipid rafts, cholesterol is hypothesized to directly modulate APP, the C-terminal fragment of APP (C99), and γ-secretase structure and function via direct interaction. To date, the molecular details involved in these fundamental events involved in Aβ genesis have yet to be resolved using experimental approaches, suggesting a critical role for computation. This thesis presents the results of investigations of lipid phase separation and cholesterol and their effects on C99 using molecular dynamics simulation. To gain insight into the nature of lipid rafts, studies characterizing the simulation system sizes required for observation of phase separation, exploring the effect of cholesterol concentration on phase separation and lipid phases, and examining the applicability of different lipid and cholesterol models for the simulation of lipid phases and protein structure were performed. To gain insight into the fundamental properties of C99, studies exploring the structure of full-length C99, the interaction of cholesterol with C99 in various mutational states, the effect of membrane thickness on the C99 extramembrane domains, and the structure of C99 monomer and dimer were performed. Taken together these studies advance our molecular-level understanding of the nature of cholesterol, the role of cholesterol in lipid phase separation, the effect of cholesterol on C99, and the structure of the full-sequence C99 monomer and dimer that play a critical role in the evolution of AD

Statistically optimal continuous free energy surfaces from biased simulations and multistate reweighting

Free energies as a function of a selected set of collective variables are commonly computed in molecular simulation and of significant value in understanding and engineering molecular behavior. These free energy surfaces are most commonly estimated using variants of histogramming techniques, but such approaches obscure two important facets of these functions. First, the empirical observations along the collective variable are defined by an ensemble of discrete observations and the coarsening of these observations into a histogram bins incurs unnecessary loss of information. Second, the free energy surface is itself almost always a continuous function, and its representation by a histogram introduces inherent approximations due to the discretization. In this study, we relate the observed discrete observations from biased simulations to the inferred underlying continuous probability distribution over the collective variables and derive histogram-free techniques for estimating this free energy surface. We reformulate free energy surface estimation as minimization of a Kullback-Leibler divergence between a continuous trial function and the discrete empirical distribution and show that this is equivalent to likelihood maximization of a trial function given a set of sampled data. We then present a fully Bayesian treatment of this formalism, which enables the incorporation of powerful Bayesian tools such as the inclusion of regularizing priors, uncertainty quantification, and model selection techniques. We demonstrate this new formalism in the analysis of umbrella sampling simulations for the $\chi$ torsion of a valine sidechain in the L99A mutant of T4 lysozyme with benzene bound in the cavity.Comment: 24 pages, 5 figure

FREE ENERGIES IN BIOMOLECULAR SIMULATIONS: FROM PROTEIN-PROTEIN INTERACTIONS TO UNFOLDING INHIBITION

Part I - Microtubules are polymeric structures formed by the self association of tubulin dimers. They are extremely dynamical structures, that can undergo phases of growing and shrinking, playing a key role during cells proliferation process. Due to its importance for mitosis, tubulin is the target of many anticancer drugs currently in use or under clinical trial. The success of these molecules, however, is limited by the onset of resistant tumor cells during the treatment, so new resistance-proof compounds need to be developed. We analyze the protein-protein interactions allowing microtubules formation using molecular dynamics and free energy calculations. We were able to identify the most important amino acids for tubulin-tubulin binding and thus to design peptides, corresponding to tubulin subsequences. These peptides, able to interfere with microtubules formations, were proved to exhibit antitumoral activity. Part II - Understanding the molecular mechanisms that allow some organisms to survive in extremely harsh conditions is an important achievement that might disclose a wide range of applications and that is constantly drawing the attention of many research fields. The simple small organic molecules, called osmolytes, responsible for the high adaptability of these living creatures are well known and of common use; nevertheless a full disclosure of the machinery behind their activity is still to be obtained. We developed a computational approach that, taking advantage of advanced simulation techniques, allowed to fully describe the effects of osmo-protectants on a small hairpin peptide and on a full mini-protein. The computational study allowed to highlight interesting new features and to develop a theory on the \u201cosmoprotection driving force\u201d

Computational strategies to include protein flexibility in Ligand Docking and Virtual Screening

The dynamic character of proteins strongly influences biomolecular recognition mechanisms. With the development of the main models of ligand recognition (lock-and-key, induced fit, conformational selection theories), the role of protein plasticity has become increasingly relevant. In particular, major structural changes concerning large deviations of protein backbones, and slight movements such as side chain rotations are now carefully considered in drug discovery and development. It is of great interest to identify multiple protein conformations as preliminary step in a screening campaign. Protein flexibility has been widely investigated, in terms of both local and global motions, in two diverse biological systems. On one side, Replica Exchange Molecular Dynamics has been exploited as enhanced sampling method to collect multiple conformations of Lactate Dehydrogenase A (LDHA), an emerging anticancer target. The aim of this project was the development of an Ensemble-based Virtual Screening protocol, in order to find novel potent inhibitors. On the other side, a preliminary study concerning the local flexibility of Opioid Receptors has been carried out through ALiBERO approach, an iterative method based on Elastic Network-Normal Mode Analysis and Monte Carlo sampling. Comparison of the Virtual Screening performances by using single or multiple conformations confirmed that the inclusion of protein flexibility in screening protocols has a positive effect on the probability to early recognize novel or known active compounds

UNCOVERING BIOPHYSICAL PROPERTIES AND FUNCTIONS OF DISORDERED HISTONES USING COMPUTER SIMULATIONS

It is a crucial task for the continuation of every species to safely store genetic information and precisely pass it on to the next generation. For all the eukaryotes including humans, this mission is carried out by chromatin, a polymer chain consisting of repeating structural units called the nucleosome, in which 146 bp of DNA wraps around a histone protein octamer. In a typical eukaryotic cell, about two meters of DNA is compacted into a micrometer-sized nucleus, where transcription and replication activities are regulated in part via modulating chromatin's condensation. A comprehensive understanding of chromatin structure and dynamics provides the necessary foundation for explaining the genome organization, which, for example, will help better understand the mechanisms of diseases caused by epigenetic modifications. As the building blocks of chromatin and nucleosome, the histone proteins are the key players in chromatin structure regulation and epigenetic control. However, studying histones has been challenging in part because histone tails lack well-defined structures, staying disordered when carrying out many functions. In this dissertation, we focus on exploring the biophysical mechanisms related to these intrinsically disordered histones using computer simulations, carefully comparing our results with related experiments. We present recent progress in the development and applications of state-of-art molecular dynamics force fields for disordered histones and histone-DNA interactions. We used these force fields to investigate the structural, dynamical, and thermodynamical properties of various disordered histones, including histone tails, linker histones, and histone monomers, in the nucleosomal environment. Our investigations have uncovered the structural preferences and binding/folding dynamics of these disordered histones, which provide novel insights into how they aid chromatin condensation