Evaluation of a deuterated triarylmethyl spin probe for in vivo R2 ∗-based EPR oximetric imaging with enhanced dynamic range.

PURPOSE: In this study, we compared two triarylmethyl (TAM) spin probes, Ox071 and Ox063 for their efficacy in measuring tissue oxygen levels under hypoxic and normoxic conditions by R2 *-based EPR oximetry. METHODS: The R2 * dependencies on the spin probe concentration and oxygen level were calibrated using deoxygenated 1, 2, 5, and 10 mM standard solutions and 2 mM solutions saturated at 0%, 2%, 5%, 10%, and 21% of oxygen. For the hypoxic model, in vivo imaging of a MIA PaCa-2 tumor implanted in the hind leg of a mouse was performed on successive days by R2 *-based EPR oximetry using either Ox071 or Ox063. For the normoxic model, renal imaging of healthy athymic mice was performed using both spin probes. The 3D images were reconstructed by single point imaging and multi-gradient technique was used to determine R2 * maps. RESULTS: The signal intensities of Ox071 were approximately three times greater than that of Ox063 in the entire partial pressure of oxygen (pO2 ) range investigated. The histograms of the tumor pO2 images were skewed for both spin probes, and Ox071 showed more frequency counts at pO2 > 32 mm Hg. In the normoxic kidney model, there was a clear delineation between the high pO2 cortex and the low pO2 medulla regions. The histogram of high-resolution kidney oximetry image using Ox071 was nearly symmetrical and frequency counts were seen up to 55 mm Hg, which were missed in Ox063 imaging. CONCLUSION: As an oximetric probe, Ox071 has clear advantages over Ox063 in terms of sensitivity and the pO2 dynamic range.

Trehalose as an alternative to glycerol as a glassing agent for in vivo DNP MRI.

PURPOSE: In dynamic nuclear polarization (DNP), the solution needs to form a glass to attain significant levels of polarization in reasonable time periods. Molecules that do not form glasses by themselves are often mixed with glass forming excipients. Although glassing agents are often essential in DNP studies, they have the potential to perturb the metabolic measurements that are being studied. Glycerol, the glassing agent of choice for in vivo DNP studies, is effective in reducing ice crystal formation during freezing, but is rapidly metabolized, potentially altering the redox and adenosine triphosphate balance of the system. METHODS: DNP buildup curves of 13 C urea and alanine with OX063 in the presence of trehalose, glycerol, and other polyol excipients were measured as a function of concentration. T1 and Tm relaxation times for OX063 in the presence of trehalose were measured by EPR. RESULTS: Approximately 15-20 wt% trehalose gives a glass that polarizes samples more rapidly than the commonly used 60%-wt formulation of glycerol and yields similar polarization levels within clinically relevant timeframes. CONCLUSIONS: Trehalose may be an attractive biologically inert alternative to glycerol for situations where there may be concerns about glycerol's glucogenic potential and possible alteration of the adenosine triphosphate/adenosine diphosphate and redox balance.

Denoising of hyperpolarized 13 C MR images of the human brain using patch-based higher-order singular value decomposition.

PURPOSE: To improve hyperpolarized 13 C (HP-13 C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD). METHODS: The benefit of using a patch-based HOSVD method to denoise dynamic HP-13 C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1-13 C]pyruvate and its metabolic product, [1-13 C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1-13 C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error. RESULTS: Simulation results demonstrated an 8-fold increase in the calculated SNR of [1-13 C]pyruvate and [1-13 C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of kPL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted kPL after denoising. The patch-based denoising performed superior to the global denoising in recovering kPL information. In volunteer data sets, [1-13 C]lactate and [13 C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping kPB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping kPL . CONCLUSIONS: Sensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research.

Detection of metabolic change in glioblastoma cells after radiotherapy using hyperpolarized 13 C-MRI.

Dynamic nuclear polarization (DNP) of 13 C-labeled substrates enables the use of magnetic resonance imaging (MRI) to monitor specific enzymatic reactions in tumors and offers an opportunity to investigate these differences. In this study, DNP-MRI chemical shift imaging with hyperpolarized [1-13 C] pyruvate was conducted to evaluate the metabolic change in glycolytic profiles after radiation of two glioma stem-like cell-derived gliomas (GBMJ1 and NSC11) and an adherent human glioblastoma cell line (U251) in an orthotopic xenograft mouse model. The DNP-MRI showed an increase in Lac/Pyr at 6 and 16 h after irradiation (18% ± 4% and 14% ± 3%, respectively; mean ± SEM) compared with unirradiated controls in GBMJ1 tumors, whereas no significant change was observed in U251 and NSC11 tumors. Metabolomic analysis likewise showed a significant increase in lactate in GBMJ1 tumors at 16 h. An immunoblot assay showed upregulation of lactate dehydrogenase-A expression in GBMJ1 following radiation exposure, consistent with DNP-MRI and metabolomic analysis. In conclusion, our preclinical study demonstrates that the DNP-MRI technique has the potential to be a powerful diagnostic method with which to evaluate GBM tumor metabolism before and after radiation in the clinical setting.

Synthesis of [1-13 C-5-12 C]-alpha-ketoglutarate enables noninvasive detection of 2-hydroxyglutarate.

Isocitrate dehydrogenase 1 (IDH1) mutations that generate the oncometabolite 2-hydroxyglutarate (2-HG) from α-ketoglutarate (α-KG) have been identified in many types of tumors and are an important prognostic factor in gliomas. 2-HG production can be determined by hyperpolarized carbon-13 magnetic resonance spectroscopy (HP-13 C-MRS) using [1-13 C]-α-KG as a probe, but peak contamination from naturally occurring [5-13 C]-α-KG overlaps with the [1-13 C]-2-HG peak. Via a newly developed oxidative-Stetter reaction, [1-13 C-5-12 C]-α-KG was synthesized. α-KG metabolism was measured via HP-13 C-MRS using [1-13 C-5-12 C]-α-KG as a probe. [1-13 C-5-12 C]-α-KG was synthesized in high yields, and successfully eliminated the signal from C5 of α-KG in the HP-13 C-MRS spectra. In HCT116 IDH1 R132H cells, [1-13 C-5-12 C]-α-KG allowed for unimpeded detection of [1-13 C]-2-HG. 12 C-enrichment represents a novel method to circumvent spectral overlap, and [1-13 C-5-12 C]-α-KG shows promise as a probe to study IDH1 mutant tumors and α-KG metabolism.

Radiation-Induced Senescence Reprograms Secretory and Metabolic Pathways in Colon Cancer HCT-116 Cells.

Understanding the global metabolic changes during the senescence of tumor cells can have implications for developing effective anti-cancer treatment strategies. Ionizing radiation (IR) was used to induce senescence in a human colon cancer cell line HCT-116 to examine secretome and metabolome profiles. Control proliferating and senescent cancer cells (SCC) exhibited distinct morphological differences and expression of senescent markers. Enhanced secretion of pro-inflammatory chemokines and IL-1, anti-inflammatory IL-27, and TGF-ß1 was observed in SCC. Significantly reduced levels of VEGF-A indicated anti-angiogenic activities of SCC. Elevated levels of tissue inhibitors of matrix metalloproteinases from SCC support the maintenance of the extracellular matrix. Adenylate and guanylate energy charge levels and redox components NAD and NADP and glutathione were maintained at near optimal levels indicating the viability of SCC. Significant accumulation of pyruvate, lactate, and suppression of the TCA cycle in SCC indicated aerobic glycolysis as the predominant energy source for SCC. Levels of several key amino acids decreased significantly, suggesting augmented utilization for protein synthesis and for use as intermediates for energy metabolism in SCC. These observations may provide a better understanding of cellular senescence basic mechanisms in tumor tissues and provide opportunities to improve cancer treatment.

High-resolution structure of a partially folded insulin aggregation intermediate.

Insulin has long been served as a model for protein aggregation, both due to the importance of aggregation in the manufacture of insulin and because the structural biology of insulin has been extensively characterized. Despite intensive study, details about the initial triggers for aggregation have remained elusive at the molecular level. We show here that at acidic pH, the aggregation of insulin is likely initiated by a partially folded monomeric intermediate. High-resolution structures of the partially folded intermediate show that it is coarsely similar to the initial monomeric structure but differs in subtle details-the A chain helices on the receptor interface are more disordered and the B chain helix is displaced from the C-terminal A chain helix when compared to the stable monomer. The result of these movements is the creation of a hydrophobic cavity in the center of the protein that may serve as nucleation site for oligomer formation. Knowledge of this transition may aid in the engineering of insulin variants that retain the favorable pharamacokinetic properties of monomeric insulin but are more resistant to aggregation.

Tensor image enhancement and optimal multichannel receiver combination analyses for human hyperpolarized 13 C MRSI.

PURPOSE: With the initiation of human hyperpolarized 13 C (HP-13 C) trials at multiple sites and the development of improved acquisition methods, there is an imminent need to maximally extract diagnostic information to facilitate clinical interpretation. This study aims to improve human HP-13 C MR spectroscopic imaging through means of Tensor Rank truncation-Image enhancement (TRI) and optimal receiver combination (ORC). METHODS: A data-driven processing framework for dynamic HP 13 C MR spectroscopic imaging (MRSI) was developed. Using patient data sets acquired with both multichannel arrays and single-element receivers from the brain, abdomen, and pelvis, we examined the theory and application of TRI, as well as 2 ORC techniques: whitened singular value decomposition (WSVD) and first-point phasing. Optimal conditions for TRI were derived based on bias-variance trade-off. RESULTS: TRI and ORC techniques together provided a 63-fold mean apparent signal-to-noise ratio (aSNR) gain for receiver arrays and a 31-fold gain for single-element configurations, which particularly improved quantification of the lower-SNR-[13 C]bicarbonate and [1-13 C]alanine signals that were otherwise not detectable in many cases. Substantial SNR enhancements were observed for data sets that were acquired even with suboptimal experimental conditions, including delayed (114 s) injection (8× aSNR gain solely by TRI), or from challenging anatomy or geometry, as in the case of a pediatric patient with brainstem tumor (597× using combined TRI and WSVD). Improved correlation between elevated pyruvate-to-lactate conversion, biopsy-confirmed cancer, and mp-MRI lesions demonstrated that TRI recovered quantitative diagnostic information. CONCLUSION: Overall, this combined approach was effective across imaging targets and receiver configurations and could greatly benefit ongoing and future HP 13 C MRI research through major aSNR improvements.

Nonproductive Binding Modes as a Prominent Feature of Aß40 Fiber Elongation: Insights from Molecular Dynamics Simulation.

The formation of amyloid fibers has been implicated in a number of neurodegenerative diseases. The growth of amyloid fibers is strongly thermodynamically favorable, but kinetic traps exist where the incoming monomer binds in an incompatible conformation that blocks further elongation. Unfortunately, this process is difficult to follow experimentally at the atomic level. It is also too complex to simulate in full detail and to date has been explored either through coarse-grained simulations, which may miss many important interactions, or full atomic simulations, in which the incoming peptide is constrained to be near the ideal fiber geometry. Here we use an alternate approach starting from a docked complex in which the monomer is from an experimental NMR structure of one of the major conformations in the unbound ensemble, a largely unstructured peptide with the central hydrophobic region in a 310 helix. A 1000 ns full atomic simulation in explicit solvent shows the formation of a metastable intermediate by sequential, concerted movements of both the fiber and the monomer. A Markov state model shows that the unfolded monomer is trapped at the end of the fiber in a set of interconverting antiparallel ß-hairpin conformations. The simulation here may serve as a model for the binding of other non-ß-sheet conformations to amyloid fibers.

Inhibition of Insulin Amyloid Fibrillation by a Novel Amphipathic Heptapeptide: MECHANISTIC DETAILS STUDIED BY SPECTROSCOPY IN COMBINATION WITH MICROSCOPY.

The aggregation of insulin into amyloid fibers has been a limiting factor in the development of fast acting insulin analogues, creating a demand for excipients that limit aggregation. Despite the potential demand, inhibitors specifically targeting insulin have been few in number. Here we report a non-toxic and serum stable-designed heptapeptide, KR7 (KPWWPRR-NH2), that differs significantly from the primarily hydrophobic sequences that have been previously used to interfere with insulin amyloid fibrillation. Thioflavin T fluorescence assays, circular dichroism spectroscopy, and one-dimensional proton NMR experiments suggest KR7 primarily targets the fiber elongation step with little effect on the early oligomerization steps in the lag time period. From confocal fluorescence and atomic force microscopy experiments, the net result appears to be the arrest of aggregation in an early, non-fibrillar aggregation stage. This mechanism is noticeably different from previous peptide-based inhibitors, which have primarily shifted the lag time with little effect on later stages of aggregation. As insulin is an important model system for understanding protein aggregation, the new peptide may be an important tool for understanding peptide-based inhibition of amyloid formation.

GLASS: a comprehensive database for experimentally validated GPCR-ligand associations.

MOTIVATION: G protein-coupled receptors (GPCRs) are probably the most attractive drug target membrane proteins, which constitute nearly half of drug targets in the contemporary drug discovery industry. While the majority of drug discovery studies employ existing GPCR and ligand interactions to identify new compounds, there remains a shortage of specific databases with precisely annotated GPCR-ligand associations. RESULTS: We have developed a new database, GLASS, which aims to provide a comprehensive, manually curated resource for experimentally validated GPCR-ligand associations. A new text-mining algorithm was proposed to collect GPCR-ligand interactions from the biomedical literature, which is then crosschecked with five primary pharmacological datasets, to enhance the coverage and accuracy of GPCR-ligand association data identifications. A special architecture has been designed to allow users for making homologous ligand search with flexible bioactivity parameters. The current database contains ∼500 000 unique entries, of which the vast majority stems from ligand associations with rhodopsin- and secretin-like receptors. The GLASS database should find its most useful application in various in silico GPCR screening and functional annotation studies. AVAILABILITY AND IMPLEMENTATION: The website of GLASS database is freely available at http://zhanglab.ccmb.med.umich.edu/GLASS/. CONTACT: zhng@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles.

The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies.

Protein structure prediction provides comparable performance to crystallographic structures in docking-based virtual screening.

Structure based virtual screening has largely been limited to protein targets for which either an experimental structure is available or a strongly homologous template exists so that a high-resolution model can be constructed. The performance of state of the art protein structure predictions in virtual screening in systems where only weakly homologous templates are available is largely untested. Using the challenging DUD database of structural decoys, we show here that even using templates with only weak sequence homology (<30% sequence identity) structural models can be constructed by I-TASSER which achieve comparable enrichment rates to using the experimental bound crystal structure in the majority of the cases studied. For 65% of the targets, the I-TASSER models, which are constructed essentially in the apo conformations, reached 70% of the virtual screening performance of using the holo-crystal structures. A correlation was observed between the success of I-TASSER in modeling the global fold and local structures in the binding pockets of the proteins versus the relative success in virtual screening. The virtual screening performance can be further improved by the recognition of chemical features of the ligand compounds. These results suggest that the combination of structure-based docking and advanced protein structure modeling methods should be a valuable approach to the large-scale drug screening and discovery studies, especially for the proteins lacking crystallographic structures.

Insights into antiamyloidogenic properties of the green tea extract (-)-epigallocatechin-3-gallate toward metal-associated amyloid-ß species.

Despite the significance of Alzheimer's disease, the link between metal-associated amyloid-ß (metal-Aß) and disease etiology remains unclear. To elucidate this relationship, chemical tools capable of specifically targeting and modulating metal-Aß species are necessary, along with a fundamental understanding of their mechanism at the molecular level. Herein, we investigated and compared the interactions and reactivities of the green tea extract, (-)-epigallocatechin-3-gallate [(2R,3R)-5,7-dihydroxy-2-(3,4,5-trihydroxyphenyl)-3,4-dihydro-2H-1-benzopyran-3-yl 3,4,5-trihydroxybenzoate; EGCG], with metal [Cu(II) and Zn(II)]-Aß and metal-free Aß species. We found that EGCG interacted with metal-Aß species and formed small, unstructured Aß aggregates more noticeably than in metal-free conditions in vitro. In addition, upon incubation with EGCG, the toxicity presented by metal-free Aß and metal-Aß was mitigated in living cells. To understand this reactivity at the molecular level, structural insights were obtained by ion mobility-mass spectrometry (IM-MS), 2D NMR spectroscopy, and computational methods. These studies indicated that (i) EGCG was bound to Aß monomers and dimers, generating more compact peptide conformations than those from EGCG-untreated Aß species; and (ii) ternary EGCG-metal-Aß complexes were produced. Thus, we demonstrate the distinct antiamyloidogenic reactivity of EGCG toward metal-Aß species with a structure-based mechanism.

Differences between amyloid-ß aggregation in solution and on the membrane: insights into elucidation of the mechanistic details of Alzheimer's disease.

The association of the amyloid-ß (Aß) peptide with cellular membranes is hypothesized to be the underlying phenomenon of neurotoxicity in Alzheimer's disease. Misfolding of proteins and peptides, as is the case with Aß, follows a progression from a monomeric state, through intermediates, ending at long, unbranched amyloid fibers. This tutorial review offers a perspective on the association of toxic Aß structures with membranes as well as details of membrane-associated mechanisms of toxicity.

Rational design of a structural framework with potential use to develop chemical reagents that target and modulate multiple facets of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by multiple, intertwined pathological features, including amyloid-ß (Aß) aggregation, metal ion dyshomeostasis, and oxidative stress. We report a novel compound (ML) prototype of a rationally designed molecule obtained by integrating structural elements for Aß aggregation control, metal chelation, reactive oxygen species (ROS) regulation, and antioxidant activity within a single molecule. Chemical, biochemical, ion mobility mass spectrometric, and NMR studies indicate that the compound ML targets metal-free and metal-bound Aß (metal-Aß) species, suppresses Aß aggregation in vitro, and diminishes toxicity induced by Aß and metal-treated Aß in living cells. Comparison of ML to its structural moieties (i.e., 4-(dimethylamino)phenol (DAP) and (8-aminoquinolin-2-yl)methanol (1)) for reactivity with Aß and metal-Aß suggests the synergy of incorporating structural components for both metal chelation and Aß interaction. Moreover, ML is water-soluble and potentially brain permeable, as well as regulates the formation and presence of free radicals. Overall, we demonstrate that a rational structure-based design strategy can generate a small molecule that can target and modulate multiple factors, providing a new tool to uncover and address AD complexity.

An evolution-based approach to De Novo protein design and case study on Mycobacterium tuberculosis.

Computational protein design is a reverse procedure of protein folding and structure prediction, where constructing structures from evolutionarily related proteins has been demonstrated to be the most reliable method for protein 3-dimensional structure prediction. Following this spirit, we developed a novel method to design new protein sequences based on evolutionarily related protein families. For a given target structure, a set of proteins having similar fold are identified from the PDB library by structural alignments. A structural profile is then constructed from the protein templates and used to guide the conformational search of amino acid sequence space, where physicochemical packing is accommodated by single-sequence based solvation, torsion angle, and secondary structure predictions. The method was tested on a computational folding experiment based on a large set of 87 protein structures covering different fold classes, which showed that the evolution-based design significantly enhances the foldability and biological functionality of the designed sequences compared to the traditional physics-based force field methods. Without using homologous proteins, the designed sequences can be folded with an average root-mean-square-deviation of 2.1 Å to the target. As a case study, the method is extended to redesign all 243 structurally resolved proteins in the pathogenic bacteria Mycobacterium tuberculosis, which is the second leading cause of death from infectious disease. On a smaller scale, five sequences were randomly selected from the design pool and subjected to experimental validation. The results showed that all the designed proteins are soluble with distinct secondary structure and three have well ordered tertiary structure, as demonstrated by circular dichroism and NMR spectroscopy. Together, these results demonstrate a new avenue in computational protein design that uses knowledge of evolutionary conservation from protein structural families to engineer new protein molecules of improved fold stability and biological functionality.

Non-selective ion channel activity of polymorphic human islet amyloid polypeptide (amylin) double channels.

Fundamental understanding of ion channel formation by amyloid peptides, which is strongly linked to cell toxicity, is very critical for (pre)clinical treatment of neurodegenerative diseases. Here, we combine atomistic simulations and experiments to demonstrate a broad range of conformational states of hIAPP double channels in lipid membranes. All individual channels display high selectivity for Cl(-) ions over cations, but the co-existence of polymorphic double channels of different conformations and orientations with different populations determines the non-ionic selectivity nature of the channels, which is different from the typical amyloid-ß channels that exhibit Ca(2+) selective ion-permeable characteristics. This work provides a more complete physicochemical mechanism of amyloid-channel-induced toxicity.

Cations as switches of amyloid-mediated membrane disruption mechanisms: calcium and IAPP.

Disruption of the integrity of the plasma membrane by amyloidogenic proteins is linked to the pathogenesis of a number of common age-related diseases. Although accumulating evidence suggests that adverse environmental stressors such as unbalanced levels of metal ions may trigger amyloid-mediated membrane damage, many features of the molecular mechanisms underlying these events are unknown. Using human islet amyloid polypeptide (hIAPP, aka amylin), an amyloidogenic peptide associated with ß-cell death in type 2 diabetes, we demonstrate that the presence of Ca(2+) ions inhibits membrane damage occurring immediately after the interaction of freshly dissolved hIAPP with the membrane, but significantly enhances fiber-dependent membrane disruption. In particular, dye leakage, quartz crystal microbalance, atomic force microscopy, and NMR experiments show that Ca(2+) ions promote a shallow membrane insertion of hIAPP, which leads to the removal of lipids from the bilayer through a detergent-like mechanism triggered by fiber growth. Because both types of membrane-damage mechanisms are common to amyloid toxicity by most amyloidogenic proteins, it is likely that unregulated ion homeostasis, amyloid aggregation, and membrane disruption are all parts of a self-perpetuating cycle that fuels amyloid cytotoxicity.

Lipid composition-dependent membrane fragmentation and pore-forming mechanisms of membrane disruption by pexiganan (MSI-78).

The potency and selectivity of many antimicrobial peptides (AMPs) are correlated with their ability to interact with and disrupt the bacterial cell membrane. In vitro experiments using model membranes have been used to determine the mechanism of membrane disruption of AMPs. Because the mechanism of action of an AMP depends on the ability of the model membrane to accurately mimic the cell membrane, it is important to understand the effect of membrane composition. Anionic lipids that are present in the outer membrane of prokaryotes but are less common in eukaryotic membranes are usually thought to be key for the bacterial selectivity of AMPs. We show by fluorescence measurements of peptide-induced membrane permeabilization that the presence of anionic lipids at high concentrations can actually inhibit membrane disruption by the AMP MSI-78 (pexiganan), a representative of a large class of highly cationic AMPs. Paramagnetic quenching studies suggest MSI-78 is in a surface-associated inactive mode in anionic sodium dodecyl sulfate micelles but is in a deeply buried and presumably more active mode in zwitterionic dodecylphosphocholine micelles. Furthermore, a switch in mechanism occurs with lipid composition. Membrane fragmentation with MSI-78 can be observed in mixed vesicles containing both anionic and zwitterionic lipids but not in vesicles composed of a single lipid of either type. These findings suggest membrane affinity and membrane permeabilization are not always correlated, and additional effects that may be more reflective of the actual cellular environment can be seen as the complexity of the model membranes is increased.