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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Endogenous Production and Vibrational Analysis of Heavy-Isotope-Labeled Peptides from Cyanobacteria

Stable isotope labeling is an extremely useful tool for characterizing the structure, tracing the metabolism, and imaging the distribution of natural products in living organisms using mass-sensitive measurement techniques. In this study, a cyanobacterium was cultured in 15 N/ 13 C-enriched media to endogenously produce labeled, bioactive oligopeptides. The extent of heavy isotope incorporation in these peptides was determined with LC–MS, while the overall extent of heavy isotope incorporation in whole cells was studied with nanoSIMS and AFM-IR. Up to 98 % heavy isotope incorporation was observed in labeled cells. Three of the most abundant peptides, microcystin-LR (MCLR), cyanopeptolin-A (CYPA), and aerucyclamide-A (ACAA), were isolated and further studied with Raman and FTIR spectroscopies and DFT calculations. This revealed several IR and Raman active vibrations associated with functional groups not common in ribosomal peptides, like diene, ester, thiazole, thiazoline, and oxazoline groups, which could be suitable for future vibrational imaging studies. More broadly, this study outlines a simple and relatively inexpensive method for producing heavy-labeled natural products. Finally, manipulating the bacterial culture conditions by the addition of specific types and amounts of heavy-labeled nutrients provides an efficient means of producing heavy-labeled natural products for mass-sensitive imaging studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Cecropin P1 antimicrobial peptide modulates differential expression of immune relevant genes in rainbow trout ( Oncorhynchus mykiss ) gill cell line, RTgill-W1

Accumulated evidence indicates that antimicrobial peptides modulate immune activities in fish. In this study, we profiled the differential expression patterns of representative immune relevant genes in an epithelial-like cell line of rainbow trout gill, RTgill-W1, in response to exposure of cecropin P1 antimicrobial peptide. RTgill-W1 cells were treated with synthetic cecropin P1 over time (0, 2, 4 and 24 h) with or without the present of lipopolysaccharide (LPS) or polyinosinic polycytidylic acid (PolyI:C). The relative abundances of each mRNA were measured by real-time quantitative PCR. The dose-response study revealed significant perturbations of mRNA levels of genes related to pro-inflammation, acute phase, surface proteins and transcription factors at 30 μM of cecropin P1. In addition, cecropin P1 altered the differential expression patterns that were induced by LPS or PolyI:C, at different time points in RTgill-W1. Overall, our results indicate that cecropin P1 exhibits pro-inflammation activity, modulate cell-cell interaction and cytokine signal transduction in rainbow trout gill cell, and may suggest a potential application of this peptide as an immune adjuvant for disease control in aquaculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor’s scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Using Multiple Isotope-Labeled Infrared Spectra for the Structural Characterization of an Intrinsically Disordered Peptide

Intrinsically disordered proteins (IDPs) rapidly interconvert between conformers, requiring an ensemble description. This complicates their experimental characterization, and force field limitations pose challenges for their simulation. Here, in this work, we use isotope-labeled and unlabeled infrared (IR) spectra to reweight simulated ensembles of the elastin-like peptide GVGVPGVG, a paradigmatic disordered peptide. By comparing the results obtained with different spectra, we explicitly show that the weights are underdetermined by the ensemble averaged data. We identify which labels and frequency regions maximize structural information while minimizing sensitivity to simulation error and show that these regions report on whether the peptide makes specific interactions. Our work shows the importance of incorporating simulations and simulated spectra at the planning stages of isotope-labeled IR experiments and more generally provides a framework for interpreting IR data for IDPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Copper-Binding Peptide with Therapeutic Potential against Alzheimer′s Disease: From the Blood–Brain Barrier to Metal Competition

Alzheimer’s disease (AD) is the most common form of dementia worldwide. AD brains are characterized by the accumulation of amyloid-β peptides (Aβ) that bind Cu 2+ and have been associated with several neurotoxic mechanisms. Although the use of copper chelators to prevent the formation of Cu 2+ -Aβ complexes has been proposed as a therapeutic strategy, recent studies show that copper is an important neuromodulator that is essential for a neuroprotective mechanism mediated by Cu 2+ binding to the cellular prion protein (PrPC). Therefore, in addition to metal selectivity and blood–brain barrier (BBB) permeability, an emerging challenge for copper chelators is to prevent the formation of neurotoxic Cu 2+ -Aβ species without perturbing the neuroprotective Cu 2+ -PrPC interaction. Previously, we reported the design of a tetrapeptide (TP) that withdraws Cu 2+ from Aβ(1–16) and impacts the Cu 2+ -induced aggregation of Aβ(1–40). In this study, we improved the drug-like properties of TP in a BBB model, evaluated the metal selectivity of the optimized peptide (TP*), and tested its effect on Cu 2+ coordination to PrPC and proteins involved in copper trafficking, such as copper transporter 1 and albumin. Our results show that changing the stereochemistry of the first residue prevents TP degradation in the BBB model and coadministration of TP with a peptide that increases BBB permeability allows its passage through the BBB model. TP* is highly selective toward Cu 2+ in the presence of Zn 2+ ions, transfers Cu 2+ to copper-trafficking proteins, and forms a ternary TP*-Cu 2+ -PrP species that does not perturb the physiological conformation of PrP and displays only a minor impact in the neuroprotective Cu 2+ -dependent interaction of PrPC with the N-methyl-d-aspartate receptor. Overall, these results show that TP* displays desirable features for a copper chelator with therapeutic potential against AD. Moreover, this is the first study that explores the effect of a Cu 2+ chelator with therapeutic potential for AD on Cu 2+ coordination to PrPC (an emerging key player in AD pathology), integrating recent knowledge about metalloproteins involved in AD with the design of copper chelators against AD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Shaping Peptide Assemblies Using Multifaceted Cyclic Tectons

Constructing distinct biomacromolecular assemblies typically necessitates target-specific selection and engineering of building blocks alongside optimization of assembly conditions. The challenge lies in achieving diverse morphological outcomes using simple, shared modules under identical conditions, a hallmark of natural systems that remains elusive in synthetic approaches. Here, in this work, we present a molecular scaffold-based strategy to instruct the coassembly of the same set of peptides into a variety of nanostructures across multiple dimensions. We create trifaceted cyclic scaffolds to manipulate two pairs of dimeric coiled-coil peptides prior to coassembly. These scaffolds, with addressable and orthogonal modules, allow controlled exposure of their cohesive faces, directing the formation of nanotriangles and fibrillar and lamellar assemblies. By tuning interpeptide arrangements that dictate scaffold geometry, we construct nonstraight fibrils with tunable curvature, which are rarely observed before. Notably, these scaffolds exhibit plasticity in adapting the sizes and orientations of cohesive faces to different assembly morphologies. The resultant nanostructures are consistent with the design and simulation results, demonstrating the reliability and predictability of this approach. Multifaceted cyclic scaffolds bridge the intellectual and physical gaps between building peptides and assemblies, holding promise for endowing various existing assembly systems with high tunability and versatility.

assembly morphology↗
DOE OSTI2023

De novo design of high-affinity binders of bioactive helical peptides

Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity to structured proteins. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Surface-mediated spontaneous emulsification of the acylated peptide, semaglutide

Acylated peptides composed of glucagon-like peptide-1 receptor agonists modified with a fatty acid side chain are an important class of therapeutics for type 2 diabetes and obesity but are susceptible to an unusual physical instability in the presence of hydrophobic surfaces, i.e., spontaneous emulsification, also known as ouzo formation in practice. In this work, light scattering, small-angle X-ray scattering, and circular dichroism measurements are used to characterize the physical properties of the semaglutide colloidal phase, including size distribution, shape, secondary structure, internal structure, and internal composition, as a function of solution physico-chemical conditions. The existence and size of the colloids formed are successfully predicted by a classical Rayleigh model, which identifies the parameters controlling their size and formation. Colloid formation is found to be catalyzed by hydrophobic surfaces, and formation rates are modeled as an autocatalytic reaction, enabling the formation of a master curve for various surfaces that elucidates the mechanism. Surfaces differ due to differences in surface wettability, which can be correlated with Hansen solubility parameters. This work provides insights into this unusual colloidal phenomenon and guides the peptide synthesis process and drug product formulation in the pharmaceutical industry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A multilayer network analysis of Alzheimer's disease pathogenesis: Roles for p‐tau, synaptic peptides, and physical activity

INTRODUCTION: In the aging brain, cognitive abilities emerge from the coordination of complex pathways arising from a balance between protective lifestyle and environmental factors and accumulation of neuropathologies. METHODS: As part of the Rush Memory and Aging Project (n = 440), we measured accelerometer-based actigraphy, cognitive performance, and after brain autopsy, selected reaction monitoring mass spectrometry. Multilevel network analysis was used to examine the relationships among the molecular machinery of vesicular neurotransmission, Alzheimer's disease (AD) neuropathology, cognition, and late-life physical activity. RESULTS: Synaptic peptides involved in neuronal secretory function were the most influential contributors to the multilayer network, reflecting the complex interdependencies among AD pathology, synaptic processes, and late-life cognition. Older adults with lower physical activity evidenced stronger adverse relationships among phosphorylated tau peptides, markers of synaptic integrity, and tangle pathology. DISCUSSION: Network-based approaches simultaneously model interdependent biological processes and advance understanding of the role of physical activity in age-associated cognitive impairment. Highlights: Network-based approaches simultaneously model interdependent biological processes. Secretory synaptic peptides were influential contributors to the multilayer network. Older adults with lower physical activity had adverse relationships among pathology. There was interdependence among phosphorylated tau, synaptic integrity, and tangles. Network methods elucidate the role of physical activity in cognitive impairment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Cryo-EM, Protein Engineering, and Simulation Enable the Development of Peptide Therapeutics against Acute Myeloid Leukemia

Cryogenic electron microscopy (cryo-EM) has emerged as a viable structural tool for molecular therapeutics development against human diseases. However, it remains a challenge to determine structures of proteins that are flexible and smaller than 30 kDa. The 11 kDa KIX domain of CREB-binding protein (CBP), a potential therapeutic target for acute myeloid leukemia and other cancers, is a protein which has defied structure-based inhibitor design. Here, we develop an experimental approach to overcome the size limitation by engineering a protein double-shell to sandwich the KIX domain between apoferritin as the inner shell and maltose-binding protein as the outer shell. To assist homogeneous orientations of the target, disulfide bonds are introduced at the target–apoferritin interface, resulting in a cryo-EM structure at 2.6 Å resolution. We used molecular dynamics simulations to design peptides that block the interaction of the KIX domain of CBP with the intrinsically disordered pKID domain of CREB. The double-shell design allows for fluorescence polarization assays confirming the binding between the KIX domain in the double-shell and these interacting peptides. Further cryo-EM analysis reveals a helix–helix interaction between a single KIX helix and the best peptide, providing a possible strategy for developments of next-generation inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Better understanding and prediction of antiviral peptides through primary and secondary structure feature importance

The emergence of viral epidemics throughout the world is of concern due to the scarcity of available effective antiviral therapeutics. The discovery of new antiviral therapies is imperative to address this challenge, and antiviral peptides (AVPs) represent a valuable resource for the development of novel therapies to combat viral infection. We present a new machine learning model to distinguish AVPs from non-AVPs using the most informative features derived from the physicochemical and structural properties of their amino acid sequences. To focus on those features that are most likely to contribute to antiviral performance, we filter potential features based on their importance for classification. These feature selection analyses suggest that secondary structure is the most important peptide sequence feature for predicting AVPs. Our Feature-Informed Reduced Machine Learning for Antiviral Peptide Prediction (FIRM-AVP) approach achieves a higher accuracy than either the model with all features or current state-of-the-art single classifiers. Understanding the features that are associated with AVP activity is a core need to identify and design new AVPs in novel systems. The FIRM-AVP code and standalone software package are available at https://github.com/pmartR/FIRM-AVP with an accompanying web application at https://msc-viz.emsl.pnnl.gov/AVPR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

X-ray fluorescence standing wave study of the interaction of the antimicrobial peptide indolicidin with a supported model membrane

Indolicidin, a cationic antimicrobial peptide, interacts with lipid bilayers through electrostatic and hydrophobic interactions, disrupting microbial membranes. We investigated the depth-dependent localization of gold-nanoparticle-labeled indolicidin in a supported model membrane using X-ray fluorescence standing wave (SWXF) analysis. Liposomes composed of DMPC and DMPG were incubated with indolicidin labeled at its C-terminus with a 1.8 nm gold nanoparticle, then deposited onto a Si/Mo multilayer substrate via vesicle bursting. SWXF measurements revealed that at low peptide incubation concentrations (2–5 μM), gold-nanoparticle-labeled indolicidin remains primarily associated with the bilayer's outer leaflet. At higher concentrations (10 μM), the peptide penetrates deeper into the bilayer, with the labeled C-terminal region either localizing near the membrane's hydrophobic core or inducing membrane breakup. In conclusion, these findings suggest a concentration-dependent insertion mechanism.

Basnet, Gobind [Northern Illinois Univ., DeKalb, I↗
DOE OSTI2023

Sneaking in SpyCatcher using cell penetrating peptides for in vivo imaging

Abstract In vivo imaging of protein complexes is a powerful method for understanding the underlying biological function of these key biomolecules. Though the engineering of small, high affinity nanobodies have become more prevalent, the off-rates of these tags may result in incomplete or partial labeling of proteins in live cells. The SpyCatcher003 and SpyTag split protein system allow for irreversible, covalent binding to a short target peptide unlike nanobody-affinity based probes. However, delivering these tags into a cell without disrupting its normal function is a key challenge. Cell penetrating peptides (CPPs) are short peptide sequences that facilitate the transduction of otherwise membrane-impermeable ‘cargo’ , such as proteins, into cells. Here we report on our efforts to engineer and characterize CPP-SpyCatcher003 fusions as modular imaging probes. We selected three CPPs, CUPID, Pentratin, and pVEC, to engineer fusion protein probes for superresolution microscopy, with the aim to eliminate prior permeabilization treatments that could introduce imaging artifacts. We find that fusing the CPP sequences to SpyCatcher003 resulted in dimer and multimer formation as determined by size exclusion chromatography, dynamic light scattering, and SDS resistant dimers on SDS-PAGE gels. By isolating and labeling the monomeric forms of the engineered protein, we show these constructs retained their ability to bind SpyTag and all three CPP sequences remain membrane active, as assessed by CD spectroscopy in the presence of SDS detergent. Using fluorescence and super resolution Lattice structured illumination microscopy (Lattice SIM) imaging we show that the CPPs did not enhance uptake of SpyCatcher by E. coli, however with Caulobacter crescentus cells, we show that Penetratin, and to a lesser degree CUPID, does enhance uptake. Our results demonstrate the ability of the CPP-SpyCatcher003 to label targets within living cells, providing the groundwork for using split protein systems for targeted in vivo imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Structural basis for the inability of chloramphenicol to inhibit peptide bond formation in the presence of A-site glycine

Ribosome serves as a universal molecular machine capable of synthesis of all the proteins in a cell. Small-molecule inhibitors, such as ribosome-targeting antibiotics, can compromise the catalytic versatility of the ribosome in a context-dependent fashion, preventing transpeptidation only between particular combinations of substrates. Classic peptidyl transferase center inhibitor chloramphenicol (CHL) fails to inhibit transpeptidation reaction when the incoming A site acceptor substrate is glycine, and the molecular basis for this phenomenon is unknown. Here, we present a set of high-resolution X-ray crystal structures that explain why CHL is unable to inhibit peptide bond formation between the incoming glycyl-tRNA and a nascent peptide that otherwise is conducive to the drug action. Our structures reveal that fully accommodated glycine residue can co-exist in the A site with the ribosome-bound CHL. Moreover, binding of CHL to a ribosome complex carrying glycyl-tRNA does not affect the positions of the reacting substrates, leaving the peptide bond formation reaction unperturbed. These data exemplify how small-molecule inhibitors can reshape the A-site amino acid binding pocket rendering it permissive only for specific amino acid residues and rejective for the other substrates extending our detailed understanding of the modes of action of ribosomal antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Discovery of unconventional and nonintuitive self-assembling peptide materials using experiment-driven machine learning

Prediction of peptide secondary structure is challenging because of complex molecular interactions, sequence-specific behavior, and environmental factors. Traditional design strategies, based on hydrophobicity and structural propensity, can be biased and could indeed prevent discovery of interesting, diverse, and unconventional peptides with desired nanostructure assembly. Using β sheet formation in pentapeptides as a case study, we used an integrated high-throughput experimental workflow and an artificial intelligence–driven active learning framework to improve prediction accuracy of self-assembly. By focusing on sequences where machine learning (ML) predictions deviate from conventional design strategies, we synthesized and tested 268 pentapeptides, successfully finding 96 forming β sheet assemblies, including unconventional sequences (e.g., ILFSM, LMISI, MITIY, MISIW, and WKIYI) not predicted by traditional methods. Our ML models outperformed conventional β sheet propensity tables, revealing useful chemical design rules. A web interface is provided to facilitate community access to these models. This work highlights the value of ML-driven approaches in overcoming the limitations of current peptide design strategies.

Talluri, Y. Nissi [Indian Inst. of Technology (IIT↗
DOE OSTI2024

Mechanical Properties of a Solvated Biomolecule: RGD (1FUV) Peptide

The mechanical properties of proteins/peptides play an essential role in their functionalities and implications, as well as their structure and dynamic properties. Understanding mechanical properties is pivotal to our knowledge of protein folding and the molecular basis of diverse cellular processes. Herein, we present a computational approach using ab initio quantum mechanical calculations to determine the mechanical properties—such as bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio—of a solvated Arg-Gly-Asp (RGD) peptide model. Since this peptide serves as the RGD-directed integrin recognition site and may participate in cellular adhesion, it is considered a promising small peptide for medicinal applications. This successful approach paves the way for investigating larger and more complex biomolecules.

Biochemistry & Molecular Biology↗
DOE OSTI2022

PET Imaging of the Neurotensin Targeting Peptide NOTA-NT-20.3 Using Cobalt-55, Copper-64 and Gallium-68

Introduction: Neurotensin receptor 1 (NTSR1) is an emerging target for imaging and therapy of many types of cancer. Nuclear imaging of NTSR1 allows for noninvasive assessment of the receptor levels of NTSR1 on the primary tumor, as well as potential metastases. This work focuses on a the neurotensin peptide analogue NT-20.3 conjugated to the chelator NOTA for radiolabeling for use in noninvasive positron emission tomography (PET). NOTA-NT-20.3 was radiolabeled with gallium-68, copper-64, and cobalt-55 to determine the effect that modification of the radiometal has on imaging and potential therapeutic properties of NOTA-NT-20.3. Methods: In vitro assays investigating cell uptake and subcellular localization of the radiolabeled peptides were performed using human colorectal adenocarcinoma HT29 cells. In vivo PET/CT imaging was used to determine the distribution and clearance of the peptide in mice bearing NTSR1 expressing HT29 tumors. Results: Cell uptake studies showed that the highest uptake was obtained with [ 55 Co] Co-NOTA-NT-20.3 (18.70 ± 1.30%ID/mg), followed by [ 64 Cu] Cu-NOTA-NT-20.3 (15.46 ± 0.91%ID/mg), and lastly [ 68 Ga] Ga-NOTA-NT-20.3 (10.94 ± 0.46%ID/mg) (p < 0.001). Subcellular distribution was similar across the three constructs, with the membranous fraction containing the highest amount of radioactivity. In vivo PET/CT imaging of the three constructs revealed similar distribution and tumor uptake at the 1 h imaging timepoint. Tumor uptake was receptor-specific and blockable by co-injection of non-radiolabeled NOTA-NT-20.3. SUV ratios of tumor to heart at the 24 h imaging timepoint show that [ 55 Co] Co-NOTA-NT-20.3 (20.28 ± 3.04) outperformed [ 64 Cu] Cu-NOTA-NT-20.3 (6.52 ± 1.97). In conclusion, our studies show that enhanced cell uptake and increasing tumor to blood ratios over time displayed the superiority of [ 55 Co] Co-NOTA-NT-20.3 over [ 68 Ga] Ga-NOTA-NT-20.3 and [ 64 Cu] Cu-NOTA-NT-20.3 for the targeting of NTSR1.

60 APPLIED LIFE SCIENCES↗