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At least 487 records · Page 27

All sources NASA NTRS DOE OSTI

DOE OSTI2023

PLAT domain protein 1 (PLAT1/PLAFP) binds to the Arabidopsis thaliana plasma membrane and inserts a lipid

Robust agricultural yields depend on the plant's ability to fix carbon amid variable environmental conditions. Over seasonal and diurnal cycles, the plant must constantly adjust its metabolism according to available resources or external stressors. The metabolic changes that a plant undergoes in response to stress are well understood, but the long-distance signaling mechanisms that facilitate communication throughout the plant are less studied. The phloem is considered the predominant conduit for the bidirectional transport of these signals in the form of metabolites, nucleic acids, proteins, and lipids. Lipid trafficking through the phloem in particular attracted our attention due to its reliance on soluble lipid-binding proteins (LBP) that generate and solubilize otherwise membrane-associated lipids. The Phloem Lipid-Associated Family Protein (PLAFP) from Arabidopsis thaliana is generated in response to abiotic stress as is its lipid-ligand phosphatidic acid (PA). PLAFP is proposed to transport PA through the phloem in response to drought stress. To understand the interactions between PLAFP and PA, nearly 100 independent systems comprised of the protein and one PA, or a plasma membrane containing varying amounts of PA, were simulated using atomistic classical molecular dynamics methods. In these simulations, PLAFP is found to bind to plant plasma membrane models independent of the PA concentration. When bound to the membrane, PLAFP adopts a binding pose where W41 and R82 penetrate the membrane surface and anchor PLAFP. This triggers a separation of the two loop regions containing W41 and R82. Subsequent simulations indicate that PA insert into the β -sandwich of PLAFP, driven by interactions with multiple amino acids besides the W41 and R82 identified during the insertion process. Finally, fine-tuning the protein-membrane and protein-PA interface by mutating a selection of these amino acids may facilitate engineering plant signaling processes by modulating the binding response.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Nanomolar Sensitivity Chirality Transfer from Designed Helical Repeat Proteins to Achiral CdS Nanorods

Bridging chirality across length scales with inorganic− organic hybrid materials is a rapidly expanding area of research. Here, we establish asymmetry at CdS nanorod (NR) interfaces using a designed helical repeat protein bearing four cysteine residues (DHR- 4Cys). Hydrophobic NRs are transferred into water with glycine, and then glycine is displaced by DHR-4Cys, leveraging the thiophilicity of cadmium. Circular dichroism (CD) in the visible, coincident with CdS electronic transitions, reveals a chiral DHR-4Cys:CdS interface. Here, the dissymmetry factor [g-factor = 4.5 × 10 −4 (short NRs) and 5.0 × 10 −4 (long NRs)] is weakly dependent on the NR length, and CD persists at nanomolar protein loadings. Additionally, control experiments demonstrate that DHR-4Cys:CdS NR chirality is dictated by the local coordination of Cys with no significant contribution from the chiral secondary structure of the protein (g-factors of short and long Cys:CdS NRs are 4.8 × 10 −4 and 4.0 × 10 −4 , respectively). Together with far-UV CD and transmission electron microscopy, which provide evidence of preserved protein structure, these results provide the first demonstration that a structurally defined protein can induce chirality in CdS nanocrystals while maintaining protein structure at biologically relevant concentrations.

Cadmium sulfide↗

DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Characterization of SETD3 methyltransferase–mediated protein methionine methylation

Most characterized protein methylation events encompass arginine and lysine N-methylation, and only a few cases of protein methionine thiomethylation have been reported. Newly discovered oncohistone mutations include lysine-to-methionine substitutions at positions 27 and 36 of histone H3.3. In these cases, the methionine substitution localizes to the active-site pocket of the corresponding histone lysine methyltransferase, thereby inhibiting the respective transmethylation activity. SET domain–containing 3 (SETD3) is a protein (i.e. actin) histidine methyltransferase. Here, we generated an actin variant in which the histidine target of SETD3 was substituted with methionine. As for previously characterized histone SET domain proteins, the methionine substitution substantially (76-fold) increased binding affinity for SETD3 and inhibited SETD3 activity on histidine. Unexpectedly, SETD3 was active on the substituted methionine, generating S-methylmethionine in the context of actin peptide. The ternary structure of SETD3 in complex with the methionine-containing actin peptide at 1.9 Å resolution revealed that the hydrophobic thioether side chain is packed by the aromatic rings of Tyr 312 and Trp 273 , as well as the hydrocarbon side chain of Ile 310 . Our results suggest that placing methionine properly in the active site—within close proximity to and in line with the incoming methyl group of SAM—would allow some SET domain proteins to selectively methylate methionine in proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Cell-Free Screening, Production and Animal Testing of a STI-Related Chlamydial Major Outer Membrane Protein Supported in Nanolipoproteins

Background: Vaccine development against Chlamydia, a prevalent sexually transmied infection (STI), is imperative due to its global public health impact. However, significant challenges arise in the production of effective subunit vaccines based on recombinant protein antigens, particularly with membrane proteins like the Major Outer Membrane Protein (MOMP). Methods: Cellfree protein synthesis (CFPS) technology is an aractive approach to address these challenges as a method of high-throughput membrane protein and protein complex production coupled with nanolipoprotein particles (NLPs). NLPs provide a supporting scaffold while allowing easy adjuvant addition during formulation. Over the last decade, we have been working toward the production and characterization of MOMP-NLP complexes for vaccine testing. Results: The work presented here highlights the expression and biophysical analyses, including transmission electron microscopy (TEM) and dynamic light scaering (DLS), which confirm the formation and functionality of MOMP-NLP complexes for use in animal studies. Moreover, immunization studies in preclinical models compare the past and present protective efficacy of MOMP-NLP formulations, particularly when co-adjuvanted with CpG and FSL1. Conclusion: Ex vivo assessments further highlight the immunomodulatory effects of MOMP-NLP vaccinations, emphasizing their potential to elicitrobust immune responses. However, further research is warranted to optimize vaccine formulations further, validate efficacy against Chlamydia trachomatis, and beer understand the underlying mechanisms of immune response.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2003

Complex formation by the human Rad51B and Rad51C DNA repair proteins and their activities in vitro

The human Rad51 protein is essential for DNA repair by homologous recombination. In addition to Rad51 protein, five paralogs have been identified: Rad51B/Rad51L1, Rad51C/Rad51L2, Rad51D/Rad51L3, XRCC2, and XRCC3. To further characterize a subset of these proteins, recombinant Rad51, Rad51B-(His)(6), and Rad51C proteins were individually expressed employing the baculovirus system, and each was purified from Sf9 insect cells. Evidence from nickel-nitrilotriacetic acid pull-down experiments demonstrates a highly stable Rad51B.Rad51C heterodimer, which interacts weakly with Rad51. Rad51B and Rad51C proteins were found to bind single- and double-stranded DNA and to preferentially bind 3'-end-tailed double-stranded DNA. The ability to bind DNA was elevated with mixed Rad51 and Rad51C, as well as with mixed Rad51B and Rad51C, compared with that of the individual protein. In addition, both Rad51B and Rad51C exhibit DNA-stimulated ATPase activity. Rad51C displays an ATP-independent apparent DNA strand exchange activity, whereas Rad51B shows no such activity; this apparent strand exchange ability results actually from a duplex DNA destabilization capability of Rad51C. By analogy to the yeast Rad55 and Rad57, our results suggest that Rad51B and Rad51C function through interactions with the human Rad51 recombinase and play a crucial role in the homologous recombinational repair pathway.

Non-NASA Center↗

NASA NTRS1992

Identification of a nuclear localization sequence in the polyomavirus capsid protein VP2

A nuclear localization signal (NLS) has been identified in the C-terminal (Glu307-Glu-Asp-Gly-Pro-Gln-Lys-Lys-Lys-Arg-Arg-Leu318) amino acid sequence of the polyomavirus minor capsid protein VP2. The importance of this amino acid sequence for nuclear transport of newly synthesized VP2 was demonstrated by a genetic "subtractive" study using the constructs pSG5VP2 (expressing full-length VP2) and pSG5 delta 3VP2 (expressing truncated VP2, lacking amino acids Glu307-Leu318). These constructs were transfected into COS-7 cells, and the intracellular localization of the VP2 protein was determined by indirect immunofluorescence. These studies revealed that the full-length VP2 was localized in the nucleus, while the truncated VP2 protein was localized in the cytoplasm and not transported to the nucleus. A biochemical "additive" approach was also used to determine whether this sequence could target nonnuclear proteins to the nucleus. A synthetic peptide identical to VP2 amino acids Glu307-Leu318 was cross-linked to the nonnuclear proteins bovine serum albumin (BSA) or immunoglobulin G (IgG). The conjugates were then labeled with fluorescein isothiocyanate and microinjected into the cytoplasm of NIH 3T6 cells. Both conjugates localized in the nucleus of the microinjected cells, whereas unconjugated BSA and IgG remained in the cytoplasm. Taken together, these genetic subtractive and biochemical additive approaches have identified the C-terminal sequence of polyoma-virus VP2 (containing amino acids Glu307-Leu318) as the NLS of this protein.

Non-NASA Center↗

DOE OSTI2024

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis

A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes. Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups. A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe. Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Abstract Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter‐chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and performed very well in estimating the global structure accuracy of assembly models. The average per‐target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per‐target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analyzed. The results demonstrate that combining the multi‐model method (PSS) with the complementary single‐model method (ICPS) is a promising approach to EMA.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Computation-guided optimization of split protein systems

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute, even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. Furthermore, this new technology will streamline the generation and use of split protein systems for diverse applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A large accessory protein interactome is rewired across environments

To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in the yeast Saccharomyces cerevisiae across 9 growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a 3-fold increase over PPIs identified in one condition. A few 'immutable' PPIs are present across all conditions, while most 'mutable' PPIs are rarely observed. Immutable PPIs aggregate into highly connected 'core' network modules, with most network remodeling occurring within a loosely connected 'accessory' module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Generative design of de novo proteins based on secondary-structure constraints using an attention-based diffusion model

We report two generative deep-learning models that predict amino acid sequences and 3D protein structures on the basis of secondary-structure design objectives via either the overall content or the per-residue structure. Both models are robust regarding imperfect inputs and offer de novo design capacity because they can discover new protein sequences not yet discovered from natural mechanisms or systems. The residue-level secondary-structure design model generally yields higher accuracy and more diverse sequences. These findings suggest unexplored opportunities for protein designs and functional outcomes within the vast amino acid sequences beyond known proteins. Our models, based on an attention-based diffusion model and trained on a dataset extracted from experimentally known 3D protein structures, offer numerous downstream applications in the conditional generative design of various biological or engineering systems. Future work could include additional conditioning and an exploration of other functional properties of the generated proteins for various properties beyond structural objectives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Simplification of the purification of heat stable recombinant low molecular weight proteins and peptides from GST-fusion products

The synthesis and purification of peptides of importance in the fields of research and medicine continue to be a challenging task. Chemical synthesis of oligopeptides, especially those greater than 25 amino acids, is cost prohibitive. On the other hand, several bottlenecks exist in the production of recombinant short peptides in heterologous expression hosts such as Escherichia coli (E. coli). In this paper, a rapid, cost-effective, and reliable method for the production and singlestep-purification of peptides and small proteins was developed. Five peptides and small proteins were overexpressed in E. coli as GST-fusion products in high yields. The recombinant peptides or proteins were successfully purified after enzymatic cleavage with selective heat-induced precipitation of the GST-affinity tag. Qualitative and quantitative analysis using SDS-PAGE and mass spectrometric methods suggest that the recombinant peptides/ proteins were purified to >95% homogeneity. Results of biophysical experiments, including multi-dimensional NMR spectroscopy, show that the purified proteins/ peptides retain their native conformation. Isothermal titration calorimetry studies indicate no significant change in the binding affinity of the heattreated purified product to their interacting partner(s) compared to the recombinant peptides purified by conventional chromatographic procedures without subjecting to heat treatment. In our opinion, the results reported render the purification of recombinant proteins/ peptides of biomedical relevance using our proposed method easy and reliable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method

Phosphorus (P) is an essential macronutrient for plant growth, but bioavailable P in soils is often limited due to immobilization resulting from pH and geochemical interactions. Understanding the dynamics of P in soils and elucidating the mechanisms by which plants access P from their environment are critical to evaluating productivity, particularly in nutrient poor environments. Phosphorus from organic matter can act as a major source of P for organisms in soil systems. Phosphatases, enzymes that liberate inorganic P from organic sources, are produced by both plants and microbes and are considered one of the most active classes of enzymes in soil. In this work we developed a root blotting method to spatially image phosphatase activity in the rhizosphere. Proteins from the rhizosphere are transferred to a nitrocellulose membrane while retaining their enzymatic activity and two-dimensional spatial distribution. Subsequent application of a fluorogenic phosphatase indicator, DDAO phosphate, enables visualization of the distribution of phosphatase activity in the sample. The proteins can then be fixed to the membrane and treated with a SYPRO® Ruby gel stain, a fluorescent total protein stain, allowing for visualization of total protein distribution. Taken together, the images of phosphatase activity and total protein localization can be mapped back to the root architecture and provide insight into factors affecting the spatial distribution of enzymatic activity and protein accumulation in the rhizosphere. Notably, this method can be applied to plants growing in rhizoboxes containing soil or soilless growth mixtures (e.g., sand or various potting mixes) and, because of the non-destructive nature of this approach, be performed over time to track changes. We anticipate that this fluorescent indicator imaging technique on root blots can be used in diverse plant-microbe-soil systems to better understand the role of phosphatases in P acquisition and soil P cycling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Can protein expression be ‘solved’?

Recombinant protein expression is central to biotechnology’s application in academic exploration as well as human health, climate applications and the bioeconomy in general. However, not all proteins can be expressed in all organisms, and the field lacks a predictive model of soluble protein overexpression that could replace laborious experimental trial-and-error. Here, we discuss the state of the field and identify the lack of large, high-fidelity datasets as the primary bottleneck to progress. We review possible assays that could be used for data collection to identify a path toward an extensible experimental platform for collecting soluble recombinant protein overexpression data across organisms. We suggest that the resulting dataset should be used to train increasingly generalizable predictive models of protein expression to answer the question: “How can predictive protein expression be solved?”.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Protein Vesicles with pH-Responsive Disassembly

We report protein biomaterials offer several advantages over those made from other components because their amino acid sequence can be precisely controlled with genetic engineering to produce a diverse set of material building blocks. In this work, three different elastin-like polypeptide (ELP) sequences were designed to synthesize pH-responsive protein vesicles. ELPs undergo a thermally induced hydrophobic transition that enables self-assembly of different kinds of protein biomaterials. The transition can be tuned by the composition of the guest residue, X, within the ELP pentapeptide repeat unit, VPGXG. When the guest residue is substituted with an ionizable amino acid, such as histidine, the ELP undergoes a pH-dependent hydrophobic phase transition. We used pH-responsive ELPs with different levels of histidine substitution, in combination with leucine zippers and globular, functional proteins, to fabricate protein vesicles. We demonstrate pH-dependent self-assembly, diameter, and disassembly of the vesicles using a combination of turbidimetry, dynamic light scattering, microscopy, and small angle X-ray scattering. As the ELP transition is dependent on the sequence, the vesicle properties also depend on the histidine content in the ELP building blocks. These results demonstrate the tunability of protein vesicles endowed with pH responsiveness, which expands their potential in drug-delivery applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures

Proteins have been found to inhabit a diverse set of three-dimensional structures. The dynamics that govern protein interconversion between structures happen over a wide range of time scales-picoseconds to seconds. Our understanding of protein functions and dynamics is largely reliant upon our ability to elucidate physically populated structures. From an experimental structural characterization perspective, we are often limited to measuring the ensemble-averaged structure both in the steady-state and time-resolved regimes. Generating kinetic models and understanding protein structure–function relationships require atomistic knowledge of the populated states in the ensemble. Here, we present ensemble refinement methodologies that integrate time-resolved experimental signals with molecular dynamics models. We first discuss integration of experimental structural restraints to molecular models in disordered protein systems that adhere to the principle of maximum entropy for creating a complete set of ensemble structures. We then propose strategies to find kinetic pathways between the refined structures, using time-resolved inputs to guide molecular dynamics trajectories and the use of inference to generate tailored stimuli to prepare a desired ensemble of protein states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗