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At least 37 records · Page 2

Data for A Generalized Platform for Artificial Intelligence-powered Autonomous Protein Engineering

Proteins are the molecular machines of life with numerous applications in energy, health, and sustainability. However, engineering proteins with desired functions for practical applications remains slow, expensive, and specialist-dependent. Here we report a generally applicable platform for autonomous enzyme engineering that integrates machine learning and large language models with biofoundry automation to eliminate the need for human intervention, judgement, and domain expertise. Requiring only an input protein sequence and a quantifiable way to measure fitness, this automated platform can be applied to engineer a wide array of proteins. As a proof of concept, we engineer Arabidopsis thaliana halide methyltransferase (AtHMT) for a 90-foldimprovement in substrate preference and 16-fold improvement in ethyl-transferase activity, along with developing a Yersinia mollaretii phytase (YmPhytase) variant with 26-fold improvement in activity at neutral pH. This is accomplished in four rounds over 4 weeks, while requiring construction and characterization of fewer than 500 variants for each enzyme. This platform for autonomous experimentation paves the way for rapid advancements across diverse industries, from medicine and biotechnology to renewable energy and sustainable chemistry.

AI/ML↗

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.

60 APPLIED LIFE SCIENCES↗

Photoactivable analogs for labeling 25-hydroxyvitamin D3 serum binding protein and for 1,25-dihydroxyvitamin D3 intestinal receptor protein

3-Azidobenzoates and 3-azidonitrobenzoates of 25-hydroxyvitamin D3 as well as 3-deoxy-3-azido-25-hydroxyvitamin D3 and 3-deoxy-3-azido-1,25-dihydroxyvitamin D3 were prepared as photoaffinity labels for vitamin D serum binding protein and 1,25-dihydroxyvitamin D3 intestinal receptor protein. The compounds prepared were easily activated by short- or long-wavelength uv light, as monitored by uv and ir spectrometry. The efficacy of the compounds to compete with 25-hydroxyvitamin D3 or 1,25-dihydroxyvitamin D3 for the binding site of serum binding protein and receptor, respectively, was studied to evaluate the vitamin D label with the highest affinity for the protein. The presence of an azidobenzoate or azidonitrobenzoate substituent at the C-3 position of 25-OH-D3 significantly decreased (10(4)- to 10(6)-fold) the binding activity. However, the labels containing the azido substituent attached directly to the vitamin D skeleton at the C-3 position showed a high affinity, only 20- to 150-fold lower than that of the parent compounds with their respective proteins. Therefore, 3-deoxy-3-azidovitamins present potential ligands for photolabeling of vitamin D proteins and for studying the structures of the protein active sites.

NASA Discipline Musculoskeletal↗

The 'tubulin-like' S1 protein of Spirochaeta is a member of the hsp65 stress protein family

A 65-kDa protein (called S1) from Spirochaeta bajacaliforniensis was identified as 'tubulin-like' because it cross-reacted with at least four different antisera raised against tubulin and was isolated, with a co-polymerizing 45-kDa protein, by warm-cold cycling procedures used to purify tubulin from mammalian brain. Furthermore, at least three genera of non-cultivable symbiotic spirochetes (Pillotina, Diplocalyx, and Hollandina) that contain conspicuous 24-nm cytoplasmic tubules displayed a strong fluorescence in situ when treated with polyclonal antisera raised against tubulin. Here we summarize results that lead to the conclusion that this 65-kDa protein has no homology to tubulin. S1 is an hsp65 stress protein homologue. Hsp65 is a highly immunogenic family of hsp60 proteins which includes the 65-kDa antigens of Mycobacterium tuberculosis (an active component of Freund's complete adjuvant), Borrelia, Treponema, Chlamydia, Legionella, and Salmonella. The hsp60s, also known as chaperonins, include E. coli GroEL, mitochondrial and chloroplast chaperonins, the pea aphid 'symbionin' and many other proteins involved in protein folding and the stress response.

NASA Discipline Exobiology↗

Chickpea protein hydrolysate as a novel plant-based cryoprotectant in frozen surimi: Insights into protein structure integrity and gelling behaviors

Chickpea protein (CP) and its enzymatic hydrolysates are one of the most widely consumed pulse ingredients manifesting versatile applications in food industry, such as binders, emulsifiers, and meat protein substitutes. Other than those well-known functionalities, however, the use of CP as a cryoprotectant remained unexplored. Here, in this study, we prepared the chickpea protein hydrolysate (CPH) and investigated its cryoprotective effects to frozen surimi in terms of the protein structure integrity and gelling behaviors. Results indicated that CPH could inhibit myofibrillar protein (MP) denaturation and oxidation during the freeze–thaw cycling, as evidenced by their increased solubility, Ca 2+ -ATPase activity, sulfhydryl concentration, and declined content of disulfide bonds, carbonyl concentration and surface hydrophobicity. Freezing-induced changes on MP secondary structures were also retarded. Moreover, gels prepared from CPH-protected frozen surimi demonstrated more stabilized microstructure, uniform water distribution, enhanced elasticity, gel strength and water holding capacity. The CPH alone, at a reducing addition content of 4% (w/w), exhibited comparable cryoprotective performance to that of the commercial formulation (4% sucrose and 4% sorbitol). Therefore, this study provides scientific insights for development of pulse proteins as novel and high-performance food cryoprotectants.

59 BASIC BIOLOGICAL SCIENCES↗

An Integral Activity-Based Protein Profiling Method for Higher Throughput Determination of Protein Target Sensitivity to Small Molecules

Activity-based protein profiling (ABPP) is a chemoproteomic technique that uses small molecule probes to label active enzymes selectively and covalently in complex proteomes. Competitive ABPP, which involves treatment of the active proteome with an analyte of interest, is especially powerful for profiling how small molecules impact specific protein activities. Advances in higher throughput workflows have made it possible to generate extensive competitive ABPP data across diverse biological samples, making this approach highly appealing for characterizing shared and unique proteins affected by perturbations such as drug or chemical exposures. To use the competitive ABPP approach effectively to understand potential adverse effects of chemicals of concern (CoC), a wide range of concentrations may be needed, particularly for chemicals that lack potency or toxicity data. In this work, we present an integral competitive ABPP method that enables target sensitivity determination for different organophosphate (OP) pesticides as model toxicants. Using previously developed OP-ABPs, we optimized conditions for tandem mass tag (TMT) multiplexing of ABPP samples and compared conventional competitive ABPP involving samples at discrete paraoxon concentrations to pooled samples across that same concentration range. We then expanded our approach to compare protein target sensitivities toward two additional OP pesticides, chlorpyrifos oxon and malaoxon. The results showed that differences in integral intensities for the pooled competition sample can be used to evaluate the relative sensitivity of specific proteins without increasing the overall number of samples. For 8 CoC concentrations of interest, this strategy reduced the number of TMT plexes and the corresponding number of LC–MS/MS analyses 3-fold. In conclusion, we envision the integral ABPP (IABPP) method will provide a means to screen diverse chemicals more rapidly to identify both high and low sensitivity protein targets.

activity-based probes↗

Casein kinase II protein kinase is bound to lamina-matrix and phosphorylates lamin-like protein in isolated pea nuclei

A casein kinase II (CK II)-like protein kinase was identified and partially isolated from a purified envelope-matrix fraction of pea (Pisum sativum L.) nuclei. When [gamma-32P]ATP was directly added to the envelope-matrix preparation, the three most heavily labeled protein bands had molecular masses near 71, 48, and 46 kDa. Protein kinases were removed from the preparation by sequential extraction with Triton X-100, EGTA, 0.3 M NaCl, and a pH 10.5 buffer, but an active kinase still remained bound to the remaining lamina-matrix fraction after these treatments. This kinase had properties resembling CK II kinases previously characterized from animal and plant sources: it preferred casein as an artificial substrate, could use GTP as efficiently as ATP as the phosphoryl donor, was stimulated by spermine, was calcium independent, and had a catalytic subunit of 36 kDa. Some animal and plant CK II kinases have regulatory subunits near 29 kDa, and a lamina-matrix-bound protein of this molecular mass was recognized on immunoblot by anti-Drosophila CK II polyclonal antibodies. Also found associated with the envelope-matrix fraction of pea nuclei were p34cdc2-like and Ca(2+)-dependent protein kinases, but their properties could not account for the protein kinase activity bound to the lamina. The 71-kDa substrate of the CK II-like kinase was lamin A-like, both in its molecular mass and in its cross-reactivity with anti-intermediate filament antibodies. Lamin phosphorylation is considered a crucial early step in the entry of cells into mitosis, so lamina-bound CK II kinases may be important control points for cellular proliferation.

NASA Discipline Plant Biology↗

The Interaction between the DOCK7 Protein and the E2 Protein of Classical Swine Fever Virus Is Not Involved with Viral Replication or Pathogenicity

The classical swine fever virus (CSFV) particle consists of three glycoproteins, all of which have been shown to be important proteins involved in many virus functions, including interaction with several host proteins. One of these proteins, E2, has been shown to be directly involved with adsorption to the host cell and important for virus virulence. Using the yeast two-hybrid system, we have previously shown that CSFV E2 specifically interacts with the (DOCK7) dedicator of cytokinesis, a scaffolding protein. In this report, the interaction between E2 and DOCK7 was evaluated. To confirm the yeast two-hybrid results and to determine that DOCK7 interacts in swine cells with E2, we performed co-immunoprecipitation and proximity ligation assay (PLA). After demonstrating the protein interaction in swine cells, E2 amino acid residues Y65, V283, and T149 were determined to be critical for interaction with Dock7 by using a random mutated library of E2 and a reverse yeast two-hybrid approach. That disruption of these three residues with mutations Y65F, V283D, and T149A abrogated the Dock7-E2 protein interaction. These mutations were then introduced into a recombinant CSFV, E2DOCK7v, by a reverse genomics approach using the highly virulent CSFV Brescia isolate as a backbone. E2DOCKv was shown to have similar growth kinetics in swine primary macrophages and SK6 cell cultures to the parental Brescia strain. Similarly, E2DOCK7v demonstrated a similar level of virulence to the parental Brescia when inoculated in domestic pigs. Animals intranasally inoculated with 10 5 TCID 50 developed a lethal form of clinical disease with virological and hematological kinetics changes indistinguishable from that produced by the parental strain. Therefore, interaction between CSFV E2 and host DOCK7 is not critically involved in the process of virus replication and disease production.

60 APPLIED LIFE SCIENCES↗

Purification method for recombinant proteins based on a fusion between the target protein and the C-terminus of calmodulin

Calmodulin (CaM) was used as an affinity tail to facilitate the purification of the green fluorescent protein (GFP), which was used as a model target protein. The protein GFP was fused to the C-terminus of CaM, and a factor Xa cleavage site was introduced between the two proteins. A CaM-GFP fusion protein was expressed in E. coli and purified on a phenothiazine-derivatized silica column. CaM binds to the phenothiazine on the column in a Ca(2+)-dependent fashion and it was, therefore, used as an affinity tail for the purification of GFP. The fusion protein bound to the affinity column was then subjected to a proteolytic digestion with factor Xa. Pure GFP was eluted with a Ca(2+)-containing buffer, while CaM was eluted later with a buffer containing the Ca(2+)-chelating agent EGTA. The purity of the isolated GFP was verified by SDS-PAGE, and the fluorescence properties of the purified GFP were characterized.

Non-NASA Center↗

Challenges in predicting protein-protein interactions of understudied viruses: Arenavirus-human interactions

Understanding protein-protein interactions (PPIs) between viruses and host organisms is crucial for uncovering infection mechanisms and identifying potential therapeutic targets. The ability to generalize PPI predictive models across understudied viruses presents a significant challenge. In this work, we use arenavirus-human PPIs to illustrate the difficulties associated with model generalization, which are compounded by a lack of both positive and negative data. We employ a Transfer Learning approach to investigate arenavirus-human PPIs by utilizing models trained on better-studied virus-human and human-human PPIs. Additionally, we curate and assess four types of negative sampling datasets to evaluate their impact on model performance. Despite the overall high accuracies (93–99 %) and AUPRC scores (0.8–0.9) appearing promising, further analysis indicates that these performance metrics can be misleading due to data leakage, data bias, and overfitting, especially concerning under-represented viral proteins. We reveal these gaps and assess the impact of data imbalance using standard k-fold cross-validation and Independent Blind Testing with a Balanced Dataset, resulting in a drop in accuracy below 50 %. We propose a viral protein-specific evaluation framework that categorizes viral proteins into majority and minority classes based on their representation in the dataset, enabling comparison of model performance across these groups using balanced accuracies. This framework offers a more robust evaluation of model generalizability, addressing biases inherent in standard evaluation techniques and paving the way for more reliable PPI prediction models for understudied viruses.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting protein functions from redundancies in large-scale protein interaction networks

Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

Proteins/chemistry/metabolism↗

Pooled PPIseq: Screening the SARS-CoV-2 and human interface with a scalable multiplexed protein-protein interaction assay platform

Protein-Protein Interactions (PPIs) are a key interface between virus and host, and these interactions are important to both viral reprogramming of the host and to host restriction of viral infection. In particular, viral-host PPI networks can be used to further our understanding of the molecular mechanisms of tissue specificity, host range, and virulence. At higher scales, viral-host PPI screening could also be used to screen for small-molecule antivirals that interfere with essential viral-host interactions, or to explore how the PPI networks between interacting viral and host genomes co-evolve. Current high-throughput PPI assays have screened entire viral-host PPI networks. However, these studies are time consuming, often require specialized equipment, and are difficult to further scale. Here, we develop methods that make larger-scale viral-host PPI screening more accessible. This approach combines the mDHFR split-tag reporter with the iSeq2 interaction-barcoding system to permit massively-multiplexed PPI quantification by simple pooled engineering of barcoded constructs, integration of these constructs into budding yeast, and fitness measurements by pooled cell competitions and barcode-sequencing. We applied this method to screen for PPIs between SARS-CoV-2 proteins and human proteins, screening in triplicate >180,000 ORF-ORF combinations represented by >1,000,000 barcoded lineages. Our results complement previous screens by identifying 74 putative PPIs, including interactions between ORF7A with the taste receptors TAS2R41 and TAS2R7, and between NSP4 with the transmembrane KDELR2 and KDELR3. We show that this PPI screening method is highly scalable, enabling larger studies aimed at generating a broad understanding of how viral effector proteins converge on cellular targets to effect replication.

60 APPLIED LIFE SCIENCES↗

Expression and purification of recombinant polyomavirus VP2 protein and its interactions with polyomavirus proteins

Recombinant polyomavirus VP2 protein was expressed in Escherichia coli (RK1448), using the recombinant expression system pFPYV2. Recombinant VP2 was purified to near homogeneity by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, electroelution, and Extracti-Gel chromatography. Polyclonal serum to this protein which reacted specifically with recombinant VP2 as well as polyomavirus virion VP2 and VP3 on Western blots (immunoblots) was produced. Purified VP2 was used to establish an in vitro protein-protein interaction assay with polyomavirus structural proteins and purified recombinant VP1. Recombinant VP2 interacted with recombinant VP1, virion VP1, and the four virion histones. Recombinant VP1 coimmunoprecipitated with recombinant VP2 or truncated VP2 (delta C12VP2), which lacked the carboxy-terminal 12 amino acids. These experiments confirmed the interaction between VP1 and VP2 and revealed that the carboxyterminal 12 amino acids of VP2 and VP3 were not necessary for formation of this interaction. In vivo VP1-VP2 interaction study accomplished by cotransfection of COS-7 cells with VP2 and truncated VP1 (delta N11VP1) lacking the nuclear localization signal demonstrated that VP2 was capable of translocating delta N11VP1 into the nucleus. These studies suggest that complexes of VP1 and VP2 may be formed in the cytoplasm and cotransported to the nucleus for virion assembly to occur.

Non-NASA Center↗

Evolution of EF-hand calcium-modulated proteins. IV. Exon shuffling did not determine the domain compositions of EF-hand proteins

In the previous three reports in this series we demonstrated that the EF-hand family of proteins evolved by a complex pattern of gene duplication, transposition, and splicing. The dendrograms based on exon sequences are nearly identical to those based on protein sequences for troponin C, the essential light chain myosin, the regulatory light chain, and calpain. This validates both the computational methods and the dendrograms for these subfamilies. The proposal of congruence for calmodulin, troponin C, essential light chain, and regulatory light chain was confirmed. There are, however, significant differences in the calmodulin dendrograms computed from DNA and from protein sequences. In this study we find that introns are distributed throughout the EF-hand domain and the interdomain regions. Further, dendrograms based on intron type and distribution bear little resemblance to those based on protein or on DNA sequences. We conclude that introns are inserted, and probably deleted, with relatively high frequency. Further, in the EF-hand family exons do not correspond to structural domains and exon shuffling played little if any role in the evolution of this widely distributed homolog family. Calmodulin has had a turbulent evolution. Its dendrograms based on protein sequence, exon sequence, 3'-tail sequence, intron sequences, and intron positions all show significant differences.

NASA Discipline Exobiology↗

Protein–protein interactions between tenascin-R and RPTPζ/phosphacan are critical to maintain the architecture of perineuronal nets

Neural plasticity, the ability to alter the structure and function of neural circuits, varies throughout the age of an individual. The end of the hyperplastic period in the central nervous system coincides with the appearance of honeycomb-like structures called perineuronal nets (PNNs) that surround a subset of neurons. PNNs are a condensed form of neural extracellular matrix that include the glycosaminoglycan hyaluronan and extracellular matrix proteins such as aggrecan and tenascin-R (TNR). PNNs are key regulators of developmental neural plasticity and cognitive functions, yet our current understanding of the molecular interactions that help assemble them remains limited. Disruption of Ptprz1, the gene encoding the receptor protein tyrosine phosphatase RPTPζ, altered the appearance of nets from a reticulated structure to puncta on the surface of cortical neuron bodies in adult mice. The structural alterations mirror those found in Tnr -/- mice, and TNR is absent from the net structures that form in dissociated cultures of Ptprz1 -/- cortical neurons. These findings raised the possibility that TNR and RPTPζ cooperate to promote the assembly of PNNs. Here, we show that TNR associates with the RPTPζ ectodomain and provide a structural basis for these interactions. Furthermore, we show that RPTPζ forms an identical complex with tenascin-C, a homolog of TNR that also regulates neural plasticity. Finally, we demonstrate that mutating residues at the RPTPζ–TNR interface impairs the formation of PNNs in dissociated neuronal cultures. Overall, this work sets the stage for analyzing the roles of protein–protein interactions that underpin the formation of nets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Graph Identification of Proteins in Tomograms (GRIP-Tomo) 2.0: Topologically aware classification for proteins

Cryo-electron tomography (cryo-ET) enables structural characterization of biomolecules under near-native conditions. Existing approaches for interpreting the resulting three-dimensional volumes are computationally expensive and have difficulty interpreting density associated with small proteins/complexes. To explore alternate approaches for identifying proteins in cryo-ET data we pursued a Graph Network and topologically invariant approach. Here, we report on a fast algorithm that classifies particles by searching for nuances of evolutionarily conversed motifs and the geometrical characteristics of protein structure. GRIP-Tomo 2.0 is a machine-learning pipeline that extracts interpretable topological features of protein structures within noisy experimental backgrounds. Compared to version 1.0, the new pipeline includes three upgrades that significantly improve performance including synthetic tomogram generation simulating realistic noise, graph-based persistent feature extraction as protein fingerprints, and high-performance computing acceleration. GRIP-Tomo 2.0 achieves over 90% accuracy in classifying between proteins and noise using both real and synthetic datasets which represents a foundational step toward advancing cryo-ET workflows and empowering automated visual proteomics.

Li, Chengxuan↗

Identification of mosquito proteins that differentially interact with alphavirus nonstructural protein 3, a determinant of vector specificity

Chikungunya virus (CHIKV) and the closely related onyong-nyong virus (ONNV) are arthritogenic arboviruses that have caused significant, often debilitating, disease in millions of people. However, despite their kinship, they are vectored by different mosquito subfamilies that diverged 180 million years ago (anopheline versus culicine subfamilies). Previous work indicated that the nonstructural protein 3 (nsP3) of these alphaviruses was partially responsible for this vector specificity. To better understand the cellular components controlling alphavirus vector specificity, a cell culture model system of the anopheline restriction of CHIKV was developed along with a protein expression strategy. Mosquito proteins that differentially interacted with CHIKV nsP3 or ONNV nsP3 were identified. Six proteins were identified that specifically bound ONNV nsP3, ten that bound CHIKV nsP3 and eight that interacted with both. In addition to identifying novel factors that may play a role in virus/vector processing, these lists included host proteins that have been previously implicated as contributing to alphavirus replication.

Byers, Nathaniel M. (ORCID:0000000157725940)↗