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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nucleic acid binding by SAMHD1 contributes to the antiretroviral activity and is enhanced by the GpsN modification

SAMHD1 impedes infection of myeloid cells and resting T lymphocytes by retroviruses, and the enzymatic activity of the protein—dephosphorylation of deoxynucleotide triphosphates (dNTPs)—implicates enzymatic dNTP depletion in innate antiviral immunity. Here we show that the allosteric binding sites of the enzyme are plastic and can accommodate oligonucleotides in place of the allosteric activators, GTP and dNTP. SAMHD1 displays a preference for oligonucleotides containing phosphorothioate bonds in the Rp configuration located 3’ to G nucleotides (GpsN), the modification pattern that occurs in a mechanism of antiviral defense in prokaryotes. In the presence of GTP and dNTPs, binding of GpsN-containing oligonucleotides promotes formation of a distinct tetramer with mixed occupancy of the allosteric sites. Mutations that impair formation of the mixed-occupancy complex abolish the antiretroviral activity of SAMHD1, but not its ability to deplete dNTPs. The findings link nucleic acid binding to the antiretroviral activity of SAMHD1, shed light on the immunomodulatory effects of synthetic phosphorothioated oligonucleotides and raise questions about the role of nucleic acid phosphorothioation in human innate immunity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Crystallization of ApoA1 and ApoE4 Nanolipoprotein Particles and Initial XFEL-Based Structural Studies

Nanolipoprotein particles (NLPs), also called “nanodiscs”, are discoidal particles with a patch of lipid bilayer corralled by apolipoproteins. NLPs have long been of interest due to both their utility as membrane-model systems into which membrane proteins can be inserted and solubilized and their physiological role in lipid and cholesterol transport via high-density lipoprotein (HDL) and low-density lipoprotein (LDL) maturation, which are important for human health. Serial femtosecond crystallography (SFX) at X-ray free electron lasers (XFELs) is a powerful approach for structural biology of membrane proteins, which are traditionally difficult to crystallize as large single crystals capable of producing high-quality diffraction suitable for structure determination. To facilitate understanding of the specific role of two apolipoprotein/lipid complexes, ApoA1 and ApoE4, in lipid binding and HDL/LDL particle maturation dynamics, and to develop new SFX methods involving NLP membrane protein encapsulation, we have prepared and crystallized homogeneous populations of ApoA1 and ApoE4 NLPs. Crystallization of empty NLPs yields semi-ordered objects that appear crystalline and give highly anisotropic and diffuse X-ray diffraction, similar to fiber diffraction. Several unit cell parameters were approximately determined for both NLPs from these measurements. Thus, low-background, sample conservative methods of delivery are critical. Here we implemented a fixed target sample delivery scheme utilizing the Roadrunner fast-scanning system and ultra-thin polymer/graphene support films, providing a low-volume, low-background approach to membrane protein SFX. This study represents initial steps in obtaining structural information for ApoA1 and ApoE4 NLPs and developing this system as a supporting scaffold for future structural studies of membrane proteins crystalized in a native lipid environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Superoxide Dismutase 1 Folding Stability as a Target for Molecular Tweezers in SOD1-Related Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation are hallmarks of many severe neurodegenerative diseases including Alzheimer's, Parkinson's and Huntington's disease. As a supramolecular ligand that binds to lysine and arginine residues, the molecular tweezer CLR01 was found to modify the aggregation pathway of disease-relevant proteins in vitro and in vivo with beneficial effects on toxicity. However, the molecular mechanisms of how tweezers exert these effects remain mainly unknown, hampering further drug development. Here, we investigate the modulation mechanism of unfolding and aggregation pathways of SOD1, which are involved in amyotrophic lateral sclerosis (ALS), by CLR01. Using a truncated version of the wildtype SOD1 protein, SOD1 bar , we show that CLR01 acts on the first step of the aggregation pathway, the unfolding of the SOD1 monomer. CLR01 increases, by ~10 °C, the melting temperatures of the A4V and G41D SOD1 mutants, which are commonly observed mutations in familial ALS. Molecular dynamics simulations and binding free energy calculations as well as native mass spectrometry and mutational studies allowed us to identify K61 and K92 as binding sites for the tweezers to mediate the stability increase. The data suggest that the modulation of SOD1 conformational stability is a promising target for future developments of supramolecular ligands against neurodegenerative diseases.

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

Binding and Translocation of Substrate Allosterically Promotes Functional Interactions Within the AlkB–AlkG Electron Transfer Complex

The alkane monooxygenase AlkB and rubredoxin AlkG form an electron transfer complex that hydroxylates terminal alkanes to produce alcohols. The recent cryoEM study of Fontimonas thermophila AlkB-AlkG complex revealed its architecture, including a dodecane (D12) substrate at the active site. However, FtAlkBG molecular mechanism of action of remains unknown. Here, in this study, we examined its dynamics and interactions by multiscale computations, including molecular dynamics simulations, elastic network models, and QM/MM of the oxygen activation mechanism at the AlkB catalytic site. D12 maintained stable interactions within the catalytic site during two MD runs, coordinated by hydrophobic residues L263-L264, I267, I133. A third extended run revealed that D12 could translocate to a membrane-exposed site near S49/F46 along a hydrophobic channel gated by I54. During this translocation, D12 was temporarily stabilized at intermediate sites IS1 (lined by I27/L30-G31/G50/L53-I54/P59/S124/A127-V128) and IS2 (I33-G34/L37/L45-F46/S49) before nearly exiting the protein, and diffused back to the active site, assisted by L30. Substrate binding and translocation across those intermediate sites affects the coupling between the iron centers in AlkBG, and interfacial interactions between AlkB-AlkG. The channel was further connected to the cytosol, near two surface-exposed arginines, potentially allowing for O 2 passage. The allosteric effects between D12 putative entry site, catalytic site and AlkB-AlkG interface were analyzed by ENM-based methods which confirmed the cooperative perturbation-responses and strongly correlated movements of residues belonging to those distal regions. Our study provides new mechanistic insights into key sites and their interactions that could be targeted for developing AlkB-variants with desirable alkane conversion functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Dual domain recognition determines SARS-CoV-2 PLpro selectivity for human ISG15 and K48-linked di-ubiquitin

The Papain-like protease (PLpro) is a domain of a multi-functional, non-structural protein 3 of coronaviruses. PLpro cleaves viral polyproteins and posttranslational conjugates with poly-ubiquitin and protective ISG15, composed of two ubiquitin-like (UBL) domains. Across coronaviruses, PLpro showed divergent selectivity for recognition and cleavage of posttranslational conjugates despite sequence conservation. We show that SARS-CoV-2 PLpro binds human ISG15 and K48-linked di-ubiquitin (K48-Ub 2 ) with nanomolar affinity and detect alternate weaker-binding modes. Crystal structures of untethered PLpro complexes with ISG15 and K48-Ub 2 combined with solution NMR and cross-linking mass spectrometry revealed how the two domains of ISG15 or K48-Ub 2 are differently utilized in interactions with PLpro. Analysis of protein interface energetics predicted differential binding stabilities of the two UBL/Ub domains that were validated experimentally. We emphasize how substrate recognition can be tuned to cleave specifically ISG15 or K48-Ub 2 modifications while retaining capacity to cleave mono-Ub conjugates. These results highlight alternative druggable surfaces that would inhibit PLpro function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Inhibition of FOXP3 by stapled alpha-helical peptides dampens regulatory T cell function

Despite continuing advances in the development of novel cellular-, antibody-, and chemotherapeutic-based strategies to enhance immune reactivity, the presence of regulatory T cells (Treg cells) remains a complicating factor for their clinical efficacy. To overcome dosing limitations and off-target effects from antibody-based Treg cell deletional strategies or small molecule drugging, we investigated the ability of hydrocarbon stapled alpha-helical (SAH) peptides to target FOXP3, the master transcription factor regulator of Treg cell development, maintenance, and suppressive function. Using the crystal structure of the FOXP3 homodimer as a guide, we developed SAHs in the likeness of a portion of the native FOXP3 antiparallel coiled-coil homodimerization domain (SAH-FOXP3) to block this key FOXP3 protein-protein interaction (PPI) through molecular mimicry. We describe the design, synthesis, and biochemical evaluation of single- and double-stapled SAHs covering the entire coiled-coil expanse. We show that lead SAH-FOXP3s bind FOXP3, are cell permeable and nontoxic to T cells, induce dose-dependent transcript and protein level alterations of FOXP3 target genes, impede Treg cell function, and lead to Treg cell gene expression changes in vivo consistent with FOXP3 dysfunction. These results demonstrate a proof of concept for rationally designed FOXP3-directed peptide therapeutics that could be used as approaches to amplify endogenous immune responsiveness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Synthetic proteins for COVID-19 diagnostics

There is an urgent need for inexpensive, rapid and specific antigen-based assays to test for vaccine efficacy and detect infection with SARS-CoV-2 and its variants. We have identified a small, synthetic protein (JS7), representing a region of maximum variability within the receptor binding domain (RBD), which binds antibodies in sera from nine patients with PCR-verified COVID-19 of varying severity. Antibodies binding to either JS7 or the SARS-CoV-2 recombinant RBD, as well as those that disrupt binding between a fragment of the ACE2 receptor and the RBD, are proportional to disease severity and clinical outcome. Binding to JS7 was inhibited by linear peptides from the RBD interface with ACE2. Variants of JS7, such as E484K or N501Y, can be quickly synthesized in pure form in large quantities by automated methods. JS7 and related synthetic antigens can provide a basis for specific diagnostics for SARS-CoV-2 infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Protein–Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools

The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to significant biological breakthroughs. For example, the study of PPIs involved in the human:SARS-CoV-2 viral infection mechanism aided in the development of the SARS-CoV-2 vaccines. Though several databases exist for the manual curation of PPI networks, text mining methods have been routinely demonstrated as useful alternatives for newly studied or understudied species where databases are incomplete. Here, the relationship extraction (RE) performance of several open-source classical text processing, machine learning (ML)-based natural language processing (NLP), and large language model (LLM)-based NLP tools were compared. Overall, our results indicated that networks derived from classical methods tend to have high true positive rates at the expense of having overconnected-networks, ML-based NLP methods have lower true positive rates but networks with the closest structures to the target network, and LLM-based NLP methods tend to exist in-between the two other approaches, with variable performances. Finally, the selection of a specific NLP approach should be tied to the needs of a study and text availability, as models varied in performance due to the amount of text provided.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Accumulation of Antifreeze Proteins on Ice Is Determined by Adsorption

Antifreeze proteins (AFPs) enable the survival of organisms in freezing environments by binding to ice crystals and suppressing their growth. The rate at which AFPs accumulate on ice is determined by an interplay between their diffusion from the aqueous solution and their adsorption to the ice crystal. To interrogate the relative importance of these two processes, we combined fluorescence experiments with reaction–diffusion modeling. We found that as AFPs accumulate on ice, their concentration in the aqueous solution does not develop a gradient but remains equal to its bulk concentration throughout our experiments. Furthermore, these findings led us to conclude that AFP accumulation on ice crystals, which are smaller than 100 μm in radius, is not limited by the diffusion of AFPs, but by the kinetics of AFP adsorption.

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

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike–antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Science & Technology - Other Topics↗
DOE OSTI2019

Attempts to develop an enzyme converting DHIV to KIV

Abstract Dihydroxy-acid dehydratase (DHAD) catalyzes the dehydration of R-2,3-dihydroxyisovalerate (DHIV) to 2-ketoisovalerate (KIV) using an Fe-S cluster as a cofactor, which is sensitive to oxidation and expensive to synthesize. In contrast, sugar acid dehydratases catalyze the same chemical reactions using a magnesium ion. Here, we attempted to substitute the high-cost DHAD with a cost-efficient engineered sugar acid dehydratase using computational protein design (CPD). First, we tried without success to modify the binding pocket of a sugar acid dehydratase to accommodate the smaller, more hydrophobic DHIV. Then, we used a chemically activated substrate analog to react with sugar acid dehydratases or other enolase superfamily enzymes. Mandelate racemase from Pseudomonas putida (PpManR) and the putative sugar acid dehydratase from Salmonella typhimurium (StPutD) showed beta-elimination activity towards chlorolactate (CLD). CPD combined with medium-throughput selection improved the PpManR kcat/KM for CLD by four-fold. However, these enzyme variants did not show dehydration activity towards DHIV. Lastly, assuming phosphorylation could also be a good activation mechanism, we found that mevalonate-3-kinase (M3K) from Picrophilus torridus (PtM3K) exhibited adenosine triphosphate (ATP) hydrolysis activity when mixed with DHIV, indicating phosphorylation activity towards DHIV. Engineering PpManR or StPutD to accept 3-phospho-DHIV as a substrate was performed, but no variants with the desired activity were obtained.

Oki, Kenji↗
DOE OSTI2020

Molecular characterization of ebselen binding activity to SARS-CoV-2 main protease

There is an urgent need to repurpose drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recent computational-experimental screenings have identified several existing drugs that could serve as effective inhibitors of the virus’ main protease, M pro , which is involved in gene expression and replication. Among these, ebselen (2-phenyl-1,2-benzoselenazol-3-one) appears to be particularly promising. Here, we examine, at a molecular level, the potential of ebselen to decrease Mpro activity. We find that it exhibits a distinct affinity for the catalytic region. Our results reveal a higher-affinity, previously unknown binding site localized between the II and III domains of the protein. A detailed strain analysis indicates that, on such a site, ebselen exerts a pronounced allosteric effect that regulates catalytic site access through surface-loop interactions, thereby inducing a reconfiguration of water hotspots. Together, these findings highlight the promise of ebselen as a repurposed drug against SARS-CoV-2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Retrospective on Recent DOE-Funded Studies Concerning the Extraction of Rare Earth Elements & Lithium from Geothermal Brines (Final Report)

Rare earth elements (REE) and lithium are non-toxic metals that are considered critical materials due to their use in electronics, magnets, batteries, and a wide variety of industrial processes important for the economy and military preparedness. Demand for REE and lithium is increasing and these critical materials are imported, so identifying and exploiting domestic sources of REE and lithium is a national priority. The U.S. Department of Energy (DOE) Geothermal Technologies Office (GTO) has been in the forefront of sponsoring research investigating the potential recovery of REE, lithium, and other critical minerals from geothermal brines. It has been proposed that the future of geothermal energy should include “hybrid systems” that combine electricity generation with other revenue-generating activities, such as recovery of valuable and critical minerals, including REE and lithium. Two recent GTO funding opportunities have focused on the recovery of REE and other valuable minerals from geothermal brines. The research supported by the GTO’s mineral recovery program is focused on three areas: resource characterization, technology for the extraction of REE, and technology for the extraction of lithium (Tables 1 and 2). This report is a retrospective study examining the outcome of GTO’s two recent mineral recovery programs (DE-FOA-0001016 in FY 2014 and DE-FOA-0001376 in FY 2016). In this report, the knowledge, technology, and techniques that were developed by researchers funded by GTO are summarized and discussed. Four projects were funded to assess the concentrations and amounts of REE found in geothermal brines and oil field produced waters. The GTO-funded studies compiled publically available data on REE concentrations from brines and produced water from all over the USA. In addition, new samples were collected and characterized from major geothermal and hydrocarbon basins in the Western USA. The studies examined the relationship between lithology and REE concentrations and developed models examining the influence of geology on REE concentrations in produced brines. It was determined that REE are frequently found at higher concentrations in oil field produced water than geothermal brines, but that some geothermal areas had significant REE resources. Significant reservoirs of REE were identified in the Western USA. In some cases, concentrations of REE were more than 1000 times the concentrations found in seawater. Collectively, these studies represent a comprehensive picture of REE resources associated with geothermal and hydrocarbon systems in the USA. The studies did not examine lithium resources, but in some cases, lithium concentration data was collected. Data from these studies are housed in the Geothermal Data Repository (GDR) and represent a significant information resource and it is recommended that these data be further analyzed in a future study. Eight projects were funded to develop new technology for REE extraction from geothermal fluids. These projects investigated sorption as an approach for removal and recovery of REE from geothermal brines. The projects investigated cutting-edge technology for selective sorption of ions from complex solutions, including the application of metal-organic frameworks and biosorbent proteins. The REE sorption studies tested different combinations of metal-binding ligands and solid supports. The most promising metal-binding ligands for REE included phosphonic acid, thiol, and carboxylic acid functional groups. Ligands were attached or incorporated into a wide variety of solid supports. In most cases, attachment was via covalent bonding to organic resins, polymers, or silica-based supports. Most of the REE projects were conducted at a low technology readiness level (TRL) and showed promise, but direct comparison between technologies was not possible based on the available information. It is recommended that testing and reporting be standardized to the extent possible to facilitate comparisons between technologies. Two projects were directed at novel lithium extraction technology. Both projects investigated the use of inorganic sorbents, including manganese oxides. One study also examined the use of metal- ion imprinted polymers as selective ion-exchange resins for the separation of lithium and manganese from brines. Both approaches showed promise for the selective extraction of lithium from brines, including potentially geothermal brines. Results from these GTO studies indicated that selective REE and lithium extraction is possible, but interference from co-occurring solutes, such as calcium, magnesium, or heavy metals, will interfere with process efficiency and negatively impact process economics. Techno-economic analysis conducted as part of the resource and technology studies suggest extraction of REE from geothermal brines is unlikely to be economically viable, especially since non-geothermal produced waters frequently have higher REE concentrations. It is recommended that benchmarks for techno-economic analysis be established to the extent possible for future studies, to facilitate direct comparison of various technologies. Based on the collective results of this program, it appears that hybrid geothermal power would benefit more from recovery of lithium and other metals, rather than REE. It is recommended that future studies be conducted at a higher- TRL and that sorbents be tested against actual geothermal fluid samples. Prior higher-TRL efforts to extract metals from geothermal brines should be further evaluated for lessons learned.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗
DOE OSTI2025

Different chemical scaffolds bind to L-phe site in Mycobacterium tuberculosis Phe-tRNA synthetase

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mt), is one of the deadliest infectious diseases. The rise of multidrug-resistant strains represents a major public health threat, requiring new therapeutic options. Bacterial aminoacyl-tRNA synthetases (aaRS) have been shown to be highly promising drug targets, including for TB treatment. These enzymes play an essential role in translating the DNA gene code into protein sequence by attaching specific amino acid to their cognate tRNAs. They have multiple binding sites that can be targeted for inhibitor discovery: amino acid binding pocket, ATP binding pocket, tRNA binding site and an editing domain. Recently we reported several high-resolution structures of M. tuberculosis phenylalanyl-tRNA synthetase (MtPheRS) complexed with tRNA Phe and either L-Phe or a nonhydrolyzable phenylalanine adenylate analog. Here, in this study, using Nucleic Magnetic Resonance (NMR) and Surface Plasmon Resonance (SPR) we identified fragments that bind to MtPheRS and we determined crystal structures of their complexes with MtPheRS/tRNA Phe . All the binders interact with the L-Phe amino acid binding site. The analysis of interactions of the new compounds combined with adenylate analog structure provides insights for the rational design of antituberculosis drugs. The 3 ' arm of the tRNA Phe in all the structures was disordered with exception of one complex with D-735 compound. In this structure the 3' CCA end of the acceptor stem is observed in the editing domain of MtPheRS providing insights regarding the post-transfer editing activity of class II aaRS.

Gade, Priyanka [Univ. of Chicago, IL (United State↗