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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

KPC-2 β-lactamase enables carbapenem antibiotic resistance through fast deacylation of the covalent intermediate

Serine active-site β-lactamases hydrolyze β-lactam antibiotics through the formation of a covalent acyl-enzyme intermediate followed by deacylation via an activated water molecule. Carbapenem antibiotics are poorly hydrolyzed by most β-lactamases owing to slow hydrolysis of the acyl-enzyme intermediate. However, the emergence of the KPC-2 carbapenemase has resulted in widespread resistance to these drugs, suggesting it operates more efficiently. Here, we investigated the unusual features of KPC-2 that enable this resistance. We show that KPC-2 has a 20,000-fold increased deacylation rate compared with the common TEM-1 β-lactamase. Furthermore, kinetic analysis of active site alanine mutants indicates that carbapenem hydrolysis is a concerted effort involving multiple residues. Substitution of Asn170 greatly decreases the deacylation rate, but this residue is conserved in both KPC-2 and non-carbapenemase β-lactamases, suggesting it promotes carbapenem hydrolysis only in the context of KPC-2. X-ray structure determination of the N170A enzyme in complex with hydrolyzed imipenem suggests Asn170 may prevent the inactivation of the deacylating water by the 6α-hydroxyethyl substituent of carbapenems. In addition, the Thr235 residue, which interacts with the C3 carboxylate of carbapenems, also contributes strongly to the deacylation reaction. In contrast, mutation of the Arg220 and Thr237 residues decreases the acylation rate and, paradoxically, improves binding affinity for carbapenems. Thus, the role of these residues may be ground state destabilization of the enzyme-substrate complex or, alternatively, to ensure proper alignment of the substrate with key catalytic residues to facilitate acylation. These findings suggest modifications of the carbapenem scaffold to avoid hydrolysis by KPC-2 β-lactamase.

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

Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody

Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG 1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~200 anti-GCGR IgG 1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2–10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Geometry-complete perceptron networks for 3D molecular graphs

Abstract Motivation The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of traditional machine learning. Within this spirit, in this work, we introduce GCPNet, a new chirality-aware SE(3)-equivariant graph neural network designed for representation learning of 3D biomolecular graphs. We show that GCPNet, unlike previous representation learning methods for 3D biomolecules, is widely applicable to a variety of invariant or equivariant node-level, edge-level, and graph-level tasks on biomolecular structures while being able to (1) learn important chiral properties of 3D molecules and (2) detect external force fields. Results Across four distinct molecular-geometric tasks, we demonstrate that GCPNet’s predictions (1) for protein–ligand binding affinity achieve a statistically significant correlation of 0.608, more than 5%, greater than current state-of-the-art methods; (2) for protein structure ranking achieve statistically significant target-local and dataset-global correlations of 0.616 and 0.871, respectively; (3) for Newtownian many-body systems modeling achieve a task-averaged mean squared error less than 0.01, more than 15% better than current methods; and (4) for molecular chirality recognition achieve a state-of-the-art prediction accuracy of 98.7%, better than any other machine learning method to date. Availability and implementation The source code, data, and instructions to train new models or reproduce our results are freely available at https://github.com/BioinfoMachineLearning/GCPNet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evolutionary engineering reveals amino acid substitutions in Ato2 and Ato3 that allow improved growth of Saccharomyces cerevisiae on lactic acid

ABSTRACT In Saccharomyces cerevisiae, the complete set of proteins involved in transport of lactic acid across the cell membrane has not been determined. In this study, we aimed to identify transport proteins not previously described to be involved in lactic acid transport via a combination of directed evolution, whole-genome resequencing and reverse engineering. Evolution of a strain lacking all known lactic acid transporters on lactate led to the discovery of mutated Ato2 and Ato3 as two novel lactic acid transport proteins. When compared to previously identified S. cerevisiae genes involved in lactic acid transport, expression of ATO3T284C was able to facilitate the highest growth rate (0.15 ± 0.01 h-1) on this carbon source. A comparison between (evolved) sequences and 3D models of the transport proteins showed that most of the identified mutations resulted in a widening of the narrowest hydrophobic constriction of the anion channel. We hypothesize that this observation, sometimes in combination with an increased binding affinity of lactic acid to the sites adjacent to this constriction, are responsible for the improved lactic acid transport in the evolved proteins.

Baldi, Nicolò↗
DOE OSTI2024

Substitution Models of Protein Evolution with Selection on Enzymatic Activity

Abstract Substitution models of evolution are necessary for diverse evolutionary analyses including phylogenetic tree and ancestral sequence reconstructions. At the protein level, empirical substitution models are traditionally used due to their simplicity, but they ignore the variability of substitution patterns among protein sites. Next, in order to improve the realism of the modeling of protein evolution, a series of structurally constrained substitution models were presented, but still they usually ignore constraints on the protein activity. Here, we present a substitution model of protein evolution with selection on both protein structure and enzymatic activity, and that can be applied to phylogenetics. In particular, the model considers the binding affinity of the enzyme–substrate complex as well as structural constraints that include the flexibility of structural flaps, hydrogen bonds, amino acids backbone radius of gyration, and solvent-accessible surface area that are quantified through molecular dynamics simulations. We applied the model to the HIV-1 protease and evaluated it by phylogenetic likelihood in comparison with the best-fitting empirical substitution model and a structurally constrained substitution model that ignores the enzymatic activity. We found that accounting for selection on the protein activity improves the fitting of the modeled functional regions with the real observations, especially in data with high molecular identity, which recommends considering constraints on the protein activity in the development of substitution models of evolution.

Ferreiro, David↗
DOE OSTI2023

Structural basis for cloverleaf RNA-initiated viral genome replication

The genomes of positive-strand RNA viruses serve as a template for both protein translation and genome replication. In enteroviruses, a cloverleaf RNA structure at the 5' end of the genome functions as a switch to transition from viral translation to replication by interacting with host poly(C)-binding protein 2 (PCBP2) and the viral 3CD pro protein. We determined the structures of cloverleaf RNA from coxsackievirus and poliovirus. Cloverleaf RNA folds into an H-type four-way junction and is stabilized by a unique adenosine-cytidine-uridine (A•C-U) base triple involving the conserved pyrimidine mismatch region. The two PCBP2 binding sites are spatially proximal and are located on the opposite end from the 3CD pro binding site on cloverleaf. We determined that the A•C-U base triple restricts the flexibility of the cloverleaf stem–loops resulting in partial occlusion of the PCBP2 binding site, and elimination of the A•C-U base triple increases the binding affinity of PCBP2 to the cloverleaf RNA. Based on the cloverleaf structures and biophysical assays, we propose a new mechanistic model by which enteroviruses use the cloverleaf structure as a molecular switch to transition from viral protein translation to genome replication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Crystal structure of MutYX: a novel clusterless adenine DNA glycosylase with a distinct C-terminal domain and 8-oxoguanine recognition sphere

Abstract The [4Fe–4S] cluster is an important cofactor of the base excision repair (BER) adenine DNA glycosylase MutY to prevent mutations associated with 8-oxoguanine (OG). Several MutYs lacking the [4Fe–4S] cofactor have been identified. Phylogenetic analysis shows that clusterless MutYs are distributed in two clades suggesting cofactor loss has occurred in multiple independent evolutionary events. Herein, we determined the first crystal structure of a clusterless MutY complexed with DNA. On the basis of the dramatic structural divergence from canonical MutYs, we refer to this as representative of a clusterless MutY subgroup “MutYX.” Interestingly, MutYX compensates for the missing [4Fe–4S] cofactor to maintain positioning of catalytic residues by expanding a pre-existing α-helix and acquisition of a new α-helix. Surprisingly, MutYX also acquired a new C-terminal domain that uniquely recognizes OG using residues Gln201 and Arg209. Adenine glycosylase assays and binding affinity measurements indicate that Arg209 is the primary residue responsible for OG:A lesion specificity, while Gln201 assists by bridging OG and Arg209. Surprisingly, replacement of Arg209 and Gln201 with Ala increased activity toward G:A mismatches. The MutYX structure serves as an example of devolution, capturing structural features required to retain function in the absence of a metal cofactor considered indispensable.

Trasviña-Arenas, Carlos H [University of Californi↗
DOE OSTI2024

Biochemical Characterization of Rice Xylan Biosynthetic Enzymes in Determining Xylan Chain Elongation and Substitutions

Abstract Grass xylan consists of a linear chain of β-1,4-linked xylosyl residues that often form domains substituted only with either arabinofuranose (Araf) or glucuronic acid (GlcA)/methylglucuronic acid (MeGlcA) residues, and it lacks the unique reducing end tetrasaccharide sequence found in dicot xylan. The mechanism of how grass xylan backbone elongation is initiated and how its distinctive substitution pattern is determined remains elusive. Here, we performed biochemical characterization of rice xylan biosynthetic enzymes, including xylan synthases, glucuronyltransferases and methyltransferases. Activity assays of rice xylan synthases demonstrated that they required short xylooligomers as acceptors for their activities. While rice xylan glucuronyltransferases effectively glucuronidated unsubstituted xylohexaose acceptors, they transferred little GlcA residues onto (Araf)-substituted xylohexaoses and rice xylan 3-O-arabinosyltransferase could not arabinosylate GlcA-substituted xylohexaoses, indicating that their intrinsic biochemical properties may contribute to the distinctive substitution patterns of rice xylan. In addition, we found that rice xylan methyltransferase exhibited a low substrate binding affinity, which may explain the partial GlcA methylation in rice xylan. Furthermore, immunolocalization of xylan in xylem cells of both rice and Arabidopsis showed that it was deposited together with cellulose in secondary walls without forming xylan-rich nanodomains. Together, our findings provide new insights into the biochemical mechanisms underlying xylan backbone elongation and substitutions in grass species.

Cell Biology↗
DOE OSTI2023

Structural and functional analysis of two SHMT8 variants associated with soybean cyst nematode resistance

Two amino acid variants in soybean serine hydroxymethyltransferase 8 (SHMT8) are associated with resistance to the soybean cyst nematode (SCN), a devastating agricultural pathogen with worldwide economic impacts on soybean production. SHMT8 is a cytoplasmic enzyme that catalyzes the pyridoxal 5‐phosphate‐dependent conversion of serine and tetrahydrofolate (THF) to glycine and 5,10‐methylenetetrahydrofolate. A previous study of the P130R/N358Y double variant of SHMT8, identified in the SCN‐resistant soybean cultivar (cv.) Forrest, showed profound impairment of folate binding affinity and reduced THF‐dependent enzyme activity, relative to the highly active SHMT8 in cv. Essex, which is susceptible to SCN. Given the importance of SCN‐resistance in soybean agriculture, we report here the biochemical and structural characterization of the P130R and N358Y single variants to elucidate their individual effects on soybean SHMT8. We find that both single variants have reduced THF‐dependent catalytic activity relative to Essex SHMT8 (10‐ to 50‐fold decrease ink cat /K m ) but are significantly more active than the P130R/N368Y double variant. The kinetic data also show that the single variants lack THF‐substrate inhibition as found in Essex SHMT8, an observation with implications for regulation of the folate cycle. Five crystal structures of the P130R and N358Y variants in complex with various ligands (resolutions from 1.49 to 2.30 Å) reveal distinct structural impacts of the mutations and provide new insights into allosterism. Our results support the notion that the P130R/N358Y double variant in Forrest SHMT8 produces unique and unexpected effects on the enzyme, which cannot be easily predicted from the behavior of the individual variants.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Synchrotron x-ray fluorescence analysis reveals diagenetic alteration of fossil melanosome trace metal chemistry

A key feature of the pigment melanin is its high binding affinity for trace metal ions. In modern vertebrates trace metals associated with melanosomes, melanin-rich organelles, can show tissue-specific and taxon-specific distribution patterns. Such signals preserve in fossil melanosomes, informing on the anatomy and phylogenetic affinities of fossil vertebrates. Fossil and modern melanosomes, however, often differ in trace metal chemistry; in particular, melanosomes from fossil vertebrate eyes are depleted in Zn and enriched in Cu relative to their extant counterparts. Whether these chemical differences are biological or taphonomic in origin is unknown, limiting our ability to use melanosome trace metal chemistry to test palaeobiological hypotheses. Here, we use maturation experiments on eye melanosomes from extant vertebrates and synchrotron rapid scan-x-ray fluorescence analysis to show that thermal maturation can dramatically alter melanosome trace element chemistry. In particular, maturation of melanosomes in Cu-rich solutions results in significant depletion of Zn, probably due to low pH and competition effects with Cu. These results confirm fossil melanosome chemistry is susceptible to alteration due to variations in local chemical conditions during diagenesis. Maturation experiments can provide essential data on melanosome chemical taphonomy required for accurate interpretations of preserved chemical signatures in fossils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multigas Adsorption with Single-Site Cooperativity in a Metal-Organic Framework

Cooperative gas adsorption in metal-organic frameworks (MOFs) is a rare phenomenon that generally involves long-range communication between multiple binding sites. We demonstrate a MOF containing cobalt(II)-methyl sites that selectively and reversibly capture two carbon monoxide (CO) molecules per site, leading to record-high adsorption capacities at ambient temperatures and pressures. Gas adsorption and structural, spectroscopic, and computational analyses support a mechanism in which binding of one CO molecule triggers a spin transition, followed by binding of a second CO molecule and migratory insertion of the first CO molecule into the cobalt-methyl bond to form an acetyl. The greater binding affinity associated with the second CO results in sigmoidal adsorption isotherms, a hallmark of cooperativity and phase-change materials, despite the absence of long-range interactions within the framework.

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

3D_MolGNN_RL

3D-MolGNNRL, couples reinforcement learning (RL) to a deep generative model based on 3D-Scaffold to generate target candidates specific to a protein pocket building up atom by atom from the core scaffold. 3D-MolGNNRL provides an efficient way to optimize key features within a protein pocket using a parallel graph neural network model. The agent learns to build molecules in 3D space while optimizing the binding affinity, potency, and synthetic accessibility of the candidates generated for the SARS-CoV-2 Main protease

Kumar, Neeraj↗
DOE OSTI2024

BIORAD

Machine learning prediction of protein-protein binding affinity

Gans, Jason [Los Alamos National Laboratory]↗
DOE OSTI2025

fast3

Code to train neural network models for binding affinity prediction

Kim, Hyojin [Lawrence Livermore National Laborator↗
DOE OSTI2020

iPNHOT: a knowledge-based approach for identifying protein-nucleic acid interaction hot spots

The interaction between proteins and nucleic acids plays pivotal roles in various biological processes such as transcription, translation, and gene regulation. Hot spots are a small set of residues that contribute most to the binding affinity of a protein-nucleic acid interaction. Compared to the extensive studies of the hot spots on protein-protein interfaces, the hot spot residues within protein-nucleic acids interfaces remain less well-studied, in part because mutagenesis data for protein-nucleic acids interaction are not as abundant as that for protein-protein interactions. In this study, we built a new computational model, iPNHOT, to effectively predict hot spot residues on protein-nucleic acids interfaces. One training data set and an independent test set were collected from dbAMEPNI and some recent literature, respectively. To build our model, we generated 97 different sequential and structural features and used a two-step strategy to select the relevant features. The final model was built based only on 7 features using a support vector machine (SVM). The features include two unique features such as ΔSASsa 1/2 and esp3, which are newly proposed in this study. Based on the cross validation results, our model gave F1 score and AUROC as 0.725 and 0.807 on the subset collected from ProNIT, respectively, compared to 0.407 and 0.670 of mCSM-NA, a state-of-the art model to predict the thermodynamic effects of protein-nucleic acid interaction. The iPNHOT model was further tested on the independent test set, which showed that our model outperformed other methods. Here, by collecting data from a recently published database dbAMEPNI, we proposed a new model, iPNHOT, to predict hotspots on both protein-DNA and protein-RNA interfaces. The results show that our model outperforms the existing state-of-art models. Our model is available for users through a webserver: http://zhulab.ahu.edu.cn/iPNHOT/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Microscale thermophoresis as a powerful tool for screening glycosyltransferases involved in cell wall biosynthesis

Background: Identification and characterization of key enzymes associated with cell wall biosynthesis and modification is fundamental to gain insights into cell wall dynamics. However, it is a challenge that activity assays of glycosyltransferases are very low throughput and acceptor substrates are generally not available. Results: We optimized and validated microscale thermophoresis (MST) to achieve high throughput screening for glycosyltransferase substrates. MST is a powerful method for the quantitative analysis of protein-ligand interactions with low sample consumption. The technique is based on the motion of molecules along local temperature gradients, measured by fluorescence changes. We expressed glycosyltransferases as YFP-fusion proteins in tobacco and optimized the MST method to allow the determination of substrate binding affinity without purification of the target protein from the cell lysate. The application of this MST method to the β-1,4-galactosyltransferase AtGALS1 validated the capability to screen both nucleotide-sugar donor substrates and acceptor substrates. We also expanded the application to members of glycosyltransferase family GT61 in sorghum for substrate screening and function prediction. Conclusions: This method is rapid and sensitive to allow determination of both donor and acceptor substrates of glycosyltransferases. MST enables high throughput screening of glycosyltransferases for likely substrates, which will narrow down their in vivo function and help to select candidates for further studies. Additionally, this method gives insight into biochemical mechanism of glycosyltransferase function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Adaptive language model training for molecular design

Abstract The vast size of chemical space necessitates computational approaches to automate and accelerate the design of molecular sequences to guide experimental efforts for drug discovery. Genetic algorithms provide a useful framework to incrementally generate molecules by applying mutations to known chemical structures. Recently, masked language models have been applied to automate the mutation process by leveraging large compound libraries to learn commonly occurring chemical sequences (i.e., using tokenization) and predict rearrangements (i.e., using mask prediction). Here, we consider how language models can be adapted to improve molecule generation for different optimization tasks. We use two different generation strategies for comparison, fixed and adaptive. The fixed strategy uses a pre-trained model to generate mutations; the adaptive strategy trains the language model on each new generation of molecules selected for target properties during optimization. Our results show that the adaptive strategy allows the language model to more closely fit the distribution of molecules in the population. Therefore, for enhanced fitness optimization, we suggest the use of the fixed strategy during an initial phase followed by the use of the adaptive strategy. We demonstrate the impact of adaptive training by searching for molecules that optimize both heuristic metrics, drug-likeness and synthesizability, as well as predicted protein binding affinity from a surrogate model. Our results show that the adaptive strategy provides a significant improvement in fitness optimization compared to the fixed pre-trained model, empowering the application of language models to molecular design tasks.

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

Unraveling the mechanism of recognition of the 3’ splice site of the adenovirus major late promoter intron by the alternative splicing factor PUF60

Pre-mRNA splicing is critical for achieving required amounts of a transcript at a given time and for regulating production of encoded protein. A given pre-mRNA may be spliced in many ways, or not at all, giving rise to multiple gene products. Numerous splicing factors are recruited to pre-mRNA splice sites to ensure proper splicing. One such factor, the 60 kDa poly(U)-binding splicing factor (PUF60), is recruited to sites that are not always spliced, but rather function as alternative splice sites. In this study, we characterized the interaction of PUF60 with a splice site from the adenovirus major late promoter (the AdML 3' splice site, AdML3’). We found that the PUF60–AdML3’ dissociation constants are in the micromolar range, with the binding affinity predominantly provided by PUF60’s two central RNA recognition motifs (RRMs). A 1.95 Å crystal structure of the two PUF60 RRMs in complex with AdML3’ revealed a dimeric organization placing two stretches of nucleic acid tracts in opposing directionalities, which can cause looping of nucleic acid and explain how PUF60 affects pre-mRNA geometry to effect splicing. Solution characterization of this complex by light-scattering and UV/Vis spectroscopy suggested a potential 2:1 (PUF60 2 :AdML3’) stoichiometry, consistent with the crystal structure. This work defines the sequence specificity of the alternative splicing factor PUF60 at the pre-mRNA 3’ splice site. Our observations suggest that control of pre-mRNA directionality is important in the early stage of spliceosome assembly, and advance our understanding of the molecular mechanism by which alternative and constitutive splicing factors differentiate among 3’ splice sites.

59 BASIC BIOLOGICAL SCIENCES↗