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Results for “binding affinities”

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 OSTI2025

Confinement-controlled selective CO 2 insertion into a dicopper dihydride core: A multiscale mechanistic study

CO 2 is an abundant C 1 feedstock for fuel and chemical synthesis. We have previously demonstrated experimentally a stepwise insertion of CO 2 into a [Cu 2 H 2 ] core via a solid–gas in crystallo reaction, forming formate species that are unstable and inaccessible under solution-phase conditions. This work elucidates how structural confinement within the crystal lattice enables such selective reactivity. In particular, co-crystallized tetrahydrofuran molecules induce site asymmetry around the [Cu 2 H 2 ] unit, modulating both the local electronic environment and CO 2 diffusion pathways. Using a multiscale computational approach that combines classical molecular mechanics, hybrid quantum mechanics/molecular mechanics molecular dynamics, and enhanced-sampling free energy calculations, we demonstrate how site asymmetry affects CO 2 binding affinities and reaction pathways. These results provide detailed mechanistic insight into CO 2 insertion and hydride transfer, highlighting key differences between crystal- and solution-phase pathways and offering a general framework for understanding how lattice confinement shapes chemical reactivity.

Chemical bonding↗
DOE OSTI2020

An isolated water droplet in the aqueous solution of a supramolecular tetrahedral cage

Water under nanoconfinement at ambient conditions has exhibited low-dimensional ice formation and liquid–solid phase transitions, but with structural and dynamical signatures that map onto known regions of water’s phase diagram. Using terahertz (THz) absorption spectroscopy and ab initio molecular dynamics, we have investigated the ambient water confined in a supramolecular tetrahedral assembly, and determined that a dynamically distinct network of 9 ± 1 water molecules is present within the nanocavity of the host. The low-frequency absorption spectrum and theoretical analysis of the water in the Ga 4 L 6 12– host demonstrate that the structure and dynamics of the encapsulated droplet is distinct from any known phase of water. A further inference is that the release of the highly unusual encapsulated water droplet creates a strong thermodynamic driver for the high-affinity binding of guests in aqueous solution for the Ga 4 L 6 12– supramolecular construct.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Enhancing ion transport in charged block copolymers by stabilizing low symmetry morphology: Electrostatic control of interfaces

Recently, the interest in charged polymers has been rapidly growing due to their uses in energy storage and transfer devices. Yet, polymer electrolyte-based devices are not on the immediate horizon because of the low ionic conductivity. In the present study, we developed a methodology to enhance the ionic conductivity of charged block copolymers comprising ionic liquids through the electrostatic control of the interfacial layers. Unprecedented reentrant phase transitions between lamellar and A15 structures were seen, which cannot be explained by well-established thermodynamic factors. X-ray scattering experiments and molecular dynamics simulations revealed the formation of fascinating, thin ionic shell layers composed of ionic complexes. The ionic liquid cations of these complexes predominantly presented near the micellar interfaces if they had strong binding affinity with the charged polymer chains. Therefore, the interfacial properties and concentration fluctuations of the A15 structures were crucially dependent on the type of tethered acid groups in the polymers. Overall, the stabilization energies of the A15 structures were greater when enriched, attractive electrostatic interactions were present at the micellar interfaces. Contrary to the conventional wisdom that block copolymer interfaces act as “dead zone” to significantly deteriorate ion transport, this study establishes a prospective avenue for advanced polymer electrolyte having tailor-made interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Identification of potent inhibitors of JUN N-terminal kinases for treatment of endometriosis and associated pain

Endometriosis, defined as the ectopic growth of endometrial tissue outside of the uterine cavity, is an inflammatory and hormone-dependent disease that causes excruciating pelvic pain, infertility, and significantly decreases quality of life in affected patients. The JUN N-terminal kinases (JNKs) are a leading class of nonhormonal therapeutic targets that have been validated in preclinical models of endometriosis and in a Phase 1/2 clinical trial. Despite their therapeutic potential, JNK inhibitors with increased potency and specificity are needed to address the inflammatory pathology of endometriosis and to prevent disease progression. Leveraging a DNA-encoded chemical library collection of ~4 billion compounds, we identified lead inhibitor CDD-2428 and optimized derivatives, CDD-2728 and CDD-3013, with excellent binding affinity to JNK1-3 (K d = 0.12 to 3.7 nM), enhanced selectivity, metabolic stability, and cellular permeability. Crystallographic and biochemical studies confirmed that CDD-3013 exhibited superior kinase selectivity with improved efficacy compared to existing JNK inhibitors. In primary endometriosis cell models, CDD-2728 and CDD-3013 suppressed JNK-dependent inflammatory signaling, dampening pathways linked to pain, invasion, angiogenesis, and macrophage recruitment. In an endometriosis mouse model, both CDD-2728 and CDD-3013 reduced endometriotic lesion size, macrophage infiltration, and cellular proliferation, showing in vivo efficacy. When tested in a lipopolysaccharide-induced hyperalgesia model, CDD-2728 and CDD-3013 decreased markers of induced pain, as measured by changes in a dynamic weight bearing test and Grimace scores. These findings nominate CDD-2728 and CDD-3013 as potent, nonhormonal therapeutic candidates for endometriosis with broad anti-inflammatory and analgesic activity, addressing a critical unmet clinical need.

Madasu, Chandrashekhar [Department of Pathology an↗
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 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]↗