Toward implementing virtual control groups in nonclinical safety studies.

Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the homogeneity of the animal collectives it has been proposed to use the historical data for building so-called virtual control groups, which could replace partly or entirely the concurrent control. This would constitute a substantial contribution to the reduction of animal use in safety studies. Before the concept can be implemented, the prerequisites regarding data collection, curation and statistical evaluation together with a validation strategy need to be identified to avoid any impairment of the study outcome and subsequent consequences for human risk assessment. To further assess and develop the concept of virtual control groups the transatlantic think tank for toxicology (t4) sponsored a workshop with stakeholders from the pharmaceutical and chemical industry, academia, FDA, pharmaceutical, contract research organizations (CROs), and non-governmental organizations in Washington, which took place in March 2023. This report summarizes the current efforts of a European initiative to share, collect and curate animal control data in a centralized database and the first approaches to identify optimal matching criteria between virtual controls and the treatment arms of a study as well as first reflections about strategies for a qualification procedure and potential pitfalls of the concept.

Animal safety studies are usually performed with three groups of animals where increasing amounts of the test chemical are given to the animals and one control group where the animals do not receive the test chemical. The design of such studies, the characteristics of the animals, and the measured parameters are often very similar from study to study. Therefore, it has been suggested that measurement data from the control groups could be reused from study to study to lower the total number of animals per study. This could reduce animal use by up to 25% for such standardized studies. A workshop was held to discuss the pros and cons of such a concept and what would have to be done to implement it without threatening the reliability of the study outcome or the resulting human risk assessment.

Using in silico tools to predict flame retardant metabolites for more informative exposomics-based approaches.

Introduction: The positive identification of xenobiotics and their metabolites in human biosamples is an integral aspect of exposomics research, yet challenges in compound annotation and identification continue to limit the feasibility of comprehensive identification of total chemical exposure. Nonetheless, the adoption of in silico tools such as metabolite prediction software, QSAR-ready structural conversion workflows, and molecular standards databases can aid in identifying novel compounds in untargeted mass spectral investigations, permitting the assessment of a more expansive pool of compounds for human health hazard. This strategy is particularly applicable when it comes to flame retardant chemicals. The population is ubiquitously exposed to flame retardants, and evidence implicates some of these compounds as developmental neurotoxicants, endocrine disruptors, reproductive toxicants, immunotoxicants, and carcinogens. However, many flame retardants are poorly characterized, have not been linked to a definitive mode of toxic action, and are known to share metabolic breakdown products which may themselves harbor toxicity. As U.S. regulatory bodies begin to pursue a subclass- based risk assessment of organohalogen flame retardants, little consideration has been paid to the role of potentially toxic metabolites, or to expanding the identification of parent flame retardants and their metabolic breakdown products in human biosamples to better inform the human health hazards imposed by these compounds. Methods: The purpose of this study is to utilize publicly available in silico tools to 1) characterize the structural and metabolic fates of proposed flame retardant classes, 2) predict first pass metabolites, 3) ascertain whether metabolic products segregate among parent flame retardant classification patterns, and 4) assess the existing coverage in of these compounds in mass spectral database. Results: We found that flame retardant classes as currently defined by the National Academies of Science, Engineering and Medicine (NASEM) are structurally diverse, with highly variable predicted pharmacokinetic properties and metabolic fates among member compounds. The vast majority of flame retardants (96%) and their predicted metabolites (99%) are not present in spectral databases, posing a challenge for identifying these compounds in human biosamples. However, we also demonstrate the utility of publicly available in silico methods in generating a fit for purpose synthetic spectral library for flame retardants and their metabolites that have yet to be identified in human biosamples. Discussion: In conclusion, exposomics studies making use of fit-for-purpose synthetic spectral databases will better resolve internal exposure and windows of vulnerability associated with complex exposures to flame retardant chemicals and perturbed neurodevelopmental, reproductive, and other associated apical human health impacts.

The Good, The Bad, and The Perplexing: Structural Alerts and Read-Across for Predicting Skin Sensitization Using Human Data.

In our earlier work (Golden et al., 2021), we showed 70-80% accuracies for several skin sensitization computational tools using human data. Here, we expanded the data set using the NICEATM human skin sensitization database to create a final data set of 1355 discrete chemicals (largely negative, ∼70%). Using this expanded data set, we analyzed model performance and evaluated mispredictions using Toxtree (v 3.1.0), OECD QSAR Toolbox (v 4.5), VEGA's (1.2.0 BETA) CAESAR (v 2.1.7), and a k-nearest-neighbor (kNN) classification approach. We show that the accuracy on this data set was lower than previous estimates, with balanced accuracies being 63% and 65% for Toxtree and OECD QSAR Toolbox, respectively, 46% for VEGA, and 59% for a kNN approach, with the lower accuracy likely due to the higher percentage of nonsensitizing chemicals. Two hundred eighty seven chemicals were mispredicted by both Toxtree and OECD QSAR Toolbox, which was approximately 20% of the entire data set, and 84% of these were false positives. The absence or presence of metabolic simulation in OECD QSAR Toolbox made no overall difference. While Toxtree is known for overpredicting, 60% of the chemicals in the data set had no alert for skin sensitization, and a substantial number of these chemicals were in fact sensitizers, pointing to sensitization mechanisms not recognized by Toxtree. Interestingly, we observed that chemicals with more than one Toxtree alert were more likely to be nonsensitizers. Finally, a kNN approach tended to mispredict different chemicals than either OECD QSAR Toolbox or Toxtree, suggesting that there was additional information to be garnered from a kNN approach. Overall, the results demonstrate that while there is merit in structural alerts as well as QSAR or read-across approaches (perhaps even more so in their combination), additional improvement will require a more nuanced understanding of mechanisms of skin sensitization.

Darting across space and time: parametric modulators of sex-biased conditioned fear responses.

Pavlovian fear conditioning is a widely used behavioral paradigm for studying associative learning in rodents. Despite early recognition that subjects may engage in a variety of both conditioned and unconditioned responses, the last several decades have seen the field narrow its focus to measure freezing as the sole indicator of conditioned fear. We previously reported that female rats were more likely than males to engage in darting, an escape-like conditioned response that is associated with heightened shock reactivity. To determine how experimental parameters contribute to the frequency of darting in both males and females, we manipulated factors such as chamber size, shock intensity, and number of trials. To better capture fear-related behavioral repertoires in our animals, we developed ScaredyRat, an open-source custom Python tool that analyzes Noldus Ethovision-generated raw data files to identify darters and quantify both conditioned and unconditioned responses. We found that, like freezing, conditioned darting occurrences scale with experimental alterations. While most darting occurs in females, we found that with an extended training protocol, darting can emerge in males as well. Collectively, our data suggest that darting reflects a behavioral switch in conditioned responding that is a product of an individual animal's sex, shock reactivity, and experimental parameters, underscoring the need for careful consideration of sex as a biological variable in classic learning paradigms.

Probabilistic risk assessment - the keystone for the future of toxicology.

Safety sciences must cope with uncertainty of models and results as well as information gaps. Acknowledging this uncer-tainty necessitates embracing probabilities and accepting the remaining risk. Every toxicological tool delivers only probable results. Traditionally, this is taken into account by using uncertainty / assessment factors and worst-case / precautionary approaches and thresholds. Probabilistic methods and Bayesian approaches seek to characterize these uncertainties and promise to support better risk assessment and, thereby, improve risk management decisions. Actual assessments of uncertainty can be more realistic than worst-case scenarios and may allow less conservative safety margins. Most importantly, as soon as we agree on uncertainty, this defines room for improvement and allows a transition from traditional to new approach methods as an engineering exercise. The objective nature of these mathematical tools allows to assign each methodology its fair place in evidence integration, whether in the context of risk assessment, sys-tematic reviews, or in the definition of an integrated testing strategy (ITS) / defined approach (DA) / integrated approach to testing and assessment (IATA). This article gives an overview of methods for probabilistic risk assessment and their application for exposure assessment, physiologically-based kinetic modelling, probability of hazard assessment (based on quantitative and read-across based structure-activity relationships, and mechanistic alerts from in vitro studies), indi-vidual susceptibility assessment, and evidence integration. Additional aspects are opportunities for uncertainty analysis of adverse outcome pathways and their relation to thresholds of toxicological concern. In conclusion, probabilistic risk assessment will be key for constructing a new toxicology paradigm - probably!

The oncogene AAMDC links PI3K-AKT-mTOR signaling with metabolic reprograming in estrogen receptor-positive breast cancer.

Adipogenesis associated Mth938 domain containing (AAMDC) represents an uncharacterized oncogene amplified in aggressive estrogen receptor-positive breast cancers. We uncover that AAMDC regulates the expression of several metabolic enzymes involved in the one-carbon folate and methionine cycles, and lipid metabolism. We show that AAMDC controls PI3K-AKT-mTOR signaling, regulating the translation of ATF4 and MYC and modulating the transcriptional activity of AAMDC-dependent promoters. High AAMDC expression is associated with sensitization to dactolisib and everolimus, and these PI3K-mTOR inhibitors exhibit synergistic interactions with anti-estrogens in IntClust2 models. Ectopic AAMDC expression is sufficient to activate AKT signaling, resulting in estrogen-independent tumor growth. Thus, AAMDC-overexpressing tumors may be sensitive to PI3K-mTORC1 blockers in combination with anti-estrogens. Lastly, we provide evidence that AAMDC can interact with the RabGTPase-activating protein RabGAP1L, and that AAMDC, RabGAP1L, and Rab7a colocalize in endolysosomes. The discovery of the RabGAP1L-AAMDC assembly platform provides insights for the design of selective blockers to target malignancies having the AAMDC amplification.

Avoiding Regrettable Substitutions: Green Toxicology for Sustainable Chemistry.

Green chemistry seeks to design less hazardous chemicals, but many of the efforts to replace chemicals have resulted in so-called "Regrettable Substitutions", when a chemical with an unknown or unforeseen hazard is used to replace a chemical identified as problematic. Here, we discuss the literature on regrettable substitution and focus on an oft-mentioned case, Bisphenol A, which was replaced with Bisphenol S-and the lessons that can be learned from this history. In particular, we focus on how Green Toxicology can offer a way to make better substitutions.

Evaluation of the global performance of eight in silico skin sensitization models using human data.

Allergic contact dermatitis, or the clinical manifestation of skin sensitization, is a leading occupational hazard. Several testing approaches exist to assess skin sensitization, but in silico models are perhaps the most advantageous due to their high speed and low-cost results. Many in silico skin sensitization models exist, though many have only been tested against results from animal studies (e.g., LLNA); this creates uncertainty in human skin sensitization assessments in both a screening and regulatory context. This project's aim was to evaluate the accuracy of eight in silico skin sensitization models against two human data sets: one highly curated (Basketter et al., 2014) and one screening level (HSDB). The binary skin sen­sitization status of each chemical in each of the two data sets was compared to the prediction from eight in silico skin sensitization tools (Toxtree, PredSkin, OECD's QSAR Toolbox, UL's REACHAcross™, Danish QSAR Database, TIMES-SS, and Lhasa Limited's Derek Nexus). Models were assessed for coverage, accuracy, sensitivity, and specificity, as well as optimization features (e.g., probability of accuracy, applicability domain, etc.), if available. While there was a wide range of sensitivity and specificity, the models generally performed comparably to the LLNA in predicting human skin sensitization status (i.e., approximately 70-80% accuracy). Additionally, the models did not mispredict the same com­pounds, suggesting there might be an advantage in combining models. In silico skin sensitization models offer accurate and useful insights in a screening context; however, further improvements are necessary so these models may be con­sidered fully reliable for regulatory applications.

Mapping Chemical Respiratory Sensitization: How Useful Are Our Current Computational Tools?

Chemical respiratory sensitization is an immunological process that manifests clinically mostly as occupational asthma and is responsible for 1 in 6 cases of adult asthma, although this may be an underestimate of the prevalence, as it is under-diagnosed. Occupational asthma results in unemployment for roughly one-third of those affected due to severe health issues. Despite its high prevalence, chemical respiratory sensitization is difficult to predict, as there are currently no validated models and the mechanisms are not entirely understood, creating a significant challenge for regulatory bodies and industry alike. The Adverse Outcome Pathway (AOP) for respiratory sensitization is currently incomplete. However, some key events have been identified, and there is overlap with the comparatively well-characterized AOP for dermal sensitization. Because of this, and the fact that dermal sensitization is often assessed by in vivo, in chemico, or in silico methods, regulatory bodies are defaulting to the dermal sensitization status of chemicals as a proxy for respiratory sensitization status when evaluating chemical safety. We identified a data set of known human respiratory sensitizers, which we used to investigate the accuracy of a structural alert model, Toxtree, designed for skin sensitization and the Centre for Occupational and Environmental Health (COEH)'s model, a model developed specifically for occupational asthma. While both models had a reasonable level of accuracy, the COEH model achieved the highest balanced accuracy at 76%; when the models agreed, the overall accuracy was 87%. There were important differences between the models: Toxtree had superior performance for some structural alerts and some categories of well-characterized skin sensitizers, while the COEH model had high accuracy in identifying sensitizers that lacked identified skin sensitization reactivity domains. Overall, both models achieved respectable accuracy. However, neither model addresses potency, which, along with data quality, remains a hurdle, and the field must prioritize these issues to move forward.

Bidirectional perisomatic inhibitory plasticity of a Fos neuronal network.

Behavioural experiences activate the FOS transcription factor in sparse populations of neurons that are critical for encoding and recalling specific events1-3. However, there is limited understanding of the mechanisms by which experience drives circuit reorganization to establish a network of Fos-activated cells. It is also not known whether FOS is required in this process beyond serving as a marker of recent neural activity and, if so, which of its many gene targets underlie circuit reorganization. Here we demonstrate that when mice engage in spatial exploration of novel environments, perisomatic inhibition of Fos-activated hippocampal CA1 pyramidal neurons by parvalbumin-expressing interneurons is enhanced, whereas perisomatic inhibition by cholecystokinin-expressing interneurons is weakened. This bidirectional modulation of inhibition is abolished when the function of the FOS transcription factor complex is disrupted. Single-cell RNA-sequencing, ribosome-associated mRNA profiling and chromatin analyses, combined with electrophysiology, reveal that FOS activates the transcription of Scg2, a gene that encodes multiple distinct neuropeptides, to coordinate these changes in inhibition. As parvalbumin- and cholecystokinin-expressing interneurons mediate distinct features of pyramidal cell activity4-6, the SCG2-dependent reorganization of inhibitory synaptic input might be predicted to affect network function in vivo. Consistent with this prediction, hippocampal gamma rhythms and pyramidal cell coupling to theta phase are significantly altered in the absence of Scg2. These findings reveal an instructive role for FOS and SCG2 in establishing a network of Fos-activated neurons via the rewiring of local inhibition to form a selectively modulated state. The opposing plasticity mechanisms acting on distinct inhibitory pathways may support the consolidation of memories over time.

Honeybee venom and melittin suppress growth factor receptor activation in HER2-enriched and triple-negative breast cancer.

Despite decades of study, the molecular mechanisms and selectivity of the biomolecular components of honeybee (Apis mellifera) venom as anticancer agents remain largely unknown. Here, we demonstrate that honeybee venom and its major component melittin potently induce cell death, particularly in the aggressive triple-negative and HER2-enriched breast cancer subtypes. Honeybee venom and melittin suppress the activation of EGFR and HER2 by interfering with the phosphorylation of these receptors in the plasma membrane of breast carcinoma cells. Mutational studies reveal that a positively charged C-terminal melittin sequence mediates plasma membrane interaction and anticancer activity. Engineering of an RGD motif further enhances targeting of melittin to malignant cells with minimal toxicity to normal cells. Lastly, administration of melittin enhances the effect of docetaxel in suppressing breast tumor growth in an allograft model. Our work unveils a molecular mechanism underpinning the anticancer selectivity of melittin, and outlines treatment strategies to target aggressive breast cancers.

Rab GTPases: Emerging Oncogenes and Tumor Suppressive Regulators for the Editing of Survival Pathways in Cancer.

The Rab GTPase family of proteins are mediators of membrane trafficking, conferring identity to the cell membranes. Recently, Rab and Rab-associated factors have been recognized as major regulators of the intracellular positioning and activity of signaling pathways regulating cell growth, survival and programmed cell death or apoptosis. Membrane trafficking mediated by Rab proteins is controlled by intracellular localization of Rab proteins, Rab-membrane interactions and GTP-activation processes. Aberrant expression of Rab proteins has been reported in multiple cancers such as lung, brain and breast malignancies. Mutations in Rab-coding genes and/or post-translational modifications in their protein products disrupt the cellular vesicle trafficking network modulating tumorigenic potential, cellular migration and metastatic behavior. Conversely, Rabs also act as tumor suppressive factors inducing apoptosis and inhibiting angiogenesis. Deconstructing the signaling mechanisms modulated by Rab proteins during apoptosis could unveil underlying molecular mechanisms that may be exploited therapeutically to selectively target malignant cells.

Oxidation of cysteine 34 of plasma albumin as a biomarker of oxidative stress.

Introduction: In order to better understand the physiological and pathophysiological roles of reactive oxygen species (ROS), multiple blood and urine biomarkers of oxidative stress have been developed. The single free thiol (Cys34) in plasma albumin is a useful biomarker of oxidative stress because thiol groups are particularly sensitive to oxidation by ROS. The primary aim of this study was to develop a gel electrophoresis-based method (mPEG assay) that would be more widely accessible than existing chromatography techniques to assay the oxidation state of albumin Cys34.Method: Blood samples were collected into a solution containing polyethylene glycol maleimide (malpeg). Plasma samples were divided into two aliquots, with a reducing agent added to one aliquot. Albumin bound to malpeg was separated from albumin by gel electrophoresis. The proportion of albumin in reduced form (-SH), disulphide form (-SSX) and irreversibly oxidised form (-SO2, -SO3) could then be calculated.Results: Data for the mPEG assay was comparable to data from chromatographic and mass spectrometric assays. The mPEG assay was more sensitive than the albumin carbonyl assay for the detection of changes in albumin oxidation level in response to exposure to hydrogen peroxide or hypochlorous acid. This assay could also be performed on small blood samples (less than 10 µL) from fingerprick, thus facilitating longitudinal tracking of changes in albumin Cys34 oxidation level.Conclusion: The mPEG assay is a user-friendly, highly sensitive, specific, cost-effective gel electrophoresis-based method for the assay of the oxidations state of albumin Cys34 as a biomarker of oxidative stress.HighlightsProtein thiol groups are sensitive to oxidation by reactive oxygen species.Plasma albumin contains a reduced cysteine residue (Cys34) sensitive to oxidation.A novel gel electrophoresis-based method (mPEG) has been developed to measure the oxidation state of Cys34.The mPEG assay can be run on a drop of blood collected by fingerprick.

Precision medicine by designer interference peptides: applications in oncology and molecular therapeutics.

In molecular cancer therapeutics only 10% of known cancer gene products are targetable with current pharmacological agents. Major oncogenic drivers, such as MYC and KRAS proteins are frequently highly overexpressed or mutated in multiple human malignancies. However, despite their key role in oncogenesis, these proteins are hard to target with traditional small molecule drugs due to their large, featureless protein interfaces and lack of deep pockets. In addition, they are inaccessible to large biologicals, which are unable to cross cell membranes. Designer interference peptides (iPeps) represent emerging pharmacological agents created to block selective interactions between protein partners that are difficult to target with conventional small molecule chemicals or with large biologicals. iPeps have demonstrated successful inhibition of multiple oncogenic drivers with some now entering clinical settings. However, the clinical translation of iPeps has been hampered by certain intrinsic limitations including intracellular localization, targeting tissue specificity and pharmacological potency. Herein, we outline recent advances for the selective inhibition of major cancer oncoproteins via iPep approaches and discuss the development of multimodal peptides to overcome limitations of the first generations of iPeps. Since many protein-protein interfaces are cell-type specific, this approach opens the door to novel programmable, precision medicine tools in cancer research and treatment for selective manipulation and reprogramming of the cancer cell oncoproteome.

Triple-hit therapeutic approach for triple negative breast cancers using docetaxel nanoparticles, EN1-iPeps and RGD peptides.

Triple negative breast cancers (TNBC) are aggressive malignancies for which chemotherapy is the only treatment option. Many TNBC acquire chemotherapy resistance, notably docetaxel, which has been associated with the overexpression of transcription factors (TFs), such as ENGRAILED1 (EN1). Here, we have developed a tumor delivery system for docetaxel-PGMA-PAA-nanoparticles and interference peptides designed to specifically inhibit EN1 (EN1-iPeps). To promote tumor specific targeting, we functionalized these nanoparticles with EN1-iPeps engineered with RGD sequences. We found that these peptides reduce cell viability and induce apoptosis in TNBC cells with negligible effects on normal cells (EN1-). Moreover, EN1-RGD-iPeps-mediated nanoparticle internalization into breast cancer cells was via integrins and intravenous injection of this nanoformulation increased tumor accumulation. Furthermore, docetaxel nanoparticles functionalized with EN1-RGD-iPeps significantly reduced TNBC growth both in vitro and in vivo without showing toxicity. Our results suggest that this targeted nanoformulation represents a new and safe therapeutic approach for chemoresistant TNBCs.

Tumor penetrating peptides inhibiting MYC as a potent targeted therapeutic strategy for triple-negative breast cancers.

Overexpression of MYC oncogene is highly prevalent in many malignancies such as aggressive triple-negative breast cancers (TNBCs) and it is associated with very poor outcome. Despite decades of research, attempts to effectively inhibit MYC, particularly with small molecules, still remain challenging due to the featureless nature of its protein structure. Herein, we describe the engineering of the dominant-negative MYC peptide (OmoMYC) linked to a functional penetrating 'Phylomer' peptide (FPPa) as a therapeutic strategy to inhibit MYC in TNBC. We found FPPa-OmoMYC to be a potent inducer of apoptosis (with IC50 from 1-2 µM) in TNBC cells with negligible effects in non-tumorigenic cells. Transcriptome analysis of FPPa-OmoMYC-treated cells indicated that the fusion protein inhibited MYC-dependent networks, inducing dynamic changes in transcriptional, metabolic, and apoptotic processes. We demonstrated the efficacy of FPPa-OmoMYC in inhibiting breast cancer growth when injected orthotopically in TNBC allografts. Lastly, we identified strong pharmacological synergisms between FPPa-OmoMYC and chemotherapeutic agents. This study highlights a novel therapeutic approach to target highly aggressive and chemoresistant MYC-activated cancers.

Computational insights for the hydride transfer and distinctive roles of key residues in cholesterol oxidase.

Cholesterol oxidase (ChOx), a member of the glucose-methanol-choline (GMC) family, catalyzes the oxidation of the substrate via a hydride transfer mechanism and concomitant reduction of the FAD cofactor. Unlike other GMC enzymes, the conserved His447 is not the catalytic base that deprotonates the substrate in ChOx. Our QM/MM MD simulations indicate that the Glu361 residue acts as a catalytic base facilitating the hydride transfer from the substrate to the cofactor. We find that two rationally chosen point mutations (His447Gln and His447Asn) cause notable decreases in the catalytic activity. The binding free energy calculations show that the Glu361 and His447 residues are important in substrate binding. We also performed high-level double-hybrid density functional theory simulations using small model systems, which support the QM/MM MD results. Our work provides a basis for unraveling the substrate oxidation mechanism in GMC enzymes in which the conserved histidine does not act as a base.

An extended N-H bond, driven by a conserved second-order interaction, orients the flavin N5 orbital in cholesterol oxidase.

The protein microenvironment surrounding the flavin cofactor in flavoenzymes is key to the efficiency and diversity of reactions catalysed by this class of enzymes. X-ray diffraction structures of oxidoreductase flavoenzymes have revealed recurrent features which facilitate catalysis, such as a hydrogen bond between a main chain nitrogen atom and the flavin redox center (N5). A neutron diffraction study of cholesterol oxidase has revealed an unusual elongated main chain nitrogen to hydrogen bond distance positioning the hydrogen atom towards the flavin N5 reactive center. Investigation of the structural features which could cause such an unusual occurrence revealed a positively charged lysine side chain, conserved in other flavin mediated oxidoreductases, in a second shell away from the FAD cofactor acting to polarize the peptide bond through interaction with the carbonyl oxygen atom. Double-hybrid density functional theory calculations confirm that this electrostatic arrangement affects the N-H bond length in the region of the flavin reactive center. We propose a novel second-order partial-charge interaction network which enables the correct orientation of the hydride receiving orbital of N5. The implications of these observations for flavin mediated redox chemistry are discussed.

Production and characterization of recombinant perdeuterated cholesterol oxidase.

Cholesterol oxidase (CO) is a FAD (flavin adenine dinucleotide) containing enzyme that catalyzes the oxidization and isomerization of cholesterol. Studies directed toward elucidating the catalytic mechanism of CO will provide an important general understanding of Flavin-assisted redox catalysis. Hydrogen atoms play an important role in enzyme catalysis; however, they are not readily visualized in protein X-ray diffraction structures. Neutron crystallography is an ideal method for directly visualizing hydrogen positions at moderate resolutions because hydrogen and deuterium have comparable neutron scattering lengths to other heavy atoms present in proteins. The negative coherent and large incoherent scattering lengths of hydrogen atoms in neutron diffraction experiments can be circumvented by replacing hydrogen atoms with its isotope, deuterium. The perdeuterated form of CO was successfully expressed from minimal medium, purified, and crystallized. X-ray crystallographic structures of the enzyme in the perdeuterated and hydrogenated states confirm that there are no apparent structural differences between the two enzyme forms. Kinetic assays demonstrate that perdeuterated and hydrogenated enzymes are functionally identical. Together, structural and functional studies indicate that the perdeuterated protein is suitable for structural studies by neutron crystallography directed at understanding the role of hydrogen atoms in enzyme catalysis.

High-resolution structures of cholesterol oxidase in the reduced state provide insights into redox stabilization.

Cholesterol oxidase (CO) is a flavoenzyme that catalyzes the oxidation and isomerization of cholesterol to cholest-4-en-3-one. The reductive half reaction occurs via a hydride transfer from the substrate to the FAD cofactor. The structures of CO reduced with dithionite under aerobic conditions and in the presence of the substrate 2-propanol under both aerobic and anaerobic conditions are presented. The 1.32 Šresolution structure of the dithionite-reduced enzyme reveals a sulfite molecule covalently bound to the FAD cofactor. The isoalloxazine ring system displays a bent structure relative to that of the oxidized enzyme, and alternate conformations of a triad of aromatic residues near to the cofactor are evident. A 1.12 Šresolution anaerobically trapped reduced enzyme structure in the presence of 2-propanol does not show a similar bending of the flavin ring system, but does show alternate conformations of the aromatic triad. Additionally, a significant difference electron-density peak is observed within a covalent-bond distance of N5 of the flavin moiety, suggesting that a hydride-transfer event has occurred as a result of substrate oxidation trapping the flavin in the electron-rich reduced state. The hydride transfer generates a tetrahedral geometry about the flavin N5 atom. High-level density-functional theory calculations were performed to correlate the crystallographic findings with the energetics of this unusual arrangement of the flavin moiety. These calculations suggest that strong hydrogen-bond interactions between Gly120 and the flavin N5 centre may play an important role in these structural features.