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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

In vitro modeling of human tibial strains during exercise in micro-gravity

Prolonged exposure to micro-gravity causes substantial bone loss (Leblanc et al., Journal of Bone Mineral Research 11 (1996) S323) and treadmill exercise under gravity replacement loads (GRLs) has been advocated as a countermeasure. To date, the magnitudes of GRLs employed for locomotion in space have been substantially less than the loads imposed in the earthbound 1G environment, which may account for the poor performance of locomotion as an intervention. The success of future treadmill interventions will likely require GRLs of greater magnitude. It is widely held that mechanical tissue strain is an important intermediary signal in the transduction pathway linking the external loading environment to bone maintenance and functional adaptation; yet, to our knowledge, no data exist linking alterations in external skeletal loading to alterations in bone strain. In this preliminary study, we used unique cadaver simulations of micro-gravity locomotion to determine relationships between localized tibial bone strains and external loading as a means to better predict the efficacy of future exercise interventions proposed for bone maintenance on orbit. Bone strain magnitudes in the distal tibia were found to be linearly related to ground reaction force magnitude (R(2)>0.7). Strain distributions indicated that the primary mode of tibial loading was in bending, with little variation in the neutral axis over the stance phase of gait. The greatest strains, as well as the greatest strain sensitivity to altered external loading, occurred within the anterior crest and posterior aspect of the tibia, the sites furthest removed from the neutral axis of bending. We established a technique for estimating local strain magnitudes from external loads, and equations for predicting strain during simulated micro-gravity walking are presented.

NASA Discipline Musculoskeletal↗
NASA NTRS2016

Multidisciplinary Model Transformation Through Simplified Intermediate Representations

There has long been a challenge of making engineering tools from multiple disciplines interoperate. This problem extends to system modeling practices. This challenge has been confronted with a wide variety of techniques. These techniques include attempting to interface tools together into combined suites, attempting to find underlying commonalities in mathematics, supporting connections through semantic encoding, various graph mappings and transformations, and code wrappers. All of these approaches have strengths and weaknesses. These are measured in multiple areas: relative freedom of action of individual domain engineers in developing their own tools, speed of execution, ease of creation, traceability, fidelity of information transfer, and degree of alignment between the concepts of different domains. This paper presents an approach to this interoperation problem currently being used in the World-Wide Web. The approach is to develop easy-to-parse formats that allow flexibility to both the file author and file interpreter. Many of the formats that are currently deployed sacrifice runtime performance for the ability of third parties to easily understand what to do with the data. XML became popular earlier as a de-facto standard format for many web applications, but is now being replaced by JSON to enhance human readability and provide a simpler data model. This is the basis for work in this paper. Our approach, which provides the key to interoperation, is a simplified “shrapnel” intermediate collection of objects and relationships that is the result of a breakdown of the system model into minimal pieces. It is then reassembled on the destination side, forming a two-step transformation. Previous efforts with single-step transformations have proven too difficult to create efficiently. In contrast, the use of this approach leads to an almost automatic procedure for transformation development. The Europa project is a large engineering project that must coordinate the efforts of many different teams with different specialties. The traditional form of exchanging engineering information has been documentation. The vision of model-based systems engineering is to make this information exchange much more digital. This paper presents the application of our simplified format to connecting two different engineering tools to the system model, with a focus on a dynamic mission simulation encoded in Modelica.

Cole, Bjorn↗
NASA NTRSDate not supplied

Evaluation of CFD Predictions of CobraMRV Control Surface Effectiveness at the NASA Langley Unitary Plan Wind Tunnel

The ability of CFD simulations to serve as a surrogate for wind tunnel testing at high supersonic speeds has been evaluated for a sub-scale model of the Co-Optimization Blunt-body Re-entry Analysis-Mid-lift-to-drag Rigid Vehicle (CobraMRV) human Mars entry vehicle concept. The vehicle was tested at the Unitary Plan Wind Tunnel (UPWT) at the NASA Langley Research Center under flow conditions and surface control configurations relevant to the entry stage of a flight mission. The CFD simulations were performed prior to gaining access to test results in order to assess how blind predictions obtained using best practices compare to experiments. Solutions of empty tunnel simulations were used as inflow boundary condition for the CobraMRV simulations in a truncated portion of the test section. Different solvers and turbulence models were used by separate teams to assess sensitivity to numerical methods, physics, and users. After release of the test results, the pre-test computations were compared to the experimental results, and additional analyses have been conducted to explain observed discrepancies. The amount of time and resources dedicated to each phase of the computational work was logged for comparison to that required for wind tunnel tests, and to inform planning of future CFD data base development projects.

ARMD↗
DOE OSTI2024

Expression of a mammalian RNA demethylase increases flower number and floral stem branching in Arabidopsis thaliana

Abstract RNA methylation plays a central regulatory role in plant biology and is a relatively new target for plant improvement efforts. In nearly all cases, perturbation of the RNA methylation machinery results in deleterious phenotypes. However, a recent landmark paper reported that transcriptome‐wide use of the human RNA demethylase FTO substantially increased the yield of rice and potatoes. Here, we have performed the first independent replication of those results and demonstrated broader transferability of the trait, finding increased flower and fruit count in the model species Arabidopsis thaliana . We also performed RNA‐seq of our FTO‐transgenic plants, which we analyzed in conjunction with previously published datasets to detect several previously unrecognized patterns in the functional and structural classification of the upregulated and downregulated genes. From these, we present mechanistic hypotheses to explain these surprising results with the goal of spurring more widespread interest in this promising new approach to plant engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

GHOST (Grid Hardware Open Source Testbed) [SWR-18-32]

The software was developed for the purpose of Microgrid Controller Procurement where multiple Microgrid Controller vendors were competing to prove the best performance. Each microgrid controller was connected to Real-Time Simulator (Opal-RT) where the Real-Time model of microgrid was simulated. Microgrid controllers were able to control most of the assets in the model. To be able to fairly compare controller's performance each controller was evaluated using exactly the same model, with the same initial conditions and exactly the same test sequence. The microgrid evaluation test sequence lasted 100 minutes and consist of various grid disturbances to which a microgrid controller must respond. The microgrid and power system will experience multiple types of disturbances while performing dispatch functions. Many functions are tested in grid-connected and islanded modes such as unexpended failures of generators, energy storage trip events, and large load fluctuations. The test sequence focuses on fault scenarios that cause the highest short-circuit fault current contribution; force a swing bus or generator capable of being a swing bus offline; cause the most reconfigurations; and cause conflicting objectives for the microgrid controller. During the test sequence execution multiple datapoints are being recorded and stored. During data postprocessing key performance parameters are extracted allowing quantitative comparison of performance on multiple aspects including: resiliency, fuel utilization, grid interconnection, ancillary services and power quality and eventually after summing all key performance parameters by comparing the overall result. To be able to perform such testing multiple tools had to be developed included in this repository including: - Real time model of microgrid (Urban-Banshee, Remote-smaller model) - Test sequence configuration tools - Test execution real-time scripts - Post processing scripts - Human Machine Interface software

Koralewicz, Przemyslaw↗
NASA NTRS1978

Use of the tilt cue in a simulated heading tracking task

The task was performed with subjects using visual-only cues and combined visual and roll-axis motion cues. Half of the experimental trials were conducted with the simulator rotating about the horizontal axis; to suppress the tilt cue, the remaining trials were conducted with the simulator cab tilted 90 deg so that roll-axis motions were about earth vertical. The presence of the tilt cue allowed a substantial and statistically significant reduction in performance scores. When the tilt cue was suppressed, the availability of motion cues did not result in significant performance improvement. These effects were accounted for by the optimal-control pilot/vehicle model, wherein the presence or absence of various motion cues was represented by appropriate definition of the perceptual quantities assumed to be used by the human operator.

Levison, W. H.↗
NASA NTRS1990

Space Station solar water heater

The feasibility of directly converting solar energy for crew water heating on the Space Station Freedom (SSF) and other human-tended missions such as a geosynchronous space station, lunar base, or Mars spacecraft was investigated. Computer codes were developed to model the systems, and a proof-of-concept thermal vacuum test was conducted to evaluate system performance in an environment simulating the SSF. The results indicate that a solar water heater is feasible. It could provide up to 100 percent of the design heating load without a significant configuration change to the SSF or other missions. The solar heater system requires only 15 percent of the electricity that an all-electric system on the SSF would require. This allows a reduction in the solar array or a surplus of electricity for onboard experiments.

Horan, D. C.↗
NASA NTRS2000

Thermal Analysis and Design of an Advanced Space Suit

The thermal dynamics and design of an Advanced Space Suit are considered. A transient model of the Advanced Space Suit has been developed and implemented using MATLAB/Simulink to help with sizing, with design evaluation, and with the development of an automatic thermal comfort control strategy. The model is described and the thermal characteristics of the Advanced Space suit are investigated including various parametric design studies. The steady state performance envelope for the Advanced Space Suit is defined in terms of the thermal environment and human metabolic rate and the transient response of the human-suit-MPLSS system is analyzed.

Lin, Chin H.↗
NASA NTRS2016

Crew Exploration Vehicle (CEV) (Orion) Occupant Protection

The purpose of this study was to determine the similarity between the response of the THUMS model and the Hybrid III Anthropometric Test Device (ATD) given existing Wright-Patterson (WP) sled tests. There were four tests selected for this comparison with frontal, spinal, rear, and lateral loading. The THUMS was placed in a sled configuration that replicated the WP configuration and the recorded seat acceleration for each test was applied to model seat. Once the modeling simulations were complete, they were compared to the WP results using two methods. The first was a visual inspection of the sled test videos compared to the THUMS d3plot files. This comparison resulted in an assessment of the overall kinematics of the two results. The other comparison was a comparison of the plotted data recorded for both tests. The metrics selected for comparison were seat acceleration, belt forces, head acceleration and chest acceleration. These metrics were recorded in all WP tests and were outputs of the THUMS model. Once the comparison of the THUMS to the WP tests was complete, the THUMS model output was also examined for possible injuries in these scenarios. These outputs included metrics for injury risk to the head, neck, thorax, lumbar spine and lower extremities. The metrics to evaluate head response were peak head acceleration, HIC15, and HIC36. For the neck, N (sub ij) was calculated. The thorax response was evaluated with peak chest acceleration, the Combined Thoracic Index (CTI), sternal deflection, chest deflection, and chest acceleration- 3 ms clip. The lumbar spine response was evaluated with lumbar spine force. Finally the lower extremity response was evaluated by femur and tibia force. The results of the simulation comparisons indicate the THUMS model had a similar response to the Hybrid III dummy given the same input. The primary difference seen between the two was a more flexible response of the THUMS compared to the Hybrid III. This flexibility was most pronounced in the neck flexion, shoulder deflection and chest deflection. Due to the flexibility of the THUMS, the resulting head and chest accelerations tended to lag the Hybrid III acceleration trace and have a lower peak value. The results of the injury metric comparison identified possible injury trends between simulations. Risk of head injury was highest for the lateral simulations. The risk of chest injury was highest for the rear impact. However, neck injury risk was approximately the same for all simulations. The injury metric value for lumbar spine force was highest for the spinal impact. The leg forces were highest for the rear and lateral impacts. The results of this comparison indicate the THUMS model performs in a similar manner as the Hybrid III ATD. The differences in the responses of model and the ATD are primarily due to the flexibility of the THUMS. This flexibility of the THUMS would be a more human like response. Based on the similarity between the two models, the THUMS should be used in further testing to assess risk of injury to the occupant.

Currie-Gregg, Nancy J.↗
DOE OSTI2025

An Alternative Ensemble Streamflow Prediction Approach Using Improved Subseasonal Precipitation Forecasts from the North America Multi-Model Ensemble Phase II

In this article, streamflow forecasting at a subseasonal time scale (10–30 days into the future) is important for various human activities. The ensemble streamflow prediction (ESP) is a widely applied technique for subseasonal streamflow forecasting. However, ESP’s reliance on the randomly resampled historical precipitation limits its predictive capability. Available dynamical subseasonal precipitation forecasts provide an alternative to the randomly resampled precipitation in ESP. Prior studies found the predictive performance of raw subseasonal precipitation forecast is limited in many regions such as the central south of the United States, which raises questions about its effectiveness in assisting streamflow forecasting. To further assess the hydrologic applicability of dynamical subseasonal precipitation forecasts, we test the subseasonal precipitation forecast from North America Multi-Model Ensemble Phase II (NMME-2) at four watersheds in the central south region of the United States. The subseasonal precipitation forecasts are postprocessed with bias correction and spatial disaggregation (BCSD) to correct bias and improve spatial resolution before replacing the randomly resampled precipitation in ESP for streamflow predictions. The performance of the resulting streamflow predictions is benchmarked with ESP. Evaluation is conducted using Kling–Gupta Efficiency (KGE), continuous ranked probability score (CRPS), probability of detection (POD), false alarm ratios (FARs), as well as reliability diagrams. Our results suggest that BCSD-corrected subseasonal precipitation forecasts lead to overall improved streamflow predictions due to added skills in winter and spring. Our results also suggest that BCSD-corrected subseasonal precipitation forecasts lead to improved predictions on the occurrence of high-percentile streamflow values above 75%. Overall, BCSD-corrected subseasonal precipitation has shown promising performance, highlighting its potential broader applications for river and flood forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Scalable Representation Learning for Long-Term Augmented Reality-Based Information Delivery in Collaborative Human-Robot Perception

Augmented reality (AR)-based information delivery has been attracting an increasing attention in the past few years to improve com- munication in human-robot teaming. In the long-term use of AR systems for collaborative human-robot perception, one of the biggest challenges is to perform place and scene matching under long-term environmental changes, such as dramatic variations in lighting, weather and vegetation across di erent times of the day, months, and seasons. To address this challenge, we introduce a novel representation learning approach that learns a scalable long-term representation model that can be used for place and scene matching in various long-term conditions. Our approach is formulated as a regularized optimization problem, which selects the most representative scene templates in di erent scenarios to construct a scalable representation of the same place that can exhibit signi cant long-term environment changes. Our approach adaptively learns to select a small subset of the templates to construct the representation model, based on a user-de ned representativeness threshold, which makes the learned model highly scalable to the long-term variations in real-world applications. To solve the formulated optimization problem, a new algo- rithmic solver is designed, which is theoretically guaranteed to converge to the global optima. Experiments are conducted using two large-scale benchmark datasets, which have demonstrated the superior performance of our approach for long-term place and scene matching.

42 ENGINEERING↗
NASA NTRS2011

A Transfer of Training Study of Control Loader Dynamics

The control inceptor used in a simulated vehicle is an important part in maintaining the fidelity of a simulation. The force feedback provided by the control inceptor gives the operator important cues to maintain adequate performance. The dynamics of a control inceptor are typically based on a second order spring mass damper system with damping, force gradient, breakout force, and natural frequency parameters. Changing these parameters can have a great effect on pilot or driver control of the vehicle. The neuromuscular system has a very important role in manipulating the control inceptor within a vehicle. Many studies by McRuer, Aponso, and Hess have dealt with modeling the neuromuscular system and quantifying the effects of a high fidelity control loader as compared to a low fidelity control loader. Humans are adaptive in nature and their control behavior changes based on different control loader dynamics. Humans will change their control behavior to maintain tracking bandwidth and minimize tracking error. This paper reports on a quasi-transfer of training experiment which was performed at the NASA Langley Research Center. The quasi transfer of training study used a high fidelity control loader and a low fidelity control loader. Subjects trained in both simulations and then were transferred to the high fidelity control loader simulation. The parameters for the high fidelity control loader were determined from the literature. The low fidelity control loader parameters were found through testing of a simple computer joystick. A disturbance compensatory task is employed. The compensatory task involves implementing a simple horizon out the window display. A disturbance consisting of a sum of sines is used. The task consists of the subject compensating for the disturbance on the roll angle of the aircraft. The vehicle dynamics are represented as 1/s and 1/s2. The subject will try to maintain level flight throughout the experiment. The subjects consist of non-pilots to remove any effects of pilot experience. First, this paper discusses the implementation of the disturbance compensation task. Second, the high and low fidelity parameters used within the experiment are presented. Finally, an explanation of results from the experiments is presented.

Cardullo, Frank M.↗
NASA NTRSDate not supplied

Validation of Cryogenic Propellant Tank Filling using Computational Fluid Dynamics Simulation

The Fluid Dynamics Branch at MSFC has positioned itself to support a wide range of customers in need of Cryogenic Fluid Management (CFM) analysis. A computational fluid dynamics (CFD) tool used for all manner of internal and external propulsion applications has been extended and refined to better model cryogenic propellant storage and tanking operations. Through the CFM Portfolio project, several validation activities were initiated. Validation of propellant tank self-pressurization, autogenous pressurization, slosh-induced ullage collapse, and jet-induced mixing all aid in defining model accuracy. The on-going validation effort has enabled confident application of the tool to in-line design and evaluation of CFM hardware and operations. Recent project support included defining the impact of in-space slosh dynamics on reaction control system mass for Space Launch System (SLS) upper stages. Propellant mixing strategies were defined to improve performance of a thermal vent system for a Commercial Lunar Payload Services (CLPS) partner. Design support of in-space maneuvers, tank hardware, and autogenous pressurization operations was also provided through Human Landing System (HLS) collaboration work. The branch has engaged the CFM community to share recent findings and capabilities through several forums including conferences, technical interchange meetings, and workshops. Development and demonstration of CFM modeling capabilities continues in this work on the no-vent fill of propellant tank in micro-gravity to meet the needs of NASA and its industry partners in the endeavor to sustainably reach the Moon and beyond.

CFD↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
DOE OSTI2022

Interpreting machine learning prediction of fire emissions and comparison with FireMIP process-based models

Annual burned areas in the United States have increased 2-fold during the past decades. With more large fires resulting in more emissions of fine particulate matter, an accurate prediction of fire emissions is critical for quantifying the impacts of fires on air quality, human health, and climate. This study aims to construct a machine learning (ML) model with game-theory interpretation to predict monthly fire emissions over the contiguous US (CONUS) and to understand the controlling factors of fire emissions. The optimized ML model is used to diagnose the process-based models in the Fire Modeling Intercomparison Project (FireMIP) to inform future development. Results show promising performance for the ML model, Community Land Model (CLM), and Joint UK Land Environment Simulator-Interactive Fire And Emission Algorithm For Natural Environments (JULES-INFERNO) in reproducing the spatial distributions, seasonality, and interannual variability of fire emissions over the CONUS. Regional analysis shows that only the ML model and CLM simulate the realistic interannual variability of fire emissions for most of the subregions (r >0.95 for ML and r =0.14~0.70 for CLM), except for Mediterranean California, where all the models perform poorly (r =0.74 for ML and r <0.30 for the FireMIP models). Regarding seasonality, most models capture the peak emission in July over the western US. However, all models except for the ML model fail to reproduce the bimodal peaks in July and October over Mediterranean California, which may be explained by the smaller wind speeds of the atmospheric forcing data during Santa Ana wind events and limitations in model parameterizations for capturing the effects of Santa Ana winds on fire activity. Furthermore, most models struggle to capture the spring peak in emissions in the southeastern US, probably due to underrepresentation of human effects and the influences of winter dryness on fires in the models. As for extreme events, both the ML model and CLM successfully reproduce the frequency map of extreme emission occurrence but overestimate the number of months with extremely large fire emissions. Comparing the fire PM 2.5 emissions from the ML model with process-based fire models highlights their strengths and uncertainties for regional analysis and prediction and provides useful insights into future directions for model improvements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Structure-based discovery of potent WD repeat domain 5 inhibitors that demonstrate efficacy and safety in preclinical animal models

WD repeat domain 5 (WDR5) is a core scaffolding component of many multiprotein complexes that perform a variety of critical chromatin-centric processes in the nucleus. WDR5 is a component of the mixed lineage leukemia MLL/SET complex and localizes MYC to chromatin at tumor-critical target genes. As a part of these complexes, WDR5 plays a role in sustaining oncogenesis in a variety of human cancers that are often associated with poor prognoses. Thus, WDR5 has been recognized as an attractive therapeutic target for treating both solid and hematological tumors. Previously, small-molecule inhibitors of the WDR5-interaction (WIN) site and WDR5 degraders have demonstrated robust in vitro cellular efficacy in cancer cell lines and established the therapeutic potential of WDR5. However, these agents have not demonstrated significant in vivo efficacy at pharmacologically relevant doses by oral administration in animal disease models. We have discovered WDR5 WIN-site inhibitors that feature bicyclic heteroaryl P 7 units through structure-based design and address the limitations of our previous series of small-molecule inhibitors. Importantly, our lead compounds exhibit enhanced on-target potency, excellent oral pharmacokinetic (PK) profiles, and potent dose-dependent in vivo efficacy in a mouse MV4:11 subcutaneous xenograft model by oral dosing. Furthermore, these in vivo probes show excellent tolerability under a repeated high-dose regimen in rodents to demonstrate the safety of the WDR5 WIN-site inhibition mechanism. Collectively, our results provide strong support for WDR5 WIN-site inhibitors to be utilized as potential anticancer therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Chemical classification program synthesis using generative artificial intelligence

Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEBI) database. These programs can be used for efficient deterministic run-time classification of SMILES structures, with natural language explanations. The programs themselves constitute an explainable computable ontological model of chemical class nomenclature, which we call the ChEBI Chemical Class Program Ontology (C3PO). We validated our approach against the ChEBI database, and compared our results against deep learning models and a naive SMARTS pattern based classifier. C3PO outperforms the naive classifier, but does not reach the performance of state of the art deep learning methods. However, C3PO has a number of strengths that complement deep learning methods, including explainability and reduced data dependence. C3PO can be used alongside deep learning classifiers to provide an explanation of the classification, where both methods agree. The programs can be used as part of the ontology development process, and iteratively refined by expert human curators.

Artificial Intelligence↗