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Datasets and U-Net Model for "A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma"

This dataset has results and the model associated with the publication Ciulla et al., (2024). It contains a U-Net semantic segmentation model (unet_model.h5) and associated code implemented in tensorflow 2.0 for the model training and identification of oil and gas well symbols in USGS historical topographic maps (HTMC). Given a quadrangle map (7.5 minutes), downloadable at this url: https://ngmdb.usgs.gov/topoview/, and a list of coordinates of the documented wells present in the area, the model returns the coordinates of oil and gas symbols in the HTMC maps. For reproducibility of our workflow, we provide a sample map in California and the documented well locations for the entire State of California (CalGEM_AllWells_20231128.csv) downloaded from https://www.conservation.ca.gov/calgem/maps/Pages/GISMapping2.aspx. Additionally, the locations of 1,301 potential undocumented orphaned wells identified using our deep learning framework or the counties of Los Angeles and Kern in California, and Osage and Oklahoma in Oklahoma are provided in the file found_potential_UOWs.zip. The results of the visual inspection of satellite imagery in Osage County is in the file visible_potential_UOWs.zip. The dataset also includes a custom tool to validate the detected symbols in the HTMC maps (vetting_tool.py). More details about the methodology can be found in the associated paper: Ciulla, F., Santos, A., Jordan, P., Kneafsey, T., Biraud, S.C., and Varadharajan, C. (2024) A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: a Case Study for California and Oklahoma. Accepted for publication in Environmental Science and Technology. The geographical coordinates provided correspond to the locations of potential undocumented orphaned oil and gas wells (UOWs) extracted from historical maps. The actual presence of wells need to be confirmed with on-the-ground investigations. For your safety, do not attempt to visit or investigate these sites without appropriate safety training, proper equipment, and authorization from local authorities. Approaching these well sites without proper personal protective equipment (PPE) may pose significant health and safety risks. Oil and gas wells can emit hazardous gasses including methane, which is flammable, odorless and colorless, as well as hydrogen sulfide, which can be fatal even at low concentrations. Additionally, there may be unstable ground near the wellhead that may collapse around the wellbore. This dataset was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Artificial Intelligence↗

SuFEx-enabled high-throughput medicinal chemistry for developing potent tamoxifen analogs as Ebola virus entry inhibitors

Ebola virus (EBOV) causes severe hemorrhagic fever with a high mortality rate in humans. In acute infection, an abnormal immune response results in excessive inflammatory cytokines and uncontrolled systemic inflammation that can result in organ damage and multi-organ failure. While vaccines and monoclonal antibody therapies are available, there is an urgent need for effective small-molecule antivirals against EBOV. Here, we report on the optimization of tamoxifen, an EBOV-glycoprotein (GP) binder that inhibits viral entry, using our Sulfur-Fluoride Exchange (SuFEx) click chemistry-based high-throughput medicinal chemistry (HTMC) strategy. Using a “Direct-to-Biology” approach, we generated a focused library of 2,496 tamoxifen analogs overnight and screened them in a cell-based pseudo-EBOV infection assay. The HTMC workflow enabled the development of a potent EBOV entry inhibitor with submicromolar EC 50 cellular antiviral activity and more than 50-fold improvement in binding affinity against EBOV-GP compared to the parent compound. Our findings underscore the use of SuFEx-enabled HTMC for rapidly generating and assessing potential therapeutic candidates against viral and immune-mediated diseases in a cell-based assay.

Immunology↗

Ultrapotent influenza hemagglutinin fusion inhibitors developed through SuFEx-enabled high-throughput medicinal chemistry

Seasonal and pandemic-associated influenza strains cause highly contagious viral respiratory infections that can lead to severe illness and excess mortality. Here, we report on the optimization of our small-molecule inhibitor F0045(S) targeting the influenza hemagglutinin (HA) stem with our Sulfur-Fluoride Exchange (SuFEx) click chemistry–based high-throughput medicinal chemistry (HTMC) strategy. A combination of SuFEx- and amide-based lead molecule diversification and structure-guided design led to identification and validation of ultrapotent influenza fusion inhibitors with subnanomolar EC 50 cellular antiviral activity against several influenza A group 1 strains. X-ray structures of six of these compounds with HA indicate that the appended moieties occupy additional pockets on the HA surface and increase the binding interaction, where the accumulation of several polar interactions also contributes to the improved affinity. The compounds here represent the most potent HA small-molecule inhibitors to date. Our divergent HTMC platform is therefore a powerful, rapid, and cost-effective approach to develop bioactive chemical probes and drug-like candidates against viral targets.

Science & Technology - Other Topics↗