Computational design of two new soluble epoxide hydrolase (sEH) inhibitors
Liem, J.; Adhikari, S.; Huang, P.; Siegel, J. B.
Show abstract
Inhibitors of soluble epoxide hydrolase (sEH) enzymes have shown great potential for the treatment of neuropathic pain. However, current sEH inhibitors have poor physicochemical properties and has not been proven to be safe for human treatments yet. New inhibitor designs could have the potential to improve current drugs efficacy, and so in this work, chemical intuition and bioisosteric replacement were used to computationally design two novel sEH inhibitors. These new candidates showed good pharmacokinetic properties and presented better docking scores compared to a known sEH inhibitor, t-TUCB, used in the treatment of pain in horses. Homology analysis revealed that Mus musculus may not be suitable organism for preclinical trials studies of these novel inhibitors.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors 97%
- Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of Rheumatoid Arthritis: Virtual screening to comprehensive in silico investigation 97%
- Identification of Natural Antiviral Drug Candidates Against Tilapia Lake Virus: Computational Drug Design Approaches 97%
Similar papers in this journal
Similar papers in this journal
- Utilizing Heteroatom Types and Numbers from Extensive Ligand Libraries to Develop Novel hERG Blocker QSAR Models Using Machine Learning-based Classifiers 98%
- Discovery of a Novel Non-Narcotic Analgesic Derived from the CL-20 Explosive: Synthesis, Pharmacology and Target Identification of Thio-wurtzine, a Potent Inhibitor of the Opioid Receptors and the Voltage-Dependent Calcium Channels 95%
- Support Vector Machine based prediction models for drug repurposing and designing novel drugs for colorectal cancer 95%
Similar papers in this journal
- De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia 97%
- Structural analysis and ensemble docking revealed the binding modes of selected progesterone receptor modulators 96%
- Pharmacophore modeling, 2D-QSAR, Molecular Docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA 96%
Similar papers in this journal
- Nitroimidazopyrazinones with oral activity against tuberculosis and Chagas disease in mouse models of infection 93%
- Discovery of Chlorofluoroacetamide-Based Covalent Inhibitors for SARS-CoV-2 3CL Protease 93%
- Design, synthesis and cellular characterization of a new class of IPMK kinase inhibitors 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.