Identification of Potential Dual Farnesol X Receptor/Retinoid X Receptor α Agonists Based on Machine Learning Models, ADMET Prediction and Molecular Docking

Abstract

Nuclear receptors (NRs) play a crucial role in the pathogenesis of metabolic syndrome. Farnesol X receptor (FXR) and retinoid X receptor (RXR) are members of the NR superfamily and are usually present as heterodimers in vivo. Screening for multi‐target NR activators is of great importance due to the complex pathogenesis of metabolic diseases. Virtual screening is often used for drug discovery. In this study, we first collected data on relevant compounds and subsequently constructed three machine learning models (Random Forest, Support Vector Machine, and Artificial Neural Network) with molecular descriptors. We then performed model fusion based on the soft voting strategy and the prediction accuracies of the fused models were 85.2 % for the FXR external validation set and 84.3 % for the RXRα external validation set, followed by virtual screening of compounds in the ZINC database according to a model score threshold of 0.7. The 499 hits commonly selected by both models were then subjected to a drug‐likeness filter and ADMET prediction using appropriate bioavailability parameters. The 10 compounds that met the criteria were processed by molecular docking using the AutoDock Vina software. The results showed that we screened four potential dual FXR/RXRα agonists with binding energies less than −8.0 kcal/mol for both targets (ZINC1557163, ZINC14824986, ZINC5273978 and ZINC40394465).

Evaluation of farnesol orally and topically against experimental cutaneous leishmaniasis: In -vivo analysis

“…The pharmacokinetic profile of Farnesol reveals a Log kp value of -3.81 cm/s, falling within the recommended range for topical drug application as determined by the Swiss-ADME profiling [ 41 ]. Furthermore, because of this drug’s high lipophilicity (Log P o/w = 4.32), it is an indication of it passes through several membrane barriers and a significant pH barrier to reach the intracellular amastigotes in the phagolysosomes of most macrophages and stop their proliferation.…”

“…Furthermore, because of this drug’s high lipophilicity (Log P o/w = 4.32), it is an indication of it passes through several membrane barriers and a significant pH barrier to reach the intracellular amastigotes in the phagolysosomes of most macrophages and stop their proliferation. It also follows all drug likeliness profiles according to ADMET profiles like Veber, Lipinski’s five rules, Ghose, Egan [ 41 ]. The bioavailability score was 0.55 which indicates that farnesol gets distributed evenly in the biological system, and suggests that it could be anticipated to produce excellent outcomes as a drug in an in vivo system.…”

Computational and Retrosynthetic Investigation of Isoxazole‐Bearing Chalcones as Antioxidant Activate Compounds

“…A low RMSD illustrates that the position of the mooring result is closer to the cocrystal ligand [17,18] . The crucial criterion used in the process of docking was the free bond energy (ΔG), the dissociation constant obtained by inhibition (K i ), the name of amino acid, and the number and type of bonds established [19] . The scores ΔG and K i evaluate the ligand affinity for the receptor active site; it is higher if ΔG is more negative and the lower K i .…”

“…[17,18] The crucial criterion used in the process of docking was the free bond energy (ΔG), the dissociation constant obtained by inhibition (K i ), the name of amino acid, and the number and type of bonds established. [19] The scores ΔG and K i evaluate the ligand affinity for the receptor active site; it is higher if ΔG is more negative and the lower K i . The cocrystal ligand validation result references all ligands tested to assess their potency as receptor inhibitors.…”