In silico pharmacological analysis of Tinospora cordifolia compounds targeting African swine fever virus B175L
Ranathunga, L.; Karunarathne, K.; Poorni, S.; Jayampathi, N.; Dhananjaya, H.; Hasintha, A.; Hulugalla, W. M. M. P.; Anupama, N. M. T.; Nethmini, N.; Iqbal, N.; Jayawardana, B.
Show abstract
African swine fever virus (ASFV) is a highly lethal DNA virus that suppresses the hosts immune response by establishing infection. B175L, one of its key immune evasion proteins, directly inhibits STING-mediated type I interferon (IFN-I) signaling, preventing antiviral defense activation. Thus, targeting B175L could be a promising strategy for antiviral drug development as effective ASFV inhibitors remain unidentified. In this study, we investigated the potential of the Tinospora cordifolia plants bioactive compounds to disrupt B175Ls function, restoring immune signaling. Gas chromatography-mass spectrometry (GC-MS) analysis of T. cordifolia stems methanol extract identified 124 compounds, of which 52 met SwissADME and DataWarrior criteria for drug-likeness and safety. We generated a highly accurate 3D B175L model with strong confidence scores for the structure accuracy, utilizing AlphaFold3. Virtual screening was performed using PyRx 0.8, and the top 4 ligands with binding affinities exceeding -6 kcal/mol advanced to CB-Dock2 and UCSF Chimera. Among them, Benzaldehyde, 5-bromo-2-hydroxy-, (5-trifluoromethyl-2pyridyl)hydrazone exhibited the highest binding affinity (-8.2 kcal/mol), confirming its strong interactions at the active site of B175L. Molecular dynamics (MD) simulations demonstrated the compounds stability, with root mean square deviation and fluctuation (RMSD, RMSF) indicating minimal conformational changes (<2 [A]). The compound maintained stable hydrogen bonds and hydrophobic interactions, reinforcing structural robustness. Taken together, these results clearly emphasize T. cordifolia-derived Benzaldehyde, 5-bromo-2-hydroxy-, (5-trifluoromethyl-2-pyridyl)hydrazone as a promising B175L inhibitor, advancing exploration towards effective antiviral solutions for ASFV.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Identification of Natural Antiviral Drug Candidates Against Tilapia Lake Virus: Computational Drug Design Approaches 98%
- Molecular docking, simulation and binding free energy analysis of small molecules as PfHT1 inhibitors 98%
- 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%
Similar papers in this journal
- Molecular and functional characterization of buffalo nasal epithelial odorant binding proteins and their structural insights by in-silico and biochemical approach 97%
- Molecular Elucidation of Pancreatic Elastase Inhibition by Baicalein 97%
- Pharmacophore modeling, 2D-QSAR, Molecular Docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA 97%
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 97%
- Chalcogen derivatives for the treatment of African trypanosomiasis: biological evaluation of thio and seleno- semicarbazones and their azole derivatives 96%
- Molecular Glue-Design-Evaluator (MOLDE): An Advanced Method for In-Silico Molecular Glue Design 95%
Similar papers in this journal
- Mechanistic insights into the Japanese Encephalitis Virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica 98%
- Novel Peptide Inhibitor of Human Tumor Necrosis Factor-α has Antiarthritic Activity 96%
- Discovery of Z1362873773: A Novel Fascin Inhibitor from a Large Chemical Library for Colorectal Cancer 96%
"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.