Accessing anti-HIV activity through the attenuation of USP18 activity: novel insights from molecular dynamic simulations, free-energy profiling, and multi-cellular inhibition assays
Sigauke, L. T.; Bvunzawabaya, J.; Le Bury, G.; Dziwornu, G. A.; Boliar, S.; Gludish, D. W.; Russell, D. G.; Govender, K.; Mugumbate, G.; Chigorimbo-Murefu, N.
Show abstract
The feasibility of achieving anti-HIV activity from the attenuation of USP18 activity was explored for the first time. A cheminformatic survey demonstrated that the current known USP18 isopeptidase inhibitors are derivatives of a bis-aryl pyranone scaffold that possesses undesirable toxicity profiles. Molecular modelling approaches applied to these active bis-aryl pyranones isolated the likely mechanism that perturbs the isopeptidase activity of USP18. Molecular dynamic simulations and free-energy profiling showed that induced-fit effects on the catalytic triad and the IBB-1 domain residues of USP18 drive a reversible non-competitive isopeptidase inhibition mechanism. Proof-of-concept multi-cellular HIV inhibition assays demonstrate the utility of achieving anti-HIV-1 activity from attenuating the activity of USP18 using small molecules. This study motivates for the pursuit of scaffolds that target the allosteric site of USP18, fine-tuning the IFN response as a strategy to enhance the natural control mechanisms that lead to an antiviral state potentially curing viral infection.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease 95%
- Structure-based identification of naphthoquinones and derivatives as novel inhibitors of main protease Mpro and papain-like protease PLpro of SARS-CoV-2 95%
- Fragment-Guided New Therapeutic Molecule Discovery and Mapping of Clinically Relevant Interactomes 95%
Similar papers in this journal
- Ligand-induced Conformational Selection Predicts the Selectivity of Cysteine Protease Inhibitors 95%
- A drug repurposing screen identifies hepatitis C antivirals as inhibitors of the SARS-CoV-2 main protease. 95%
- 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 94%
Similar papers in this journal
- Structural Models for a Series of Allosteric Inhibitors of IGF1R Kinase 95%
- Entrectinib - a SARS-CoV-2 inhibitor in Human Lung Tissue (HLT) cells 94%
- Structural distortions induced by Kinase Inhibiting RNase Attenuator (KIRA) compounds prevent the formation of face-to-face dimers of Inositol Requiring Enzyme 1α 94%
Similar papers in this journal
- Discovery of Aminoglycosides as First in Class, Nanomolar Inhibitors of Heptosyltransferase I 94%
- Mechanistic insights into the Japanese Encephalitis Virus RNA dependent RNA polymerase protein inhibition by bioflavonoids from Azadirachta indica 94%
- Discovery of Z1362873773: A Novel Fascin Inhibitor from a Large Chemical Library for Colorectal Cancer 94%
Similar papers in this journal
- In silico screening and testing of FDA approved small molecules to block SARS-CoV-2 entry to the host cell by inhibiting Spike protein cleavage 97%
- Allosteric inhibitors of Zika virus NS2B-NS3 protease targeting protease in super-open conformation 96%
- Kite-shaped molecules block SARS-CoV-2 cell entry at a post-attachment step 95%
"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.