tetano
Editor, Senior Moderator
Med Chem
. 2022 Jan 18.
doi: 10.2174/1573406418666220118153541. Online ahead of print.
Ligand-Based Modeling of CXC Chemokine Receptor 4 and Identification of Inhibitors of Novel Chemotypes as Potential Leads towards New Anti-COVID-19 Treatments
Safa Daoud[SUP] 1 [/SUP], Mutasem Taha[SUP] 2 [/SUP]
Affiliations
Abstract
Background: Chemokines are involved in several human diseases and in different stages of COVID-19 infection and play critical role in the pathophysiology of the associated acute respiratory disease syndrome, a major complication leading to death among COVID-19 patients. In particular, CXC chemokine receptor 4 (CXCR4) was found to be highly expressed in COVID-19 patients.
Methods: We herein describe a computational workflow based on combining pharmacophore modeling and QSAR analysis towards the discovery of novel CXCR4 inhibitors. Subsequent virtual screening identified two promising CXCR4 inhibitors from the National Cancer Institute (NCI) list of compounds. The most active hit showed in vitro IC50 value of 24.4 µM.
Results and conclusion: These results prove the validity of the QSAR model and associated pharmacophore models as means to screen virtual databases towards new CXCR4 inhibitors as leads for the development of new COVID-19 therapies.
Keywords: CXCR4; Coronavirus disease; QSAR; in vitro assay; pharmacophore modeling; virtual screening.
. 2022 Jan 18.
doi: 10.2174/1573406418666220118153541. Online ahead of print.
Ligand-Based Modeling of CXC Chemokine Receptor 4 and Identification of Inhibitors of Novel Chemotypes as Potential Leads towards New Anti-COVID-19 Treatments
Safa Daoud[SUP] 1 [/SUP], Mutasem Taha[SUP] 2 [/SUP]
Affiliations
- PMID: 35040417
- DOI: 10.2174/1573406418666220118153541
Abstract
Background: Chemokines are involved in several human diseases and in different stages of COVID-19 infection and play critical role in the pathophysiology of the associated acute respiratory disease syndrome, a major complication leading to death among COVID-19 patients. In particular, CXC chemokine receptor 4 (CXCR4) was found to be highly expressed in COVID-19 patients.
Methods: We herein describe a computational workflow based on combining pharmacophore modeling and QSAR analysis towards the discovery of novel CXCR4 inhibitors. Subsequent virtual screening identified two promising CXCR4 inhibitors from the National Cancer Institute (NCI) list of compounds. The most active hit showed in vitro IC50 value of 24.4 µM.
Results and conclusion: These results prove the validity of the QSAR model and associated pharmacophore models as means to screen virtual databases towards new CXCR4 inhibitors as leads for the development of new COVID-19 therapies.
Keywords: CXCR4; Coronavirus disease; QSAR; in vitro assay; pharmacophore modeling; virtual screening.