Journal
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES
Volume 155, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.ejps.2020.105537
Keywords
HIV-1; Virtual screening; Chemokine receptors; CCR5; CXCR4
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Chemokine receptors are key regulators of cell migration in terms of immunity and inflammation. Among these, CCR5 and CXCR4 play pivotal roles in cancer metastasis and HIV-1 transmission and infection. They act as essential co-receptors for HIV and furnish a route to the cell entry. In particular, inhibition of either CCR5 or CXCR4 leads very often the virus to shift to a more virulent dual-tropic strain. Therefore, dual receptor inhibition might improve the therapeutic strategies against HIV. In this study, we aimed to discover selective CCR5, CXCR4, and dual CCR5/CXCR4 antagonists using both receptor- and ligand-based computational methods. We employed this approach to fully incorporate the interaction attributes of the binding pocket together with molecular dynamics (MD) simulations and binding free energy calculations. The best hits were evaluated for their anti-HIV-1 activity against CXCR4- and CCR5-specific NL4.3 and BaL strains. Moreover, the Ca2+ mobilization assay was used to evaluate their antagonistic activity. From the 27 tested compounds, three were identified as inhibitors: compounds 27 (CCR5), 6 (CXCR4) and 3 (dual) with IC50 values ranging from 10.64 to 64.56 mu M. The binding mode analysis suggests that the active compounds form a salt bridge with the glutamates and pi-stacking interactions with the aromatic side chains binding site residues of the respective co-receptor. The presented hierarchical virtual screening approach provides essential aspects in identifying potential antagonists in terms of selectivity against a specific co-receptor. The compounds having multiple heterocyclic nitrogen atoms proved to be relatively more specific towards CXCR4 inhibition as compared to CCR5. The identified compounds serve as a starting point for further development of HIV entry inhibitors through synthesis and quantitative structure-activity relationship studies.
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