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Current Topics in Medicinal Chemistry

Author(s): Neda Fayyazi, Somayeh Esmaeili, Salman Taheri, Frederico F. Ribeiro, Marcus T. Scotti, Luciana Scotti, Jahan B. Ghasemi*, Lotfollah Saghaei* and Afshin Fassihi

DOI: 10.2174/1568026619666191116160326

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Pharmacophore Modeling, Synthesis, Scaffold Hopping and Biological β- Hematin Inhibition Interaction Studies for Anti-malaria Compounds

Page: [2743 - 2765] Pages: 23

  • * (Excluding Mailing and Handling)

Abstract

Backgound: Exploring potent compounds is critical to generating multi-target drug discovery. Hematin crystallization is an important mechanism of malaria.

Methods: A series of chloroquine analogues were designed using a repositioning approach to develop new anticancer compounds. Protein-ligand interaction fingerprints and ADMET descriptors were used to assess docking performance in virtual screenings to design chloroquine hybrid β-hematin inhibitors. A PLS algorithm was applied to correlate the molecular descriptors to IC50 values. The modeling presented excellent predictive power with correlation coefficients for calibration and cross-validation of r2 = 0.93 and q2 = 0.72. Using the model, a series of 4-aminoquinlin hybrids were synthesized and evaluated for their biological activity as an external test series. These compounds were evaluated for cytotoxic cell lines and β-hematin inhibition.

Results: The target compounds exhibited high β-hematin inhibition activity and were 3-9 times more active than the positive control. Furthermore, all the compounds exhibited moderate to high cytotoxic activity. The most potent compound in the dataset was docked with hemoglobin and its pharmacophore features were generated. These features were used as input to the Pharmit server for screening of six databases.

Conclusion: The compound with the best score from ChEMBL was 2016904, previously reported as a VEGFR-2 inhibitor. The 11 compounds selected presented the best Gold scores with drug-like properties and can be used for drug development.

Keywords: Computer-aided drug design, Computational ADME/Tox, Database, Cancer, Cell lines, QSAR, Partial least square, β-hematin, Receptor.

Graphical Abstract

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