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Computational analysis using ADMET profiling, DFT calculations and molecular docking of two anti-cancer drugs
2023
Journal:  
Turkish Computational and Theoretical Chemistry
Author:  
Abstract:

U.S. FDA approved anti-cancer drugs, namely ribociclib and copanlisib used for treating breast cancer and follicular lymphoma, respectively, were chosen for computational study. Quantum chemical calculations via DFT and MP2 were used for energy optimization of the drugs. Chemical descriptor parameters were compared between DFT and MP2 values for each atom, and the most reactive and stable atoms were reported. To describe the reactivity and stability of the drug molecules, Fukui functions were calculated. Molecular docking of the drugs was performed against epidermal growth factor receptor (EGFR) and cellular inhibitor of apoptosis protein-1 (cIAP1) receptor proteins to study the drug-protein binding interactions. The binding energy values before optimization and after optimization were found to be -11.21 and -14.41 kcal.mol-1 for copanlisib and -13.58 kcal and -29.08 kcal for ribociclib respectively. Atoms O27 and O10 are reported to be the most reactive atom based on high softness value. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of the drugs were evaluated using open-source in-silico tools. ADME profiling of drug molecules indicated good to moderate solubility and low to high absorption in the gastrointestinal tract. Predicted toxicity was class five for both anti-cancer drugs. The structural and bioactive properties of the drugs focused on in this study help evaluate the better reactivity patterns of anticancer medicines.

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2023
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Turkish Computational and Theoretical Chemistry

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Turkish Computational and Theoretical Chemistry