In Silico Molecular Docking and ADMET Evaluation for Investigating the Anti-Cancer Potential of Ketoprofen Amides against Cyclooxygenase-2 (Cox-2) - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Drug and Alcohol Research Année : 2023

In Silico Molecular Docking and ADMET Evaluation for Investigating the Anti-Cancer Potential of Ketoprofen Amides against Cyclooxygenase-2 (Cox-2)

Résumé

Many epithelial cancers overexpress the inducible cyclooxygenase-2 COX-2, which is thought to be the cause of NSAIDs' antitumor effects. While ketoprofens (Ket) are well-known NSAIDs and analgesics, their anticancer potential has not yet gotten much attention, despite the fact that they are used to treat mild to moderate pain, fever, and inflammation. Effective drugs can be expensive, time-consuming, and labor intensive to introduce in a traditional or customary method. Contrarily, computer-aided drug design, commonly referred to as In Silico drug design, is a relatively recent method for high-throughput screening of a vast database of chemicals. By producing hits for lead compounds in less time and at a lower cost, the In Silico virtual screening technique assists in the development of innovative medications. The compound 1 shows the least binding energy value which-9.9 while compound 2 shows the highest which is-7.7. The overall purpose of this study is to assess the potential of different ketoprofen amides and to determine the effectiveness of these amides on the target protein COX-2 (PDB ID: 3Q7D). Additionally, this research compares and characterizes the ADMET profiles of the target ligands, ketoprofen amides. The drug score revealed that ketoprofens adhere to all regulations, is not hazardous, and is not carcinogenic.
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hal-04129804 , version 1 (15-06-2023)

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Muhammad Zeeshan, Sidra Batool, Muhammad Usman Alvi, Zarif Gul, Maryam Ahmed, et al.. In Silico Molecular Docking and ADMET Evaluation for Investigating the Anti-Cancer Potential of Ketoprofen Amides against Cyclooxygenase-2 (Cox-2). Journal of Drug and Alcohol Research, 2023, ⟨10.4303/JDAR/236218⟩. ⟨hal-04129804⟩
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