High-Throughput Screening and Molecular Dynamics Simulation of Natural Products for the Identification of Anticancer Agents against MCM7 Protein

Targeted Screening of Curcumin Derivatives as Pancreatic Lipase Inhibitors Using Computer-Aided Drug Design

Curcumin has demonstrated promising preclinical antiobesity effects, but its low bioavailability makes it difficult to exert its full effect at a suitable dose. The objective of this study was to screen curcumin derivatives with enhanced bioavailability and lipid-lowering activity under the guidance of computer-aided drug design (CADD). CAAD was used to perform virtual assays on curcumin derivatives to assess their pharmacokinetic properties and effects on pancreatic lipase activity. Subsequently, 19 curcumin derivatives containing 5 skeletons were synthesized to confirm the above virtual assay. The in vitro pancreatic lipase inhibition assay was employed to determine the half-maximal inhibitory concentration (IC50) of these 19 curcumin derivatives. Based on CADD analysis and in vitro pancreatic lipase inhibition, 2 curcumin derivatives outperformed curcumin in both aspects. Microscale thermophoresis (MST) experiments were employed to assess the binding equilibrium constants (K d) of the aforementioned 2 curcumin derivatives, curcumin, and the positive control drug with pancreatic lipase. Through virtual screening utilizing a chemoinformatics database and molecular docking, 6 derivatives of curcumin demonstrated superior solubility, absorption, and pancreatic lipase inhibitory activity compared to curcumin. The IC50 value for 1,7-bis(4-hydroxyphenyl)heptane-3,5-dione (C4), which displayed the most effective inhibitory effect, was 42.83 μM, while the IC50 value for 1,7-bis(4-hydroxy-3-methoxyphenyl)heptane-3,5-dione (C6) was 98.62 μM. On the other hand, the IC50 value for curcumin was 142.24 μM. The MST experiment results indicated that the K d values of C4, C6, and curcumin were 2.91, 18.20, and 23.53 μM, respectively. The results of the activity assays exhibited a relatively high degree of concordance with the outcomes yielded by CADD screening. Under the guidance of CADD, the targeted screening of curcumin derivatives with excellent properties in this study exhibited high-efficiency and low-cost benefits.

Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies

Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.

Retracted: High-Throughput Screening and Molecular Dynamics Simulation of Natural Products for the Identification of Anticancer Agents against MCM7 Protein

[This retracts the article DOI: 10.1155/2022/8308192.].