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In-silico predicting as a tool to develop plant-based biomedicines and nanoparticles: Lycium shawii metabolites

Afrah E. MohammedDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaFuád AmeénDepartment of Botany & Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi ArabiaKawther AabedDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaRasha Saad Suliman‏Department of Pharmaceutical Sciences, College of Pharmacy, King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia; King Abdullah International Medical Research Center (KAIMRC), Riyadh, Saudi ArabiaSahar S. Alghamdi‏Department of Pharmaceutical Sciences, College of Pharmacy, King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia; King Abdullah International Medical Research Center (KAIMRC), Riyadh, Saudi ArabiaFatmah Ahmed SafhiDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaDalal Sulaiman AlshayaDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaHayat Ali AlafariDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaAreej S. JalalDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaAreej A. AlosaimiDepartment of Biology, College of Science, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi ArabiaSalha M. ALshamraniDepartment of Biology, College of Science, Jeddah University, Jeddah, Saudi ArabiaIshrat RahmanDepartment of Basic Dental Sciences, College of Dentistry, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia. Electronic address: [email protected]
2022en
ABI

Аннотация

In silico approach helps develop biomedicines and is useful for exploring the pharmacology of potential therapeutics using computer-simulated models. In vitro assays were used to determine the anti-microbial and cytotoxic efficacies of silver nanoparticles (AgNPs) synthesized with the shrub Lycium shawii. In silico predicting was performed to assess the L. shawii metabolites identified using QTOF-LCMS for their pharmacological properties. L. shawii mediated AgNPs were synthesized and characterized (FTIR, TEM, SEM, DLS and EDX). The anti-bacterial efficacies of L. shawii extract, AgNPs, and penicillin-conjugated AgNPs (pen-AgNPs) were determined. The cytotoxicity of the AgNPs was measured against colorectal cancer cell line (HCT116), normal breast epithelium (MCF 10 A), and breast cancer cell line (MDA MB 231). Five molecules (costunolide, catechin, emodin, lyciumaside, and aloe emodin 11-O-rhamnoside) were detected in the L. shawii extract. AgNPs (69 nm) were spherical with crystallographic structure. All three agents prepared showed inhibitory activity against the tested bacteria, the most efficacious being pen-AgNPs. High cytotoxicity of AgNPs (IC50 62 μg/ml) was observed against HCT116, IC50 was 78 μg/ml for MCF 10 A, and 250 μg/ml for MDA MB 231, of which cells showed apoptotic features under TEM examination. The in silico approach indicated that the carbonic anhydrase IX enzyme was the target molecule mediating anti-cancer and anti-bacterial activities and that emodin was the metabolite in action. Combining in vitro studies and in silico molecular target prediction helps find novel therapeutic agents. Among L. shawii metabolites, emodin is suggested for further studies as an agent for drug development against pathogenic bacteria and cancer.

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