TY - JOUR
AU - Alhadrami, Hani A.
AU - Sayed, Ahmed M.
AU - Hassan, Hossam M.
AU - Youssif, Khayrya A.
AU - Gaber, Yasser
AU - Moatasim, Yassmin
AU - Kutkat, Omnia
AU - Mostafa, Ahmed
AU - Ali, Mohamed Ahmed
AU - Rateb, Mostafa E.
AU - Abdelmohsen, Usama Ramadan
AU - Gamaleldin, Noha M.
PY - 2021
DA - May
TI - Cnicin as an anti-SARS-CoV-2: an integrated in silico and in vitro approach for the rapid identification of potential COVID-19 therapeutics
JO - Antibiotics
VL - 10
IS - 5
DO - https://doi.org/10.3390/antibiotics10050542
AB - Since the emergence of the SARS-CoV-2 pandemic in 2019, it has remained a significant global threat, especially with the newly evolved variants. Despite the presence of different COVID-19 vaccines, the discovery of proper antiviral therapeutics is an urgent necessity. Nature is considered as a historical trove for drug discovery, especially in global crises. During our efforts to discover potential anti-SARS CoV-2 natural therapeutics, screening our in-house natural products and plant crude extracts library led to the identification of C. benedictus extract as a promising candidate. To find out the main chemical constituents responsible for the extract’s antiviral activity, we utilized recently reported SARS CoV-2 structural information in comprehensive in silico investigations (e.g., ensemble docking and physics-based molecular modeling). As a result, we constructed protein–protein and protein–compound interaction networks that suggest cnicin as the most promising anti-SARS CoV-2 hit that might inhibit viral multi-targets. The subsequent in vitro validation confirmed that cnicin could impede the viral replication of SARS CoV-2 in a dose-dependent manner, with an IC50 value of 1.18 µg/mL. Furthermore, drug-like property calculations strongly recommended cnicin for further in vivo and clinical experiments. The present investigation highlighted natural products as crucial and readily available sources for developing antiviral therapeutics. Additionally, it revealed the key contributions of bioinformatics and computer-aided modeling tools in accelerating the discovery rate of potential therapeutics, particularly in emergency times like the current COVID-19 pandemic.
PB - MDPI
UR - https://research-portal.uws.ac.uk/en/publications/9346604d-7368-4286-b202-04fe1fbdfe20
KW - Coronavirus (COVID-19)
ER