Identification of bio-active food compounds as potential SARS-CoV-2 PLpro inhibitors-modulators via negative image-based screening and computational simulations

Predicting anti-COVID-19 potential: in silico analysis of Mauritine compound from Ziziphus-spina christi as a promising papain-like protease (PLpro) inhibitor

The COVID-19 pandemic caused by the SARS-CoV-2 virus, recognized by the World Health Organization (WHO), has led to 164,523,894 confirmed cases and 3,412,032 deaths globally as of May 20, 2021. SARS-CoV-2 encodes crucial proteases for its replication cycle, including the papain-like protease (PLpro), presenting a potential target for developing COVID-19 treatments. Mauritine, a cyclopeptide alkaloid found in the Ziziphus-spina christi plant, exhibits antiviral properties and was investigated for its affinity and toxicity towards PLpro using molecular docking through MGLTools 1.5.6 with Autodock Tools 4.2. Preceding this, toxicity and ADME prediction were performed via Toxtree 3.1.0 software and SwissADME servers. Results from molecular docking revealed free binding energy values of -8.58; -7.73; -8.36; -6.07; -6.67; -7.83; -7.67; -7.40; and -6.87 Kcal/mol for Mauritine-A, Mauritine-B, Mauritine-C, Mauritine-D, Mauritine-F, Mauritine-H, Mauritine-J, Mauritine-L, and Mauritine-M, respectively. Correspondingly, inhibition constants were 0.51724; 2.14; 0.7398; 35.43; 12.95; 1.83; 2.38; 3.80; and 9.17 µM, respectively. Interactions observed included hydrogen bonds, hydrophobic interactions, and electrostatic interactions between the Mauritine compounds and the receptor. Mauritine-A and Mauritine-C emerged as a promising anti-COVID-19 candidate due to its superior affinity compared to other derivatives, as indicated by research findings. Interestingly, Mauritine-A and Mauritine-C exhibits notable stability as depicted by the RMSD and RMSF graphs, along with a considerable MM-PBSA binding free energy value of -162.431 and -137.500 kJ/mol, respectively.Communicated by Ramaswamy H. Sarma.

Screening and Identification of Anti-Inflammatory Compounds from Erdong Gao via Multiple-Target-Cell Extraction Coupled with HPLC-Q-TOF-MS/MS and Their Structure-Activity Relationship

Erdong Gao (EDG), consisting equally of roots of Asparagi Radix and Ophiopogonis Radix, is a well-known traditional Chinese formulation that has been used to treat cough and throat pain for centuries. However, the bioactive components in EDG remain to be elucidated. In this study, a rapid and effective method involving live cell bio-specific extraction and HPLC-Q-TOF-MS/MS was established to rapidly screen and identify the anti-inflammatory compounds of an EDG extract. One hundred and twenty-four components were identified in EDG extract using HPLC-Q-TOF-MS/MS analysis. After co-incubation with 16HBE, HPAEpiCs and HUVECs, which have been validated as the key target cells for pulmonary diseases, sixteen components were demonstrated to exhibit an affinity for binding to them. Furthermore, fifteen components were subsequently verified to exert anti-inflammatory effects on lipopolysaccharide (LPS)-induced 16HBE, HPAEpiCs and HUVECs via inhibiting the release of TNF-α and IL-6, indicating that nine steroidal saponins may possess potential for the treatment of lung-related diseases. Taken together, our study provides evidence that live cell biospecific extraction combined with the HPLC-Q-TOF-MS/MS technique was an efficient method for rapid screening potential bioactive components in traditional Chinese medicines and the structure activity relationship of steroidal saponins in EDG was summarized for the first time.

Virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is considered the etiological agent of the disease that caused the COVID-19 pandemic, and for which there is currently no effective treatment. This pandemic has shown that the rapid identification of therapeutic compounds is critical (when a new virus with high transmissibility occurs) to prevent or reduce as much as possible the loss of human lives. To meet the urgent need for drugs, many strategies were applied for the discovery, respectively the identification of potential therapies / drugs for SARS-CoV-2. Molecular docking and virtual screening are two of the in silico tools/techniques that provided the identification of few SARS-CoV-2 inhibitors, removing ineffective or less effective drugs and thus preventing the loss of resources such as time and additional costs. The main target of this review is to provide a comprehensive overview of how in-silico tools have been used in the crisis management of anti-SARS-CoV-2 drugs, especially in virtual screening of substances used in the treatment of SARS-CoV-2 infection and analysis of compounds with known action on structurally similar proteins from other viruses; also, completions were added to the way in which these methods came to meet the requirements of biomedical research in the field. Moreover, the importance and impact of the topic approached for researchers was highlighted by conducting an extensive bibliometric analysis.