In Silico Evaluation of Iranian Medicinal Plant Phytoconstituents as Inhibitors against Main Protease and the Receptor-Binding Domain of SARS-CoV-2.

The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which initially appeared in Wuhan, China, in December 2019. Elderly individuals and those with comorbid conditions may be more vulnerable to this disease. Consequently, several research laboratories continue to focus on developing drugs to treat this infection because this disease has developed into a global pandemic with an extremely limited number of specific treatments available. Natural herbal remedies have long been used to treat illnesses in a variety of cultures. Modern medicine has achieved success due to the effectiveness of traditional medicines, which are derived from medicinal plants. The objective of this study was to determine whether components of natural origin from Iranian medicinal plants have an antiviral effect that can prevent humans from this coronavirus infection using the most reliable molecular docking method; in our case, we focused on the main protease (Mpro) and a receptor-binding domain (RBD). The results of molecular docking showed that among 169 molecules of natural origin from common Iranian medicinal plants, 20 molecules (chelidimerine, rutin, fumariline, catechin gallate, adlumidine, astragalin, somniferine, etc.) can be proposed as inhibitors against this coronavirus based on the binding free energy and type of interactions between these molecules and the studied proteins. Moreover, a molecular dynamics simulation study revealed that the chelidimerine-Mpro and somniferine-RBD complexes were stable for up to 50 ns below 0.5 nm. Our results provide valuable insights into this mechanism, which sheds light on future structure-based designs of high-potency inhibitors for SARS-CoV-2.

PRIMoRDiA: A Software to Explore Reactivity and Electronic Structure in Large Biomolecules.

Plenty of enzymes with structural data do not have their mechanism of catalysis elucidated. Reactivity descriptors, theoretical quantities generated from resolved electronic structure, provide a way to predict and rationalize chemical processes of such systems. In this Application Note, we present PRIMoRDiA (PRIMoRDiA Macromolecular Reactivity Descriptors Access), a software built to calculate the reactivity descriptors of large biosystems by employing an efficient and accurate treatment of the large output files produced by quantum chemistry packages. Here, we show the general implementation details and the software main features. Calculated descriptors were applied for a set of enzymatic systems in order to show their relevance for biological studies and the software potential for use in large scale. Also, we test PRIMoRDiA to aid in the interaction depiction between the SARS-CoV-2 main protease and a potential inhibitor.

Structure-Based Virtual Screening to Discover Potential Lead Molecules for the SARS-CoV-2 Main Protease.

The COVID-19 disease is caused by a new strain of the coronavirus family (SARS-CoV-2), and it has affected at present millions of people all over the world. The indispensable role of the main protease (Mpro) in viral replication and gene expression makes this enzyme an attractive drug target. Therefore, inhibition of SARS-CoV-2 Mpro as a proposition to halt virus ingression is being pursued by scientists globally. Here we carried out a study with two objectives: the first being to perform comparative protein sequence and 3D structural analysis to understand the effect of 12 point mutations on the active site. Among these, two mutations, viz., Ser46 and Phe134, were found to cause a significant change at the active sites of SARS-CoV-2. The Ser46 mutation present at the entrance of the S5 subpocket of SARS-CoV-2 increases the contribution of other two hydrophilic residues, while the Phe134 mutation, present in the catalytic cysteine loop, can cause an increase in catalytic efficiency of Mpro by facilitating fast proton transfer from the Cys145 to His41 residue. It was observed that active site remained conserved among Mpro of both SARS-CoVs, except at the entrance of the S5 subpocket, suggesting sustenance of substrate specificity. The second objective was to screen the inhibitory effects of three different data sets (natural products, coronaviruses main protease inhibitors, and FDA-approved drugs) using a structure-based virtual screening approach. A total of 73 hits had a combo score >2.0. Eight different structural scaffold classes were identified, such as one/two tetrahydropyran ring(s), dipeptide/tripeptide/oligopeptide, large (approximately 20 atoms) cyclic peptide, and miscellaneous. The screened hits showed key interactions with subpockets of the active site. Further, molecular dynamics studies of selected screened compounds confirmed their perfect fitting into the subpockets of the active site. This study suggests promising structures that can fit into the SARS-CoV-2 Mpro active site and also offers direction for further lead optimization and rational drug design.