Combining computational and experimental evidence on the activity of antimalarial drugs on papain-like protease of SARS-CoV-2: A repurposing study

Identification of SARS-CoV-2 Main Protease Inhibitors Using Chemical Similarity Analysis Combined with Machine Learning

SARS-CoV-2 Main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome, which is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development. Herein, we performed a large-scale virtual screening by comparing multiple structural descriptors of reference molecules with reported anti-coronavirus activity against a library with >17 million compounds. Further filtering, performed by applying two machine learning algorithms, identified eighteen computational hits as anti-SARS-CoV-2 compounds with high structural diversity and drug-like properties. The activities of twelve compounds on Mpro's enzymatic activity were evaluated by fluorescence resonance energy transfer (FRET) assays. Compound 13 (ZINC13878776) significantly inhibited SARS-CoV-2 Mpro activity and was employed as a reference for an experimentally hit expansion. The structural analogues 13a (ZINC4248385), 13b (ZNC13523222), and 13c (ZINC4248365) were tested as Mpro inhibitors, reducing the enzymatic activity of recombinant Mpro with potency as follows: 13c > 13 > 13b > 13a. Then, their anti-SARS-CoV-2 activities were evaluated in plaque reduction assays using Vero CCL81 cells. Subtoxic concentrations of compounds 13a, 13c, and 13b displayed in vitro antiviral activity with IC50 in the mid micromolar range. Compounds 13a-c could become lead compounds for the development of new Mpro inhibitors with improved activity against anti-SARS-CoV-2.

Target identification by structure-based computational approaches: Recent advances and perspectives

The use of computational techniques in the early stages of drug discovery has recently experienced a boost, especially in the target identification step. Finding the biological partner(s) for new or existing synthetic and/or natural compounds by "wet" approaches may be challenging; therefore, preliminary in silico screening is even more recommended. After a brief overview of some of the most known target identification techniques, recent advances in structure-based computational approaches for target identification are reported in this digest, focusing on Inverse Virtual Screening and its recent applications. Moreover, future perspectives concerning the use of such methodologies, coupled or not with other approaches, are analyzed.

Investigation on the Essential Oils of the Achillea Species: From Chemical Analysis to the In Silico Uptake against SARS-CoV-2 Main Protease

In this study, phytochemicals extracted from three different Achillea genera were identified and analyzed to be screened for their interactions with the SARS-CoV-2 main protease. In particular, the antiviral potential of these natural products against the SARS-CoV-2 main protease was investigated, as was their effectiveness against the SARS-CoV-1 main protease as a standard (due to its high similarity with SARS-CoV-2). These enzymes play key roles in the proliferation of viral strains in the human cytological domain. GC-MS analysis was used to identify the essential oils of the Achillea species. Chemi-informatics tools, such as AutoDock 4.2.6, SwissADME, ProTox-II, and LigPlot, were used to investigate the action of the pharmacoactive compounds against the main proteases of SARS-CoV-1 and SARS-CoV-2. Based on the binding energies of kessanyl acetate, chavibetol (m-eugenol), farnesol, and 7-epi-β-eudesmol were localized at the active site of the coronaviruses. Furthermore, these molecules, through hydrogen bonding with the amino acid residues of the active sites of viral proteins, were found to block the progression of SARS-CoV-2. Screening and computer analysis provided us with the opportunity to consider these molecules for further preclinical studies. Furthermore, considering their low toxicity, the data may pave the way for new in vitro and in vivo research on these natural inhibitors of the main SARS-CoV-2 protease.