Caio Cheohen

Background: The development of multitarget drugs capable of simultaneously inhibiting SARS-CoV-2 proteases—3CL^pro and PL^pro—may enhance therapeutic efficacy against COVID-19. Given the historical use of Traditional Chinese Medicine (TCM) in the management of respiratory diseases, phenylethanoid glycosides (PGs) represent an attractive and chemically diverse natural product scaffold for the discovery of antiviral agents. Objectives: This study aimed to identify promising candidates within this class capable of simultaneously inhibiting both target proteases. Methods: The PG structures described in the literature between 1950 and 2020 were gathered and curated to construct a dedicated database, which was subsequently subjected to virtual screening. In silico ADMETox predictions and 2D ligand–protein interaction analyses were then employed to evaluate the identified hit PGs. Ligand stability within the binding sites of the proteases was further assessed using free energy landscape (FEL) and MM/GBSA calculations, while enzymatic inhibition of the commercial PG was evaluated via FRET assays. Results: Virtual screening identified 22 PGs with multitarget potential, predominantly sourced from Asia, followed by the Americas and Europe. The hit compound magnoloside I is found in Magnolia officinalis, a species widely used in TCM for respiratory conditions and officially prescribed during the COVID-19 pandemic. A second hit, calceolarioside B, inhibited more than 90% of the enzymatic activity of both proteases in the FRET assay. Conclusions: Together, these findings highlight phenylethanoid glycosides as promising scaffolds for dual protease inhibition.

The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the critical need for accurate prediction of disease severity to optimize healthcare resource allocation and patient management. The spike protein, which facilitates viral entry into host cells, exhibits high mutation rates, particularly in the receptor-binding domain, influencing viral pathogenicity. Artificial intelligence approaches, such as deep learning, offer promising solutions for leveraging genomic and clinical data to predict disease outcomes. Objective: This study aimed to develop a hybrid CNN-LSTM deep learning model to predict COVID-19 severity using spike protein sequences and associated clinical metadata from South American patients. Methods: We retrieved 9,570 spike protein sequences from the GISAID database, of which 3,467 met inclusion criteria after standardization. The dataset included 2,313 severe and 1,154 mild cases. A feature engineering pipeline extracted features from sequences, while demographic and clinical variables were one-hot encoded. A hybrid CNN-LSTM architecture was trained, combining CNN layers for local pattern extraction and an LSTM layer for long-term dependency modeling. Results: The model achieved an F1 score of 82.92%, ROC-AUC of 0.9084, precision of 83.56%, and recall of 82.85%, demonstrating robust classification performance. Training stabilized at 85% accuracy with minimal overfitting. The most prevalent lineages (P.1, AY.99.2) and clades (GR, GK) aligned with regional epidemiological trends, suggesting potential associations between viral genetics and clinical outcomes. Conclusion: The CNN-LSTM hybrid model effectively predicted COVID-19 severity using spike protein sequences and clinical data, highlighting the utility of AI in genomic surveillance and precision public health. Despite limitations, this approach provides a framework for early severity prediction in future outbreaks.

The LABEXTRACT plant extract bank, featuring diverse members of the Myrtaceae family from Brazilian hot spot regions, provides a promising avenue for bioprospection. Given the pivotal roles of the Spike protein and 3CL^pro and PL^pro proteases in SARS-CoV-2 infection, this study delves into the correlations between the Myrtaceae species from the Atlantic Forest and these targets, as well as an antiviral activity through both in vitro and in silico analyses. The results uncovered notable inhibitory effects, with Eugenia prasina and E. mosenii standing out, while E. mosenii proved to be multitarget, presenting inhibition values above 72% in the three targets analyzed. All extracts inhibited viral replication in Calu-3 cells (EC₅₀ was lower than 8.3 µg·mL⁻¹). Chemometric analyses, through LC-MS/MS, encompassing prediction models and molecular networking, identified potential active compounds, such as myrtucommulones, described in the literature for their antiviral activity. Docking analyses showed that one undescribed myrtucommulone (m/z 841 [M − H]⁻) had a higher fitness score when interacting with the targets of this study, including ACE2, Spike, PL^pro and 3CL^pro of SARS-CoV-2. Also, the study concludes that Myrtaceae extracts, particularly from E. mosenii and E. prasina, exhibit promising inhibitory effects against crucial stages in SARS-CoV-2 infection. Compounds like myrtucommulones emerge as potential anti-SARS-CoV-2 agents, warranting further exploration.

Coronavirus disease (COVID-19) pandemic has infected 630 million people and led to 6.59 million deaths worldwide since its outbreak. To control COVID-19 advance, finding new molecules with potential to inhibit viral spread is pivotal. Papain-like protease (PLpro) is one of the most interesting targets of pharmacological inhibition since it is implicated not only in viral replication but also in modulation of host immune response. Natural products are of great interest to the pharmaceutical industry due to their diverse structure and biological activities. The NuBBEDB (Nuclei of Bioassays, Biosynthesis and Ecophysiology of Natural Products Database) is an excellent source of natural products (NPs) from the Brazilian flora. In this study, we performed virtual screening, molecular dynamics, and binding energy analyses of the NuBBEDB library to target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) papain-like protease (PLpro), the virus’s protease essential for replication. Among the top-ranked molecules, the indole alkaloids raputindoles A, C, and D emerged as potential SARS-CoV-2 inhibitors, showing significant interactions with the pivotal Beta-Loop-2 (BL2) region, including the catalytic Y268 residue. Notably, raputindole D displayed enhanced stabilization of the BL2 region, while raputindole C exhibited superior overall stability. These in silico findings suggest that raputindoles, especially D, might offer therapeutic value against COVID-19, laying the groundwork for further experimental evaluations.

Antivirals are substances that inhibit viral infection or virus replication, acting as drugs to treat viral diseases. However, due the diversity of pathogens, it is important to seek new antivirals. Among the options, repositioning already approved drugs is a cheaper and faster strategy when compared to classical research and development methods. Since there is a lack of compiled and standardized data on these drugs, this work aims to build a database of in vitro antiviral tests. Thus, the compounds and their information were obtained through publications of in vitro methods for testing antiviral drugs, we created six databases covering SMILES, MOL, SDF 2D, MOL2, PDB and PDBQT extensions, classified by the presence and/or absence of antiviral activity. Each file contains its IUPAC name and structural data in up to three dimensions.

At the end of 2019 a new coronavirus surfaced in China, SARS-CoV-2, responsible for the ongoing pandemic. There is a need for novel and stable therapies to help patients of COVID-19. Drug repositioning is a strategy to quickly find medicines already used to treatment to another pathology. In this work, we used the PLpro as molecular target for it being responsible for cleaving other viral proteins and interfering with the immune system. In the Brazilian Pharmacopeia is described many different Active Pharmaceutical Ingredients (API) used in Brazil and the world. Using the in silico techniques of virtual screening, the top 44 API pass through Toxicity prediction, where 36 API prove to not be mutagenic. Using molecular weight, distance to the protein, and literature information 19 API go through prediction of chemical interactions, we determine the top 6 APIs with the best chance of interacting with the PLpro. With this result, we determine new possible API that will be tested in vitro to determine its ability to inhibit SARS-CoV-2’s PLpro, and could be readily made available to the infected populous.

The SARS-CoV-2 virus infection led to millions of deaths during the COVID-19 pandemic. Hundreds of workers from several other Brazilian cities, as well as from other countries, arrive daily in Macaé to work in the oil supply chain, making this city a putative hotspot for the introduction of new viral lineages. In this study, we performed a genomic survey of SARS-CoV-2 samples from Macaé during the first outbreak of COVID-19, combined with clinical data and a molecular integrative analysis. First, phylogenomic analyses showed a high occurrence of viral introduction events and the establishment of local transmissions in Macaé, including the ingression and spread of the B.1.1.28 lineage in the municipality from June to August 2020. Second, SARS-CoV-2 mutations were identified in patients with distinct levels of COVID-19 severity. Third, molecular interactions of the mutated spike protein from three B.1.1.33 local samples and human ACE2 showed higher interactions than that of the wild-type spike protein from the ancestral virus. Altogether, these results elucidate the SARS-CoV-2 genomic profile in a strategic Brazilian city and further explore the functional aspects of SARS-CoV-2 with a characterization of emerging viral mutations associated with clinical data and the potential targets for drug development against SARS-CoV-2.

Active Pharmaceutical Ingredients (APIs) are molecules that can be used for the manufacturing of Drugs. The Brazilian Health Regulatory Agency (Agência Nacional de Vigilância Sanitária) is responsible for the oversight and approval of production and distribution of all drugs in Brazilian territory. Four different databases, including 336 out of the 346 total APIs, were created from the APIs text information available in the 6th edition of the Brazilian pharmacopeia, volume 2, “Active Pharmaceutical Ingredients” monography. Each database is composed by a different extension file, they are: two-dimensional sdf, three-dimensional sdf, mol2 and PDBQT file extensions, converted by using OpenBabel and Marvin Sketch software.

The novel coronavirus SARS-CoV-2 has been affecting the world, causing severe pneumonia and acute respiratory syndrome, leading people to death. Therefore, the search for anti-SARS-CoV-2 compounds is pivotal for public health. Natural products may present sources of bioactive compounds; among them, flavonoids are known in literature for their antiviral activity. Siparuna species are used in Brazilian folk medicine for the treatment of colds and flu. This work describes the isolation of 3,3′,4′-tri-O-methyl-quercetin, 3,7,3′,4′-tetra-O-methyl-quercetin (retusin), and 3,7-di-O-methyl-kaempferol (kumatakenin) from the dichloromethane extract of leaves of Siparuna cristata (Poepp. & Endl.) A.DC., Siparunaceae, using high-speed countercurrent chromatography in addition to the investigation of their inhibitory effect against SARS-CoV-2 viral replication. Retusin and kumatakenin inhibited SARS-CoV-2 replication in Vero E6 and Calu-3 cells, with a selective index greater than lopinavir/ritonavir and chloroquine, used as control. Flavonoids and their derivatives may stand for target compounds to be tested in future clinical trials to enrich the drug arsenal against coronavirus infections. Graphical abstract