Following the coronavirus disease-2019 outbreak caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), there is an ongoing need to seek drugs that target COVID-19. First off, novel drugs have a long development cycle, high investment cost, and are high risk. Second, novel drugs must be evaluated for activity, efficacy, safety, and metabolic performance, contributing to the development cycle, investment cost, and risk. We searched the Cochrane COVID-19 Study Register (including PubMed, Embase, CENTRAL, ClinicalTrials.gov, WHO ICTRP, and medRxiv), Web of Science (Science Citation Index, Emerging Citation Index), and WHO COVID-19 Coronaviral Disease Global Literature to identify completed and ongoing studies as of February 20, 2024. We evaluated the pharmacological effects, in vivo and in vitro data of the 16 candidates in the paper. The difficulty of studying these candidates in clinical trials involving COVID-19 patients, dosage of repurposed drugs, etc. is discussed in detail. Ultimately, Metformin is more suitable for prophylactic administration or mildly ill patients; the combination of Oseltamivir, Tamoxifen, and Dexamethasone is suitable for moderately and severely ill patients; and more clinical trials are needed for Azvudine, Ribavirin, Colchicine, and Cepharanthine to demonstrate efficacy.

In the colorectal cancer (CRC) niche, the transcription factors signal transducer and activator of transcription 3 (STAT3) and nuclear factor-κB (NF-κB) are hyperactivated in both malignant cells and tumor-infiltrating leukocytes (TILs) and cooperate to maintain cancer cell proliferation/survival and drive protumor inflammation. Through drug repositioning studies, the anthelmintic drug rafoxanide has recently emerged as a potent and selective antitumor molecule for different types of cancer, including CRC. Here, we investigate whether rafoxanide could negatively modulate STAT3/NF-κB and inflammation-associated CRC. The antineoplastic effect of rafoxanide was explored in a murine model of CRC resembling colitis-associated disease. Cell proliferation and/or STAT3/NF-κB activation were evaluated in colon tissues taken from mice with colitis-associated CRC, human CRC cells, and CRC patient-derived explants and organoids after treatment with rafoxanide. The STAT3/NF-κB activation and cytokine production/secretion were assessed in TILs isolated from CRC specimens and treated with rafoxanide. Finally, we investigated the effects of TIL-derived supernatants cultured with or without rafoxanide on CRC cell proliferation and STAT3/NF-κB activation. The results showed that rafoxanide restrains STAT3/NF-κB activation and inflammation-associated colon tumorigenesis in vivo without apparent effects on normal intestinal cells. Rafoxanide markedly reduces STAT3/NF-κB activation in cultured CRC cells, CRC-derived explants/organoids, and TILs. Finally, rafoxanide treatment impairs the ability of TILs to produce protumor cytokines and promote CRC cell proliferation. We report the novel observation that rafoxanide negatively affects STAT3/NF-κB oncogenic activity at multiple levels in the CRC microenvironment. Our data suggest that rafoxanide could potentially be deployed as an anticancer drug in inflammation-associated CRC.

Drug-resistant parasitic nematodes pose a grave threat to plants, animals, and humans. An innovative paradigm for treating parasitic nematodes is emphasized in this opinion. This approach relies on repurposing methuosis (a death characterized by accumulation of large vacuoles) inducing anticancer drugs as anthelmintics. We review drugs/chemicals that have shown to kill nematodes or cancerous cells by inducing multiple vacuoles that eventually coalesce and rupture. This perspective additionally offers a succinct summary on Structure-Activity Relationship (SAR) of methuosis-inducing small molecules. This strategy holds promise for the development of broad-spectrum anthelmintics, shedding light on shared molecular mechanisms between cancer and nematodes in response to these inducers, thereby potentially transforming both therapeutic domains.

BACKGROUND: Cystic echinococcosis (CE) is a zoonotic disease caused by the larval stage of the dog tapeworm Echinococcus granulosus sensu lato (E. granulosus), with a worldwide distribution. The current treatment strategy for CE is insufficient. Limited drug screening models severely hamper the discovery of effective anti-echinococcosis drugs.
METHODS: In the present study, using high-content screening technology, we developed a novel high-throughput screening (HTS) assay by counting the ratio of propidium iodide-stained dead protoscoleces (PSCs) to the total number of PSCs. In vitro and ex vivo cyst viability assays were utilized to determine the effect of drugs on cyst viability.
RESULTS: Using the newly established HTS assay, we screened approximately 12,000 clinical-stage or The Food and Drug Administration (FDA)-approved small molecules from the Repurposing, Focused Rescue, and Accelerated Medchem (ReFRAME) library, as well as the LOPAC1280 and SelleckChem libraries, as a strategic approach to facilitate the drug discovery process. Initial screening yielded 173 compounds with anti-echinococcal properties, 52 of which demonstrated dose-response efficacy against E. granulosus PSCs in vitro. Notably, two agents, omaveloxolone and niclosamide, showed complete inhibition upon further validation in cyst and microcyst viability assays in vitro after incubation for 3 days, and in an ex vivo cyst viability assay using cysts isolated from the livers of mice infected with E. granulosus, as determined by morphological assessment.
CONCLUSIONS: Through the development of a novel HTS assay and by repurposing libraries, we identified omaveloxolone and niclosamide as potent inhibitors against E. granulosus. These compounds show promise as potential anti-echinococcal drugs, and our strategic approach has the potential to promote drug discovery for parasitic infections.

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

We present an in silico approach for drug discovery, dubbed connectivity enhanced structure activity relationship (ceSAR). Building on the landmark LINCS library of transcriptional signatures of drug-like molecules and gene knockdowns, ceSAR combines cheminformatic techniques with signature concordance analysis to connect small molecules and their targets and further assess their biophysical compatibility using molecular docking. Candidate compounds are first ranked in a target structure-independent manner, using chemical similarity to LINCS analogs that exhibit transcriptomic concordance with a target gene knockdown. Top candidates are subsequently rescored using docking simulations and machine learning-based consensus of the two approaches. Using extensive benchmarking, we show that ceSAR greatly reduces false-positive rates, while cutting run times by multiple orders of magnitude and further democratizing drug discovery pipelines. We further demonstrate the utility of ceSAR by identifying and experimentally validating inhibitors of BCL2A1, an important antiapoptotic target in melanoma and preterm birth-associated inflammation.

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 is an unparalleled health risk, needing fast antiviral medication development. One of the most effective strategies for developing therapies against novel and emerging viruses is drug repurposing. Recently, systems biology approaches toward the discovery of repurposing medications are gaining prominence.
OBJECTIVE: This study aimed to implement a systems biology approach to identify crucial drug targets as well as potential drug candidates against COVID infection.
METHODS: Our approach utilizes differential gene expression in COVID conditions that enable the construction of a protein-protein interaction (PPI) network. Core clusters were extracted from this network, followed by molecular enrichment analysis. This process identified critical drug targets and potential drug candidates targeting various stages of COVID-19 infection.
RESULTS: The network was built using the top 200 differently expressed genes in mild, moderate, and severe COVID-19 infections. Top 3 clusters for each disease condition were identified, representing the core mechanism of the network. Molecular enrichment revealed the majority of the pathways in the mild state were associated with transcription regulation, protein folding, angiogenesis, and cytokine-signaling pathways. Whereas, the enriched pathways in moderate and severe disease states were predominately linked with the immune system and apoptotic processes, which include NF-kappaB signaling, cytokine signaling, TNF-mediated signaling, and oxidative stress-induced cell death. Further analysis identifies 28 potential drugs that can be repurposed to treat moderate and severe COVID-19, most of which are currently used in cancer treatment.
CONCLUSIONS: Interestingly, some of the proposed drugs have demonstrated inhibitory effects against SARS-CoV-2, as supported by literature evidence. Overall, the drug repurposing method described here will help develop potential antiviral medications to treat emerging COVID strains.

Dengue fever, prevalent in Southeast Asian countries, currently lacks effective pharmaceutical interventions for virus replication control. This study employs a strategy that combines machine learning (ML)-based quantitative-structure-activity relationship (QSAR), molecular docking, and molecular dynamics simulations to discover potential inhibitors of the NS3 protease of the dengue virus. We used nine molecular fingerprints from PaDEL to extract features from the NS3 protease dataset of dengue virus type 2 in the ChEMBL database. Feature selection was achieved through the low variance threshold, F-Score, and recursive feature elimination (RFE) methods. Our investigation employed three ML models - support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) - for classifier development. Our SVM model, combined with SVM-RFE, had the best accuracy (0.866) and ROC_AUC (0.964) in the testing set. We identified potent inhibitors on the basis of the optimal classifier probabilities and docking binding affinities. SHAP and LIME analyses highlighted the significant molecular fingerprints (e.g. ExtFP69, ExtFP362, ExtFP576) involved in NS3 protease inhibitory activity. Molecular dynamics simulations indicated that amphotericin B exhibited the highest binding energy of -212 kJ/mol and formed a hydrogen bond with the critical residue Ser196. This approach enhances NS3 protease inhibitor identification and expedites the discovery of dengue therapeutics.

The increasing prevalence of non-alcoholic fatty liver disease (NAFLD) is a growing concern for the high incidence rate of hepatocellular carcinoma (HCC) globally. The progression of NAFLD to HCC is heterogeneous and non-linear, involving intermediate stages of non-alcoholic steatohepatitis (NASH), liver fibrosis, and cirrhosis. There is a high unmet clinical need for appropriate diagnostic, prognostic, and therapeutic options to tackle this emerging epidemic. Unfortunately, at present, there is no validated marker to identify the risk of developing HCC in patients suffering from NAFLD or NASH. Additionally, the current treatment protocols for HCC don\'t differentiate between viral infection or NAFLD-specific etiology of the HCC and have a limited success rate. The mammalian target of rapamycin complex 1 (mTORc1) is an important protein involved in many vital cellular processes like lipid metabolism, glucose homeostasis, and inflammation. These cellular processes are highly implicated in NAFLD and its progression to severe liver manifestations. Additionally, hyperactivation of mTORc1 is known to promote cell proliferation, which can contribute to the genesis and progression of tumors. Many mTORc1 inhibitors are being evaluated for different types of cancers under various phases of clinical trials. This paper deliberates on the strong pathological implication of the mTORc1 signaling pathway in NAFLD and its progression to NASH and HCC and advocates for a systematic investigation of known mTORc1 inhibitors in suitable pre-clinical models of HCC having NAFLD/NASH-specific etiology.

Advancing climate change increases the risk of future infectious disease outbreaks, particularly of zoonotic diseases, by affecting the abundance and spread of viral vectors. Concerningly, there are currently no approved drugs for some relevant diseases, such as the arboviral diseases chikungunya, dengue or zika. The development of novel inhibitors takes 10-15 years to reach the market and faces critical challenges in preclinical and clinical trials, with approximately 30% of trials failing due to side effects. As an early response to emerging infectious diseases, CavitOmiX allows for a rapid computational screening of databases containing 3D point-clouds representing binding sites of approved drugs to identify candidates for off-label use. This process, known as drug repurposing, reduces the time and cost of regulatory approval. Here, we present potential approved drug candidates for off-label use, targeting the ADP-ribose binding site of Alphavirus chikungunya non-structural protein 3. Additionally, we demonstrate a novel in silico drug design approach, considering potential side effects at the earliest stages of drug development. We use a genetic algorithm to iteratively refine potential inhibitors for (i) reduced off-target activity and (ii) improved binding to different viral variants or across related viral species, to provide broad-spectrum and safe antivirals for the future.