Establishment of a high-throughput screening platform based on drug repurposing targeting alpha-1-acid glycoprotein and discovery of potential weight loss drugs / 药学实践杂志

Objective Alpha-1-acid glycoprotein （ORM） was a new target for the development of weight loss drugs. To search for potential weight loss drugs that could target ORM from the compound library of already marketed drugs based on drug repurposing. Methods The pGL4.20-ORM1 promoter recombinant plasmid was contructed and validated, and then a lentiviral vector was utilized to establish stable AML12 cell lines expressing ORM1 promoter-LUC-PURO. This cell line was employed for high-throughput screening of compounds from the marketed drug library, and the luminescence value of the cells was characterized by enzyme marker. Results Primary screening and secondary screening of 1 470 compounds identified 42 compounds that increased ORM1 promoter expression and could be used for further weight loss effect assessment. Conclusion This study successfully constructed LV-AML12-ORM1 promoter-LUC-PURO stable expression cell lines using lentiviral vectors, laying a foundation for efficient and stable screening of weight loss drugs targeting ORM.

Trilogy of drug repurposing for developing cancer and chemotherapy-induced heart failure co-therapy agent

Chemotherapy-induced complications, particularly lethal cardiovascular diseases, pose significant challenges for cancer survivors. The intertwined adverse effects, brought by cancer and its complication, further complicate anticancer therapy and lead to diminished clinical outcomes. Simple supplementation of cardioprotective agents falls short in addressing these challenges. Developing bi-functional co-therapy agents provided another potential solution to consolidate the chemotherapy and reduce cardiac events simultaneously. Drug repurposing was naturally endowed with co-therapeutic potential of two indications, implying a unique chance in the development of bi-functional agents. Herein, we further proposed a novel "trilogy of drug repurposing" strategy that comprises function-based, target-focused, and scaffold-driven repurposing approaches, aiming to systematically elucidate the advantages of repurposed drugs in rationally developing bi-functional agent. Through function-based repurposing, a cardioprotective agent, carvedilol (CAR), was identified as a potential neddylation inhibitor to suppress lung cancer growth. Employing target-focused SAR studies and scaffold-driven drug design, we synthesized 44 CAR derivatives to achieve a balance between anticancer and cardioprotection. Remarkably, optimal derivative 43 displayed promising bi-functional effects, especially in various self-established heart failure mice models with and without tumor-bearing. Collectively, the present study validated the practicability of the "trilogy of drug repurposing" strategy in the development of bi-functional co-therapy agents.

Drug repurposing for Alzheimer''s disease using knowledge graph embedding / 中国药科大学学报

@#Alzheimer''s disease (AD) has brought to us huge medical and economic burdens, and so discovery of its therapeutic drugs is of great significance.In this paper, we utilized knowledge graph embedding (KGE) models to explore drug repurposing for AD on the publicly available drug repurposing knowledge graph (DRKG).Specifically, we applied four KGE models, namely TransE, DistMult, ComplEx, and RotatE, to learn the embedding vectors of entities and relations on DRKG.By using three classical knowledge graph evaluation metrics, we then evaluated and compared the performance of these models as well as the quality of the learned embedded vectors.Based on our results, we selected the RotatE model for link prediction and identified 16 drugs that might be repurposed for the treatment of AD.Previous studies have confirmed the potential therapeutic effects of 12 drugs against AD, i.e., glutathione, haloperidol, capsaicin, quercetin, estradiol, glucose, disulfire, adenosine, paroxetine, paclitaxel, glybride and amitriptyline.Our study demonstrates that drug repurposing based on KGE may provide new ideas and methods for AD drug discovery.Moreover, the RotatE model effectively integrates multi-source information of DRKG, enabling promising AD drug repurposing.The source code of this paper is available at https://github.com/LuYF-Lemon-love/AD-KGE.

Research progress of feature-based deep learning for predicting compound-protein interaction / 中国药科大学学报

@#The prediction of compound-protein interaction (CPI) is a critical technological tool for discovering lead compounds and drug repurposing during the process of drug development.In recent years, deep learning has been widely used in CPI research, which has accelerated the development of CPI prediction in drug discovery.This review focuses on feature-based CPI prediction models.First, we described the datasets, as well as typical feature representation methods commonly used for compounds and proteins in CPI prediction.Based on the critical problems in modeling, we discussed models for CPI prediction from two perspectives: multimodal features and attention mechanisms.Then, the performance of 12 selected models was evaluated on 3 benchmark datasets for both classification and regression tasks.Finally, the review summarizes the existing challenges in this field and prospects for future directions.We believe that this investigation will provide some reference and insight for further research on CPI prediction.

Drug Repurposing of Clinically Approved Drugs to Target Epithelial-mesenchymal Transition Using Molecular Docking Approach

@#Introduction: Epithelial-mesenchymal transition (EMT) is a process of epithelial transformation into mesenchymal cells. It is also a process that contributes to the progression of fibrosis and cancer metastasis. Transforming growth factor-beta (TGF-β), as a potent inducer of EMT, has therefore became a potential therapeutic target. However, clinical developments of TGF-β inhibitors have been un-successful due to safety risks. Hence, drug repurposing of existing safe-to-use drugs could over-come this issue. Methods: In this study, the TGF-β receptor type 1 (ALK5) was selected as the target protein. Molecular docking was performed using known ALK5 inhibitors as positive controls. Clinical drugs with similar binding affinity and amino acid interaction were selected for in vitro experimental validation. Results: ALK5 inhibitor demonstrated binding affinities ranging from -11.2 to -9.5 kcal/mol. Analysis of amino acid interaction revealed that Val219, Ala230, Lys232, and Leu340 amino acid residues are crucial for binding. Subsequent screening of clinically approved drugs against ALK5 showed top five potential drugs (ergotamine, telmisartan, saquinavir, indinavir, and nelfinavir). The selected drugs were tested in TGF-β1-induced normal human bronchial epithelial cell line, BEAS-2B. Western blot analysis showed that the drugs did not exhibit inhibitory effects on the downregulation of epithelial proteins (E-cadherin) and upregulation of mesenchymal proteins (vimentin and α-smooth muscle actin). Conclusion: Based on these experimental outcome, it is postulated that the results from molecular docking were false positives. The tested drugs in this study could serve as negative controls in future screening against ALK5 protein.

Progress of the development of anti-COVID-19 drugs / 药学学报

Since the outbreak of the novel coronavirus (SARS-CoV-2) disease COVID-19 (also known as 2019-nCoV) caused by SARS-CoV-2 in the end of 2019, it has spread rapidly in worldwide. Besides developing effective vaccines, it is urgent to develop safe and effective anti-SARS-CoV-2 drugs to fight this disease. Paxlovid, molnupiravir, sotrovimab and bebtelovimab are urgently authorized by FDA have been proved to be effective against Omicron. This manuscript mainly reviews the recent progress of effective inhibitors against the virus in the world, including receptor inhibitors, antibodies, natural product inhibitors, synthetic inhibitors and broad-spectrum antiviral drugs that are effective against other RNA viruses.

ETCM v2.0: An update with comprehensive resource and rich annotations for traditional Chinese medicine

Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

Structural repurposing of SGLT2 inhibitor empagliflozin for strengthening anti-heart failure activity with lower glycosuria

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been reapproved for heart failure (HF) therapy in patients with and without diabetes. However, the initial glucose-lowering indication of SGLT2i has impeded their uses in cardiovascular clinical practice. A challenge of SGLT2i then becomes how to separate their anti-HF activity from glucose-lowering side-effect. To address this issue, we conducted structural repurposing of EMPA, a representative SGLT2 inhibitor, to strengthen anti-HF activity and reduce the SGLT2-inhibitory activity according to structural basis of inhibition of SGLT2. Compared to EMPA, the optimal derivative JX01, which was produced by methylation of C2-OH of the glucose ring, exhibited weaker SGLT2-inhibitory activity (IC50 > 100 nmol/L), and lower glycosuria and glucose-lowering side-effect, better NHE1-inhibitory activity and cardioprotective effect in HF mice. Furthermore, JX01 showed good safety profiles in respect of single-dose/repeat-dose toxicity and hERG activity, and good pharmacokinetic properties in both mouse and rat species. Collectively, the present study provided a paradigm of drug repurposing to discover novel anti-HF drugs, and indirectly demonstrated that SGLT2-independent molecular mechanisms play an important role in cardioprotective effects of SGLT2 inhibitors.

Network pharmacology approaches for research of Traditional Chinese Medicines / 中国天然药物

Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.

Inhibitory effects of simeprevir on Staphylococcusepidermidis and itsbiofilm in vitro / 中南大学学报(医学版)

OBJECTIVES@#Staphylococcus epidermidis (S. epidermidis) is a Gram-positive opportunistic pathogen that often causes hospital infections. With the abuse of antibiotics, the resistance of S. epidermidis gradually increases, and drug repurposing has become a research hotspot in the treating of refractory drug-resistant bacterial infections. This study aims to study the antimicrobial and antibiofilm effects of simeprevir, an antiviral hepatitis drug, on S. epidermidis in vitro.@*METHODS@#The micro-dilution assay was used to determine the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of simeprevir against S. epidermidis. Crystal violet staining assay was used to detect the biofilm inhibitory effect of simeprevir. The antimicrobial activity of simeprevir against S. epidermidis and its biofilm were explored by SYTO9/PI fluorescent staining. The combined effect between simeprevir and gentamycin was assessed by checkerboard assay and was confirmed by time-inhibition assay.@*RESULTS@#Simeprevir showed significant antimicrobial effects against S. epidermidis type strains and clinical isolates with the MIC and MBC at 2-16 μg/mL and 4-32 μg/mL, respectively. The antimicrobial effects of simeprevir were confirmed by SYTO9/PI staining. Simeprevir at MIC could significantly inhibit and break the biofilm on cover slides. Similarly, simeprevir also significantly inhibit the biofilm formation on the surface of urine catheters either in TSB [from (0.700±0.020) to (0.050±0.004)] (t=54.03, P<0.001), or horse serum [from (1.00±0.02) to (0.13±0.01)] (t=82.78, P<0.001). Synergistic antimicrobial effect was found between simeprevir and gentamycin against S. epidermidis with the fractional inhibitory concentration index of 0.5.@*CONCLUSIONS@#Simeprevir shows antimicrobial effect and anti-biofilm activities against S. epidermidis.

Evaluation of predictive machine learning models for drug repurposing against delta variant of SARS-CoV-2 spike protein-Supplementary Data

Drug repurposing is a major approach used by researchers to tackle the COVID-19 pandemic which has been worsened by the current surge of delta variant in many countries. Though drugs like Remdesivir and Hydroxychloroquine have been repurposed, studies prove these drugs have insignificant effect in treatment. So, in this study, we use the already FDA approved database of 1615 drugs to apply semi-flexible and flexible molecular docking methods to calculate the docking scores and identify the best 20 potential inhibitors for our modelled delta variant spike protein RBD. Then, we calculate 2325 1-D and 2-D molecular descriptors and use machine-learning algorithms like K-Nearest Neighbor, Random Forest, Support Vector Machine and ensemble stacking method to build regression-based prediction models. We identify 15 best descriptors for the dataset all of which were found to be inversely correlated with ligand binding. With only these few descriptors, the models performed excellently with an area under curve (AUC) value of 0.952 in Regression Error Characteristic curve for ensemble stacking. Therefore, we comment that these 15 descriptors are the most important features for the binding of inhibitors to the spike protein and hence these should be studied properly in terms of drug repurposing and drug discovery.

Evaluation of predictive machine learning models for drug repurposing against delta variant of SARS-CoV-2 spike protein

Drug repurposing is a major approach used by researchers to tackle the COVID-19 pandemic which has been worsened by the current surge of delta variant in many countries. Though drugs like Remdesivir and Hydroxychloroquine have been repurposed, studies prove these drugs have insignificant effect in treatment. So, in this study, we use the already FDA approved database of 1615 drugs to apply semi-flexible and flexible molecular docking methods to calculate the docking scores and identify the best 20 potential inhibitors for our modelled delta variant spike protein RBD. Then, we calculate 2325 1-D and 2-D molecular descriptors and use machine-learning algorithms like K-Nearest Neighbor, Random Forest, Support Vector Machine and ensemble stacking method to build regression-based prediction models. We identify 15 best descriptors for the dataset all of which were found to be inversely correlated with ligand binding. With only these few descriptors, the models performed excellently with an area under curve (AUC) value of 0.952 in Regression Error Characteristic curve for ensemble stacking. Therefore, we comment that these 15 descriptors are the most important features for the binding of inhibitors to the spike protein and hence these should be studied properly in terms of drug repurposing and drug discovery.

A novel approach for drug discovery-drug repurposing

Drug repurposing refers to finding a new indication for a pre-existing drug. It is a novel way of drug discovery that greatly reduces the time and money spent in the drug discovery process. This approach is associated with a better chance of successful drug approval. Both previously approved drugs as well as drugs that have failed in the trials conducted for their original indication can be repurposed. Even drugs withdrawn from market for their original indication can be repurposed for a new indication. Starting with Sildenafil which is the oldest example of repurposed drug to the recently repurposed drug tocilizumab for COVID-19, the list of repurposed drugs is a big one. The regulatory pathway to be followed for a repurposed drug is different from that for a new chemical entity. Furthermore, the period of marketing exclusivity for repurposed drug is only 3 years as against the 20 years of patent protection period for new drug. The strategy for drug repurposing may be a serendipitous one or hypothesis driven one. The hypothesis driven strategy includes the experimental and computational approaches. Computational approaches for drug discovery, especially the Connectivity map approach, offer a lot of scope to understand the drug-disease-gene link, thereby acting as a kick-starter for drug repurposing. Drug repurposing has real potential to offer a cure for rare genetic conditions and cancers. This review covers the various drug repurposing approaches in detail, the regulatory pathway for repurposed drugs, salient examples of repurposed drugs and also the challenges associated with drug repurposing.

New possibilities for chromoblastomycosis and phaeohyphomycosis treatment: identification of two compounds from the MMV Pathogen Box® that present synergism with itraconazole

BACKGROUND Black fungi of the Herpotrichiellaceae family are agents of chromoblastomycosis and phaeohyphomycosis. There are few therapeutic options for these infections and it is common to associate antifungal drugs in their treatment. OBJECTIVES To investigate the Medicines for Malaria Venture (MMV) Pathogen Box® for possible compounds presenting synergism with antifungal drugs used to treat black fungal infections. METHODS An initial screening of the Pathogen Box® compounds was performed in combination with itraconazole or terbinafine at sub-inhibitory concentrations against Fonsecaea pedrosoi. Hits were further tested against eight Herpotrichiellaceae using the checkerboard method. FINDINGS No synergism was observed with terbinafine. MMV687273 (SQ109) and MMV688415 showed synergism with itraconazole against F. pedrosoi. Synergism of these compounds was confirmed with some black fungi by the checkerboard method. SQ109 and itraconazole presented synergism for Exophiala dermatitidis, F. pedrosoi, F. monophora and F. nubica, with fungicidal activity for F. pedrosoi and F. monophora. MMV688415 presented synergism with itraconazole only for F. pedrosoi, with fungicidal activity. The synergic compounds had high selectivity index values when combined with itraconazole. MAIN CONCLUSIONS These compounds in combination, particularly SQ109, are promising candidates to treat Fonsecaea spp. and E. dermatitidis infections, which account for most cases of chromoblastomycosis and phaeohyphomycosis.

Repositioning drug strategy against Trypanosoma cruzi: lessons learned from HIV aspartyl peptidase inhibitors

Chagas disease (CD) is an old neglected problem that affects more than 6 million people through 21 endemic countries in Latin America. Despite being responsible for more than 12 thousand deaths per year, the disease disposes basically of two drugs for its treatment, the nitroimidazole benznidazole and the nitrofuran nifurtimox. However, these drugs have innumerous limitations that greatly reduce the chances of cure. In Brazil, for example, only benznidazole is available to treat CD patients. Therefore, some proof-of-concept phase II clinical trials focused on improving the current treatment with benznidazole, also comparing it with repositioned drugs or combining them. Indeed, repositioning already marketed drugs in view of combating neglected tropical diseases is a very interesting approach in the context of decreased time for approval, better treatment options and low cost for development and implementation. After the introduction of human immunodeficiency virus aspartyl peptidase inhibitors (HIV-PIs) in the treatment of acquired immune deficiency syndrome (AIDS), the prevalence and incidence of parasitic, fungal and bacterial co-infections suffered a marked reduction, making these HIV-PIs attractive for drug repositioning. In this line, the present perspective presents the promising and beneficial data concerning the effects of HIV-PIs on the clinically relevant forms of Trypanosoma cruzi (i.e., trypomastigotes and amastigotes) and also highlights the ultrastructural and physiological targets for the HIV-PIs on this parasite. Therefore, we raise the possibility that HIV-PIs could be considered as alternative treatment options in the struggle against CD.

Proteolytic inhibitors as alternative medicines to treat trypanosomatid-caused diseases: experience with calpain inhibitors

The treatment for tropical neglected diseases, such as Chagas disease (CD) and leishmaniasis, is extremely limited to a handful of drugs that suffer from unacceptable toxicity, tough administration routes, like parenteral, and increasing treatment failures due to the parasite resistance. Consequently, there is urgency for the development of new therapeutic options to treat such diseases. Since peptidases from these parasites are responsible for crucial functions in their biology, these molecules have been explored as alternative targets. In this context, a myriad of proteolytic inhibitors has been developed against calcium-dependent cysteine-type peptidases, collectively called calpains, which are implicated in several human pathophysiological diseases. These molecules are highly expanded in the genome of trypanosomatids and they have been reported participating in several parasite biological processes. In the present perspective, we discuss our almost two decades of experience employing the calpain inhibitors as an interesting shortcut to a possible repurpose strategy to treat CD and leishmaniasis.

Targeting PFKL with penfluridol inhibits glycolysis and suppresses esophageal cancer tumorigenesis in an AMPK/FOXO3a/BIM-dependent manner

As one of the hallmarks of cancer, metabolic reprogramming leads to cancer progression, and targeting glycolytic enzymes could be useful strategies for cancer therapy. By screening a small molecule library consisting of 1320 FDA-approved drugs, we found that penfluridol, an antipsychotic drug used to treat schizophrenia, could inhibit glycolysis and induce apoptosis in esophageal squamous cell carcinoma (ESCC). Gene profiling and Ingenuity Pathway Analysis suggested the important role of AMPK in action mechanism of penfluridol. By using drug affinity responsive target stability (DARTS) technology and proteomics, we identified phosphofructokinase, liver type (PFKL), a key enzyme in glycolysis, as a direct target of penfluridol. Penfluridol could not exhibit its anticancer property in PFKL-deficient cancer cells, illustrating that PFKL is essential for the bioactivity of penfluridol. High PFKL expression is correlated with advanced stages and poor survival of ESCC patients, and silencing of PFKL significantly suppressed tumor growth. Mechanistically, direct binding of penfluridol and PFKL inhibits glucose consumption, lactate and ATP production, leads to nuclear translocation of FOXO3a and subsequent transcriptional activation of BIM in an AMPK-dependent manner. Taken together, PFKL is a potential prognostic biomarker and therapeutic target in ESCC, and penfluridol may be a new therapeutic option for management of this lethal disease.

Repurposing non-oncology small-molecule drugs to improve cancer therapy: Current situation and future directions

Drug repurposing or repositioning has been well-known to refer to the therapeutic applications of a drug for another indication other than it was originally approved for. Repurposing non-oncology small-molecule drugs has been increasingly becoming an attractive approach to improve cancer therapy, with potentially lower overall costs and shorter timelines. Several non-oncology drugs approved by FDA have been recently reported to treat different types of human cancers, with the aid of some new emerging technologies, such as omics sequencing and artificial intelligence to overcome the bottleneck of drug repurposing. Therefore, in this review, we focus on summarizing the therapeutic potential of non-oncology drugs, including cardiovascular drugs, microbiological drugs, small-molecule antibiotics, anti-viral drugs, anti-inflammatory drugs, anti-neurodegenerative drugs, antipsychotic drugs, antidepressants, and other drugs in human cancers. We also discuss their novel potential targets and relevant signaling pathways of these old non-oncology drugs in cancer therapies. Taken together, these inspiring findings will shed new light on repurposing more non-oncology small-molecule drugs with their intricate molecular mechanisms for future cancer drug discovery.

Discovery and repurposing of artemisinin / 医学前沿

Malaria is an ancient infectious disease that threatens millions of lives globally even today. The discovery of artemisinin, inspired by traditional Chinese medicine (TCM), has brought in a paradigm shift and been recognized as the "best hope for the treatment of malaria" by World Health Organization. With its high potency and low toxicity, the wide use of artemisinin effectively treats the otherwise drug-resistant parasites and helps many countries, including China, to eventually eradicate malaria. Here, we will first review the initial discovery of artemisinin, an extraordinary journey that was in stark contrast with many drugs in western medicine. We will then discuss how artemisinin and its derivatives could be repurposed to treat cancer, inflammation, immunoregulation-related diseases, and COVID-19. Finally, we will discuss the implications of the "artemisinin story" and how that can better guide the development of TCM today. We believe that artemisinin is just a starting point and TCM will play an even bigger role in healthcare in the 21st century.

Dexamethasone for treating SARS-CoV-2 infection: a systematic review and meta-analysis

ABSTRACT BACKGROUND: Considering the disruptions imposed by lockdowns and social distancing recommendations, coupled with overwhelmed healthcare systems, researchers worldwide have been exploring drug repositioning strategies for treating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). OBJECTIVE: To compile results from randomized clinical trials on the effect of dexamethasone, compared with standard treatment for management of SARS-CoV-2. DESIGN AND SETTING: We conducted a systematic review and meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in a Brazilian public university. METHODS: We sought to compile data from 6724 hospitalized patients with confirmed or suspected SARS-CoV-2 infection. RESULTS: Treatment with dexamethasone significantly reduced mortality within 28 days (risk ratio, RR: 0.89; 95% confidence interval, CI: 0.82-0.97). Dexamethasone use was linked with being discharged alive within 28 days (odds ratio, OR: 1.20; 95% CI: 1.07-1.33). CONCLUSIONS: This study suggests that dexamethasone may significantly improve the outcome among hospitalized patients with SARS-CoV-2 infection and associated severe respiratory complications. ­Further studies need to consider both dose-dependent administration and outcomes in early and later stages of the disease. PROSPERO platform: CRD42021229825.