Drug repurposing: a nexus of innovation, science, and potential

Environmental microbiome, human fungal pathogens, and antimicrobial resistance

Traditionally, antifungal resistance (AFR) has received much less attention compared with bacterial resistance to antibiotics. However, global changes, pandemics, and emerging new fungal infections have highlighted global health consequences of AFR. The recent report of the World Health Organisation (WHO) has identified fungal priority pathogens, and recognised AFR among the greatest global health threats. This is particularly important given the significant increase in fungal infections linked to climate change and pandemics. Environmental factors play critical roles in AFR and fungal infections, as many clinically relevant fungal pathogens and AFR originate from the environment (mainly soil). In addition, the environment serves as a potential rich source for the discovery of new antifungal agents, including mycoviruses and bacterial probiotics, which hold promise for effective therapies. In this article, we summarise the environmental pathways of AFR development and spread among high priority fungal pathogens, and propose potential mechanisms of AFR development and spread. We identify a research priority list to address key knowledge gaps in our understanding of environmental AFR. Further, we propose an integrated roadmap for predictive risk management of AFR that is critical for effective surveillance and forecasting of public health outcomes under current and future climatic conditions.

Rapid Deployment of Antiviral Drugs Using Single-Virus Tracking and Machine Learning

The outbreak of emerging acute viral diseases urgently requires the acceleration of specialized antiviral drug development, thus widely adopting phenotypic screening as a strategy for drug repurposing in antiviral research. However, traditional phenotypic screening methods typically require several days of experimental cycles and lack visual confirmation of a drug's ability to inhibit viral infection. Here, we report a robust method that utilizes quantum-dot-based single-virus tracking and machine learning to generate unique single-virus infection fingerprint data from viral trajectories and detect the dynamic changes in viral movement following drug administration. Our findings demonstrated that this approach can successfully identify viral infection patterns at various infection phases and predict antiviral drug efficacy through machine learning within 90 min. This method provides valuable support for assessing the efficacy of antiviral drugs and offers promising applications for responding to future outbreaks of emerging viruses.

Antiviral Development for the Polio Endgame: Current Progress and Future Directions

As the world is approaching the eradication of wild poliovirus serotype 1, the last of the three wild types, the question of how to maintain a polio-free world becomes imminent. To mitigate the risk of sporadic vaccine-associated paralytic polio (VAPP) caused by oral polio vaccines (OPVs) that are routinely used in global immunization programs, the Polio Antivirals Initiative (PAI) was established in 2006. The primary goal of the PAI is to facilitate the discovery and development of antiviral drugs to stop the excretion of immunodeficiency-associated vaccine-derived poliovirus (iVDPV) in B cell-deficient individuals. This review summarizes the major progress that has been made in the development of safe and effective poliovirus antivirals and highlights the candidates that have shown promising results in vitro, in vivo, and in clinical trials.

Metal chelation as an antibacterial strategy for Pseudomonas aeruginosa and Acinetobacter baumannii

It is estimated that by 2050, bacterial infections will cause 1.8 million more deaths than cancer annually, and the current lack of antibiotic drug discovery is only exacerbating the crisis. Two pathogens in particular, Gram-negative bacteria A. baumannii and P. aeruginosa, are of grave concern because of their heightened multi-drug resistance due to a dense, impermeable outer membrane. However, targeting specific cellular processes may prove successful in overcoming bacterial resistance. This review will concentrate on a novel approach to combatting pathogenicity by disarming bacteria through the disruption of metal homeostasis to reduce virulence and enhance antibiotic uptake. The varying levels of success in bringing metallophores to clinical trials, with currently only one FDA-approved siderophore antibiotic to date, will also be detailed.

Antineoplastics for treating Alzheimer's disease and dementia: Evidence from preclinical and observational studies

As the world population ages, there will be an increasing need for effective therapies for aging-associated neurodegenerative disorders, which remain untreatable. Dementia due to Alzheimer's disease (AD) is one of the leading neurological diseases in the aging population. Current therapeutic approaches to treat this disorder are solely symptomatic, making the need for new molecular entities acting on the causes of the disease extremely urgent. One of the potential solutions is to use compounds that are already in the market. The structures have known pharmacokinetics, pharmacodynamics, toxicity profiles, and patient data available in several countries. Several drugs have been used successfully to treat diseases different from their original purposes, such as autoimmunity and peripheral inflammation. Herein, we divulge the repurposing of drugs in the area of neurodegenerative diseases, focusing on the therapeutic potential of antineoplastics to treat dementia due to AD and dementia. We briefly touch upon the shared pathological mechanism between AD and cancer and drug repurposing strategies, with a focus on artificial intelligence. Next, we bring out the current status of research on the development of drugs, provide supporting evidence from retrospective, clinical, and preclinical studies on antineoplastic use, and bring in new areas, such as repurposing drugs for the prion-like spreading of pathologies in treating AD.

Repurposing of SARS-CoV-2 compounds against Marburg Virus using MD simulation, mm/GBSA, PCA analysis, and free energy landscape

The significant mortality rate associated with Marburg virus infection made it the greatest hazard among infectious diseases. Drug repurposing using in silico methods has been crucial in identifying potential compounds that could prevent viral replication by targeting the virus's primary proteins. This study aimed at repurposing the drugs of SARS-CoV-2 for identifying potential candidates against the matrix protein VP40 of the Marburg virus. Virtual screening was performed where the control compound, Nilotinib, showed a binding score of -9.99 kcal/mol. Based on binding scores, hit compounds 9549298, 11960895, 44545852, 51039094, and 89670174 were selected that had a lower binding score than the control. Subsequent molecular dynamics (MD) simulation revealed that compound 9549298 consistently formed a hydrogen bond with the residue Gln290. This was observed both in molecular docking and MD simulation poses, indicating a strong and significant interaction with the protein. 11960895 had the most stable and consistent RMSD pattern exhibited in 100 ns simulation, while 9549298 had the most identical RMSD plot compared to the control molecule. MM/PBSA analysis showed that the binding free energy (ΔG) of 9549298 and 11960895 was lower than the control, with -30.84 and -38.86 kcal/mol, respectively. It was observed by the PCA (principal component analysis) and FEL (free energy landscape) analysis that compounds 9549298 and 11960895 had lesser conformational variation. Overall, this study proposed 9549298 and 11960895 as potential binders of VP40 MARV that can cause its inhibition, however it inherently lacks experimental validation. Furthermore, the study proposes in-vitro experiments as the next step to validate these computational findings, offering a practical approach to further explore these compounds' potential as antiviral agents.Communicated by Ramaswamy H. Sarma.

A high-throughput screening approach to discover potential colorectal cancer chemotherapeutics: Repurposing drugs to disrupt 14-3-3 protein-BAD interactions

Inducing apoptosis in different types of cancer cells is an effective therapeutic strategy. However, the success of existing chemotherapeutics can be compromised by tumor cell resistance and systemic off-target effects. Therefore, the discovery of pro-apoptotic compounds with minimal systemic side-effects is crucial. 14-3-3 proteins are molecular scaffolds that serve as important regulators of cell survival. Our previous study demonstrated that 14-3-3ζ can sequester BAD, a pro-apoptotic member of the BCL-2 protein family, in the cytoplasm and prevent its translocation to mitochondria to inhibit the induction of apoptosis. Despite being a critical mechanism of cell survival, it is unclear whether disrupting 14-3-3 protein:BAD interactions could be harnessed as a chemotherapeutic approach. Herein, we established a BRET-based high-throughput drug screening approach (Z'-score= 0.52) capable of identifying molecules that can disrupt 14-3-3ζ:BAD interactions. An FDA-approved drug library containing 1971 compounds was used for screening, and the capacity of identified hits to induce cell death was examined in NIH3T3-fibroblasts and colorectal cancer cell lines, HT-29 and Caco-2. Our in vitro results suggest that terfenadine, penfluridol, and lomitapide could be potentially repurposed for treating colorectal cancer. Moreover, our screening method demonstrates the feasibility of identifying pro-apoptotic agents that can be applied towards conditions where aberrant cell growth or function are key determinants of disease pathogenesis.