ACS Chem Biol. 2023 Sep 14. doi: 10.1021/acschembio.3c00339. Online ahead of print.

ABSTRACT

Despite the well-established role of oxidative stress in the pathogenesis of age-related macular degeneration (AMD), the mechanism underlying phototoxicity remains unclear. Herein, we used a drug repurposing approach to isolate an FDA-approved drug that blocks the aggregation of the photoinducible major fluorophore of lipofuscin, the bis-retinoid N-retinylidene-N-retinylethanolamine (A2E). Our fluorescence-based screening combined with dynamic light scattering (DLS) analysis led to the identification of entacapone as a potent inhibitor of A2E fluorescence and aggregation. The entacapone-mediated inhibition of A2E aggregation blocks its photodegradation and offers photoprotection in A2E-loaded retinal pigment epithelial (RPE) cells exposed to blue light. In-depth mechanistic analysis suggests that entacapone prevents the conversion of toxic aggregates by redirecting A2E into off-pathway oligomers. These findings provide evidence that aggregation contributes to the phototoxicity of A2E.

PMID:37708070 | DOI:10.1021/acschembio.3c00339

J Comput Aided Mol Des. 2023 Sep 14. doi: 10.1007/s10822-023-00529-x. Online ahead of print.

ABSTRACT

DrugCentral, accessible at https://drugcentral.org , is an open-access online drug information repository. It covers over 4950 drugs, incorporating structural, physicochemical, and pharmacological details to support drug discovery, development, and repositioning. With around 20,000 bioactivity data points, manual curation enhances information from several major digital sources. Approximately 724 mechanism-of-action (MoA) targets offer updated drug target insights. The platform captures clinical data: over 14,300 on- and off-label uses, 27,000 contraindications, and around 340,000 adverse drug events from pharmacovigilance reports. DrugCentral encompasses information from molecular structures to marketed formulations, providing a comprehensive pharmaceutical reference. Users can easily navigate basic drug information and key features, making DrugCentral a versatile, unique resource. Furthermore, we present a use-case example where we utilize experimentally determined data from DrugCentral to support drug repurposing. A minimum activity threshold t should be considered against novel targets to repurpose a drug. Analyzing 1156 bioactivities for human MoA targets suggests a general threshold of 1 µM: t = 6 when expressed as - log[Activity(M)]). This applies to 87% of the drugs. Moreover, t can be refined empirically based on water solubility (S): t = 3 - logS, for logS < - 3. Alongside the drug repurposing classification scheme, which considers intellectual property rights, market exclusivity protections, and market accessibility, DrugCentral provides valuable data to prioritize candidates for drug repurposing programs efficiently.

PMID:37707619 | DOI:10.1007/s10822-023-00529-x

Bioinformatics. 2023 Sep 14:btad570. doi: 10.1093/bioinformatics/btad570. Online ahead of print.

ABSTRACT

SUMMARY: Knowledge graphs are an increasingly common data structure for representing biomedical information. These knowledge graphs can easily represent heterogeneous types of information, and many algorithms and tools exist for querying and analyzing graphs. Biomedical knowledge graphs have been used in a variety of applications, including drug repurposing, identification of drug targets, prediction of drug side effects, and clinical decision support. Typically, knowledge graphs are constructed by centralization and integration of data from multiple disparate sources. Here, we describe BioThings Explorer, an application that can query a virtual, federated knowledge graph derived from the aggregated information in a network of biomedical web services. BioThings Explorer leverages semantically precise annotations of the inputs and outputs for each resource, and automates the chaining of web service calls to execute multi-step graph queries. Because there is no large, centralized knowledge graph to maintain, BioThings Explorer is distributed as a lightweight application that dynamically retrieves information at query time.

AVAILABILITY AND IMPLEMENTATION: More information can be found at https://explorer.biothings.io, and code is available at https://github.com/biothings/biothings_explorer.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:37707514 | DOI:10.1093/bioinformatics/btad570

J Med Microbiol. 2023 Sep;72(9). doi: 10.1099/jmm.0.001751.

ABSTRACT

Introduction. Antibiotic resistance is a major threat to public health, particularly with methicillin-resistant Staphylococcus aureus (MRSA) being a leading cause of antimicrobial resistance. To combat this problem, drug repurposing offers a promising solution for the discovery of new antibacterial agents.Hypothesis. Menadione exhibits antibacterial activity against methicillin-sensitive and methicillin-resistant S. aureus strains, both alone and in combination with oxacillin. Its primary mechanism of action involves inducing oxidative stress.Methodology. Sensitivity assays were performed using broth microdilution. The interaction between menadione, oxacillin, and antioxidants was assessed using checkerboard technique. Mechanism of action was evaluated using flow cytometry, fluorescence microscopy, and in silico analysis.Aim. The aim of this study was to evaluate the in vitro antibacterial potential of menadione against planktonic and biofilm forms of methicillin-sensitive and resistant S. aureus strains. It also examined its role as a modulator of oxacillin activity and investigated the mechanism of action involved in its activity.Results. Menadione showed antibacterial activity against planktonic cells at concentrations ranging from 2 to 32 µg ml-1, with bacteriostatic action. When combined with oxacillin, it exhibited an additive and synergistic effect against the tested strains. Menadione also demonstrated antibiofilm activity at subinhibitory concentrations and effectively combated biofilms with reduced sensitivity to oxacillin alone. Its mechanism of action involves the production of reactive oxygen species (ROS) and DNA damage. It also showed interactions with important targets, such as DNA gyrase and dehydroesqualene synthase. The presence of ascorbic acid reversed its effects.Conclusion. Menadione exhibited antibacterial and antibiofilm activity against MRSA strains, suggesting its potential as an adjunct in the treatment of S. aureus infections. The main mechanism of action involves the production of ROS, which subsequently leads to DNA damage. Additionally, the activity of menadione can be complemented by its interaction with important virulence targets.

PMID:37707372 | DOI:10.1099/jmm.0.001751

J Phys Chem Lett. 2023 Sep 14:8385-8396. doi: 10.1021/acs.jpclett.3c01440. Online ahead of print.

ABSTRACT

Open reading frame 6 (ORF6), the accessory protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that suppresses host type-I interferon signaling, possesses amyloidogenic sequences. ORF6 amyloidogenic peptides self-assemble to produce cytotoxic amyloid fibrils. Currently, the molecular properties of the ORF6 remain elusive. Here, we investigate the structural dynamics of the full-length ORF6 protein in a near-physiological environment using high-speed atomic force microscopy. ORF6 oligomers were ellipsoidal and readily assembled into ORF6 protofilaments in either a circular or a linear pattern. The formation of ORF6 protofilaments was enhanced at higher temperatures or on a lipid substrate. ORF6 filaments were sensitive to aliphatic alcohols, urea, and SDS, indicating that the filaments were predominantly maintained by hydrophobic interactions. In summary, ORF6 self-assembly could be necessary to sequester host factors and causes collateral damage to cells via amyloid aggregates. Nanoscopic imaging unveiled the innate molecular behavior of ORF6 and provides insight into drug repurposing to treat amyloid-related coronavirus disease 2019 complications.

PMID:37707320 | DOI:10.1021/acs.jpclett.3c01440

Int J Immunopathol Pharmacol. 2023 Jan-Dec;37:3946320231202349. doi: 10.1177/03946320231202349.

ABSTRACT

Objectives: Our objective was to assess the effects and mechanisms of nifuratel on IgE-mediated mast cell (MC) degranulation and anaphylaxis in both in vitro and in vivo settings.Methods: The anti-allergic activity of nifuratel was evaluated in mast cell cultures and the passive cutaneous anaphylaxis (PCA) model. The effects of nifuratel on signaling pathways stimulated by antigen in mast cells were measured by immunoblotting, immunoprecipitation, in vitro protein tyrosine kinase assay, and other molecular biological methods.Results: Nifuratel reversibly inhibited antigen-induced degranulation of MCs (IC50, approximately 0.34 μM for RBL-2H3 cells; approximately 0.94 μM for BMMCs) and suppressed the secretion of inflammatory cytokines IL-4 (IC50, approximately 0.74 μM) and TNF-α (IC50, approximately 0.48 μM). Mechanism studies showed that nifuratel inhibited the phosphorylation of Syk by antigen via the inhibition of recruitment of cytosolic Syk to the ɣ subunit of FcεRI, and decreased the activation of Syk downstream signaling proteins LAT, Akt, and MAPKs. Finally, nifuratel dose-dependently suppressed the IgE-mediated passive cutaneous anaphylaxis in mice (ED50, approximately 22 mg/kg).Conclusion: Our findings suggest that nifuratel inhibits pathways essential for the activation of mast cells to suppress anaphylaxis, thereby indicating that the anti-microbial drug, nifuratel, could be a potential drug candidate for IgE-mediated allergic disorders.

PMID:37706235 | DOI:10.1177/03946320231202349

Expert Opin Ther Targets. 2023 Sep 13. doi: 10.1080/14728222.2023.2259097. Online ahead of print.

ABSTRACT

BACKGROUND: Drug repurposing is an attractive strategy for extending the arsenal of oncology therapies. Tolperisone is an old centrally acting muscle relaxant used for treatment of chronic pain conditions. In this study, we investigated the therapeutic effect and mechanism of tolperisone in human cancers and explored the combination strategy with proteasome inhibitor and immunotherapy.

RESEARCH DESIGN AND METHODS: The antitumor effect of tolperisone was evaluated by measuring half maximal inhibitory concentration, cell death and cell growth. RNA sequencing, western blotting, molecule docking, enzyme activity assay and ChIP-qPCR were performed to reveal the underlying mechanism. Xenograft models were used to evaluate the efficacy of tolperisone alone or in combination with proteasome inhibitor or immunotherapy.

RESULTS: Tolperisone inhibited cell growth and induced cell death in human cancer cell lines. Unfolded protein responses (UPR) pathway was hyperactivated in tolperisone-treated cells. We further identified histone lysine-specific demethylase 1 (LSD1) as a potential target of tolperisone, which directly demethylates UPR-related genes in H3K4me2. Tolperisone synergistically improved the efficacy of MG132 by enhancing UPR and sensitized tumors to immunotherapy by reprogramming M2 macrophages into M1 phenotype.

CONCLUSIONS: Tolperisone inhibits human cancer by targeting LSD1. Repurposing tolperisone in cancer therapy by combination strategy implies clinical potential.

PMID:37704953 | DOI:10.1080/14728222.2023.2259097

Methods Mol Biol. 2024;2716:223-240. doi: 10.1007/978-1-0716-3449-3_10.

ABSTRACT

Building and analyzing knowledge graphs (KGs) to aid drug discovery is a topical area of research. A salient feature of KGs is their ability to combine many heterogeneous data sources in a format that facilitates discovering connections. The utility of KGs has been exemplified in areas such as drug repurposing, with insights made through manual exploration and modeling of the data. In this chapter, we discuss promises and pitfalls of using natural language processing (NLP) to mine "unstructured text"- typically from scientific literature- as a data source for KGs. This draws on our experience of initially parsing "structured" data sources-such as ChEMBL-as the basis for data within a KG, and then enriching or expanding upon them using NLP. The fundamental promise of NLP for KGs is the automated extraction of data from millions of documents-a task practically impossible to do via human curation alone. However, there are many potential pitfalls in NLP-KG pipelines, such as incorrect named entity recognition and ontology linking, all of which could ultimately lead to erroneous inferences and conclusions.

PMID:37702942 | DOI:10.1007/978-1-0716-3449-3_10

Cornea. 2023 Sep 12. doi: 10.1097/ICO.0000000000003391. Online ahead of print.

ABSTRACT

Antibiotic resistance has emerged as a critical threat for the treatment of bacterial ocular infections. To address the critical need for novel therapeutics, antibiotic drug repurposing holds significant promise. As such, examples of existing FDA-approved drugs currently under development for new applications, novel combinations, and improved delivery systems are discussed.

PMID:37702607 | DOI:10.1097/ICO.0000000000003391

Infez Med. 2023 Sep 1;31(3):384-393. doi: 10.53854/liim-3103-12. eCollection 2023.

ABSTRACT

Scrub typhus is an acute febrile illness caused by Orientia tsutsugamushi, a Gram-negative bacillus, commonly occurring in the Asia-Pacific region. It is transmitted to humans by the bite of an infected Leptotrombidium mite and the bacterium causes endothelial dysfunction resulting in widespread vasculitis and the possible development of thrombocytopenia, meningitis, acute respiratory distress syndrome, and infrequently, myocarditis. Early diagnosis and prompt treatment are crucial in managing scrub typhus. Here, we present four cases of scrub typhus with a comprehensive literature review. This study highlights the significance of considering scrub typhus as a possible diagnosis in patients of all ages from endemic regions who exhibit symptoms such as fever, thrombocytopenia, or transaminitis, even in the absence of typical clinical features. Two cases exhibited the characteristic lesion of eschar at the site of mite feeding. One case involved a middle-aged woman who was diagnosed with typhus-induced myocarditis with left ventricular dysfunction. Another case involved a 23-day-old neonate with poor feeding and seizures, who was diagnosed with late-onset sepsis with meningitis. Scrub typhus was confirmed in all cases using a positive qualitative IgM ELISA. However, it is preferred to use paired (ELISA before and after antibiotic therapy) or quantitative titers for confirmation. Healthcare providers must consider the patient's exposure history and clinical presentation to diagnose and treat scrub typhus promptly.

PMID:37701392 | PMC:PMC10495056 | DOI:10.53854/liim-3103-12

Curr Res Microb Sci. 2023 Sep 7;5:100202. doi: 10.1016/j.crmicr.2023.100202. eCollection 2023.

ABSTRACT

Influenza virus infection, more commonly known as the 'cold flu', is an etiological agent that gives rise to recurrent annual flu and many pandemics. Dated back to the 1918- Spanish Flu, the influenza infection has caused the loss of many human lives and significantly impacted the economy and daily lives. Influenza virus can be classified into four different genera: influenza A-D, with the former two, influenza A and B, relevant to humans. The capacity of antigenic drift and shift in Influenza A has given rise to many novel variants, rendering vaccines and antiviral therapies useless. In light of the emergence of a novel betacoronavirus, the SARS-CoV-2, unravelling the underpinning mechanisms that support the recurrent influenza epidemics and pandemics is essential. Given the symptom similarities between influenza and covid infection, it is crucial to reiterate what we know about the influenza infection. This review aims to describe the origin and evolution of influenza infection. Apart from that, the risk factors entail the implication of co-infections, especially regarding the COVID-19 pandemic is further discussed. In addition, antiviral strategies, including the potential of drug repositioning, are discussed in this context. The diagnostic approach is also critically discussed in an effort to understand better and prepare for upcoming variants and potential influenza pandemics in the future. Lastly, this review encapsulates the challenges in curbing the influenza spread and provides insights for future directions in influenza management.

PMID:37700857 | PMC:PMC10493511 | DOI:10.1016/j.crmicr.2023.100202

Comput Biol Med. 2023 Sep 9;165:107465. doi: 10.1016/j.compbiomed.2023.107465. Online ahead of print.

ABSTRACT

Arsenic trioxide (ATO) is a great discovery in the treatment of acute promyelocytic leukemia (APL), which has been used in an increasing number of malignant diseases. Systematic integrative analysis will help to precisely understand the mechanism of ATO and find new combined drugs. Therefore, we developed a one-stop comprehensive database of ATO named ATOdb by manually compiling a wealth of experimentally supported ATO-related data from 3479 articles, and integrated analysis tools. The current version of ATOdb contains 8373 associations among 2300 ATO targets, 80 conditions and 262 combined drugs. Each entry in ATOdb contains detailed information on ATO targets, therapeutic/side effects, systems, cell names, cell types, regulations, detection methods, brief descriptions, references, etc. Furthermore, ATOdb also provides data visualization and analysis results such as the drug similarities, protein-protein interactions, and miRNA-mRNA relationships. An easy-to-use web interface was deployed in ATOdb for users to easily browse, search and download the data. In conclusion, ATOdb will serve as a valuable resource for in-depth study of the mechanism of ATO, discovery of new drug combination strategies, promotion of rational drug use and individualized treatments. ATOdb is freely available at http://bio-bigdata.hrbmu.edu.cn/ATOdb/index.jsp.

PMID:37699323 | DOI:10.1016/j.compbiomed.2023.107465

Orphanet J Rare Dis. 2023 Sep 12;18(1):287. doi: 10.1186/s13023-023-02753-y.

ABSTRACT

BACKGROUND: We consider two key challenges that early-stage biotechnology firms face in developing a sustainable financing strategy and a sustainable business model: developing a valuation model for drug compounds, and choosing an appropriate operating model and corporate structure. We use the specific example of Unravel Biosciences-a therapeutics platform company that identifies novel drug targets through off-target mechanisms of existing drugs and then develops optimized new molecules-throughout the paper and explore a specific scenario of drug repurposing for rare genetic diseases.

RESULTS: The first challenge consists of producing a realistic financial valuation of a potential rare disease repurposed drug compound, in this case targeting Rett syndrome. More generally, we develop a framework to value a portfolio of pairwise correlated rare disease compounds in early-stage development and quantify its risk profile. We estimate the probability of a negative return to be [Formula: see text] for a single compound and [Formula: see text] for a portfolio of 8 drugs. The probability of selling the project at a loss decreases from [Formula: see text] (phase 3) for a single compound to [Formula: see text] (phase 3) for the 8-drug portfolio. For the second challenge, we find that the choice of operating model and corporate structure is crucial for early-stage biotech startups and illustrate this point with three concrete examples.

CONCLUSIONS: Repurposing existing compounds offers important advantages that could help early-stage biotech startups better align their business and financing issues with their scientific and medical objectives, enter a space that is not occupied by large pharmaceutical companies, and accelerate the validation of their drug development platform.

PMID:37700316 | DOI:10.1186/s13023-023-02753-y

Pharmaceut Med. 2023 Sep 12. doi: 10.1007/s40290-023-00499-3. Online ahead of print.

ABSTRACT

Spinal cord injury (SCI) encompasses a plethora of complex mechanisms like the involvement of major cell death pathways, neurodegeneration of spinal cord neurons, overexpression of glutaminergic transmission and inflammation cascade, along with different co-morbidities like neuropathic pain, urinary and sexual dysfunction, respiratory and cardiac failures, making it one of the leading causes of morbidity and mortality globally. Corticosteroids such as methylprednisolone and dexamethasone, and non-steroidal anti-inflammatory drugs such as naproxen, aspirin and ibuprofen are the first-line treatment options for SCI, inhibiting primary and secondary progression by preventing inflammation and action of reactive oxygen species. However, they are constrained by a short effective drug administration window and their pharmacological action being limited to symptomatic relief of the secondary effects related to spinal cord injury only. Although post-injury rehabilitation treatments may enable functional recovery, they take a long time to show results. Drug repurposing might be an innovative method for expanding therapy alternatives, utilising drugs that are already approved by various esteemed federal agencies throughout the world. Reutilising a drug molecule to treat SCI can eliminate the need for expensive and lengthy drug discovery processes and pave the way for new therapeutic approaches in SCI. This review summarises marketed drugs that could be repurposed based on their safety and efficacy data. We also discuss their mechanisms of action and provide a list of repurposed drugs under clinical trials for SCI therapy.

PMID:37698762 | DOI:10.1007/s40290-023-00499-3

FASEB J. 2023 Oct;37(10):e23178. doi: 10.1096/fj.202300600RR.

ABSTRACT

Systemic inflammatory response syndrome (SIRS), at least in part driven by necroptosis, is characterized by life-threatening multiple organ failure. Blocking the progression of SIRS and consequent multiple organ dysfunction is challenging. Receptor-interacting serine/threonine protein kinase 1 (RIPK1) is an important cell death and inflammatory mediator, making it a potential treatment target in several diseases. Here, using a drug repurposing approach, we show that inhibiting RIPK1 is also an effective treatment for SIRS. We performed cell-based high-throughput drug screening of an US Food and Drug Administration (FDA)-approved drug library that contains 1953 drugs to identify effective inhibitors of necroptotic cell death by SYTOX green staining. Dose-response validation of the top candidate, quizartinib, was conducted in two cell lines of HT-22 and MEFs. The effect of quizartinib on necroptosis-related proteins was evaluated using western blotting, immunoprecipitation, and an in vitro RIPK1 kinase assay. The in vivo effects of quizartinib were assessed in a murine tumor necrosis factor α (TNFα)-induced SIRS model. High-throughput screening identified quizartinib as the top "hit" in the compound library that rescued cells from necroptosis in vitro. Quizartinib inhibited necroptosis by directly inhibiting RIPK1 kinase activity and blocking downstream complex IIb formation. Furthermore, quizartinib protected mice against TNFα-induced SIRS. Quizartinib, as an FDA-approved drug with proven safety and efficacy, was repurposed for targeted inhibition of RIPK1. This work provides essential preclinical data for transferring quizartinib to the treatment of RIPK1-dependent necroptosis-induced inflammatory diseases, including SIRS.

PMID:37698367 | DOI:10.1096/fj.202300600RR

Biochim Biophys Acta Mol Basis Dis. 2023 Sep 9:166880. doi: 10.1016/j.bbadis.2023.166880. Online ahead of print.

ABSTRACT

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the world's fourth most deadly cancer. CRC, as a genetic susceptible disease, faces significant challenges in optimizing prognosis through optimal drug treatment modalities. In recent decades, the development of innovative small-molecule drugs is expected to provide targeted interventions that accurately address the different molecular characteristics of CRC. Although the clinical application of single-target drugs is limited by the heterogeneity and high metastasis of CRC, novel small-molecule drug treatment strategies such as dual/multiple-target drugs, drug repurposing, and combination therapies can help overcome these challenges and provide new insights for improving CRC treatment. In this review, we focus on the current status of a range of small molecule drugs that are being considered for CRC therapy, including single-target drugs, dual/multiple-target drugs, drug repurposing and combination strategies, which will pave the way for targeting CRC vulnerabilities with small-molecule drugs in future personalized treatment.

PMID:37696461 | DOI:10.1016/j.bbadis.2023.166880

Redox Biol. 2023 Sep 7;67:102881. doi: 10.1016/j.redox.2023.102881. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is an age-dependent neurodegenerative disorder and the most common cause of cognitive decline. The alarming epidemiological features of Alzheimer's disease, combined with the high failure rate of candidate drugs tested in the preclinical phase, impose more intense investigations for new curative treatments. NRF2 (Nuclear factor-erythroid factor 2-related factor 2) plays a critical role in the inflammatory response and in the cellular redox homeostasis and provides cytoprotection in several diseases including those in the neurodegeneration spectrum. These roles suggest that NRF2 and its directly associated proteins may be novel attractive therapeutic targets in the fight against AD. In this study, through a systemics perspective, we propose an in silico drug repurposing approach for AD, based on the NRF2 interactome and regulome, with the aim of highlighting possible repurposed drugs for AD. Using publicly available information based on differential expressions of the NRF2-neighborhood in AD and through a computational drug repurposing pipeline, we derived to a short list of candidate repurposed drugs and small molecules that affect the expression levels of the majority of NRF2-partners. The relevance of these findings was assessed in a four-step computational meta-analysis including i) structural similarity comparisons with currently ongoing NRF2-related drugs in clinical trials ii) evaluation based on the NRF2-diseasome iii) comparison of relevance between targeted pathways of shortlisted drugs and NRF2-related drugs in clinical trials and iv) further comparison with existing knowledge on AD and NRF2-related drugs in clinical trials based on their known modes of action. Overall, our analysis yielded in 5 candidate repurposed drugs for AD. In cell culture, these 5 candidates activated a luciferase reporter for NRF2 activity and in hippocampus derived TH22 cells they increased NRF2 protein levels and the NRF2 transcriptional signatures as determined by increased expression of its downstream target heme oxygenase 1. We expect that our proposed candidate repurposed drugs will be useful for further research and clinical translation for AD.

PMID:37696195 | DOI:10.1016/j.redox.2023.102881

Bioinformation. 2022 Nov 30;18(11):1050-1061. doi: 10.6026/973206300181050. eCollection 2022.

ABSTRACT

Artificial Intelligence (AI) is expanding with colossal applications in various sectors. In the healthcare sector, it is booming to make life simpler with utmost accuracy by predicting, diagnosing and up to care with the help of Machine Learning (ML) and Deep Learning (DL) applications. Modern computer algorithms have attained accuracy levels comparable to those of human specialists in medical sciences, although computers often do jobs more quickly than people do. It is also expected that there will not be a mandate for humans to be present for the jobs that machines can do, and it is gaining the highest peak because of good trained artificial models in the medical field. ML enhances the therapeutic process and improves health by encouraging more patient participation. ML may get more accurate patient data when used with the Internet of Medical Things (IoMT) and automate message notifications that prompt patients to respond at certain times. The motivation behind this article is to make a comprehensive review of the on-going implementation of ML in medical science, what challenges it is facing now, and how it can be simplified for future researchers to contribute better to medical sciences while applying it to the practitioners' jobs easier. In this review, we have extensively mined the data and brought up systematised applications of AI in healthcare, what challenges have been faced by the experts, and what ethical responsibilities are liable to them while taking the data. We also tabulated which algorithms will be helpful for what kind of data and disease conditions will be useful for future researchers and developers. This article will provide a better insight into AI and ML for the beginner to the advanced developer and researcher to understand the concepts from the basics.

PMID:37693078 | PMC:PMC10484692 | DOI:10.6026/973206300181050

Am J Transl Res. 2023 Aug 15;15(8):4984-5006. eCollection 2023.

ABSTRACT

Drug repurposing, also known as drug repositioning, entails the application of pre-approved or formerly assessed drugs having potentially functional therapeutic amalgams for curing various disorders or disease conditions distinctive from their original remedial indication. It has surfaced as a substitute for the development of drugs for treating cancer, cardiovascular diseases, neurodegenerative disorders, and various infectious diseases like Covid-19. Although the earlier lines of findings in this area were serendipitous, recent advancements are based on patient centered approaches following systematic, translational, drug targeting practices that explore pathophysiological ailment mechanisms. The presence of definite information and numerous records with respect to beneficial properties, harmfulness, and pharmacologic characteristics of repurposed drugs increase the chances of approval in the clinical trial stages. The last few years have showcased the successful emergence of repurposed drug immunotherapy in treating various diseases. In this light, the present review emphasises on incorporation of drug repositioning with Immunotherapy targeted for several disorders.

PMID:37692967 | PMC:PMC10492070

J Adv Pharm Technol Res. 2023 Jul-Sep;14(3):196-201. doi: 10.4103/JAPTR.JAPTR_129_23. Epub 2023 Jul 28.

ABSTRACT

Fusobacterium nucleatum is a Gram-negative anaerobic bacteria that is commonly found in oral cavities and is associated with connective tissue destruction in periodontitis. UDP-N-acetylglucosamine 1-carboxyltransferase with enzyme commission number 2.5.1.7 is a transferases enzyme that plays a role in bacterial pathogenesis. Inhibiting binding sites of UDP-N-acetylglucosamine 1-carboxyltransferase is needed to find potential antibiotic candidates for periodontitis treatment. Hence, the research aimed to present potential UDP-N-acetylglucosamine 1-carboxyltransferase inhibiting compounds through molecular docking simulation by in silico analysis. DrugBank database was used to obtain the antibacterial candidates, which were further screened computationally using the AutoDock Vina program on Google Colab Pro. The top nine compounds yielded binding affinity ranging from -12.1 to -12.8 kcal/mol, with conivaptan as one of the three compounds having the highest binding affinity. Molecular dynamic study revealed that the ligand-protein complex for conivaptan had root-mean-square deviation values of 0.05-1.1 nm, indicating likeliness for stable interaction. Our findings suggest that conivaptan is the potent UDP-N-acetylglucosamine 1-carboxyltransferase inhibitor, hence its efficacy against periodontitis-causing bacteria.

PMID:37692019 | PMC:PMC10483916 | DOI:10.4103/JAPTR.JAPTR_129_23