Ther Adv Cardiovasc Dis. 2023 Jan-Dec;17:17539447231215213. doi: 10.1177/17539447231215213.

ABSTRACT

New evidence continues to accumulate regarding a significant association between excessive inflammation and dysregulated immunity (local and systemic) and the risk of cardiovascular events in different patient cohorts. Whilst research has sought to identify novel atheroprotective therapies targeting inflammation and immunity, several marketed drugs for rheumatological conditions may serve a similar purpose. One such drug, methotrexate, has been used since 1948 for treating cancer and, more recently, for a wide range of dysimmune conditions. Over the last 30 years, epidemiological and experimental studies have shown that methotrexate is independently associated with a reduced risk of cardiovascular disease, particularly in rheumatological patients, and exerts several beneficial effects on vascular homeostasis and blood pressure control. This review article discusses the current challenges with managing cardiovascular risk and the new frontiers offered by drug discovery and drug repurposing targeting inflammation and immunity with a focus on methotrexate. Specifically, the article critically appraises the results of observational, cross-sectional and intervention studies investigating the effects of methotrexate on overall cardiovascular risk and individual risk factors. It also discusses the putative molecular mechanisms underpinning the atheroprotective effects of methotrexate and the practical advantages of using methotrexate in cardiovascular prevention, and highlights future research directions in this area.

PMID:38115784 | DOI:10.1177/17539447231215213

IEEE J Biomed Health Inform. 2023 Dec 18;PP. doi: 10.1109/JBHI.2023.3344031. Online ahead of print.

ABSTRACT

The traditional drug development process requires a significant investment in workforce and financial resources. Drug repositioning as an efficient alternative has attracted much attention during the last few years. Despite the wide application and success of the method, there are still many shortcomings in the existing model. For example, sparse datasets will seriously affect the existing methods' performance. Additionally, these methods do not pay attention to the noise in datasets. In response to the above defects, we propose a semantic-enriched augmented graph contrastive learning with an adaptive denoising method, called SGCD. This method enhances data from the perspective of the embedding layer, deeply mines potential neighborhood relation-ships in semantic space, and combines similar drugs in the semantic neighborhoods into prototype comparison targets, thus effectively mitigating the impact of data sparsity on the model. Moreover, to enhance the model's robustness to noisy data, we use the adaptive denoising method, which can effectively identify noisy data in the training process. Exhaustive experiments on multiple real datasets show the effectiveness of the proposed model. The code implementation is available at https://github.com/yuhuimin11/SGCD-master.

PMID:38109249 | DOI:10.1109/JBHI.2023.3344031

Naunyn Schmiedebergs Arch Pharmacol. 2023 Dec 18. doi: 10.1007/s00210-023-02903-w. Online ahead of print.

ABSTRACT

Breast cancer and osteosarcoma are common cancers in women and children, respectively, but ideal drugs for treating patients with breast cancer or osteosarcoma remain to be found. Micafungin is an antifungal drug with antitumor activity on leukemia. Based on the notion of drug repurposing, this study aims to evaluate the antitumor effects of micafungin on breast cancer and osteosarcoma in vitro and in vivo, and to elucidate the underlying mechanisms. Five breast cancer cell lines (MDA-MB-231, BT-549, SK-BR-3, MCF-7, and 4T1) and one osteosarcoma cell line (143B) were chosen for the in vitro studies. Micafungin exerted an inhibitory effect on the viability of all cell lines, and MCF-7 cells were most sensitive to micafungin among the breast cancer cell lines. In addition, micafungin showed an inhibitory effect on the proliferation, clone formation, and migration in MCF7 and 143B cells. The inhibitory effect of micafungin on the growth of breast cancer and osteosarcoma was further confirmed with xenograft tumor mouse models. To explore the underlying mechanisms, the effect of micafungin on epithelial-mesenchymal transition (EMT) was examined. As expected, the levels of matrix metalloproteinase 9 and vimentin in MCF-7 and 143B cells were notably reduced in the presence of micafungin, concomitant with the decreased levels of ubiquitin-specific protease 7 (USP7), p-AKT, and p-GSK-3β. Based on these observations, we conclude that micafungin exerts antitumor effect on breast cancer and osteosarcoma through preventing EMT in an USP7/AKT/GSK-3β pathway-dependent manner.

PMID:38108838 | DOI:10.1007/s00210-023-02903-w

Heliyon. 2023 Nov 22;9(12):e22605. doi: 10.1016/j.heliyon.2023.e22605. eCollection 2023 Dec.

ABSTRACT

Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system with a low early diagnosis rate. Owing to the side effects, tolerance, and patient contraindications of existing therapies, effective drug treatments for HCC remain a major clinical challenge. However, using approved or investigational drugs not initially intended for cancer therapy is a promising strategy for resolving this problem because their safety have been tested in clinic. Therefore, this study evaluated differentially expressed genes between liver cancer and normal tissues in a cohort of patients with HCC from The Cancer Genome Atlas and applied them to query a connectivity map to identify candidate anti-HCC drugs. As a result, fluphenazine was identified as a candidate for anti-HCC therapy in vitro and in vivo. Fluphenazine suppressed HCC cell proliferation and migration and induced cell cycle arrest and apoptosis, possibly owing to disrupted lysosomal function, blocking autophagy flux. Additionally, in vivo studies demonstrated that fluphenazine suppresses HCC subcutaneous xenografts growth without causing severe side effects. Strikingly, fluphenazine could be used as an analgesic to alleviate oxaliplatin-induced pain as well as pain related anxiety-like behavior. Therefore, fluphenazine could be a novel liver cancer treatment candidate.

PMID:38107270 | PMC:PMC10724577 | DOI:10.1016/j.heliyon.2023.e22605

Res Sq. 2023 Dec 6:rs.3.rs-3675752. doi: 10.21203/rs.3.rs-3675752/v1. Preprint.

ABSTRACT

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.

PMID:38106039 | PMC:PMC10723546 | DOI:10.21203/rs.3.rs-3675752/v1

Methods. 2023 Dec 15:S1046-2023(23)00210-4. doi: 10.1016/j.ymeth.2023.12.001. Online ahead of print.

ABSTRACT

MOTIVATION: The COVID-19 pandemic has been spreading globally for four years, yet specific drugs that effectively suppress the virus remain elusive. Furthermore, the emergence of complications associated with COVID-19 presents significant challenges, making the development of therapeutics for COVID-19 and its complications an urgent task. However, traditional drug development processes are time-consuming. Drug repurposing, which involves identifying new therapeutic applications for existing drugs, presents a viable alternative.

RESULT: In this study, we construct a knowledge graph by retrieving information on genes, drugs, and diseases from databases such as DRUGBANK and GNBR. Next, we employ the TransR knowledge representation learning approach to embed entities and relationships into the knowledge graph. Subsequently, we train the knowledge graph using a graph neural network model based on TransR scoring. This trained knowledge graph is then utilized to predict drugs for the treatment of COVID-19 and its complications. Based on experimental results, we have identified 15 drugs out of the top 30 with the highest success rates associated with treating COVID-19 and its complications. Notably, out of these 15 drugs, 10 specifically aimed at treating COVID-19, such as Torcetrapib and Tocopherol, has not been previously identified in the knowledge graph. This finding highlights the potential of our model in aiding healthcare professionals in drug development and research related to this disease.

PMID:38104883 | DOI:10.1016/j.ymeth.2023.12.001

Biomed Pharmacother. 2023 Dec 15;170:116013. doi: 10.1016/j.biopha.2023.116013. Online ahead of print.

ABSTRACT

The Wnt/β-catenin pathway's significance in cancer initiation, progression, and stem cell biology underscores its therapeutic potential. However, the clinical application of Wnt inhibitors remains limited due to challenges posed by off-target effects and complex cross-talk of Wnt signaling with other pathways. In this study, we leveraged a zebrafish model to perform a robust and rapid drug screening of 773 FDA-approved compounds to identify Wnt/β-catenin inhibitors with minimal toxicity. Utilizing zebrafish expressing a Wnt reporter, we identified several drugs that suppressed Wnt signaling without compromising zebrafish development. The efficacy of the top hit, Erlotinib, extended to human cells, where it blocked Wnt/β-catenin signaling downstream of the destruction complex. Notably, Erlotinib treatment reduced self-renewal in human T-cell Acute Lymphoblastic Leukemia cells, which rely on active β-catenin signaling for maintenance of leukemia-initiating cells. Erlotinib also reduced leukemia-initiating cell frequency and delayed disease formation in zebrafish models. This study underscores zebrafish's translational potential in drug discovery and repurposing and highlights a new use for Erlotinib as a Wnt inhibitor for cancers driven by aberrant Wnt/β-catenin signaling.

PMID:38104416 | DOI:10.1016/j.biopha.2023.116013

BMC Cancer. 2023 Dec 16;23(1):1242. doi: 10.1186/s12885-023-11689-2.

ABSTRACT

BACKGROUND: Despite the diverse genetic mutations in head and neck cancer, the chemotherapy outcome for this cancer has not improved for decades. It is urgent to select prognostic factors and therapeutic targets for oropharyngeal cancer to establish precision medicine. Recent studies have identified PSMD1 as a potential prognostic marker in several cancers. We aimed to assess the prognostic significance of PSMD1 expression in oropharyngeal squamous cell carcinoma (OPSCC) patients using immunohistochemistry.

METHODS: We studied 64 individuals with OPSCC tissue from surgery at Seoul National University Bundang Hospital between April 2008 and August 2017. Immunostaining analysis was conducted on the tissue microarray (TMA) sections (4 μm) for p16 and PSMD1. H-score, which scale from 0 to 300, was calculated from each nucleus, cytoplasm, and cellular expression. Clinicopathological data were compared with Chi-squared test, Fisher's exact test, t-test, and logistic regression. Survival data until 2021 were achieved from national statistical office of Korea. Kaplan-Meier method and cox-regression model were used for disease-specific survival (DSS) analysis.

RESULTS: H-score of 90 in nucleus was appropriate cutoff value for 'High PSMD1 expression' in OPSCC. Tonsil was more frequent location in low PSMD1 group (42/52, 80.8%) than in high PSMD1 group (4/12, 33.3%; P = .002). Early-stage tumor was more frequent in in low PSMD1 group (45/52, 86.5%) than in high PSMD1 group (6/12, 50%; P = .005). HPV was more positive in low PSMD1 group (43/52, 82.7%) than in high PSMD1 group (5/12, 41.7%; P = .016). Patients with PSMD1 high expression showed poorer DSS than in patients with PSMD1 low expression (P = .006 in log rank test). In multivariate analysis, PSMD1 expression, pathologic T staging, and specimen age were found to be associated with DSS (P = .011, P = .025, P = .029, respectively).

CONCLUSIONS: In our study, we established PSMD1 as a negative prognostic factor in oropharyngeal squamous cell carcinoma, indicating its potential as a target for targeted therapy and paving the way for future in vitro studies on drug repositioning.

PMID:38104103 | DOI:10.1186/s12885-023-11689-2

Interdiscip Sci. 2023 Dec 16. doi: 10.1007/s12539-023-00593-9. Online ahead of print.

ABSTRACT

Drug repositioning is critical to drug development. Previous drug repositioning methods mainly constructed drug-disease heterogeneous networks to extract drug-disease features. However, these methods faced difficulty when we are using structurally simple models to deal with complex heterogeneous networks. Therefore, in this study, the researchers introduced a drug repositioning method named DRDSA. The method utilizes a deep sparse autoencoder and integrates drug-disease similarities. First, the researchers constructed a drug-disease feature network by incorporating information from drug chemical structure, disease semantic data, and existing known drug-disease associations. Then, we learned the low-dimensional representation of the feature network using a deep sparse autoencoder. Finally, we utilized a deep neural network to make predictions on new drug-disease associations based on the feature representation. The experimental results show that our proposed method has achieved optimal results on all four benchmark datasets, especially on the CTD dataset where AUC and AUPR reached 0.9619 and 0.9676, respectively, outperforming other baseline methods. In the case study, the researchers predicted the top ten antiviral drugs for COVID-19. Remarkably, six out of these predictions were subsequently validated by other literature sources. Schematic diagrams of data processing and DRDSA model. A Construction of drug and disease feature vectors, B The workflow of DRDSA model.

PMID:38103130 | DOI:10.1007/s12539-023-00593-9

J Chem Inf Model. 2023 Dec 16. doi: 10.1021/acs.jcim.3c01665. Online ahead of print.

ABSTRACT

Drug repositioning plays a key role in disease treatment. With the large-scale chemical data increasing, many computational methods are utilized for drug-disease association prediction. However, most of the existing models neglect the positive influence of non-Euclidean data and multisource information, and there is still a critical issue for graph neural networks regarding how to set the feature diffuse distance. To solve the problems, we proposed SiSGC, which makes full use of the biological knowledge information as initial features and learns the structure information from the constructed heterogeneous graph with the adaptive selection of the information diffuse distance. Then, the structural features are fused with the denoised similarity information and fed to the advanced classifier of CatBoost to make predictions. Three different data sets are used to confirm the robustness and generalization of SiSGC under two splitting strategies. Experiment results demonstrate that the proposed model achieves superior performance compared with the six leading methods and four variants. Our case study on breast neoplasms further indicates that SiSGC is trustworthy and robust yet simple. We also present four drugs for breast cancer treatment with high confidence and further give an explanation for demonstrating the rationality. There is no doubt that SiSGC can be used as a beneficial supplement for drug repositioning.

PMID:38103039 | DOI:10.1021/acs.jcim.3c01665

Respir Res. 2023 Dec 15;24(1):315. doi: 10.1186/s12931-023-02621-0.

ABSTRACT

BACKGROUND: The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated.

METHODS: We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis.

RESULTS: We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, PPLACO=1.38 × 10- 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis.

CONCLUSIONS: Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

PMID:38102678 | DOI:10.1186/s12931-023-02621-0

Int J Biol Macromol. 2023 Dec 13:128667. doi: 10.1016/j.ijbiomac.2023.128667. Online ahead of print.

ABSTRACT

Streptococcus pyogenes (Group A Streptococcus - GAS) is a human pathogen causing wide range of infections and toxin-mediated diseases in human beings of all age groups with fatality of 10-30 %. The limited success of antibiotics and the non-availability of vaccines makes GAS a global burden. The multi-subunit RNA polymerase (RNAP) is a validated bacterial therapeutic target as it is involved in transcription and can arrest growth. Of the five subunits of this enzyme complex, the β'-subunit (RpoC) has attracted specific attention as a drug target, particularly in the switch region. Here we attempt to repurpose non-antimicrobial drugs to act as RpoC inhibitors against S. pyogenes. In this study, 1826 FDA approved drugs have been identified through high-throughput virtual screening. Free Energy Perturbation (FEP) based binding free energy calculations have been performed at the final step of the virtual screening funnel to ensure high accuracy in silico results. Three compounds identified have been tested for susceptibility of S. pyogenes MTCC 442 strain and two antibiotic-resistant clinical isolates of S. pyogenes using microdilution assay. Among the three, two drugs Amlodipine Besylate (Amd) and Ranitidine hydrochloride (Rnt) have shown inhibition against all the tested strains and its mechanism of interaction with RpoC has been studied. The docked complexes were analyzed to understand the binding mode of the drugs to the target. Classical Molecular Dynamics studies for RpoC-Rnt complex and the two stable conformations of RpoC-Amd complex was carried out. Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (RoG) and Solvent Accessible Surface Area (SASA) of the complexes were plotted and studied. The thermodynamic parameters of protein-drug were experimentally determined using Isothermal Titration Calorimetry (ITC). Infrared spectroscopic studies and Fluorescence quenching studies provided insights into the secondary structural changes in RpoC on binding to the drugs.

PMID:38101681 | DOI:10.1016/j.ijbiomac.2023.128667

SLAS Discov. 2023 Dec 13:S2472-5552(23)00093-X. doi: 10.1016/j.slasd.2023.12.003. Online ahead of print.

ABSTRACT

Three-dimensional (3D) cell culture technology has been steadily studied since the 1990's due to its superior biocompatibility compared to the conventional two-dimensional (2D) cell culture technology, and has recently developed into an organoid culture technology that further improved biocompatibility. Since the 3D culture of human cell lines in artificial scaffolds was demonstrated in the early 90's, 3D cell culture technology has been actively developed owing to various needs in the areas of disease research, precision medicine, new drug development, and some of these technologies have been commercialized. In particular, 3D cell culture technology is actively being applied and utilized in drug development and cancer-related precision medicine research. Drug development is a long and expensive process that involves multiple steps-from target identification to lead discovery and optimization, preclinical studies, and clinical trials for approval for clinical use. Cancer ranks first among life-threatening diseases owing to intra-tumoral heterogeneity associated with metastasis, recurrence, and treatment resistance, ultimately contributing to treatment failure and adverse prognoses. Therefore, there is an urgent need for the development of efficient drugs using 3D cell culture techniques that can closely mimic in vivo cellular environments and customized tumor models that faithfully represent the tumor heterogeneity of individual patients. This review discusses 3D cell culture technology focusing on research trends, commercialization status, and expected effects developed until recently. We aim to summarize the great potential of 3D cell culture technology and contribute to expanding the base of this technology.

PMID:38101575 | DOI:10.1016/j.slasd.2023.12.003

Pathol Res Pract. 2023 Dec 13;253:155038. doi: 10.1016/j.prp.2023.155038. Online ahead of print.

ABSTRACT

Lung cancer is one of the leading causes of death worldwide, whereby the major contributing factors are cigarette smoking and exposure to environmental pollutants. Despite the availability of numerous treatment options, including chemotherapy, the five-year survival rate is still extremely low, highlighting the urgent need to develop novel, more effective therapeutic strategies. In this context, the repurposing of previously approved drugs is an advantage in terms of time and resources invested. Ribavirin is an antiviral drug approved for the treatment of hepatitis C, which shows potential for repurposing as an anticancer agent. Among the many signaling molecules promoting carcinogenesis, the interleukins (ILs) IL-6 and IL-8 are interesting therapeutic targets as they promote a variety of cancer hallmarks such as cell proliferation, migration, metastasis, and angiogenesis. In the present study, we show that ribavirin significantly downregulates the expression of IL-6 and IL-8 in vitro in A549 human lung adenocarcinoma cells. The results of this study shed light on the anticancer mechanisms of ribavirin, providing further proof of its potential as a repurposed drug for the treatment of lung cancer.

PMID:38101157 | DOI:10.1016/j.prp.2023.155038

Expert Opin Emerg Drugs. 2023 Dec 15. doi: 10.1080/14728214.2023.2296079. Online ahead of print.

ABSTRACT

INTRODUCTION: Despite the recent full FDA approval of lecanemab, there is currently no disease modifying therapy (DMT) that can efficiently slow down the progression of Alzheimer's disease (AD) in the general population. This statement emphasizes the need to identify novel DMTs in the shortest time possible to prevent a global epidemic of AD cases as the world population experiences an increase in lifespan.

AREAS COVERED: Here, we review several classes of anti-cancer drugs that have been or are being investigated in Phase II/III clinical trials for AD, including immunomodulatory drugs, RXR agonists, sex hormone therapies, tyrosine kinase inhibitors, and monoclonal antibodies.

EXPERT OPINION: Given the overall course of brain pathologies during the progression of AD, we express a great enthusiasm for the repositioning of anti-cancer drugs as possible AD DMTs. We anticipate an increasing number of combinatorial therapy strategies to tackle AD symptoms and their underlying pathologies. However, we strongly encourage improvements in clinical trial study designs to better assess target engagement and possible efficacy over sufficient periods of drug exposure.

PMID:38100555 | DOI:10.1080/14728214.2023.2296079

J Invest Dermatol. 2023 Dec 14:S0022-202X(23)03111-1. doi: 10.1016/j.jid.2023.10.030. Online ahead of print.

ABSTRACT

Pachyonychia congenita (PC) is a dominantly inherited genetic disorder of cornification. PC stands out among other genodermatoses because despite its rarity, it has been the focus of a very large number of pioneering translational research efforts over the past 2 decades, mostly driven by a patient support organization, the Pachyonychia Congenita Project. These efforts have laid the ground for innovative strategies that may broadly impact approaches to the management of other inherited cutaneous and noncutaneous diseases. This article outlines current avenues of research in PC, expected outcomes, and potential hurdles.

PMID:38099888 | DOI:10.1016/j.jid.2023.10.030

Mol Inform. 2023 Dec 14. doi: 10.1002/minf.202300206. Online ahead of print.

ABSTRACT

Fungal infections caused by Candida are still a public health concern. Particularly, the resistance to traditional chemotherapeutic agents is a major issue that requires efforts to develop new therapies. One of the most interesting approaches to finding new active compounds is drug repurposing aided by computational methods. In this work, two databases containing anticandidal agents and drugs were studied employing cheminformatics and compared by similarity methods. The results showed 36 drugs with high similarities to some candicidals. From these drugs, trimetozin, osalmid and metochalcone were evaluated against C. albicans (18804), C. glabrata (90030), and miconazole-resistant strain C. glabrata (32554). Osalmid and metochalcone were the best, with activity in the micromolar range. These findings represent an opportunity to continue with the research on the potential antifungal application of osalmid and metochalcone as well as the design of structurally related derivatives.

PMID:38095132 | DOI:10.1002/minf.202300206

Front Behav Neurosci. 2023 Nov 29;17:1257881. doi: 10.3389/fnbeh.2023.1257881. eCollection 2023.

ABSTRACT

Calorie restriction (CR) is considered an effective intervention for anxiety, aging, and obesity. We investigated the effects of short- and long-term CR on behavior as well as transcriptome profiles in the hypothalamus, amygdala, prefrontal cortex, pituitary, and adrenal glands of Hooded Wistar and Long Evans male rats. A reduction in anxiety-like behavior, as assessed via the elevated plus maze, was observed in both short- and long-term CR. Despite this, short- and long-term CR regulated different sets of genes, leading to distinct transcriptomic signatures. The employed models were able to simultaneously analyze categorical and numerical variables, evaluating the effect of tissue type along with expression data. In all tissues, transcription factors, zinc finger protein 45-like and zinc finger BTB domain-containing two, were the top selected genes by the models in short and long-term CR treatments, respectively. Text mining identified associations between genes of the short-term CR signature and neurodegeneration, stress, and obesity and between genes of the long-term signature and the nervous system. Literature mining-based drug repurposing showed that alongside known CR mimetics such as resveratrol and rapamycin, candidates not typically associated with CR mimetics may be repurposed based on their interaction with transcriptomic signatures of CR. This study goes some way to unravelling the global effects of CR and opens new avenues for treatment for emotional disorders, neurodegeneration, and obesity.

PMID:38094940 | PMC:PMC10716537 | DOI:10.3389/fnbeh.2023.1257881

Front Pharmacol. 2023 Nov 29;14:1333747. doi: 10.3389/fphar.2023.1333747. eCollection 2023.

NO ABSTRACT

PMID:38094888 | PMC:PMC10716446 | DOI:10.3389/fphar.2023.1333747

Biochem Biophys Res Commun. 2023 Dec 4;692:149354. doi: 10.1016/j.bbrc.2023.149354. Online ahead of print.

ABSTRACT

Aging is an intricate process characterized by the gradual deterioration of the physiological integrity of a living organism. This unfortunate phenomenon inevitably leads to a decline in functionality and a heightened susceptibility to the ultimate fate of mortality. Therefore, it is of utmost importance to implement interventions that possess the capability to reverse or preempt age-related pathology. Caloric restriction mimetics (CRMs) refer to a class of molecules that have been observed to elicit advantageous outcomes on both health and longevity in various model organisms and human subjects. Notably, these compounds offer a promising alternative to the arduous task of adhering to a caloric restriction diet and mitigate the progression of the aging process and extend the duration of life in laboratory animals and human population. A plethora of molecular signals have been linked to the practice of caloric restriction, encompassing Insulin-like Growth Factor 1 (IGF1), Mammalian Target of Rapamycin (mTOR), the Adenosine Monophosphate-Activated Protein Kinase (AMPK) pathway, and Sirtuins, with particular emphasis on SIRT1. Therefore, this review will center its focus on several compounds that act as CRMs, highlighting their molecular targets, chemical structures, and mechanisms of action. Moreover, this review serves to underscore the significant relationship between post COVID-19 syndrome, antiaging, and importance of utilizing CRMs. This particular endeavor will serve as a comprehensive guide for medicinal chemists and other esteemed researchers, enabling them to meticulously conceive and cultivate novel molecular entities with the potential to function as efficacious antiaging pharmaceutical agents.

PMID:38091837 | DOI:10.1016/j.bbrc.2023.149354