Biotechnol J. 2024 Feb;19(2):e2300437. doi: 10.1002/biot.202300437.

ABSTRACT

Psoriasis is a common immune-mediated skin condition characterized by aberrant keratinocytes and cell proliferation. The purpose of this study was to explore the FDA-approved drugs by 3D-QSAR pharmacophore model and evaluate their efficiency by in-silico, in vitro, and in vivo psoriasis animal model. A 3D-QSAR pharmacophore model was developed by utilizing HypoGen algorithm using the structural features of 48 diaryl derivatives with diverse molecular patterns. The model was validated by a test set of 27 compounds, by cost analysis method, and Fischer's randomization test. The correlation coefficient of the best model (Hypo2) was 0.9601 for the training set while it was 0.805 for the test set. The selected model was taken as a 3D query for the virtual screening of over 3000 FDA-approved drugs. Compounds mapped with the pharmacophore model were further screened through molecular docking. The hits that showed the best docking results were screened through in silico skin toxicity approach. Top five hits were selected for the MD simulation studies. Based on MD simulations results, the best two hit molecules, that is, ebastine (Ebs) and mebeverine (Mbv) were selected for in vitro and in vivo antioxidant studies performed in mice. TNF-α and COX pro-inflammatory mediators, biochemical assays, histopathological analyses, and immunohistochemistry observations confirmed the anti-inflammatory response of the selected drugs. Based on these findings, it appeared that Ebs can effectively treat psoriasis-like skin lesions and down-regulate inflammatory responses which was consistent with docking predictions and could potentially be employed for further research on inflammation-related skin illnesses such as psoriasis.

PMID:38403464 | DOI:10.1002/biot.202300437

Adv Drug Deliv Rev. 2024 Feb 23:115218. doi: 10.1016/j.addr.2024.115218. Online ahead of print.

ABSTRACT

Interest in myelin and its roles in almost all brain functions has been greatly increasing in recent years, leading to countless new studies on myelination, as a dominant process in the development of cognitive functions. Here, we explore the unique role myelin plays in the central nervous system and specifically discuss the results of altered myelination in neurodevelopmental disorders. We present parallel developmental trajectories involving myelination that correlate with the onset of cognitive impairment in neurodevelopmental disorders and discuss the key challenges in the treatment of these chronic disorders. Recent developments in drug repurposing and nano/micro particle-based therapies are reviewed as a possible pathway to circumvent some of the main hurdles associated to the early intervention - patient's adherence and compliance, side effects, relapse - and faster route to possible treatment of these disorders. The strategy of drug encapsulation overcomes drug solubility and metabolism, with the possibility of drug targeting to a specific compartment, reducing side effects upon systemic administration.

PMID:38403255 | DOI:10.1016/j.addr.2024.115218

Biochem Pharmacol. 2024 Feb 23:116078. doi: 10.1016/j.bcp.2024.116078. Online ahead of print.

ABSTRACT

A drug Mechanism of Action (MoA) is a complex biological phenomenon that describes how a bioactive compound produces a pharmacological effect. The complete knowledge of MoA is fundamental to fully understanding the drug activity. Over the years, many experimental methods have been developed and a huge quantity of data has been produced. Nowadays, considering the increasing omics data availability and the improvement of the accessible computational resources, the study of a drug MoA is conducted by integrating experimental and bioinformatics approaches. The development of new in silico solutions for this type of analysis is continuously ongoing; herein, an updating review on such bioinformatic methods is presented. The methodologies cited are based on multi-omics data integration in biochemical networks and Machine Learning (ML). The multiple types of usable input data and the advantages and disadvantages of each method have been analyzed, with a focus on their applications. Three specific research areas (i.e. cancer drug development, antibiotics discovery, and drug repurposing) have been chosen for their importance in the drug discovery fields in which the study of drug MoA, through novel bioinformatics approaches, is particularly productive.

PMID:38402909 | DOI:10.1016/j.bcp.2024.116078

Viruses. 2024 Jan 28;16(2):202. doi: 10.3390/v16020202.

ABSTRACT

Japanese encephalitis virus (JEV) belongs to the Flaviviridae family and is a representative mosquito-borne flavivirus responsible for acute encephalitis and meningitis in humans. Despite the availability of vaccines, JEV remains a major public health threat with the potential to spread globally. According to the World Health Organization (WHO), there are an estimated 69,000 cases of JE each year, and this figure is probably an underestimate. The majority of JE victims are children in endemic areas, and almost half of the surviving patients have motor or cognitive sequelae. Thus, the absence of a clinically approved drug for the treatment of JE defines an urgent medical need. Recently, several promising and potential drug candidates were reported through drug repurposing studies, high-throughput drug library screening, and de novo design. This review focuses on the historical aspects of JEV, the biology of JEV replication, targets for therapeutic strategies, a target product profile, and drug development initiatives.

PMID:38399978 | DOI:10.3390/v16020202

Pharmaceuticals (Basel). 2024 Jan 31;17(2):189. doi: 10.3390/ph17020189.

ABSTRACT

Drug repurposing is a promising approach that has the potential to revolutionize the drug discovery and development process. By leveraging existing drugs, we can bring new treatments to patients more quickly and affordably. Anti-inflammatory drugs have been shown to target multiple pathways involved in cancer development and progression. This suggests that they may be more effective in treating cancer than drugs that target a single pathway. Cell viability was measured using the MTT assay. The expression of genes related to inflammation (TNFa, IL1b, COX-1, COX-2, and 5-LOX) was measured in HepG2, MCF7, and THLE-2 cells using qPCR. The levels of TNFα, IL1b, COX-1, COX-2, and 5-LOX were also measured in these cells using an ELISA kit. An enzyme binding assay revealed that sulfadiazine expressed weaker inhibitory activity against COX-2 (IC50 = 5.27 μM) in comparison with the COX-2 selective reference inhibitor celecoxib (COX-2 IC50 = 1.94 μM). However, a more balanced inhibitory effect was revealed for sulfadiazine against the COX/LOX pathway with greater affinity towards 5-LOX (IC50 = 19.1 μM) versus COX-1 (IC50 = 18.4 μM) as compared to celecoxib (5-LOX IC50 = 16.7 μM, and COX-1 IC50 = 5.9 μM). MTT assays revealed the IC50 values of 245.69 ± 4.1 µM and 215.68 ± 3.8 µM on HepG2 and MCF7 cell lines, respectively, compared to the standard drug cisplatin (66.92 ± 1.8 µM and 46.83 ± 1.3 µM, respectively). The anti-inflammatory effect of sulfadiazine was also depicted through its effect on the levels of inflammatory markers and inflammation-related genes (TNFα, IL1b, COX-1, COX-2, 5-LOX). Molecular simulation studies revealed key binding interactions that explain the difference in the activity profiles of sulfadiazine compared to celecoxib. The results suggest that sulfadiazine exhibited balanced inhibitory activity against the 5-LOX/COX-1 enzymes compared to the selective COX-2 inhibitor, celecoxib. These findings highlight the potential of sulfadiazine as a potential anticancer agent through balanced inhibitory activity against the COX/LOX pathway and reduction in the expression of inflammatory genes.

PMID:38399404 | DOI:10.3390/ph17020189

Pharmaceutics. 2024 Jan 31;16(2):212. doi: 10.3390/pharmaceutics16020212.

ABSTRACT

The potential benefits of drug repurposing have gained attention as an alternative to developing de novo drugs. The potential of using central nervous system (CNS) drugs as anticancer drugs has been explored in several types of human cancers, such as breast and colon cancer, among others. Here, we examine the effect of the CNS drugs sertraline, paroxetine, and chlorpromazine on human squamous carcinoma cells of the bladder (UM-UC-5). After exposing UM-UC-5 cells to increased concentrations of each drug for 48 h, we assessed their metabolic activity using an MTT assay. Based on those results, we calculated cell viability and the half-maximal inhibitory concentration (IC50) values. The results suggest that the CNS drugs were effective against UM-UC-5 in the order of potency of sertraline > chlorpromazine > paroxetine. Interestingly, sertraline was more potent than 5-fluorouracil (5-FU), a widely used anticancer drug. This study demonstrated, for the first time, the promising anticancer activity of CNS drugs on human bladder cancer cells in vitro and supports the repurposing of CNS drugs to improve cancer treatment. Nevertheless, further studies are necessary to understand their mechanism of action and in vivo activity.

PMID:38399266 | DOI:10.3390/pharmaceutics16020212

Life (Basel). 2024 Feb 7;14(2):233. doi: 10.3390/life14020233.

ABSTRACT

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI's role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.

PMID:38398742 | DOI:10.3390/life14020233

Biomedicines. 2024 Jan 26;12(2):286. doi: 10.3390/biomedicines12020286.

ABSTRACT

The primary cause of atherosclerotic cardiovascular disease (ASCVD) is elevated levels of low-density lipoprotein cholesterol (LDL-C). Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays a crucial role in this process by binding to the LDL receptor (LDL-R) domain, leading to reduced influx of LDL-C and decreased LDL-R cell surface presentation on hepatocytes, resulting higher circulating levels of LDL-C. As a consequence, PCSK9 has been identified as a crucial target for drug development against dyslipidemia and hypercholesterolemia, aiming to lower plasma LDL-C levels. This research endeavors to identify promising inhibitory candidates that target the allosteric site of PCSK9 through an in silico approach. To start with, the FDA-approved Drug Library from Selleckchem was selected and virtually screened by docking studies using Glide extra-precision (XP) docking mode and Smina software (Version 1.1.2). Subsequently, rescoring of 100 drug compounds showing good average docking scores were performed using Gnina software (Version 1.0) to generate CNN Score and CNN binding affinity. Among the drug compounds, amikacin, bestatin, and natamycin were found to exhibit higher docking scores and CNN affinities against the PCSK9 enzyme. Molecular dynamics simulations further confirmed that these drug molecules established the stable protein-ligand complexes when compared to the apo structure of PCSK9 and the complex with the co-crystallized ligand structure. Moreover, the MM-GBSA calculations revealed binding free energy values ranging from -84.22 to -76.39 kcal/mol, which were found comparable to those obtained for the co-crystallized ligand structure. In conclusion, these identified drug molecules have the potential to serve as inhibitors PCSK9 enzyme and these finding could pave the way for the development of new PCSK9 inhibitory drugs in future in vitro research.

PMID:38397888 | DOI:10.3390/biomedicines12020286

Int J Mol Sci. 2024 Feb 8;25(4):2059. doi: 10.3390/ijms25042059.

ABSTRACT

The in-silico strategy of identifying novel uses for already existing drugs, known as drug repositioning, has enhanced drug discovery. Previous studies have shown a positive correlation between expression changes induced by the anticancer agent trabectedin and those caused by irinotecan, a topoisomerase I inhibitor. Leveraging the availability of transcriptional datasets, we developed a general in-silico drug-repositioning approach that we applied to investigate novel trabectedin synergisms. We set a workflow allowing the identification of genes selectively modulated by a drug and possible novel drug interactions. To show its effectiveness, we selected trabectedin as a case-study drug. We retrieved eight transcriptional cancer datasets including controls and samples treated with trabectedin or its analog lurbinectedin. We compared gene signature associated with each dataset to the 476,251 signatures from the Connectivity Map database. The most significant connections referred to mitomycin-c, topoisomerase II inhibitors, a PKC inhibitor, a Chk1 inhibitor, an antifungal agent, and an antagonist of the glutamate receptor. Genes coherently modulated by the drugs were involved in cell cycle, PPARalpha, and Rho GTPases pathways. Our in-silico approach for drug synergism identification showed that trabectedin modulates specific pathways that are shared with other drugs, suggesting possible synergisms.

PMID:38396735 | DOI:10.3390/ijms25042059

Eur J Epidemiol. 2024 Feb 24. doi: 10.1007/s10654-024-01103-x. Online ahead of print.

ABSTRACT

Findings on the correlation between the use of antihypertensive medication and the risk of breast cancer (BC) have been inconsistent. We performed a two-sample Mendelian randomization (MR) using instrumental variables to proxy changes in gene expressions of antihypertensive medication targets to interrogate this. Genetic instruments for expression of antihypertensive drug target genes were identified with expression quantitative trait loci in blood, which should be associated with systolic blood pressure to proxy for the effect of antihypertensive drug. The association between genetic variants and BC risk were obtained from genome-wide association study summary statistics. The summary-based MR was employed to estimate the drug effects on BC risk. We further performed sensitivity analyses to confirm the discovered MR associations such as assessment of horizontal pleiotropy, colocalization, and multiple tissue enrichment analyses. The overall BC risk was only associated with SLC12A2 gene expression at a Bonferroni-corrected threshold. One standard deviation (SD) decrease of SLC12A2 gene expression in blood was associated with a decrease of 1.12 (95%CI, 0.80-1.58) mmHg of systolic blood pressure, but a 16% increased BC risk (odds ratio, 1.16, 95% confidential interval, 1.06-1.28). This signal was further observed for estrogen receptor positive (ER +) BC (1.17, 1.06-1.28). In addition, one SD decrease in expression of PDE1B in blood was associated with 7% decreased risk of ER + BC (0.93, 0.90-0.97). We detected no evidence of horizontal pleiotropy for these associations and the probability of the causal variants being shared between the gene expression and BC risk was 81.5, 40.5 and 66.8%, respectively. No significant association was observed between other target gene expressions and BC risk. Changes in expression of SLC12A2 and PDE1B mediated possibly via antihypertensive drugs may result in increased and decreased BC risk, respectively.

PMID:38396187 | DOI:10.1007/s10654-024-01103-x

Br J Cancer. 2024 Feb 23. doi: 10.1038/s41416-024-02608-8. Online ahead of print.

ABSTRACT

BACKGROUND: Glioblastoma represents a brain tumor with a notoriously poor prognosis. First-line therapy may include adjunctive Tumor Treating Fields (TTFields) which are electric fields that are continuously delivered to the brain through non-invasive arrays. On a different note, CUSP9v3 represents a drug repurposing strategy that includes 9 repurposed drugs plus metronomic temozolomide. Here, we examined whether TTFields enhance the antineoplastic activity of CUSP9v3 against this disease.

METHODS: We performed preclinical testing of a multimodal approach of TTFields and CUSP9v3 in different glioblastoma models.

RESULTS: TTFields had predominantly synergistic inhibitory effects on the cell viability of glioblastoma cells and non-directed movement was significantly impaired when combined with CUSP9v3. TTFields plus CUSP9v3 significantly enhanced apoptosis, which was associated with a decreased mitochondrial outer membrane potential (MOMP), enhanced cleavage of effector caspase 3 and reduced expression of Bcl-2 and Mcl-1. Moreover, oxidative phosphorylation and expression of respiratory chain complexes I, III and IV was markedly reduced.

CONCLUSION: TTFields strongly enhance the CUSP9v3-mediated anti-glioblastoma activity. TTFields are currently widely used for the treatment of glioblastoma patients and CUSP9v3 was shown to have a favorable safety profile in a phase Ib/IIa trial (NCT02770378) which facilitates transition of this multimodal approach to the clinical setting.

PMID:38396172 | DOI:10.1038/s41416-024-02608-8

Biochem Pharmacol. 2024 Feb 21:116075. doi: 10.1016/j.bcp.2024.116075. Online ahead of print.

ABSTRACT

Cancer is recognized as the major cause of death worldwide and the most challenging public health issues. Tumor cells exhibit molecular adaptations and metabolic reprograming to sustain their high proliferative rate and autophagy plays a pivotal role to supply the high demand for metabolic substrates and for recycling cellular components, which has attracted the attention of the researchers. The modulation of the autophagic process sensitizes tumor cells to chemotherapy-induced cell death and reverts drug resistance. In this regard, many in vitro and in vivo studies having shown the anticancer activity of phenothiazine (PTZ) derivatives due to their potent cytotoxicity in tumor cells. Interestingly, PTZ have been used as antiemetics in antitumor chemotherapy-induced vomiting, maybe exerting a combined antitumor effect. Among the mechanisms of cytotoxicity, the modulation of autophagy by these drugs has been highlighted. Therefore, the use of PTZ derivatives can be considered as a repurposing strategy in antitumor chemotherapy. Here, we provided an overview of the effects of antipsychotic PTZ on autophagy in tumor cells, evidencing the molecular targets and discussing the underlying mechanisms. The modulation of autophagy by PTZ in tumor cells have been consistently related to their cytotoxic action. These effects depend on the derivative, their concentration, and also the type of cancer. Most data have shown the impairment of autophagic flux by PTZ, probably due to the blockade of lysosome-autophagosome fusion, but some studies have also suggested the induction of autophagy. These data highlight the therapeutic potential of targeting autophagy by PTZ in cancer chemotherapy.

PMID:38395266 | DOI:10.1016/j.bcp.2024.116075

Trop Med Infect Dis. 2024 Jan 25;9(2):30. doi: 10.3390/tropicalmed9020030.

ABSTRACT

One of the major drawbacks of current treatments for neglected tropical diseases is the low safety of the drugs used and the emergence of resistance. Leishmaniasis is a group of neglected diseases caused by protozoa of the trypanosomatidae family that lacks preventive vaccines and whose pharmacological treatments are scarce and unsafe. Combination therapy is a strategy that could solve the above-mentioned problems, due to the participation of several mechanisms of action and the reduction in the amount of drug necessary to obtain the therapeutic effect. In addition, this approach also increases the odds of finding an effective drug following the repurposing strategy. From the previous screening of two collections of repositioning drugs, we found that pyrvinium pamoate had a potent leishmanicidal effect. For this reason, we decided to combine it separately with two clinically used leishmanicidal drugs, miltefosine and paromomycin. These combinations were tested in axenic amastigotes of Leishmania infantum obtained from bone marrow cells and in intramacrophagic amastigotes obtained from primary cultures of splenic cells, both cell types coming from experimentally infected mice. Some of the combinations showed synergistic behavior, especially in the case of the combination of pyrvinium pamoate with paromomycin, and exhibited low cytotoxicity and good tolerability on intestinal murine organoids, which reveal the potential of these combinations for the treatment of leishmaniasis.

PMID:38393119 | DOI:10.3390/tropicalmed9020030

Biology (Basel). 2024 Jan 29;13(2):82. doi: 10.3390/biology13020082.

ABSTRACT

The glucocorticoid receptor (GR) and ten-eleven translocation 2 (TET2), respectively, play a crucial role in regulating immunity and inflammation, and GR interacts with TET2. However, their synergetic roles in inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn's disease (CD), remain unclear. This study aimed to investigate the co-target gene signatures of GR and TET2 in IBD and provide potential therapeutic interventions for IBD. By integrating public data, we identified 179 GR- and TET2-targeted differentially expressed genes (DEGs) in CD and 401 in UC. These genes were found to be closely associated with immunometabolism, inflammatory responses, and cell stress pathways. In vitro inflammatory cellular models were constructed using LPS-treated HT29 and HCT116 cells, respectively. Drug repositioning based on the co-target gene signatures of GR and TET2 derived from transcriptomic data of UC, CD, and the in vitro model was performed using the Connectivity Map (CMap). BMS-536924 emerged as a top therapeutic candidate, and its validation experiment within the in vitro inflammatory model confirmed its efficacy in mitigating the LPS-induced inflammatory response. This study sheds light on the pathogenesis of IBD from a new perspective and may accelerate the development of novel therapeutic agents for inflammatory diseases including IBD.

PMID:38392301 | DOI:10.3390/biology13020082

Antibiotics (Basel). 2024 Feb 10;13(2):177. doi: 10.3390/antibiotics13020177.

ABSTRACT

The aims of this study were (i) to determine if the combination of mitomycin C with pentamidine or existing antibiotics resulted in enhanced efficacy versus infections with MDR P. aeruginosa in vivo; and (ii) to determine if the doses of mitomycin C and pentamidine in combination can be reduced to levels that are non-toxic in humans but still retain antibacterial activity. Resistant clinical isolates of P. aeruginosa, a mutant strain over-expressing the MexAB-OprM resistance nodulation division (RND) efflux pump and a strain with three RND pumps deleted, were used. MIC assays indicated that all strains were sensitive to mitomycin C, but deletion of three RND pumps resulted in hypersensitivity and over-expression of MexAB-OprM caused some resistance. These results imply that mitomycin C is a substrate of the RND efflux pumps. Mitomycin C monotherapy successfully treated infected Galleria mellonella larvae, albeit at doses too high for human administration. Checkerboard and time-kill assays showed that the combination of mitomycin C with pentamidine, or the antibiotic gentamicin, resulted in synergistic inhibition of most P. aeruginosa strains in vitro. In vivo, administration of a combination therapy of mitomycin C with pentamidine, or gentamicin, to G. mellonella larvae infected with P. aeruginosa resulted in enhanced efficacy compared with monotherapies for the majority of MDR clinical isolates. Notably, the therapeutic benefit conferred by the combination therapy occurred with doses of mitomycin C close to those used in human medicine. Thus, repurposing mitomycin C in combination therapies to target MDR P. aeruginosa infections merits further investigation.

PMID:38391563 | DOI:10.3390/antibiotics13020177

Int J Oncol. 2024 Apr;64(4):39. doi: 10.3892/ijo.2024.5627. Epub 2024 Feb 23.

ABSTRACT

Neddylation, akin to ubiquitination, represents a post‑translational modification of proteins wherein neural precursor cell‑expressed developmentally downregulated protein 8 (NEDD8) is modified on the substrate protein through a series of reactions. Neddylation plays a pivotal role in the growth and proliferation of animal cells. In colorectal cancer (CRC), it predominantly contributes to the proliferation, metastasis and survival of tumor cells, decreasing overall patient survival. The strategic manipulation of the NEDD8‑mediated neddylation pathway holds immense therapeutic promise in terms of the potential to modulate the growth of tumors by regulating diverse biological responses within cancer cells, such as DNA damage response and apoptosis, among others. MLN4924 is an inhibitor of NEDD8, and its combined use with platinum drugs and irinotecan, as well as cycle inhibitors and NEDD activating enzyme inhibitors screened by drug repurposing, has been found to exert promising antitumor effects. The present review summarizes the recent progress made in the understanding of the role of NEDD8 in the advancement of CRC, suggesting that NEDD8 is a promising anti‑CRC target.

PMID:38391033 | DOI:10.3892/ijo.2024.5627

J Biomol Struct Dyn. 2024 Feb 22:1-31. doi: 10.1080/07391102.2024.2319104. Online ahead of print.

ABSTRACT

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

PMID:38385447 | DOI:10.1080/07391102.2024.2319104

Front Pharmacol. 2024 Feb 7;15:1337764. doi: 10.3389/fphar.2024.1337764. eCollection 2024.

ABSTRACT

Accurately identifying novel indications for drugs is crucial in drug research and discovery. Traditional drug discovery is costly and time-consuming. Computational drug repositioning can provide an effective strategy for discovering potential drug-disease associations. However, the known experimentally verified drug-disease associations is relatively sparse, which may affect the prediction performance of the computational drug repositioning methods. Moreover, while the existing drug-disease prediction method based on metric learning algorithm has achieved better performance, it simply learns features of drugs and diseases only from the drug-centered perspective, and cannot comprehensively model the latent features of drugs and diseases. In this study, we propose a novel drug repositioning method named RSML-GCN, which applies graph convolutional network and reinforcement symmetric metric learning to predict potential drug-disease associations. RSML-GCN first constructs a drug-disease heterogeneous network by integrating the association and feature information of drugs and diseases. Then, the graph convolutional network (GCN) is applied to complement the drug-disease association information. Finally, reinforcement symmetric metric learning with adaptive margin is designed to learn the latent vector representation of drugs and diseases. Based on the learned latent vector representation, the novel drug-disease associations can be identified by the metric function. Comprehensive experiments on benchmark datasets demonstrated the superior prediction performance of RSML-GCN for drug repositioning.

PMID:38384286 | PMC:PMC10879308 | DOI:10.3389/fphar.2024.1337764

Sci Rep. 2024 Feb 21;14(1):4328. doi: 10.1038/s41598-024-55013-9.

ABSTRACT

The COVID-19 pandemic caused by the SARS-CoV-2 virus has greatly affected global health. Emerging evidence suggests a complex interplay between Alzheimer's disease (AD), diabetes (DM), and COVID-19. Given COVID-19's involvement in the increased risk of other diseases, there is an urgent need to identify novel targets and drugs to combat these interconnected health challenges. Lysophosphatidic acid receptors (LPARs), belonging to the G protein-coupled receptor family, have been implicated in various pathological conditions, including inflammation. In this regard, the study aimed to investigate the involvement of LPARs (specifically LPAR1, 3, 6) in the tri-directional relationship between AD, DM, and COVID-19 through network analysis, as well as explore the therapeutic potential of selected anti-AD, anti-DM drugs as LPAR, SPIKE antagonists. We used the Coremine Medical database to identify genes related to DM, AD, and COVID-19. Furthermore, STRING analysis was used to identify the interacting partners of LPAR1, LPAR3, and LPAR6. Additionally, a literature search revealed 78 drugs on the market or in clinical studies that were used for treating either AD or DM. We carried out docking analysis of these drugs against the LPAR1, LPAR3, and LPAR6. Furthermore, we modeled the LPAR1, LPAR3, and LPAR6 in a complex with the COVID-19 spike protein and performed a docking study of selected drugs with the LPAR-Spike complex. The analysis revealed 177 common genes implicated in AD, DM, and COVID-19. Protein-protein docking analysis demonstrated that LPAR (1,3 & 6) efficiently binds with the viral SPIKE protein, suggesting them as targets for viral infection. Furthermore, docking analysis of the anti-AD and anti-DM drugs against LPARs, SPIKE protein, and the LPARs-SPIKE complex revealed promising candidates, including lupron, neflamapimod, and nilotinib, stating the importance of drug repurposing in the drug discovery process. These drugs exhibited the ability to bind and inhibit the LPAR receptor activity and the SPIKE protein and interfere with LPAR-SPIKE protein interaction. Through a combined network and targeted-based therapeutic intervention approach, this study has identified several drugs that could be repurposed for treating COVID-19 due to their expected interference with LPAR(1, 3, and 6) and spike protein complexes. In addition, it can also be hypothesized that the co-administration of these identified drugs during COVID-19 infection may not only help mitigate the impact of the virus but also potentially contribute to the prevention or management of post-COVID complications related to AD and DM.

PMID:38383841 | DOI:10.1038/s41598-024-55013-9

Schizophrenia (Heidelb). 2024 Feb 21;10(1):22. doi: 10.1038/s41537-024-00445-5.

ABSTRACT

Multimorbidity represents an increasingly important public health challenge with far-reaching implications for health management and policy. Mental health and metabolic diseases have a well-established epidemiological association. In this study, we investigate the genetic intersection between type 2 diabetes and schizophrenia. We use Mendelian randomization to examine potential causal relationships between the two conditions and related endophenotypes. We report no compelling evidence that type 2 diabetes genetic liability potentially causally influences schizophrenia risk and vice versa. Our findings show that increased body mass index (BMI) has a protective effect against schizophrenia, in contrast to the well-known risk-increasing effect of BMI on type 2 diabetes risk. We identify evidence of colocalization of association signals for these two conditions at 11 genomic loci, six of which have opposing directions of effect for type 2 diabetes and schizophrenia. To elucidate these colocalizing signals, we integrate multi-omics data from bulk and single-cell gene expression studies, along with functional information. We identify putative effector genes and find that they are enriched for homeostasis and lipid-related pathways. We also highlight drug repurposing opportunities including N-methyl-D-aspartate (NMDA) receptor antagonists. Our findings provide insights into shared biological mechanisms for type 2 diabetes and schizophrenia, highlighting common factors that influence the risk of the two conditions in opposite directions and shedding light on the complex nature of this comorbidity.

PMID:38383672 | DOI:10.1038/s41537-024-00445-5