Int J Mol Sci. 2023 Nov 20;24(22):16511. doi: 10.3390/ijms242216511.

ABSTRACT

Drug repurposing is a widely used approach originally developed to aid in the identification of new uses of already existing drugs outside the scope of the original medical indication [...].

PMID:38003701 | DOI:10.3390/ijms242216511

Int J Mol Sci. 2023 Nov 16;24(22):16396. doi: 10.3390/ijms242216396.

ABSTRACT

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary brain tumor whose median survival is less than 15 months. The current treatment regimen comprising surgical resectioning, chemotherapy with Temozolomide (TMZ), and adjuvant radiotherapy does not achieve total patient cure. Stem cells' presence and GBM tumor heterogeneity increase their resistance to TMZ, hence the poor overall survival of patients. A dysregulated cell cycle in glioblastoma enhances the rapid progression of GBM by evading senescence or apoptosis through an over-expression of cyclin-dependent kinases and other protein kinases that are the cell cycle's main regulatory proteins. Herein, we identified and validated the biomarker and predictive properties of a chemoradio-resistant oncogenic signature in GBM comprising CDK1, PBK, and CHEK1 through our comprehensive in silico analysis. We found that CDK1/PBK/CHEK1 overexpression drives the cell cycle, subsequently promoting GBM tumor progression. In addition, our Kaplan-Meier survival estimates validated the poor patient survival associated with an overexpression of these genes in GBM. We used in silico molecular docking to analyze and validate our objective to repurpose Dapagliflozin against CDK1/PBK/CHEK1. Our results showed that Dapagliflozin forms putative conventional hydrogen bonds with CDK1, PBK, and CHEK1 and arrests the cell cycle with the lowest energies as Abemaciclib.

PMID:38003585 | DOI:10.3390/ijms242216396

Int J Mol Sci. 2023 Nov 11;24(22):16209. doi: 10.3390/ijms242216209.

ABSTRACT

Dysregulated metal homeostasis is associated with many pathological conditions, including arthritic diseases. Osteoarthritis and rheumatoid arthritis are the two most prevalent disorders that damage the joints and lead to cartilage and bone destruction. Recent studies show that the levels of zinc (Zn) and copper (Cu) are generally altered in the serum of arthritis patients. Therefore, metal dyshomeostasis may reflect the contribution of these trace elements to the disease's pathogenesis and manifestations, suggesting their potential for prognosis and treatment. Carnosine (Car) also emerged as a biomarker in arthritis and exerts protective and osteogenic effects in arthritic joints. Notably, its zinc(II) complex, polaprezinc, has been recently proposed as a drug-repurposing candidate for bone fracture healing. On these bases, this review article aims to provide an overview of the beneficial roles of Cu and Zn in bone and cartilage health and their potential application in tissue engineering. The effects of Car and polaprezinc in promoting cartilage and bone regeneration are also discussed. We hypothesize that polaprezinc could exchange Zn for Cu, present in the culture media, due to its higher sequestering ability towards Cu. However, future studies should unveil the potential contribution of Cu in the beneficial effects of polaprezinc.

PMID:38003398 | DOI:10.3390/ijms242216209

Eur J Pharmacol. 2023 Nov 22:176176. doi: 10.1016/j.ejphar.2023.176176. Online ahead of print.

ABSTRACT

One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The advantage of computational drug repositioning method is saving time and cost to remove the pre-clinical step and accelerate the drug discovery process. Hence, an ensemble computational-experimental approach, consisting of three different steps, a machine learning model, simulation of drug-target interaction and experimental characterization, was developed. The machine learning type used here was different tree classification method, which is one of the best randomize machine learning model to identify potential inhibitors from weak inhibitors. This model was trained more than one-hundred times, and forty top trained models were extracted for the drug repositioning step. The machine learning step aimed to discover the approved drugs with the highest possible success rate in the experimental step. Therefore, among all the identified molecules with more than 0.9 probability in more than 70% of the models, nine compounds, were selected. Besides, out of the nine chosen drugs, seven compounds have been confirmed to inhibit EGF in the published articles since 2019. Hence, two identified compounds, in addition to gefitinib, as a positive control, five weak-inhibitors and one neutral, were considered via molecular docking study. Finally, eight proposed drugs, including gefitinib, were investigated using MTT assay and In-Cell ELISA to characterize the drugs effect on A431 cell growth and EGF-signaling. From our experiments, we could conclude that salicylic acid and piperazine could play an EGF-inhibitor role like gefitinib.

PMID:38000720 | DOI:10.1016/j.ejphar.2023.176176

Exp Biol Med (Maywood). 2023 Nov 24:15353702231209413. doi: 10.1177/15353702231209413. Online ahead of print.

ABSTRACT

The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and close to seven million deaths worldwide. It is essential to further explore and design effective COVID-19 treatment drugs that target the main protease of SARS-CoV-2, a major target for COVID-19 drugs. In this study, machine learning was applied for predicting the SARS-CoV-2 main protease binding of Food and Drug Administration (FDA)-approved drugs to assist in the identification of potential repurposing candidates for COVID-19 treatment. Ligands bound to the SARS-CoV-2 main protease in the Protein Data Bank and compounds experimentally tested in SARS-CoV-2 main protease binding assays in the literature were curated. These chemicals were divided into training (516 chemicals) and testing (360 chemicals) data sets. To identify SARS-CoV-2 main protease binders as potential candidates for repurposing to treat COVID-19, 1188 FDA-approved drugs from the Liver Toxicity Knowledge Base were obtained. A random forest algorithm was used for constructing predictive models based on molecular descriptors calculated using Mold2 software. Model performance was evaluated using 100 iterations of fivefold cross-validations which resulted in 78.8% balanced accuracy. The random forest model that was constructed from the whole training dataset was used to predict SARS-CoV-2 main protease binding on the testing set and the FDA-approved drugs. Model applicability domain and prediction confidence on drugs predicted as the main protease binders discovered 10 FDA-approved drugs as potential candidates for repurposing to treat COVID-19. Our results demonstrate that machine learning is an efficient method for drug repurposing and, thus, may accelerate drug development targeting SARS-CoV-2.

PMID:37997891 | DOI:10.1177/15353702231209413

BMC Chem. 2023 Nov 22;17(1):161. doi: 10.1186/s13065-023-01082-2.

ABSTRACT

Melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Furthermore, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis, we identified two potent drugs (Tadalafil and Finasteride) that can efficiently inhibit AKT1 and MDM2 proteins. We propose that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma.

PMID:37993971 | DOI:10.1186/s13065-023-01082-2

BMC Geriatr. 2023 Nov 22;23(1):767. doi: 10.1186/s12877-023-04457-1.

ABSTRACT

BACKGROUND: Delirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.

METHODS: We used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.

RESULTS: We have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.

CONCLUSION: This study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

PMID:37993790 | DOI:10.1186/s12877-023-04457-1

BMC Bioinformatics. 2023 Nov 22;24(1):442. doi: 10.1186/s12859-023-05572-x.

ABSTRACT

Drug repurposing is an exciting field of research toward recognizing a new FDA-approved drug target for the treatment of a specific disease. It has received extensive attention regarding the tedious, time-consuming, and highly expensive procedure with a high risk of failure of new drug discovery. Data-driven approaches are an important class of methods that have been introduced for identifying a candidate drug against a target disease. In the present study, a model is proposed illustrating the integration of drug-disease association data for drug repurposing using a deep neural network. The model, so-called IDDI-DNN, primarily constructs similarity matrices for drug-related properties (three matrices), disease-related properties (two matrices), and drug-disease associations (one matrix). Then, these matrices are integrated into a unique matrix through a two-step procedure benefiting from the similarity network fusion method. The model uses a constructed matrix for the prediction of novel and unknown drug-disease associations through a convolutional neural network. The proposed model was evaluated comparatively using two different datasets including the gold standard dataset and DNdataset. Comparing the results of evaluations indicates that IDDI-DNN outperforms other state-of-the-art methods concerning prediction accuracy.

PMID:37993777 | DOI:10.1186/s12859-023-05572-x

Transl Res. 2023 Oct 30:S1931-5244(23)00177-9. doi: 10.1016/j.trsl.2023.10.005. Online ahead of print.

ABSTRACT

ADPKD is characterized by progressive cyst formation and enlargement leading to kidney failure. Tolvaptan is currently the only FDA-approved treatment for ADPKD; however, it can cause serious adverse effects including hepatotoxicity. There remains an unmet clinical need for effective and safe treatments for ADPKD. The extracellular Ca2+-sensing receptor (CaSR) is a regulator of epithelial ion transport. FDA-approved CaSR activator cinacalcet can reduce cAMP-induced Cl- and fluid secretion in various epithelial cells by activating phosphodiesterases (PDE) that hydrolyze cAMP. Since elevated cAMP is a key mechanism of ADPKD progression by promoting cell proliferation, cyst formation and enlargement (via Cl- and fluid secretion), here we tested efficacy of cinacalcet in cell and animal models of ADPKD. Cinacalcet treatment reduced cAMP-induced Cl- secretion and CFTR activity in MDCK cells as suggested by ∼70 % lower short-circuit current (Isc) changes in response to forskolin and CFTRinh-172, respectively. Cinacalcet treatment inhibited forskolin-induced cAMP elevation by 60 % in MDCK cells, and its effect was completely reversed by IBMX (PDE inhibitor). In MDCK cells treated with forskolin, cinacalcet treatment concentration-dependently reduced cell proliferation, cyst formation and cyst enlargement by up to 50 % without affecting cell viability. Cinacalcet treatment (20 mg/kg/day for 7 days, subcutaneous) reduced renal cyst index in a mouse model of ADPKD (Pkd1flox/flox;Ksp-Cre) by 20 %. Lastly, cinacalcet treatment reduced cyst enlargement and cell proliferation in human ADPKD cells by 60 %. Considering its efficacy as shown here, and favorable safety profile including extensive post-approval data, cinacalcet can be repurposed as a novel ADPKD treatment.

PMID:37990828 | DOI:10.1016/j.trsl.2023.10.005

Int Arch Allergy Immunol. 2023 Nov 21:1-12. doi: 10.1159/000534827. Online ahead of print.

ABSTRACT

INTRODUCTION: Allergic disorders are common diseases marked by the abnormal immune response toward foreign antigens that are not pathogens. Often patients with food allergy also suffer from asthma and eczema. Given the similarities of these diseases and a shortage of effective treatments, developing novel therapeutics against common targets of multiple allergies would offer an efficient and cost-effective treatment for patients.

METHODS: We employed the artificial intelligence-driven target discovery platform, PandaOmics, to identify common targets for treating asthma, eczema, and food allergy. Thirty-two case-control comparisons were generated from 15, 11, and 6 transcriptomics datasets related to asthma (558 cases, 315 controls), eczema (441 cases, 371 controls), and food allergy (208 cases, 106 controls), respectively, and allocated into three meta-analyses for target identification. Top-100 high-confidence targets and Top-100 novel targets were prioritized by PandaOmics for each allergic disease.

RESULTS: Six common high-confidence targets (i.e., IL4R, IL5, JAK1, JAK2, JAK3, and NR3C1) across all three allergic diseases have approved drugs for treating asthma and eczema. Based on the targets' dysregulated expression profiles and their mechanism of action in allergic diseases, three potential therapeutic targets were proposed. IL5 was selected as a high-confidence target due to its strong involvement in allergies. PTAFR was identified for drug repurposing, while RNF19B was selected as a novel target for therapeutic innovation. Analysis of the dysregulated pathways commonly identified across asthma, eczema, and food allergy revealed the well-characterized disease signature and novel biological processes that may underlie the pathophysiology of allergies.

CONCLUSION: Altogether, our study dissects the shared pathophysiology of allergic disorders and reveals the power of artificial intelligence in the exploration of novel therapeutic targets.

PMID:37989115 | DOI:10.1159/000534827

IEEE J Biomed Health Inform. 2023 Nov 21;PP. doi: 10.1109/JBHI.2023.3335275. Online ahead of print.

ABSTRACT

Drug repositioning has emerged as a promising strategy for identifying new therapeutic applications for existing drugs. In this study, we present DRGBCN, a novel computational method that integrates heterogeneous information through a deep bilinear attention network to infer potential drugs for specific diseases. DRGBCN involves constructing a comprehensive drug-disease network by incorporating multiple similarity networks for drugs and diseases. Firstly, we introduce a layer attention mechanism to effectively learn the embeddings of graph convolutional layers from these networks. Subsequently, a bilinear attention network is constructed to capture pairwise local interactions between drugs and diseases. This combined approach enhances the accuracy and reliability of predictions. Finally, a multi-layer perceptron module is employed to evaluate potential drugs. Through extensive experiments on three publicly available datasets, DRGBCN demonstrates better performance over baseline methods in 10-fold cross-validation, achieving an average area under the receiver operating characteristic curve (AUROC) of 0.9399. Furthermore, case studies on bladder cancer and acute lymphoblastic leukemia confirm the practical application of DRGBCN in real-world drug repositioning scenarios. Importantly, our experimental results from the drug-disease network analysis reveal the successful clustering of similar drugs within the same community, providing valuable insights into drug-disease interactions. In conclusion, DRGBCN holds significant promise for uncovering new therapeutic applications of existing drugs, thereby contributing to the advancement of precision medicine.

PMID:37988217 | DOI:10.1109/JBHI.2023.3335275

Expert Opin Drug Discov. 2023 Nov 20:1-8. doi: 10.1080/17460441.2023.2284830. Online ahead of print.

ABSTRACT

INTRODUCTION: Selenium possesses numerous advantageous properties in the field of medicine, and a variety of selenium-containing compounds have been documented to exhibit anti-HIV activity. This paper aims to categorize these compounds and conduct SAR analysis to offer guidance for drug design and optimization.

AREAS COVERED: The authors present a comprehensive review of the reported SAR analysis conducted on selenium-based compounds against HIV, accompanied by a concise discussion regarding the pivotal role of selenium in drug development.

EXPERT OPINION: In addition to the conventional bioisosterism strategy, advanced strategies such as covalent inhibition, fragment-based growth and drug repositioning can also be incorporated into research on selenium-containing anti-HIV drugs. Ebselen, which acts as an HIV capsid inhibitor, serves as a valuable probe compound for the discovery of novel HIV integrase inhibitors. Furthermore, it is crucial not to underestimate the potential toxicity associated with organic selenium compounds despite no reported instances of severe toxicity.

PMID:37988053 | DOI:10.1080/17460441.2023.2284830

Naunyn Schmiedebergs Arch Pharmacol. 2023 Nov 21. doi: 10.1007/s00210-023-02849-z. Online ahead of print.

NO ABSTRACT

PMID:37987797 | DOI:10.1007/s00210-023-02849-z

medRxiv. 2023 Nov 7:2023.11.06.23297993. doi: 10.1101/2023.11.06.23297993. Preprint.

ABSTRACT

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, with one in nine people over the age of 65 living with the disease in 2023. In this study, we used a phenome wide association study (PheWAS) approach to identify cross-phenotype associations between previously identified genetic AD and for electronic health record (EHR) diagnoses from the UK Biobank (UKBB) (n=361,194 of European ancestry) and the eMERGE Network (n=105,108 of diverse ancestry). Based on 497 previously identified AD-associated variants from the Alzheimer's Disease Variant Portal (ADVP), we found significant associations primarily in immune and cardiac related diseases in our PheWAS. Replicating variants have widespread impacts on immune genes in diverse tissue types. This study demonstrates the potential of using the PheWAS strategy to improve our understanding of AD progression as well as identify potential drug repurposing opportunities for new treatment and disease prevention strategies.

PMID:37986758 | PMC:PMC10659497 | DOI:10.1101/2023.11.06.23297993

Virol Sin. 2023 Nov 18:S1995-820X(23)00138-4. doi: 10.1016/j.virs.2023.11.006. Online ahead of print.

ABSTRACT

Hepatitis E virus (HEV) infection can cause severe complications and high mortality, particularly in pregnant women, organ transplant recipients, individuals with pre-existing liver disease and immunosuppressed patients. However, there are still unmet needs for treating chronic HEV infections. Herein, we screened a best-in-class drug repurposing library consisting of 262 drugs/compounds. Upon screening, we identified vidofludimus calcium and pyrazofurin as novel anti-HEV entities. Vidofludimus calcium is the next-generation dihydroorotate dehydrogenase (DHODH) inhibitor in the phase 3 pipeline to treat autoimmune diseases or SARS-CoV-2 infection. Pyrazofurin selectively targets uridine monophosphate synthetase (UMPS). Their anti-HEV effects were further investigated in a range of cell culture models and human liver organoids models with wild type HEV strains and ribavirin treatment failure-associated HEV strains. Encouragingly, both drugs exhibited a sizeable therapeutic window against HEV. For instance, the IC50 value of vidofludimus calcium is 4.6-7.6-fold lower than the current therapeutic doses in patients. Mechanistically, their anti-HEV mode of action depends on the blockage of pyrimidine synthesis. Notably, two drugs robustly inhibited ribavirin treatment failure-associated HEV mutants (Y1320H, G1634R). Their combination with IFN-α resulted in synergistic antiviral activity. In conclusion, we identified vidofludimus calcium and pyrazofurin as potent candidates for the treatment of HEV infections. Based on their antiviral potency, and also the favorable safety profile identified in clinical studies, our study supports the initiation of clinical studies to repurpose these drugs for treating chronic hepatitis E.

PMID:37984761 | DOI:10.1016/j.virs.2023.11.006

J Med Chem. 2023 Nov 20. doi: 10.1021/acs.jmedchem.3c00281. Online ahead of print.

ABSTRACT

Recent studies revealed that intestinal microbiota played important roles in colorectal cancer (CRC) carcinogenesis. Particularly, Fusobacterium nucleatum was confirmed to promote the proliferation and metastasis of CRC. Therefore, targeting F. nucleatum may be a potential preventive and therapeutic approach for CRC. Herein, 2,272 off-patent drugs were screened inhibitory activity against F. nucleatum. Among the hits, nitisinone was identified as a promising anti-F. nucleatum lead compound. Further optimization of nitisinone led to the discovery of more potent derivatives. Particularly, compounds 19q and 22c showed potent anti-F. nucleatum activity (MIC50 = 1 and 2 μg/mL, respectively) with low cytotoxicity. Among them, compound 19q effectively attenuated the migratory ability of MC-38 cells induced by F. nucleatum. Preliminary mechanism studies suggested that nitisinone and its derivatives might act by downregulating nitroreductase and tryptophanase. Thus, the development of small molecule F. nucleatum inhibitors represents an effective strategy to treat CRC.

PMID:37983010 | DOI:10.1021/acs.jmedchem.3c00281

Pharm Pat Anal. 2023 Nov 20. doi: 10.4155/ppa-2023-0019. Online ahead of print.

ABSTRACT

Repurposing of approved drugs allows strong savings in time and investment. Rimantadine is an FDA-approved drug for prevention and treatment of influenza A infection. Patent US2021330605 describes the use of rimantadine, an adamantane derivative, for the treatment of melanoma, breast cancer and head and neck squamous cell carcinoma. Rimantadine inhibited proliferation of cell lines of melanoma, breast cancer, and head and neck squamous cell carcinoma, increased the survival of mice injected with cancer cell lines and restores the expression of MHC class I. Rimantadine has the potential to be used successfully in the treatment of head and neck squamous cell carcinoma.

PMID:37982658 | DOI:10.4155/ppa-2023-0019

Future Med Chem. 2023 Nov 20. doi: 10.4155/fmc-2023-0245. Online ahead of print.

ABSTRACT

Aim: To synthesize and explore the therapeutic potential of amodiaquine analogues. Methodology: New promising analogues were synthesized by nucleophilic substitution at the 4-amino position and were characterized using 1H NMR, 13C NMR and FT-IR spectroscopic techniques. Results: Antibacterial and cytotoxic screening revealed the high potency of these compounds; analogue AS1 had a 34.3 ± 0.18 mm zone of inhibition against Pseudomonas aeruginosa. Excellent activity against fungal strains, that is, Candida albicans (39.6 ± 0.23 mm) was shown by analogue AS2. Analogue AS1 had a IC50 = 4.2 μg/ml against the HeLa cell line (cervical cancer) and binding energy against 5GWK (-8.32688 kcal/mol), 1PFK (-6.4780 kcal/mol) and 1TUP (-6.5279 kcal/mol) in the docking study. Conclusion: The obtained results reveal that these analogues exhibit potent antimicrobial and cytotoxic potential.

PMID:37982232 | DOI:10.4155/fmc-2023-0245

J Genet Eng Biotechnol. 2023 Nov 17;21(1):125. doi: 10.1186/s43141-023-00591-w.

ABSTRACT

BACKGROUND: Salmonella Typhi stands as the etiological agent responsible for the onset of human typhoid fever. The pressing demand for innovative therapeutic targets against S. Typhi is underscored by the escalating prevalence of this pathogen and the severe nature of its infections. Consequently, this study employs pangenome analysis to scrutinize 119 S. Typhi-resistant strains, aiming to identify the most promising therapeutic targets originating from its core genome.

RESULTS: Subtractive genomics was employed to systematically eliminate non-homologous (n=1147), essential (n=551), drug-like (n=80), and pathogenicity-related (n=18) proteins from the initial pool of 3351 core genome proteins. Consequently, lipopolysaccharide 1,2-glucosyltransferase RfaJ was designated as the optimal pharmacological target due to its potential versatility. Furthermore, a compendium of 9000 FDA-approved compounds was repurposed for evaluation against the RfaJ drug target, with the specific intent of prioritizing novel, high-potency therapeutic candidates for combating S. Typhi. Ultimately, four compounds, namely DB00549 (Zafirlukast), DB15637 (Fluzoparib), DB15688 (Zavegepant), and DB12411 (Bemcentinib), were singled out as potential inhibitors based on the ligand-protein binding affinity (indicated by the lowest anticipated binding energy) and the overall stability of these compounds. Notably, molecular dynamics simulations, conducted over a 50 nanosecond interval, convincingly demonstrated the stability of these compounds in the context of the RfaJ protein.

CONCLUSION: In summary, the present findings hold significant promise as an initial stride in the broader drug discovery endeavor against S. Typhi infections. However, the experimental validation of the identified drug target and drug candidate is further required to increase the effectiveness of the applied methodology.

PMID:37975995 | DOI:10.1186/s43141-023-00591-w

3 Biotech. 2023 Dec;13(12):397. doi: 10.1007/s13205-023-03814-6. Epub 2023 Nov 14.

ABSTRACT

Glioma coined as a "butterfly" tumor associated with a dismal prognosis. Marine algal compounds with the richest sources of bioactive components act as significant anti-tumor therapeutics. However, there is a paucity of studies conducted on Fucoidan to enhance the anti-glioma efficacy of Temozolomide. Therefore, the present study aimed to evaluate the synergistic anti-proliferative, anti-inflammatory and pro-apoptotic effects of Fucoidan with Temozolomide in in vitro and in silico experimental setup. The anti-proliferative effects of Temozolomide and Fucoidan were evaluated on C6 glioma cells by MTT and migration assay. Modulation of inflammatory markers and apoptosis induction was affirmed at the morphological and transcriptional level by dual staining and gene expression. Molecular docking (MD) and molecular dynamics simulation (MDS) studies were performed against the targets to rationalize the inhibitory effect. The dual-drug combination significantly reduced the cell viability and migration of glioma cells in a synergistic dose-dependent manner. At the molecular level, the dual-drug combination significantly down-regulated inflammatory genes with a concomitant upregulation of pro-apoptotic marker. In consensus with our in vitro findings, molecular docking and simulation studies revealed that the anti-tumor ligands: Temozolomide, Fucoidan with 5-(3-Methy1-trizeno)-imidazole-4-carboxamide (MTIC), and 4-amino-5-imidazole-carboxamide (AIC) had the potency to bind to the inflammatory proteins at their active sites, mediated by H-bonds and other non-covalent interactions. The dual-drug combinatorial treatment synergistically inhibited the proliferation, migration of glioma cells and promoted apoptosis; conversely with the down-regulation of inflammatory genes. However, pre-clinical experimental evidence is warranted for the possible translation of this combination.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13205-023-03814-6.

PMID:37974928 | PMC:PMC10645720 | DOI:10.1007/s13205-023-03814-6