Dig Dis Sci. 2021 Nov 2. doi: 10.1007/s10620-021-07273-y. Online ahead of print.

ABSTRACT

BACKGROUND: Beneficial response to first-line immunosuppressive azathioprine in patients with inflammatory bowel disease (IBD) is low due to high rates of adverse events. Co-administrating allopurinol has been shown to improve tolerability. However, data on this co-therapy as first-line treatment are scarce.

AIM: Retrospective comparison of long-term effectiveness and safety of first-line low-dose azathioprine-allopurinol co-therapy (LDAA) with first-line azathioprine monotherapy (AZAm) in patients with IBD without metabolite monitoring.

METHODS: Clinical benefit was defined as ongoing therapy without initiation of steroids, biologics or surgery. Secondary outcomes included CRP, HBI/SCCAI, steroid withdrawal and adverse events.

RESULTS: In total, 166 LDAA and 118 AZAm patients (median follow-up 25 and 27 months) were evaluated. Clinical benefit was more frequently observed in LDAA patients at 6 months (74% vs. 53%, p = 0.0003), 12 months (54% vs. 37%, p = 0.01) and in the long-term (median 36 months; 37% vs. 24%, p = 0.04). Throughout follow-up, AZAm patients were 60% more likely to fail therapy, due to a higher intolerance rate (45% vs. 26%, p = 0.001). Only 73% of the effective AZA dose was tolerated in AZAm patients, while LDAA could be initiated and maintained at its target dose. Incidence of myelotoxicity and elevated liver enzymes was similar in both cohorts, and both conditions led to LDAA withdrawal in only 2%. Increasing allopurinol from 100 to 200-300 mg/day significantly lowered liver enzymes in 5/6 LDAA patients with hepatotoxicity.

CONCLUSIONS: Our poor AZAm outcomes emphasize that optimization of azathioprine is needed. We demonstrated a long-term safe and more effective profile of first-line LDAA. This co-therapy may therefore be considered standard first-line immunosuppressive.

PMID:34729677 | DOI:10.1007/s10620-021-07273-y

Drug Discov Today. 2021 Oct 30:S1359-6446(21)00475-X. doi: 10.1016/j.drudis.2021.10.019. Online ahead of print.

ABSTRACT

Drug repurposing is an attractive strategy for identifying new indications for existing drugs. Three approved antidepressants have advanced into clinical trials for cancer therapy. In particular, further medicinal chemistry efforts with tranylcypromine (TCP) have led to the discovery of several TCP-based histone lysine specific demethylase 1 (LSD1) inhibitors that display therapeutic promise for treating cancer in the clinic. Thus repurposing antidepressants could be a promising strategy for cancer treatment. In this review, we illustrate the anticancer mechanisms of action of antidepressants and also discuss the challenges and future directions of repurposing antidepressants for anticancer drug discovery, to provide an overview of approved antidepressant cancer therapies.

PMID:34728374 | DOI:10.1016/j.drudis.2021.10.019

iScience. 2021 Oct 23:103331. doi: 10.1016/j.isci.2021.103331. Online ahead of print.

ABSTRACT

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression data sets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene-pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis and pyrimidine metabolism. By in silico screening of FDA-approved drugs on the putative disease-specific essential genes and gene-pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov).

PMID:34723158 | PMC:PMC8536485 | DOI:10.1016/j.isci.2021.103331

Front Genet. 2021 Oct 14;12:756784. doi: 10.3389/fgene.2021.756784. eCollection 2021.

ABSTRACT

Over 50% of diffuse large B-cell lymphoma (DLBCL) patients are diagnosed at an advanced stage. Although there are a few therapeutic strategies for DLBCL, most of them are more effective in limited-stage cancer patients. The prognosis of patients with advanced-stage DLBCL is usually poor with frequent recurrence and metastasis. In this study, we aimed to identify gene expression and network differences between limited- and advanced-stage DLBCL patients, with the goal of identifying potential agents that could be used to relieve the severity of DLBCL. Specifically, RNA sequencing data of DLBCL patients at different clinical stages were collected from the cancer genome atlas (TCGA). Differentially expressed genes were identified using DESeq2, and then, weighted gene correlation network analysis (WGCNA) and differential module analysis were performed to find variations between different stages. In addition, important genes were extracted by key driver analysis, and potential agents for DLBCL were identified according to gene-expression perturbations and the Crowd Extracted Expression of Differential Signatures (CREEDS) drug signature database. As a result, 20 up-regulated and 73 down-regulated genes were identified and 79 gene co-expression modules were found using WGCNA, among which, the thistle1 module was highly related to the clinical stage of DLBCL. KEGG pathway and GO enrichment analyses of genes in the thistle1 module indicated that DLBCL progression was mainly related to the NOD-like receptor signaling pathway, neutrophil activation, secretory granule membrane, and carboxylic acid binding. A total of 47 key drivers were identified through key driver analysis with 11 up-regulated key driver genes and 36 down-regulated key diver genes in advanced-stage DLBCL patients. Five genes (MMP1, RAB6C, ACCSL, RGS21 and MOCOS) appeared as hub genes, being closely related to the occurrence and development of DLBCL. Finally, both differentially expressed genes and key driver genes were subjected to CREEDS analysis, and 10 potential agents were predicted to have the potential for application in advanced-stage DLBCL patients. In conclusion, we propose a novel pipeline to utilize perturbed gene-expression signatures during DLBCL progression for identifying agents, and we successfully utilized this approach to generate a list of promising compounds.

PMID:34721544 | PMC:PMC8551569 | DOI:10.3389/fgene.2021.756784

Front Immunol. 2021 Oct 13;12:724277. doi: 10.3389/fimmu.2021.724277. eCollection 2021.

ABSTRACT

Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.

PMID:34721386 | PMC:PMC8548825 | DOI:10.3389/fimmu.2021.724277

Med Chem Res. 2021 Oct 27:1-15. doi: 10.1007/s00044-021-02808-4. Online ahead of print.

ABSTRACT

Methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Staphylococcus aureus (VRSA) are primary causes of skin and soft tissue infections worldwide. To address the emergency caused due to increasing multidrug-resistant (MDR) bacterial infections, a series of novel fluoro and trifluoromethyl-substituted salicylanilide derivatives were synthesized and their antimicrobial activity was investigated. MIC data reveal that the compounds inhibited S. aureus specifically (MIC 0.25-64 µg/mL). The in vitro cytotoxicity of compounds with MIC < 1 µg/mL against Vero cells led to identification of four compounds (20, 22, 24 and 25) with selectivity index above 10. These four compounds were tested against MDR S. aureus panel. Remarkably, 5-chloro-N-(4'-bromo-3'-trifluoromethylphenyl)-2-hydroxybenzamide (22) demonstrated excellent activity against nine MRSA and three VRSA strains with MIC 0.031-0.062 µg/mL, which is significantly better than the control drugs methicillin and vancomycin. The comparative time-kill kinetic experiment revealed that the effect of bacterial killing of 22 is comparable with vancomycin. Compound 22 did not synergize with or antagonize any FDA-approved antibiotic and reduced pre-formed S. aureus biofilm better than vancomycin. Overall, study suggested that 22 could be further developed as a potent anti-staphylococcal therapeutic.

PMID:34720564 | PMC:PMC8548355 | DOI:10.1007/s00044-021-02808-4

Biol Pharm Bull. 2021 Oct 30. doi: 10.1248/bpb.b21-00324. Online ahead of print.

ABSTRACT

With the development of structural biology and data mining, computer-aided drug design (CADD) has been playing an important role in all aspects of new drug development. Reverse docking, a method of virtual screening based on molecular docking in CADD, is widely used in drug repositioning, drug rescue, and traditional Chinese medicine (TCM) research, for it can search for macromolecular targets that can bind to a given ligand molecule. This review revealed the principle of reverse docking, summarized common target protein databases and docking procedures, and enumerated the applications of reverse docking in drug repositioning, adverse drug reactions, traditional Chinese medicine, and COVID-19 treatment. Hope our work can give some inspiration to researchers engaged in drug development.

PMID:34719576 | DOI:10.1248/bpb.b21-00324

J Parkinsons Dis. 2021 Oct 23. doi: 10.3233/JPD-212929. Online ahead of print.

ABSTRACT

Parkinson's disease is a debilitating neurodegenerative disorder whose etiology is still unclear, hampering the development of effective treatments. There is an urgent need to identify the etiology and provide further effective treatments. Recently, accumulating evidence has indicated that infection may play a role in the etiology of Parkinson's disease. The infective pathogens may act as a trigger for Parkinson's disease, the most common of which are hepatitis C virus, influenza virus, and Helicobacter pylori. In addition, gut microbiota is increasingly recognized to influence brain function through the gut-brain axis, showing an important role in the pathogenesis of Parkinson's disease. Furthermore, a series of anti-infective agents exhibit surprising neuroprotective effects via various mechanisms, such as interfering with α-synuclein aggregation, inhibiting neuroinflammation, attenuating oxidative stress, and preventing from cell death, independent of their antimicrobial effects. The pleiotropic agents affect important events in the pathogenesis of Parkinson's disease. Moreover, most of them are less toxic, clinically safe and have good blood-brain penetrability, making them hopeful candidates for the treatment of Parkinson's disease. However, the use of antibiotics and subsequent gut dysbiosis may also play a role in Parkinson's disease, making the long-term effects of anti-infective drugs worthy of further consideration and exploration. This review summarizes the current evidence for the association between infective pathogens and Parkinson's disease and subsequently explores the application prospects of anti-infective drugs in Parkinson's disease treatment, providing novel insights into the pathogenesis and treatment of Parkinson's disease.

PMID:34719435 | DOI:10.3233/JPD-212929

Drug Discov Today. 2021 Oct 27:S1359-6446(21)00448-7. doi: 10.1016/j.drudis.2021.10.010. Online ahead of print.

ABSTRACT

Drug repositioning is an attractive strategy for discovering new therapeutic uses for approved or investigational drugs, with potentially shorter development timelines and lower development costs. Various computational methods have been used in drug repositioning, promoting the efficiency and success rates of this approach. Recently, deep learning (DL) has attracted wide attention for its potential in target prediction and drug repositioning. Here, we provide an overview of the basic principles of commonly used DL architectures and their applications in target prediction and drug repositioning, and discuss possible ways of dealing with current challenges to help achieve its expected potential for drug repositioning.

PMID:34718208 | DOI:10.1016/j.drudis.2021.10.010

J Oral Biosci. 2021 Oct 27:S1349-0079(21)00141-9. doi: 10.1016/j.job.2021.10.005. Online ahead of print.

ABSTRACT

BACKGROUND: Several recent studies have focused on the utility of drug repurposing to expand clinical application of approved therapeutics. Here, we investigate the efficacy of midazolam (MDZ) and cytokines for regenerating calcified tissue, using immortalized porcine dental pulp (PPU7) and mouse skeletal muscle derived myoblast (C2C12) cells, with the goal of repurposing MDZ as a new treatment to facilitate calcified tissue regeneration.

HIGHLIGHTS: We noted that PPU7 and C2C12 cells cultured with various MDZ regimens displayed increased bone morphogenic protein (BMP-2), transforming growth factor beta (TGF-β), and alkaline phosphatase activity. These increases were highest in PPU7 cells cultured with MDZ alone, and in C2C12 cells cultured with MDZ and BMP-2. PPU7 cells cultured under these conditions demonstrated markedly elevated expression of odontoblastic gene markers, indicating their likely differentiation into odontoblasts. Expression levels of osteoblastic gene markers also increased in C2C12 cells, suggesting that MDZ potentiates the effect of BMP-2, inducing osteoblast differentiation in these cells. Newly formed calcified deposits in both PPU7 and C2C12 cells were identified as hydroxyapatite via crystallographic and crystal engineering analyses.

CONCLUSION: MDZ increases ALP activity, inducing expression of specific marker genes for both odontoblasts and osteoblasts while promoting hydroxyapatite production in both PPU7 and C2C12 cells. These responses were cell type specific. MDZ treatment alone could induce these changes in PPU7 cells, but C2C12 cell differentiation required BMP-2 addition.

PMID:34718143 | DOI:10.1016/j.job.2021.10.005

Pharmacol Ther. 2021 Oct 27:108027. doi: 10.1016/j.pharmthera.2021.108027. Online ahead of print.

ABSTRACT

Responding quickly to emerging respiratory viruses, such as SARS-CoV-2 the causative agent of coronavirus disease 2019 (COVID-19) pandemic, is essential to stop uncontrolled spread of these pathogens and mitigate their socio-economic impact globally. This can be achieved through drug repurposing, which tackles inherent time- and resource-consuming processes associated with conventional drug discovery and development. In this review, we examine key preclinical and clinical therapeutic and prophylactic approaches that have been applied for treatment of SARS-CoV-2 infection. We break these strategies down into virus- versus host-targeting and discuss their reported efficacy, advantages, and disadvantages. Importantly, we highlight emerging evidence on application of host serine protease-inhibiting anticoagulants, such as nafamostat mesylate, as a potentially powerful therapy to inhibit virus activation and offer cross-protection against multiple strains of coronavirus, lower inflammatory response independent of its antiviral effect, and modulate clotting problems seen in COVID-19 pneumonia.

PMID:34718070 | DOI:10.1016/j.pharmthera.2021.108027

BMC Bioinformatics. 2021 Oct 30;22(1):532. doi: 10.1186/s12859-021-04406-y.

ABSTRACT

BACKGROUND: Drug repositioning has caught the attention of scholars at home and abroad due to its effective reduction of the development cost and time of new drugs. However, existing drug repositioning methods that are based on computational analysis are limited by sparse data and classic fusion methods; thus, we use autoencoders and adaptive fusion methods to calculate drug repositioning.

RESULTS: In this study, a drug repositioning algorithm based on a deep autoencoder and adaptive fusion was proposed to mitigate the problems of decreased precision and low-efficiency multisource data fusion caused by data sparseness. Specifically, a drug is repositioned by fusing drug-disease associations, drug target proteins, drug chemical structures and drug side effects. First, drug feature data integrated by drug target proteins and chemical structures were processed with dimension reduction via a deep autoencoder to characterize feature representations more densely and abstractly. Then, disease similarity was computed using drug-disease association data, while drug similarity was calculated with drug feature and drug-side effect data. Predictions of drug-disease associations were also calculated using a top-k neighbor method that is commonly used in predictive drug repositioning studies. Finally, a predicted matrix for drug-disease associations was acquired after fusing a wide variety of data via adaptive fusion. Based on experimental results, the proposed algorithm achieves a higher precision and recall rate than the DRCFFS, SLAMS and BADR algorithms with the same dataset.

CONCLUSION: The proposed algorithm contributes to investigating the novel uses of drugs, as shown in a case study of Alzheimer's disease. Therefore, the proposed algorithm can provide an auxiliary effect for clinical trials of drug repositioning.

PMID:34717542 | DOI:10.1186/s12859-021-04406-y

PLoS One. 2021 Oct 29;16(10):e0259129. doi: 10.1371/journal.pone.0259129. eCollection 2021.

ABSTRACT

Influenza viruses cause respiratory tract infections and substantial health concerns. Infection may result in mild to severe respiratory disease associated with morbidity and some mortality. Several anti-influenza drugs are available, but these agents target viral components and are susceptible to drug resistance. There is a need for new antiviral drug strategies that include repurposing of clinically approved drugs. Drugs that target cellular machinery necessary for influenza virus replication can provide a means for inhibiting influenza virus replication. We used RNA interference screening to identify key host cell genes required for influenza replication, and then FDA-approved drugs that could be repurposed for targeting host genes. We examined the effects of Clopidogrel and Triamterene to inhibit A/WSN/33 (EC50 5.84 uM and 31.48 uM, respectively), A/CA/04/09 (EC50 6.432 uM and 3.32 uM, respectively), and B/Yamagata/16/1988 (EC50 0.28 uM and 0.11 uM, respectively) replication. Clopidogrel and Triamterene provide a druggable approach to influenza treatment across multiple strains and subtypes.

PMID:34714852 | DOI:10.1371/journal.pone.0259129

Front Pharmacol. 2021 Oct 12;12:714643. doi: 10.3389/fphar.2021.714643. eCollection 2021.

ABSTRACT

This research was designed to analyze the composition of immune cells in obesity and identify novel and potent drugs for obesity management by epigenetic and transcriptomic conjoint analysis. DNA methylation data set (GSE166611) and mRNA expression microarray (GSE18897) were obtained from the Gene Expression Omnibus database. A total of 72 objects (35 obese samples and 37 controls) were included in the study. Immune cell composition analysis, drug repositioning, and gene set enrichment analysis (GSEA) were performed using CIBERSORT, connectivity map (CMap), and GSEA tools. Besides, we performed a single-cell RNA-seq of the immune cells from whole blood samples obtained from one obese patient and one healthy control. mRNA levels of drug target genes were analyzed by qPCR assay in blood samples from six patients and six healthy controls. Immune cell composition analysis found that CD8 + T cells and NK cells were significantly lower in the obese group. 11 drugs/compounds are considered to possess obesity-control potential, such as atorvastatin. Moreover, the expression of drug targets (STAT3, MCL1, PMAIP1, SOD2, FOX O 3, FOS, FKBP5) in obese patients were higher than those in controls. In conclusion, immune cells are potential therapeutic targets for obesity. Our results also contribute to accelerate research on drug development of obesity.

PMID:34712134 | PMC:PMC8546369 | DOI:10.3389/fphar.2021.714643

Med Hypotheses. 2021 Oct 20;157:110713. doi: 10.1016/j.mehy.2021.110713. Online ahead of print.

ABSTRACT

Osteoarthritis is still a disease burden for pharmaceutical scientists and strategy makers. It is associated with the chronic inflammation of joints especially weight-bearing joints like knee, hip, backbone, and phalanges. NSAIDs that are used for the management of inflammation associated with osteoarthritis have high side effects related to gastric upset, gastric ulcer, and long term treatment associated with liver and kidney damage. Nanotechnology has gained a huge scope for the management of arthritis as it can reach out to the deep inside the cell and alter cellular physiology as desired. The present study hypothesizes the use of polyion complex nanoparticles of hyaluronic acid linked Pentosan polysulfate sodium, a disease-modifying agent for the treatment of osteoarthritis administered through transdermal route. The hypothesis involves the use of drug repurposing as the drug was initially approved for interstitial cystitis, a condition of the urinary bladder associated with pain and swelling. Being very low oral bioavailability and gastric irritation profile, the transdermal route would be beneficial. To overcome the problem associated with the oral route, there is a need for the targeted approach that will particularly reach at inflammatory sites. Thereby transdermal delivery of hyaluronic acid linked Pentosan polysulfate sodium through polyion complex nanoparticle therapy will be a novel therapeutic approach to combat osteoarthritis.

PMID:34710749 | DOI:10.1016/j.mehy.2021.110713

Mol Syst Biol. 2021 Nov;17(11):e10396. doi: 10.15252/msb.202110396.

ABSTRACT

Treatment options for COVID-19, caused by SARS-CoV-2, remain limited. Understanding viral pathogenesis at the molecular level is critical to develop effective therapy. Some recent studies have explored SARS-CoV-2-host interactomes and provided great resources for understanding viral replication. However, host proteins that functionally associate with SARS-CoV-2 are localized in the corresponding subnetwork within the comprehensive human interactome. Therefore, constructing a downstream network including all potential viral receptors, host cell proteases, and cofactors is necessary and should be used as an additional criterion for the validation of critical host machineries used for viral processing. This study applied both affinity purification mass spectrometry (AP-MS) and the complementary proximity-based labeling MS method (BioID-MS) on 29 viral ORFs and 18 host proteins with potential roles in viral replication to map the interactions relevant to viral processing. The analysis yields a list of 693 hub proteins sharing interactions with both viral baits and host baits and revealed their biological significance for SARS-CoV-2. Those hub proteins then served as a rational resource for drug repurposing via a virtual screening approach. The overall process resulted in the suggested repurposing of 59 compounds for 15 protein targets. Furthermore, antiviral effects of some candidate drugs were observed in vitro validation using image-based drug screen with infectious SARS-CoV-2. In addition, our results suggest that the antiviral activity of methotrexate could be associated with its inhibitory effect on specific protein-protein interactions.

PMID:34709727 | DOI:10.15252/msb.202110396

Mol Syst Biol. 2021 Nov;17(11):e10260. doi: 10.15252/msb.202110260.

ABSTRACT

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy.

PMID:34709707 | DOI:10.15252/msb.202110260

NPJ Syst Biol Appl. 2021 Oct 27;7(1):40. doi: 10.1038/s41540-021-00199-1.

ABSTRACT

The utility of pathway signatures lies in their capability to determine whether a specific pathway or biological process is dysregulated in a given patient. These signatures have been widely used in machine learning (ML) methods for a variety of applications including precision medicine, drug repurposing, and drug discovery. In this work, we leverage highly predictive ML models for drug response simulation in individual patients by calibrating the pathway activity scores of disease samples. Using these ML models and an intuitive scoring algorithm to modify the signatures of patients, we evaluate whether a given sample that was formerly classified as diseased, could be predicted as normal following drug treatment simulation. We then use this technique as a proxy for the identification of potential drug candidates. Furthermore, we demonstrate the ability of our methodology to successfully identify approved and clinically investigated drugs for four different cancers, outperforming six comparable state-of-the-art methods. We also show how this approach can deconvolute a drugs' mechanism of action and propose combination therapies. Taken together, our methodology could be promising to support clinical decision-making in personalized medicine by simulating a drugs' effect on a given patient.

PMID:34707117 | DOI:10.1038/s41540-021-00199-1

Appl Biochem Biotechnol. 2021 Oct 27. doi: 10.1007/s12010-021-03718-2. Online ahead of print.

ABSTRACT

Cervical cancer is the second most common cause of cancer deaths in women worldwide and remains the main reason of mortality among women of reproductive age in developing countries. Nitric oxide is involved in several physiological functions inclusive of inflammatory and immune responses. However, the function of NO in tumor biology is debatable. The inducible NOS (iNOS/NOS2) isoform is the one responsible to maintain the levels of NO, and it exhibits pleotropic effects in various cancers with concentration-dependent pro- and anti-tumor effects. iNOS triggers angiogenesis and endothelial cell migration in tumors by regulating the levels of vascular endothelial growth factor (VEGF). In drug discovery, drug repurposing involves investigations of approved drug candidates to treat various other diseases. In this study, we used anti-cancer drugs and small molecules to target iNOS and identify a potential selective iNOS inhibitor. The structures of ligands were geometrically optimized and energy minimized using Hyperchem software. Molecular docking was performed using Molegro virtual docker, and ligands were selected based on MolDock score, Rerank score, and H-bonding energy. In the study shown, venetoclax compound demonstrated excellent binding affinity to iNOS protein. This compound exhibited the lowest MolDock score and Rerank score with better H-bonding energy to iNOS. The binding efficacy of venetoclax was analyzed by performing molecular docking and molecular dynamic simulations. Multiple parameters were used to analyze the simulation trajectory, like root mean square deviation (RMSD), radius of gyration (Rg), and hydrogen bond interactions. Based on the results, venetoclax emerges to be a promising potential iNOS inhibitor to curtail cervical cancer progression.

PMID:34705247 | DOI:10.1007/s12010-021-03718-2

Aging Cell. 2021 Oct 27:e13497. doi: 10.1111/acel.13497. Online ahead of print.

ABSTRACT

The study of parental lifespan has emerged as an innovative tool to advance aging biology and our understanding of the genetic architecture of human longevity and aging-associated diseases. Here, we leveraged summary statistics of a genome-wide association study including over one million parental lifespans to identify genetically regulated genes from the Genotype-Tissue Expression project. Through a combination of multi-tissue transcriptome-wide association analyses and genetic colocalization, we identified novel genes that may be associated with parental lifespan. Mendelian randomization (MR) analyses also identified circulating proteins and metabolites causally associated with parental lifespan and chronic diseases offering new drug repositioning opportunities such as those targeting apolipoprotein-B-containing lipoproteins. Liver expression of HP, the gene encoding haptoglobin, and plasma haptoglobin levels were causally linked with parental lifespan. Phenome-wide MR analyses were used to map genetically regulated genes, proteins and metabolites with other human traits as well as the disease-related phenome in the FinnGen cohorts (n = 135,638). Altogether, this study identified new candidate genes, circulating proteins and metabolites that may influence human aging as well as potential therapeutic targets for chronic diseases that warrant further investigation.

PMID:34704651 | DOI:10.1111/acel.13497