Annu Rev Med. 2023 Oct 12. doi: 10.1146/annurev-med-060622-101239. Online ahead of print.

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. COPD heterogeneity has hampered progress in developing pharmacotherapies that affect disease progression. This issue can be addressed by precision medicine approaches, which focus on understanding an individual's disease risk, and tailoring management based on pathobiology, environmental exposures, and psychosocial issues. There is an urgent need to identify COPD patients at high risk for poor outcomes and to understand at a mechanistic level why certain individuals are at high risk. Genetics, omics, and network analytic techniques have started to dissect COPD heterogeneity and identify patients with specific pathobiology. Drug repurposing approaches based on biomarkers of specific inflammatory processes (i.e., type 2 inflammation) are promising. As larger data sets, additional omics, and new analytical approaches become available, there will be enormous opportunities to identify high-risk individuals and treat COPD patients based on their specific pathophysiological derangements. These approaches show great promise for risk stratification, early intervention, drug repurposing, and developing novel therapeutic approaches for COPD. Expected final online publication date for the Annual Review of Medicine, Volume 75 is January 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

PMID:37827193 | DOI:10.1146/annurev-med-060622-101239

Nat Commun. 2023 Oct 12;14(1):6156. doi: 10.1038/s41467-023-41876-5.

ABSTRACT

Raynaud's phenomenon (RP) is a common vasospastic disorder that causes severe pain and ulcers, but despite its high reported heritability, no causal genes have been robustly identified. We conducted a genome-wide association study including 5,147 RP cases and 439,294 controls, based on diagnoses from electronic health records, and identified three unreported genomic regions associated with the risk of RP (p < 5 × 10-8). We prioritized ADRA2A (rs7090046, odds ratio (OR) per allele: 1.26; 95%-CI: 1.20-1.31; p < 9.6 × 10-27) and IRX1 (rs12653958, OR: 1.17; 95%-CI: 1.12-1.22, p < 4.8 × 10-13) as candidate causal genes through integration of gene expression in disease relevant tissues. We further identified a likely causal detrimental effect of low fasting glucose levels on RP risk (rG = -0.21; p-value = 2.3 × 10-3), and systematically highlighted drug repurposing opportunities, like the antidepressant mirtazapine. Our results provide the first robust evidence for a strong genetic contribution to RP and highlight a so far underrated role of α2A-adrenoreceptor signalling, encoded at ADRA2A, as a possible mechanism for hypersensitivity to catecholamine-induced vasospasms.

PMID:37828025 | DOI:10.1038/s41467-023-41876-5

JCO Precis Oncol. 2023 Sep;7:e2300261. doi: 10.1200/PO.23.00261.

ABSTRACT

Given the high attrition rate of de novo drug discovery and limited efficacy of single-agent therapies in cancer treatment, combination therapy prediction through in silico drug repurposing has risen as a time- and cost-effective alternative for identifying novel and potentially efficacious therapies for cancer. The purpose of this review is to provide an introduction to computational methods for cancer combination therapy prediction and to summarize recent studies that implement each of these methods. A systematic search of the PubMed database was performed, focusing on studies published within the past 10 years. Our search included reviews and articles of ongoing and retrospective studies. We prioritized articles with findings that suggest considerations for improving combination therapy prediction methods over providing a meta-analysis of all currently available cancer combination therapy prediction methods. Computational methods used for drug combination therapy prediction in cancer research include networks, regression-based machine learning, classifier machine learning models, and deep learning approaches. Each method class has its own advantages and disadvantages, so careful consideration is needed to determine the most suitable class when designing a combination therapy prediction method. Future directions to improve current combination therapy prediction technology include incorporation of disease pathobiology, drug characteristics, patient multiomics data, and drug-drug interactions to determine maximally efficacious and tolerable drug regimens for cancer. As computational methods improve in their capability to integrate patient, drug, and disease data, more comprehensive models can be developed to more accurately predict safe and efficacious combination drug therapies for cancer and other complex diseases.

PMID:37824797 | DOI:10.1200/PO.23.00261

Hum Mol Genet. 2023 Oct 12:ddad174. doi: 10.1093/hmg/ddad174. Online ahead of print.

ABSTRACT

Stroke, characterized by sudden neurological deficits, is the second leading cause of death worldwide. Although genome-wide association studies (GWAS) have successfully identified many genomic regions associated with ischemic stroke (IS), the genes underlying risk and their regulatory mechanisms remain elusive. Here, we integrate a large-scale GWAS (N = 1 296 908) for IS together with molecular QTLs data, including mRNA, splicing, enhancer RNA (eRNA), and protein expression data from up to 50 tissues (total N = 11 588). We identify 136 genes/eRNA/proteins associated with IS risk across 60 independent genomic regions and find IS risk is most enriched for eQTLs in arterial and brain-related tissues. Focusing on IS-relevant tissues, we prioritize 9 genes/proteins using probabilistic fine-mapping TWAS analyses. In addition, we discover that blood cell traits, particularly reticulocyte cells, have shared genetic contributions with IS using TWAS-based pheWAS and genetic correlation analysis. Lastly, we integrate our findings with a large-scale pharmacological database and identify a secondary bile acid, deoxycholic acid, as a potential therapeutic component. Our work highlights IS risk genes/splicing-sites/enhancer activity/proteins with their phenotypic consequences using relevant tissues as well as identify potential therapeutic candidates for IS.

PMID:37824084 | DOI:10.1093/hmg/ddad174

Front Immunol. 2023 Sep 26;14:1254873. doi: 10.3389/fimmu.2023.1254873. eCollection 2023.

ABSTRACT

INTRODUCTION: Severe COVID-19 and non-COVID-19 pulmonary sepsis share pathophysiological, immunological, and clinical features, suggesting that severe COVID-19 is a form of viral sepsis. Our objective was to identify shared gene expression trajectories strongly associated with eventual mortality between severe COVID-19 patients and contemporaneous non-COVID-19 sepsis patients in the intensive care unit (ICU) for potential therapeutic implications.

METHODS: Whole blood was drawn from 20 COVID-19 patients and 22 non-COVID-19 adult sepsis patients at two timepoints: ICU admission and approximately a week later. RNA-Seq was performed on whole blood to identify differentially expressed genes and significantly enriched pathways. Using systems biology methods, drug candidates targeting key genes in the pathophysiology of COVID-19 and sepsis were identified.

RESULTS: When compared to survivors, non-survivors (irrespective of COVID-19 status) had 3.6-fold more "persistent" genes (genes that stayed up/downregulated at both timepoints) (4,289 vs. 1,186 genes); these included persistently downregulated genes in T-cell signaling and persistently upregulated genes in select innate immune and metabolic pathways, indicating unresolved immune dysfunction in non-survivors, while resolution of these processes occurred in survivors. These findings of persistence were further confirmed using two publicly available datasets of COVID-19 and sepsis patients. Systems biology methods identified multiple immunomodulatory drug candidates that could target this persistent immune dysfunction, which could be repurposed for possible therapeutic use in both COVID-19 and sepsis.

DISCUSSION: Transcriptional evidence of persistent immune dysfunction was associated with 28-day mortality in both COVID-19 and non-COVID-19 septic patients. These findings highlight the opportunity for mitigating common mechanisms of immune dysfunction with immunomodulatory therapies for both diseases.

PMID:37822940 | PMC:PMC10562687 | DOI:10.3389/fimmu.2023.1254873

J Exp Clin Cancer Res. 2023 Oct 11;42(1):264. doi: 10.1186/s13046-023-02849-0.

ABSTRACT

BACKGROUND: Disseminated tumor cells (DTCs) can enter a dormant state and cause no symptoms in cancer patients. On the other hand, the dormant DTCs can reactivate and cause metastases progression and lethal relapses. In prostate cancer (PCa), relapse can happen after curative treatments such as primary tumor removal. The impact of surgical removal on PCa dissemination and dormancy remains elusive. Furthermore, as dormant DTCs are asymptomatic, dormancy-induction can be an operational cure for preventing metastases and relapse of PCa patients.

METHODS: We used a PCa subcutaneous xenograft model and species-specific PCR to survey the DTCs in various organs at different time points of tumor growth and in response to tumor removal. We developed in vitro 2D and 3D co-culture models to recapitulate the dormant DTCs in the bone microenvironment. Proliferation assays, fluorescent cell cycle reporter, qRT-PCR, and Western Blot were used to characterize the dormancy phenotype. We performed RNA sequencing to determine the dormancy signature of PCa. A drug repurposing algorithm was applied to predict dormancy-inducing drugs and a top candidate was validated for the efficacy and the mechanism of dormancy induction.

RESULTS: We found DTCs in almost all mouse organs examined, including bones, at week 2 post-tumor cell injections. Surgical removal of the primary tumor reduced the overall DTC abundance, but the DTCs were enriched only in the bones. We found that osteoblasts, but not other cells of the bones, induced PCa cell dormancy. RNA-Seq revealed the suppression of mitochondrial-related biological processes in osteoblast-induced dormant PCa cells. Importantly, the mitochondrial-related biological processes were found up-regulated in both circulating tumor cells and bone metastases from PCa patients' data. We predicted and validated the dormancy-mimicking effect of PF-562,271 (PF-271), an inhibitor of focal adhesion kinase (FAK) in vitro. Decreased FAK phosphorylation and increased nuclear translocation were found in both co-cultured and PF-271-treated C4-2B cells, suggesting that FAK plays a key role in osteoblast-induced PCa dormancy.

CONCLUSIONS: Our study provides the first insights into how primary tumor removal enriches PCa cell dissemination in the bones, defines a unique osteoblast-induced PCa dormancy signature, and identifies FAK as a PCa cell dormancy gatekeeper.

PMID:37821954 | DOI:10.1186/s13046-023-02849-0

Sci Transl Med. 2023 Oct 11;15(717):eade1844. doi: 10.1126/scitranslmed.ade1844. Epub 2023 Oct 11.

ABSTRACT

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer. Although cSCC contributes to substantial morbidity and mortality in high-risk individuals, deployment of otherwise effective chemoprevention of cSCC is limited by toxicities. Our systematic computational drug repurposing screen predicted that selumetinib, a MAPK (mitogen-activated protein kinase) kinase inhibitor (MEKi), would reverse transcriptional signatures associated with cSCC development, consistent with our genomic analysis implicating MEK as a chemoprevention target. Although systemic MEKi suppresses the formation of cSCC in mice, systemic MEKi can cause severe adverse effects. Here, we report the development of a metabolically labile MEKi, NFX-179, designed to potently and selectively suppress the MAPK pathway in the skin before rapid metabolism in the systemic circulation. NFX-179 was identified on the basis of its biochemical and cellular potency, selectivity, and rapid metabolism upon systemic absorption. In our ultraviolet-induced cSCC mouse model, topical application of NFX-179 gel reduced the formation of new cSCCs by an average of 60% at doses of 0.1% and greater at 28 days. We further confirmed the localized nature of these effects in an additional split-mouse randomized controlled study where suppression of cSCC was observed only in drug-treated areas. No toxicities were observed. NFX-179 inhibits the growth of human SCC cell lines in a dose-dependent manner, and topical NFX-179 application penetrates human skin and inhibits MAPK signaling in human cSCC explants. Together, our data provide a compelling rationale for using topical MEK inhibition through the application of NFX-179 gel as an effective strategy for cSCC chemoprevention.

PMID:37820007 | DOI:10.1126/scitranslmed.ade1844

J Control Release. 2023 Oct 8:S0168-3659(23)00664-8. doi: 10.1016/j.jconrel.2023.10.014. Online ahead of print.

ABSTRACT

The widespread use of small interfering RNA (siRNA) is limited by the multiple extra- and intracellular barriers upon in vivo administration. Hence, suitable delivery systems, based on siRNA encapsulation in nanoparticles or its conjugation to targeting ligands, have been developed. Nevertheless, at the intracellular level, these state-of-the-art delivery systems still suffer from a low endosomal escape efficiency. Consequently, the bulk of the endocytosed siRNA drug rapidly accumulates in the lysosomal compartment. We recently reported that a wide variety of cationic amphiphilic drugs (CADs) can promote small nucleic acid delivery from the endolysosomal compartment into the cytosol via transient induction of lysosomal membrane permeabilization. Here, we describe the identification of alternate siRNA delivery enhancers from the NIH Clinical Compound Collection that do not have the typical physicochemical properties of CADs. Additionally, we demonstrate improved endolysosomal escape of siRNA via a cholesterol conjugate and polymeric carriers with the α1-adrenergic antagonist prazosin, which was identified as the best performing delivery enhancer from the compound screen. A more detailed assessment of the mode-of-action of prazosin suggests that a different cellular phenotype compared to typical CAD adjuvants drives cytosolic siRNA delivery. As it has been described in the literature that prazosin also induces cancer cell apoptosis and promotes antigen cross-presentation in dendritic cells, the proof-of-concept data in this work provides opportunities for the repurposing of prazosin in an anti-cancer combination strategy with siRNA.

PMID:37816483 | DOI:10.1016/j.jconrel.2023.10.014

Int J Biol Macromol. 2023 Oct 8:127208. doi: 10.1016/j.ijbiomac.2023.127208. Online ahead of print.

ABSTRACT

With the advancements of high throughput computational screening procedures, drug repurposing became the privileged framework for drug discovery. The structure-based drug discovery is the widely used method of drug repurposing, consisting of computational screening of compounds and testing them in-vitro. This current method of repurposing leaves room for mechanistic insights into how these screened hits interact with and influence their targets. We addressed this gap in the current study by integrating highly sensitive biophysical methods into existing computational repurposing methods. We also corroborated our computational and biophysical findings on H37Rv for the anti-mycobacterial action of selected drugs in-vitro and ex-vivo conditions. Atosiban and Rutin were screened as highly interacting hits against HemD through multi-stage docking and were cross-validated in biophysical studies. The affinity of these drugs (K ~ 106 M-1) was quantified using fluorescence quenching studies. Differential Scanning Fluorimetry (DSF) and urea-based chemical denaturation studies revealed a destabilizing effect of these drugs on target which was further validated using MD simulations. Conformational rearrangements of secondary structures were established using CD spectra and intrinsic fluorescence. Furthermore, Atosiban and Rutin inhibited M.tb growth in-vitro and ex-vivo while remaining non-toxic to mice peritoneal macrophages.

PMID:37816464 | DOI:10.1016/j.ijbiomac.2023.127208

NPJ Syst Biol Appl. 2023 Oct 10;9(1):49. doi: 10.1038/s41540-023-00311-7.

ABSTRACT

Proteomics technologies, which include a diverse range of approaches such as mass spectrometry-based, array-based, and others, are key technologies for the identification of biomarkers and disease mechanisms, referred to as mechanotyping. Despite over 15,000 published studies in 2022 alone, leveraging publicly available proteomics data for biomarker identification, mechanotyping and drug target identification is not readily possible. Proteomic data addressing similar biological/biomedical questions are made available by multiple research groups in different locations using different model organisms. Furthermore, not only various organisms are employed but different assay systems, such as in vitro and in vivo systems, are used. Finally, even though proteomics data are deposited in public databases, such as ProteomeXchange, they are provided at different levels of detail. Thus, data integration is hampered by non-harmonized usage of identifiers when reviewing the literature or performing meta-analyses to consolidate existing publications into a joint picture. To address this problem, we present ProHarMeD, a tool for harmonizing and comparing proteomics data gathered in multiple studies and for the extraction of disease mechanisms and putative drug repurposing candidates. It is available as a website, Python library and R package. ProHarMeD facilitates ID and name conversions between protein and gene levels, or organisms via ortholog mapping, and provides detailed logs on the loss and gain of IDs after each step. The web tool further determines IDs shared by different studies, proposes potential disease mechanisms as well as drug repurposing candidates automatically, and visualizes these results interactively. We apply ProHarMeD to a set of four studies on bone regeneration. First, we demonstrate the benefit of ID harmonization which increases the number of shared genes between studies by 50%. Second, we identify a potential disease mechanism, with five corresponding drug targets, and the top 20 putative drug repurposing candidates, of which Fondaparinux, the candidate with the highest score, and multiple others are known to have an impact on bone regeneration. Hence, ProHarMeD allows users to harmonize multi-centric proteomics research data in meta-analyses, evaluates the success of the ID conversions and remappings, and finally, it closes the gaps between proteomics, disease mechanism mining and drug repurposing. It is publicly available at https://apps.cosy.bio/proharmed/ .

PMID:37816770 | DOI:10.1038/s41540-023-00311-7

Nat Commun. 2023 Oct 10;14(1):6332. doi: 10.1038/s41467-023-41828-z.

ABSTRACT

Drug combinations are key to circumvent resistance mechanisms compromising response to single anti-cancer targeted therapies. The implementation of combinatorial approaches involving MEK1/2 or KRASG12C inhibitors in the context of KRAS-mutated lung cancers focuses fundamentally on targeting KRAS proximal activators or effectors. However, the antitumor effect is highly determined by compensatory mechanisms arising in defined cell types or tumor subgroups. A potential strategy to find drug combinations targeting a larger fraction of KRAS-mutated lung cancers may capitalize on the common, distal gene expression output elicited by oncogenic KRAS. By integrating a signature-driven drug repurposing approach with a pairwise pharmacological screen, here we show synergistic drug combinations consisting of multi-tyrosine kinase PKC inhibitors together with MEK1/2 or KRASG12C inhibitors. Such combinations elicit a cytotoxic response in both in vitro and in vivo models, which in part involves inhibition of the PKC inhibitor target AURKB. Proteome profiling links dysregulation of MYC expression to the effect of both PKC inhibitor-based drug combinations. Furthermore, MYC overexpression appears as a resistance mechanism to MEK1/2 and KRASG12C inhibitors. Our study provides a rational framework for selecting drugs entering combinatorial strategies and unveils MEK1/2- and KRASG12C-based therapies for lung cancer.

PMID:37816716 | DOI:10.1038/s41467-023-41828-z

Sci Rep. 2023 Oct 9;13(1):17037. doi: 10.1038/s41598-023-43911-3.

ABSTRACT

Drug repurposing is an important strategy in COVID-19 treatment, but many clinically approved compounds have not been extensively studied in the context of embryogenesis, thus limiting their administration during pregnancy. Here we used the zebrafish embryo model organism to test the effects of 162 marketed drugs on cardiovascular development. Among the compounds used in the clinic for COVD-19 treatment, we found that Remdesivir led to reduced body size and heart functionality at clinically relevant doses. Ritonavir and Baricitinib showed reduced heart functionality and Molnupiravir and Baricitinib showed effects on embryo activity. Sabizabulin was highly toxic at concentrations only 5 times higher than Cmax and led to a mean mortality of 20% at Cmax. Furthermore, we tested if zebrafish could be used as a model to study inflammatory response in response to spike protein treatment and found that Remdesivir, Ritonavir, Molnupiravir, Baricitinib as well as Sabizabulin counteracted the inflammatory response related gene expression upon SARS-CoV-2 spike protein treatment. Our results show that the zebrafish allows to study immune-modulating properties of COVID-19 compounds and highlights the need to rule out secondary defects of compound treatment on embryogenesis. All results are available on a user friendly web-interface https://share.streamlit.io/alernst/covasc_dataapp/main/CoVasc_DataApp.py that provides a comprehensive overview of all observed phenotypic effects and allows personalized search on specific compounds or group of compounds. Furthermore, the presented platform can be expanded for rapid detection of developmental side effects of new compounds for treatment of COVID-19 and further viral infectious diseases.

PMID:37813860 | DOI:10.1038/s41598-023-43911-3

Genomics Inform. 2023 Sep;21(3):e31. doi: 10.5808/gi.23011. Epub 2023 Sep 27.

ABSTRACT

Multiple myeloma (MM) is a hematological malignancy. It is widely believed that genetic factors play a significant role in the development of MM, as investigated in numerous studies. However, the application of genomic information for clinical purposes, including diagnostic and prognostic biomarkers, remains largely confined to research. In this study, we utilized genetic information from the Genomic-Driven Clinical Implementation for Multiple Myeloma database, which is dedicated to clinical trial studies on MM. This genetic information was sourced from the genome-wide association studies catalog database. We prioritized genes with the potential to cause MM based on established annotations, as well as biological risk genes for MM, as potential drug target candidates. The DrugBank database was employed to identify drug candidates targeting these genes. Our research led to the discovery of 14 MM biological risk genes and the identification of 10 drugs that target three of these genes. Notably, only one of these 10 drugs, panobinostat, has been approved for use in MM. The two most promising genes, calcium signal-modulating cyclophilin ligand (CAMLG) and histone deacetylase 2 (HDAC2), were targeted by four drugs (cyclosporine, belinostat, vorinostat, and romidepsin), all of which have clinical evidence supporting their use in the treatment of MM. Interestingly, five of the 10 drugs have been approved for other indications than MM, but they may also be effective in treating MM. Therefore, this study aimed to clarify the genomic variants involved in the pathogenesis of MM and highlight the potential benefits of these genomic variants in drug discovery.

PMID:37813627 | DOI:10.5808/gi.23011

Int J Drug Policy. 2023 Oct 7;122:104210. doi: 10.1016/j.drugpo.2023.104210. Online ahead of print.

ABSTRACT

In 2016, the Australian Government legislated to allow cannabis to be prescribed to patients as an unapproved medicine under the special access provisions of the Therapeutic Goods Act. This paper compares the Australian regulatory approach with other national approaches, outlines the main provisions of the Special Access Scheme for medical cannabis, describes how the program has evolved since 2017, includes an analysis of adverse events reported to the Therapeutic Goods Administration, and discusses the barriers that remain for patients who wish to access medical cannabis. It assesses how well the Australian program has addressed the challenges of providing patients with easier access to medical cannabis while ensuring that high-quality products are used safely and effectively under medical guidance.

PMID:37813082 | DOI:10.1016/j.drugpo.2023.104210

Heliyon. 2023 Sep 21;9(10):e20284. doi: 10.1016/j.heliyon.2023.e20284. eCollection 2023 Oct.

ABSTRACT

This study investigated the drug repositioning potential of metformin for cardiovascular risk due to influenza A virus infection. Statistical analysis was performed to analyze factors related to the risk of death after IAV infection in diabetic patients. Through in vitro and in vivo experiments, the effect of metformin on influenza A virus infection in non-diabetic conditions was analyzed. In logistic regression analysis, influenza vaccination (OR = 0.378, p-value = 0.007, 0.186 < 95% C·I < 0.768) and metformin treatment (OR = 0.380, p-value = 0.016, 0.173 < 95% C·I < 0.835) were associated with a decreased influenza-related mortality in diabetic patients. In vitro and in vivo studies showed that viral replication and influenza A virus-induced cytokine expression were inhibited by metformin. In particular, MCP-1 and IP-10, cytokines related to cell infiltration and cardiovascular disease development, were significantly reduced by metformin under influenza A virus infection condition. As a result, the acute exacerbation of atherosclerosis caused by influenza A virus in mouse aorta was inhibited by metformin. In addition, we found that regulation of AKT/MAPK signaling plays an important role in the mechanism of metformin. In conclusion, we demonstrated the potential and mechanism of metformin as a treatment for acute exacerbation of atherosclerosis caused by influenza A virus infection.

PMID:37810823 | PMC:PMC10556598 | DOI:10.1016/j.heliyon.2023.e20284

ACS Omega. 2023 Sep 18;8(39):35580-35591. doi: 10.1021/acsomega.3c01309. eCollection 2023 Oct 3.

ABSTRACT

Malaria has spread in many countries, with a 12% increase in deaths after the coronavirus disease 2019 pandemic. Malaria is one of the most concerning diseases in the Greater Mekong subregion, showing increased drug-resistant rates. Serine hydroxymethyltransferase (SHMT), a key enzyme in the deoxythymidylate synthesis pathway, has been identified as a promising antimalarial drug target due to its conserved folate binding pocket. This study used a molecular docking approach to screen 2509 US Food and Drug Administration (FDA)-approved drugs against seven Plasmodium SHMT structures. Eight compounds had significantly lower binding energies than the known SHMT inhibitors pyrazolopyran(+)-86, tetrahydrofolate, and antimalarial drugs, ranging from 4 to 10 kcal/mol. Inhibition assays testing the eight compounds against Plasmodium falciparum SHMT (PfSHMT) showed that amphotericin B was a competitive inhibitor of PfSHMT with a half-maximal inhibitory concentration (IC50) of 106 ± 1 μM. Therefore, a 500 ns molecular dynamics simulation of PfSHMT/PLS/amphotericin B was performed. The backbone root-mean-square deviation of the protein-ligand complex indicated the high complex stability during simulations, supported by its radius of gyration, hydrogen-bond interactions, and number of atom contacts. The appreciable binding affinity of amphotericin B for PfSHMT was indicated by their solvated interaction energy (-11.15 ± 0.09 kcal/mol) and supported by strong ligand-protein interactions (≥80% occurrences) with its essential residues (i.e., Y78, K151, N262, F266, and V365) predicted by pharmacophore modeling and per-residue decomposition free energy methods. Therefore, our findings identify a promising new PfSHMT inhibitor, albeit with less inhibitory activity, and suggest a core structure that differs from that of previous SHMT inhibitors, thus being a rational approach for novel antimalarial drug design.

PMID:37810721 | PMC:PMC10552471 | DOI:10.1021/acsomega.3c01309

Diabetes Obes Metab. 2023 Oct 9. doi: 10.1111/dom.15310. Online ahead of print.

ABSTRACT

AIM: To evaluate the effect of metformin on urate metabolism.

MATERIALS AND METHODS: Using the UK Biobank, we first performed association analyses of metformin use with urate levels, risk of hyperuricaemia and incident gout in patients with diabetes. To explore the causal effect of metformin on urate and gout, we identified genetic variants proxying the glycated haemoglobin (HbA1c)-lowering effect of metformin targets and conducted a two-sample Mendelian randomization (MR) utilizing the urate and gout genetic summary-level data from the CKDGen (n = 288 649) and the FinnGen cohort. We conducted two-step MR to explore the mediation effect of body mass index and systolic blood pressure. We also performed non-linear MR in the UK Biobank (n = 414 055) to show the results across HbA1c levels.

RESULTS: In 18 776 patients with type 2 diabetes in UK Biobank, metformin use was associated with decreased urate [β = -4.3 μmol/L, 95% confidence interval (CI) -7.0, -1.7, p = .001] and reduced hyperuricaemia risk (odds ratio = 0.87, 95% CI 0.79, 0.96, p = .004), but not gout. Genetically proxied averaged HbA1c-lowering effects of metformin targets, equivalent to a 0.62% reduction in HbA1c, was associated with reduced urate (β = -12.5 μmol/L, 95% CI -21.4, -4.2, p = .004). Body mass index significantly mediated this association (proportion mediated = 33.0%, p = .002). Non-linear MR results suggest a linear trend of the effect of metformin on urate reduction across various HbA1c levels.

CONCLUSIONS: The effect of metformin may reduce urate levels but not incident gout in the general population.

PMID:37807832 | DOI:10.1111/dom.15310

ACS Infect Dis. 2023 Oct 9. doi: 10.1021/acsinfecdis.3c00212. Online ahead of print.

ABSTRACT

BX795 is an emerging drug candidate that has shown a lot of promise as a next-generation non-nucleoside antiviral agent for the topical treatment of herpes simplex virus type-1 (HSV-1) and herpes simplex virus type-2 (HSV-2) infections. Our studies indicated that BX795 has limited oral bioavailability, which could be attributed to its low and pH-dependent solubility. Lipid-based formulations such as self-nanoemulsifying systems (SNESs) can improve the solubility and oral bioavailability of BX795, but the poor lipid solubility of BX795 further limits the development of SNES. To improve the loading of BX795 into SNES, we evaluated the ability of various bulky and biocompatible anions to transform BX795 into an ionic liquid (IL) with higher lipid solubility. Our studies showed that sodium lauryl sulfate and docusate sodium were able to transform BX795 into IL. Compared to pure BX795, the developed BX795 ILs showed differential in vitro cytocompatibility to HeLa cells but exhibited similar in vitro antiviral activity against HSV-2. Interestingly, BX795 docusate (BX795-Doc), an IL of BX795 with ∼135-fold higher lipid solubility than pure BX795, could be successfully incorporated into an SNES, and the developed BX795-Doc-SNES could readily form nanoemulsions of size ≤200 nm irrespective of the pH of the buffer used for dilution. Our in vitro studies showed that BX795-Doc-SNES retained the inherent antiviral activity against HSV-2 and showed similar in vitro cytocompatibility, indicating the availability of BX795 from the SNES in vitro. Finally, orally delivered SNES containing BX795-Doc showed a significant reduction in HSV-2 infection in mice compared to the untreated control. Thus, the transformation of BX795 into IL and the subsequent incorporation of the BX795 IL into the SNES are an effective strategy to improve oral therapy of genital herpes infection.

PMID:37807721 | DOI:10.1021/acsinfecdis.3c00212

Comput Biol Med. 2023 Sep 27;166:107518. doi: 10.1016/j.compbiomed.2023.107518. Online ahead of print.

ABSTRACT

BACKGROUND: Histone deacetylase 2 (HDAC2), belonging to the class I HDAC family, holds significant therapeutic potential as a crucial target for diverse cancer types. As key players in the realm of epigenetic regulatory enzymes, histone deacetylases (HDACs) are intricately involved in the onset and progression of cancer. Consequently, pursuing isoform-specific inhibitors targeting histone deacetylases (HDACs) has garnered substantial interest in both biological and medical circles. The objective of the present investigation was to employ a drug repurposing approach to discover novel and potent HDAC2 inhibitors.

MATERIALS AND METHODS: In this study, our protocol is presented on virtual screening to identify novel potential HDAC2 inhibitors through 3D-QSAR, molecular docking, pharmacophore modeling, and molecular dynamics (MD) simulation. Afterward, In-vitro assays were employed to evaluate the cytotoxicity, apoptosis, and migration of HCT-116 cell lines under treatment of hit compound and valproic acid as a control inhibitor. The expression levels of HDAC2, TP53, BCL2, and BAX were evaluated by QRT-PCR.

RESULTS: RMSD, RMSF, H-bond, and DSSP analysis results confirmed that among bioinformatically selected compounds, lansoprazole exhibited the highest HDAC2 inhibitory potential. Experimental validation revealed that lansoprazole displayed significant antiproliferative activity. The determined IC50 value was 400 ± 2.36 μM. Furthermore, the apoptotic cells ratio concentration-dependently increased under Lansoprazole treatment. Results of the Scratch assay indicated that lansoprazole led to decreasing the migration of CRC cells. Finally, under Lansoprazole treatment the expression level of BCL2 and HDAC2 decreased and BAX and TP53 increased.

CONCLUSION: Taking together the results of the current study indicated that Lansoprazole as a novel HDAC2 inhibitor, could be used as a potential therapeutic agent for the treatment of CRC. Although, further experimental studies should be performed before using this compound in the clinic.

PMID:37806058 | DOI:10.1016/j.compbiomed.2023.107518

Environ Res. 2023 Oct 5:117117. doi: 10.1016/j.envres.2023.117117. Online ahead of print.

ABSTRACT

INTRODUCTION: Colorectal cancer (CRC) is one of the most malignant tumors and in which various efforts for screening is inconclusive.The intracrine FGF panel, the non-tyrosine kinase receptors (NTKR) FGFs and affiliated antisenses play a pivotal role in FGF signaling.The expression levels of coding and non-coding intracrine FGFs were assessed in CRC donors.Also, substantial costs and slow pace of drug discovery give high attraction to repurpose of previously discovered drugs to new opportunities.

OBJECTIVES: The aim of present study was to evaluate the potential role of the coding and non-coding intracrine FGFs as a new biomarkers for CRC cases and defining drug repurposing to alleviate FGF down regulation.

METHODS: RNA-seq data of colon adenocarcinomas (COAD) was downloaded using TCGA biolinks package in R.The DrugBank database (https://go.drugbank.com/) was used to extract interactions between drugs and candidate genes. A total of 200 CRC patients with detailed criteria were enrolled.RNAs were extracted with TRIzol-based protocol and amplified via LightCycler® instrument.FGF11 and FGF13 proteins validation was performed by used of immunohistochemistry technique in tumor and non-tumoral samples.Pearson's correlation analysis and ROC curve plotted by Prism 8.0 software.

RESULTS: RNA-seq data from TCGA was analyzed by normalizing with edgeR.Differentially expressed gene (DEG) analysis was generated. WCC algorithm extracted the most significant genes with a total of 47 genes. Expression elevation of iFGF antisenses (12AS,13As,14AS) compared with the normal colon tissue were observed (P = 0.0003,P = 0.042,P = 0.026, respectively). Moreover,a significant decrease in expression of the corresponding sense iFGF genes was detected (P < 0.0001).Plotted receiver operating characteristic (ROC) curves for iFGF components' expression showed an area of over 0.70 (FGF11-13: 0.71% and FGF12-14: 0.78%, P < 0.001) for sense mRNA expression, with the highest sensitivity for FGF12 (92.8%) and lowest for FGF11 (61.41%).The artificial intelligence (AI) revealed the valproic acid as a repurposing drug to relief the down regulation of FGF12 and 13 in CRC patients.

CONCLUSION: Intracrine FGFs panel was down regulated versus up regulation of dependent antisenses. Thus, developing novel biomarkers based on iFGF can be considered as a promising strategy for CRC screening.In advanced, valporic acid detected by AI as a repurposing drug which may be applied in clinical trials for CRC treatment.

PMID:37805185 | DOI:10.1016/j.envres.2023.117117