Brief Bioinform. 2022 Jul 12:bbac272. doi: 10.1093/bib/bbac272. Online ahead of print.

ABSTRACT

In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the problem of drug-target interaction prediction. Our proposed model is inspired by sentence classification models in the field of Natural Language Processing, where the drug-target complex is treated as a sentence with relational meaning between its biochemical entities a.k.a. protein pockets and drug molecule. AttentionSiteDTI enables interpretability by identifying the protein binding sites that contribute the most toward the drug-target interaction. Results on three benchmark datasets show improved performance compared with the current state-of-the-art models. More significantly, unlike previous studies, our model shows superior performance, when tested on new proteins (i.e. high generalizability). Through multidisciplinary collaboration, we further experimentally evaluate the practical potential of our proposed approach. To achieve this, we first computationally predict the binding interactions between some candidate compounds and a target protein, then experimentally validate the binding interactions for these pairs in the laboratory. The high agreement between the computationally predicted and experimentally observed (measured) drug-target interactions illustrates the potential of our method as an effective pre-screening tool in drug repurposing applications.

PMID:35817396 | DOI:10.1093/bib/bbac272

Brief Bioinform. 2022 Jul 12:bbac268. doi: 10.1093/bib/bbac268. Online ahead of print.

ABSTRACT

The cost of drug development continues to rise and may be prohibitive in cases of unmet clinical need, particularly for rare diseases. Artificial intelligence-based methods are promising in their potential to discover new treatment options. The task of drug repurposing hypothesis generation is well-posed as a link prediction problem in a knowledge graph (KG) of interacting of drugs, proteins, genes and disease phenotypes. KGs derived from biomedical literature are semantically rich and up-to-date representations of scientific knowledge. Inference methods on scientific KGs can be confounded by unspecified contexts and contradictions. Extracting context enables incorporation of relevant pharmacokinetic and pharmacodynamic detail, such as tissue specificity of interactions. Contradictions in biomedical KGs may arise when contexts are omitted or due to contradicting research claims. In this review, we describe challenges to creating literature-scale representations of pharmacological knowledge and survey current approaches toward incorporating context and resolving contradictions.

PMID:35817308 | DOI:10.1093/bib/bbac268

EBioMedicine. 2022 Jul 8;82:104149. doi: 10.1016/j.ebiom.2022.104149. Online ahead of print.

ABSTRACT

BACKGROUND: Medulloblastoma is the most frequent brain malignancy of childhood. The current multimodal treatment comes at the expense of serious and often long-lasting side effects. Drug repurposing is a strategy to fast-track anti-cancer therapy with low toxicity. Here, we showed the ability of β-blockers to potentiate radiotherapy in medulloblastoma with bad prognosis.

METHODS: Medulloblastoma cell lines, patient-derived xenograft cells, 3D spheroids and an innovative cerebellar organotypic model were used to identify synergistic interactions between β-blockers and ionising radiations. Gene expression profiles of β-adrenergic receptors were analysed in medulloblastoma samples from 240 patients. Signaling pathways were explored by RT-qPCR, RNA interference, western blotting and RNA sequencing. Medulloblastoma cell bioenergetics were evaluated by measuring the oxygen consumption rate, the extracellular acidification rate and superoxide production.

FINDINGS: Low concentrations of β-blockers significantly potentiated clinically relevant radiation protocols. Although patient biopsies showed detectable expression of β-adrenergic receptors, the ability of the repurposed drugs to potentiate ionising radiations did not result from the inhibition of the canonical signaling pathway. We highlighted that the efficacy of the combinatorial treatment relied on a metabolic catastrophe that deprives medulloblastoma cells of their adaptive bioenergetics capacities. This led to an overproduction of superoxide radicals and ultimately to an increase in ionising radiations-mediated DNA damages.

INTERPRETATION: These data provide the evidence of the efficacy of β-blockers as potentiators of radiotherapy in medulloblastoma, which may help improve the treatment and quality of life of children with high-risk brain tumours.

FUNDING: This study was funded by institutional grants and charities.

PMID:35816899 | DOI:10.1016/j.ebiom.2022.104149

Curr Res Chem Biol. 2022;2:100025. doi: 10.1016/j.crchbi.2022.100025. Epub 2022 Apr 22.

ABSTRACT

The rapid spread of COVID-19 has caused a worldwide public health crisis. For prompt and effective development of antivirals for SARS-CoV-2, the pathogen of COVID-19, drug repurposing has been broadly conducted by targeting the main protease (MPro), a key enzyme responsible for the replication of virus inside the host. In this study, we evaluate the inhibition potency of a nitrothiazole-containing drug, halicin, and reveal its reaction and interaction mechanism with MPro. The in vitro potency test shows that halicin inhibits the activity of MPro an IC50 of 181.7 ​nM. Native mass spectrometry and X-ray crystallography studies clearly indicate that the nitrothiazole fragment of halicin covalently binds to the catalytic cysteine C145 of MPro. Interaction and conformational changes inside the active site of MPro suggest a favorable nucleophilic aromatic substitution reaction mechanism between MPro C145 and halicin, explaining the high inhibition potency of halicin towards MPro.

PMID:35815070 | PMC:PMC9023366 | DOI:10.1016/j.crchbi.2022.100025

Front Oncol. 2022 Jun 24;12:900985. doi: 10.3389/fonc.2022.900985. eCollection 2022.

ABSTRACT

The combinatory use of drugs for systemic cancer therapy commonly aims at the direct elimination of tumor cells through induction of apoptosis. An alternative approach becomes the focus of attention if biological changes in tumor tissues following combinatory administration of regulatorily active drugs are considered as a therapeutic aim, e.g., differentiation, transdifferentiation induction, reconstitution of immunosurveillance, the use of alternative cell death mechanisms. Editing of the tumor tissue establishes new biological 'hallmarks' as a 'pressure point' to attenuate tumor growth. This may be achieved with repurposed, regulatorily active drug combinations, often simultaneously targeting different cell compartments of the tumor tissue. Moreover, tissue editing is paralleled by decisive functional changes in tumor tissues providing novel patterns of target sites for approved drugs. Thus, agents with poor activity in non-edited tissue may reveal new clinically meaningful outcomes. For tissue editing and targeting edited tissue novel requirements concerning drug selection and administration can be summarized according to available clinical and pre-clinical data. Monoactivity is no pre-requisite, but combinatory bio-regulatory activity. The regulatorily active dose may be far below the maximum tolerable dose, and besides inhibitory active drugs stimulatory drug activities may be integrated. Metronomic scheduling often seems to be of advantage. Novel preclinical approaches like functional assays testing drug combinations in tumor tissue are needed to select potential drugs for repurposing. The two-step drug repurposing procedure, namely establishing novel functional systems states in tumor tissues and consecutively providing novel target sites for approved drugs, facilitates the systematic identification of drug activities outside the scope of any original clinical drug approvals.

PMID:35814409 | PMC:PMC9270020 | DOI:10.3389/fonc.2022.900985

J Alzheimers Dis. 2022 Jul 7. doi: 10.3233/JAD-220120. Online ahead of print.

ABSTRACT

BACKGROUND: Human diseases are multi-factorial biological phenomena resulting from perturbations of numerous functional networks. The complex nature of human diseases explains frequently observed marginal or transitory efficacy of mono-therapeutic interventions. For this reason, combination therapy is being increasingly evaluated as a biologically plausible strategy for reversing disease state, fostering the development of dedicated methodological and experimental approaches. In parallel, genome-wide association studies (GWAS) provide a prominent opportunity for disclosing human-specific therapeutic targets and rational drug repurposing.

OBJECTIVE: In this context, our objective was to elaborate an integrated computational platform to accelerate discovery and experimental validation of synergistic combinations of repurposed drugs for treatment of common human diseases.

METHODS: The proposed approach combines adapted statistical analysis of GWAS data, pathway-based functional annotation of genetic findings using gene set enrichment technique, computational reconstruction of signaling networks enriched in disease-associated genes, selection of candidate repurposed drugs and proof-of-concept combinational experimental screening.

RESULTS: It enables robust identification of signaling pathways enriched in disease susceptibility loci. Therapeutic targeting of the disease-associated signaling networks provides a reliable way for rational drug repurposing and rapid development of synergistic drug combinations for common human diseases.

CONCLUSION: Here we demonstrate the feasibility and efficacy of the proposed approach with an experiment application to Alzheimer's disease.

PMID:35811522 | DOI:10.3233/JAD-220120

Comput Biol Med. 2022 Jun 30;147:105788. doi: 10.1016/j.compbiomed.2022.105788. Online ahead of print.

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the worldwide spread of coronavirus disease 19 (COVID-19), and till now, it has caused death to more than 6.2 million people. Although various vaccines and drug candidates are being tested globally with limited to moderate success, a comprehensive therapeutic cure is yet to be achieved. In this study, we applied computational drug repurposing methods complemented with the analyses of the already existing gene expression data to find better therapeutics in treatment and recovery. Primarily, we identified the most crucial proteins of SARS-CoV-2 and host human cells responsible for viral infection and host response. An in-silico screening of the existing drugs was performed against the crucial proteins for SARS-CoV-2 infection, and a few existing drugs were shortlisted. Further, we analyzed the gene expression data of SARS-CoV-2 in human lung epithelial cells and investigated the molecules that can reverse the cellular mRNA expression profiles in the diseased state. LINCS L1000 and Comparative Toxicogenomics Database (CTD) were utilized to obtain two sets of compounds that can be used to counter SARS-CoV-2 infection from the gene expression perspective. Indomethacin, a nonsteroidal anti-inflammatory drug (NSAID), and Vitamin-A were found in two sets of compounds, and in the in-silico screening of existing drugs to treat SARS-CoV-2. Our in-silico findings on Indomethacin were further successfully validated by in-vitro testing in Vero CCL-81 cells with an IC50 of 12 μM. Along with these findings, we briefly discuss the possible roles of Indomethacin and Vitamin-A to counter the SARS-CoV-2 infection in humans.

PMID:35809412 | DOI:10.1016/j.compbiomed.2022.105788

Molecules. 2022 Jun 25;27(13):4098. doi: 10.3390/molecules27134098.

ABSTRACT

NIMA-related kinase7 (NEK7) plays a multifunctional role in cell division and NLRP3 inflammasone activation. A typical expression or any mutation in the genetic makeup of NEK7 leads to the development of cancer malignancies and fatal inflammatory disease, i.e., breast cancer, non-small cell lung cancer, gout, rheumatoid arthritis, and liver cirrhosis. Therefore, NEK7 is a promising target for drug development against various cancer malignancies. The combination of drug repurposing and structure-based virtual screening of large libraries of compounds has dramatically improved the development of anticancer drugs. The current study focused on the virtual screening of 1200 benzene sulphonamide derivatives retrieved from the PubChem database by selecting and docking validation of the crystal structure of NEK7 protein (PDB ID: 2WQN). The compounds library was subjected to virtual screening using Auto Dock Vina. The binding energies of screened compounds were compared to standard Dabrafenib. In particular, compound 762 exhibited excellent binding energy of -42.67 kJ/mol, better than Dabrafenib (-33.89 kJ/mol). Selected drug candidates showed a reactive profile that was comparable to standard Dabrafenib. To characterize the stability of protein-ligand complexes, molecular dynamic simulations were performed, providing insight into the molecular interactions. The NEK7-Dabrafenib complex showed stability throughout the simulated trajectory. In addition, binding affinities, pIC50, and ADMET profiles of drug candidates were predicted using deep learning models. Deep learning models predicted the binding affinity of compound 762 best among all derivatives, which supports the findings of virtual screening. These findings suggest that top hits can serve as potential inhibitors of NEK7. Moreover, it is recommended to explore the inhibitory potential of identified hits compounds through in-vitro and in-vivo approaches.

PMID:35807344 | DOI:10.3390/molecules27134098

Int J Mol Sci. 2022 Jun 29;23(13):7213. doi: 10.3390/ijms23137213.

ABSTRACT

Despite the recent development of precision medicine and targeted therapies, lung cancer remains the top cause of cancer-related mortality worldwide. The patients diagnosed with metastatic disease have a five-year survival rate lower than 6%. In metastatic disease, EGFR is the most common driver of mutation, with the most common co-driver hitting TP53. EGFR-positive patients are offered the frontline treatment with tyrosine kinase inhibitors, yet the development of resistance and the lack of alternative therapies make this group of patients only fit for clinical trial participation. Since mutant p53 is the most common co-driver in the metastatic setting, therapies reactivating the p53 pathway might serve as a promising alternative therapeutic approach in patients who have developed a resistance to tyrosine kinase inhibitors. This review focuses on the molecular background of EGFR-mutated lung cancer and discusses novel therapeutic options converging on the reactivation of p53 tumor suppressor pathways.

PMID:35806218 | DOI:10.3390/ijms23137213

Int J Mol Sci. 2022 Jun 26;23(13):7109. doi: 10.3390/ijms23137109.

ABSTRACT

Nanoparticulate systems have been widely investigated as delivery vectors for efficient drug delivery in different diseases. Nanostructured lipid carriers (NLC) are composed of both solid and liquid lipids (glyceryl dibehenate and diethylene glycol monoethyl ether) and have demonstrated enhanced biological compatibility and increased drug loading capability. Furthermore, the use of peptides, in particular cell-penetrating peptides, to functionalize nanoparticles and enhance cell membrane permeation was explored in this paper. In this paper, we described the synthesis of a new conjugated of tranylcypromine with MAP. In addition, taking into consideration our previous results, this study developed different NLCs loaded with three central nervous system (CNS) drugs (tacrine (TAC), rasagiline (RAS), and tranylcypromine (TCP)) functionalized with model amphipathic peptide (MAP) and evaluated their activity against cancer cells. Particle size analysis demonstrated NLC presented less than 200 nm and a polydispersity index less than 0.3. Moreover, in vitro results showed that conjugation of MAP with drugs led to a higher decrease in cell viability of a neuroblastoma cell line and Caco-2 cell line, more than MAP alone. Furthermore, NLC encapsulation contributed to higher cellular delivery and enhanced toxic activity at lower concentrations when compared with free or co-administration drug-MAP conjugate.

PMID:35806112 | DOI:10.3390/ijms23137109

Int J Mol Sci. 2022 Jun 21;23(13):6889. doi: 10.3390/ijms23136889.

ABSTRACT

Treatment options for Coronavirus Disease 2019 (COVID-19) remain limited, and the option of repurposing approved drugs with promising medicinal properties is of increasing interest in therapeutic approaches to COVID-19. Using computational approaches, we examined griseofulvin and its derivatives against four key anti-SARS-CoV-2 targets: main protease, RdRp, spike protein receptor-binding domain (RBD), and human host angiotensin-converting enzyme 2 (ACE2). Molecular docking analysis revealed that griseofulvin (CID 441140) has the highest docking score (-6.8 kcal/mol) with main protease of SARS-CoV-2. Moreover, griseofulvin derivative M9 (CID 144564153) proved the most potent inhibitor with -9.49 kcal/mol, followed by A3 (CID 46844082) with -8.44 kcal/mol against M protease and ACE2, respectively. Additionally, H bond analysis revealed that compound A3 formed the highest number of hydrogen bonds, indicating the strongest inhibitory efficacy against ACE2. Further, molecular dynamics (MD) simulation analysis revealed that griseofulvin and these derivatives are structurally stable. These findings suggest that griseofulvin and its derivatives may be considered when designing future therapeutic options for SARS-CoV-2 infection.

PMID:35805893 | DOI:10.3390/ijms23136889

Cancers (Basel). 2022 Jul 1;14(13):3248. doi: 10.3390/cancers14133248.

ABSTRACT

Growing evidence shows that nerves play an active role in cancer development and progression by altering crucial molecular pathways and cell functions. Conversely, the use of neurotropic drugs, such as tricyclic antidepressants (TCAs), may modulate these molecular signals with a therapeutic purpose based on a direct antitumoral effect and beyond the TCA use to treat neuropathic pain in oncology patients. In this review, we discuss the TCAs' safety and their central effects against neuropathic pain in cancer, and the antitumoral effects of TCAs in in vitro and preclinical studies, as well as in the clinical setting. The current evidence points out that TCAs are safe and beneficial to treat neuropathic pain associated with cancer and chemotherapy, and they block different molecular pathways used by cancer cells from different locations for tumor growth and promotion. Likewise, ongoing clinical trials evaluating the antineoplastic effects of TCAs are discussed. TCAs are very biologically active compounds, and their repurposing as antitumoral drugs is a promising and straightforward approach to treat specific cancer subtypes and to further define their molecular targets, as well as an interesting starting point to design analogues with increased antitumoral activity.

PMID:35805019 | DOI:10.3390/cancers14133248

Cancers (Basel). 2022 Jun 29;14(13):3198. doi: 10.3390/cancers14133198.

ABSTRACT

Glioblastoma (GBM) is an aggressive form of brain tumor with a median survival of approximately 12 months. With no new drugs in the last few decades and limited success in clinics for known therapies, drug repurposing is an attractive choice for its treatment. Here, we examined the efficacy of pyronaridine (PYR), an anti-malarial drug in GBM cells. PYR induced anti-proliferative activity in GBM cells with IC50 ranging from 1.16 to 6.82 µM. Synergistic activity was observed when PYR was combined with Doxorubicin and Ritonavir. Mechanistically, PYR triggered mitochondrial membrane depolarization and enhanced the ROS levels causing caspase-3 mediated apoptosis. PYR significantly decreased markers associated with proliferation, EMT, hypoxia, and stemness and upregulated the expression of E-cadherin. Interestingly, PYR induced the expression of intracellular as well as secretory Par-4, a tumor suppressor in GBM cells, which was confirmed using siRNA. Notably, Par-4 levels in plasma samples of GBM patients were significantly lower than normal healthy volunteers. Thus, our study demonstrates for the first time that PYR can be repurposed against GBM with a novel mechanism of action involving Par-4. Herewith, we discuss the role of upregulated Par-4 in a highly interconnected signaling network thereby advocating its importance as a therapeutic target.

PMID:35804970 | DOI:10.3390/cancers14133198

J Am Chem Soc. 2022 Jul 8. doi: 10.1021/jacs.2c03324. Online ahead of print.

ABSTRACT

The global crisis of untreatable microbial infections necessitates the design of new antibiotics. Drug repurposing is a promising strategy for expanding the antibiotic repertoire. In this study, we repurpose the clinically approved anticancer agent cisplatin into a targeted antibiotic by conjugating its Pt(IV) prodrug to enterobactin (Ent), a triscatecholate siderophore employed by Enterobacteriaceae for iron (Fe) acquisition. The l-Ent-Pt(IV) conjugate (l-EP) exhibits antibacterial activity against Escherichia coli K12 and the uropathogenic isolate E. coli CFT073. Similar to cisplatin, l-EP causes a filamentous morphology in E. coli and initiates lysis in lysogenic bacteria. Studies with E. coli mutants defective in Ent transport proteins show that Ent mediates the delivery of l-EP into the E. coli cytoplasm, where reduction of the Pt(IV) prodrug releases the cisplatin warhead, causing growth inhibition and filamentation of E. coli. Substitution of Ent with its enantiomer affords the d-Ent-Pt(IV) conjugate (d-EP), which displays enhanced antibacterial activity, presumably because d-Ent cannot be hydrolyzed by Ent esterases and thus Fe cannot be released from this conjugate. E. coli treated with l/d-EP accumulate ≥10-fold more Pt as compared to cisplatin treatment. By contrast, human embryonic kidney cells (HEK293T) accumulate cisplatin but show negligible Pt uptake after treatment with either conjugate. Overall, this work demonstrates that the attachment of a siderophore repurposes a Pt anticancer agent into a targeted antibiotic that is recognized and transported by siderophore uptake machinery, providing a design strategy for drug repurposing by siderophore modification and heavy-metal "trojan-horse" antibiotics.

PMID:35803281 | DOI:10.1021/jacs.2c03324

J Mol Graph Model. 2022 Jun 18;116:108254. doi: 10.1016/j.jmgm.2022.108254. Online ahead of print.

ABSTRACT

Calcitonin gene-related peptide receptor (CGRPR) is a heterodimer consisting of CLR and RAMP1 proteins. Activation of the CGRPR with the endogenous peptide CGRP is known to play a crucial role in migraine pathophysiology. CGRP occupies two regions in the CGRPR upon binding, namely ectodomain and transmembrane sites (sites 1 and 2, respectively). The disruption of the CGRPR heterodimer interface is one of the main strategies to prevent CGRPR activation and its resulting effects. So far, FDA approved monoclonal antibodies and small molecule gepant inhibitors are considered for the treatment of acute or chronic migraine symptoms. However, most of these gepants have severe side effects. Thus, in this study, a virtual drug repurposing approach is applied to CGRPR to find alternative or better molecules that would have a potential to inhibit or block the CLR - RAMP1 interface compared to known gepant molecules. A small molecule library of FDA-approved molecules was screened in these two different binding sites, further simulations were performed and analyzed. The objectives of this study are (i) to repurpose an FDA-approved drug having more potent features for CGRPR inhibition compared to gepants, and (ii) to examine whether the transmembrane binding site (site 2) accepts small molecules or small peptide analogues for binding. As a result of this extensive in silico analysis, two molecules were identified, namely pentagastrin and leuprorelin. It is shown that FDA approved compound rimegepant and the identified pentagastrin molecules form and maintain the interactions through CLR W72 and RAMP1 W74, which are the residues revealed to have an important role in CGRPR antagonism at binding site 1. At binding site 2, the interactions needed to be formed for CGRP binding are not captured by rimegepant nor leuprorelin, yet leuprorelin forms more interactions throughout the simulations, meaning that small molecules are also capable of binding to site 2. Moreover, it is found that the crucial interactions for receptor signaling and heterodimerization occurred between CLR and RAMP1 interface are disrupted more with the ligands bound to ectodomain site, rather than the transmembrane domain. These findings of pentagastrin and leuprorelin molecules are recommended to be considered in further de novo drug development and/or experimental studies related to CGRPR signaling blockade and antagonism.

PMID:35803082 | DOI:10.1016/j.jmgm.2022.108254

Angew Chem Int Ed Engl. 2022 Jul 8. doi: 10.1002/anie.202204139. Online ahead of print.

ABSTRACT

Drug repurposing is considered a promising strategy to fight antimicrobial resistance (AMR). Methotrexate (Mtx), a classical anticancer drug, could strongly inhibit bacterial dihydrofolate reductase (DHFR). However, its poor permeability into bacteria and potent human cytotoxicity make it unsuitable as an antibacterial. Herein, we reported the conjugation of Mtx with a siderophore to construct "Trojan horse" antibacterials. The most potent conjugate 8 with nanomolar minimum inhibitory concentration (MIC) values exhibited over 1.00×10 3 -fold improved activity against Gram-positive Streptococcus pneumoniae ( S. pneumoniae ) and Gram-negative Yersinia enterocolitica ( Y. enterocolitica ) compared with Mtx, while possessing 2.31×10 3 -fold reduced human cytotoxicity, resulting in 2.08×10 6 -fold improvements in the therapeutic index. This proof-of-principle study verifies that siderophore conjugation is an effective stratefy for developing new antibacterials from anticancer drugs.

PMID:35802518 | DOI:10.1002/anie.202204139

Neuro Oncol. 2022 Jul 8:noac171. doi: 10.1093/neuonc/noac171. Online ahead of print.

ABSTRACT

BACKGROUND: Glioblastoma is the most common and devastating primary brain cancer. Radiotherapy is standard of care; however, it is associated with brain radiation toxicity (BRT). This study used a multi-omics approach to determine whether BRT-related genes (RGs) harbor survival prognostic value and whether their encoded proteins represent novel therapeutic targets for glioblastoma.

METHODS: RGs were identified through analysis of single nucleotide variants associated with BRT. Functional relationships between RGs were established using Protein-Protein Interaction networks. The influence of RGs and their functional groups on glioblastoma prognosis was evaluated using clinical samples from the Glioblastoma Bio-Discovery Portal database, and validated using the Chinese Glioma Genome Atlas dataset. The identification of clusters of radiotoxic (R-SNVs) and putative pathogenic variants in proteins encoded by RGs was achieved by computational 3D structural analysis.

RESULTS: We identified the BRT-related 15CAcBRT molecular signature with prognostic value in glioblastoma, by analysis of the COMT and APOE protein functional groups. Its external validation confirmed clinical relevance independent of age, MGMT promoter methylation status, and IDH mutation status. Interestingly, the genes IL6, APOE, and MAOB documented significant gene expression levels alteration, useful for drug repositioning. Biological networks associated with 15CAcBRT signature involved pathways relevant in cancer and neurodegenerative diseases. Analysis of 3D clusters of radiotoxic and putative pathogenic variants in proteins coded by RGs unveiled potential novel therapeutic targets in neuro-oncology.

CONCLUSIONS: 15CAcBRT is a BRT-related molecular signature with prognostic significance for glioblastoma patients and represents a hub for drug repositioning and development of novel therapies.

PMID:35802478 | DOI:10.1093/neuonc/noac171

Epilepsia Open. 2022 Jul 8. doi: 10.1002/epi4.12623. Online ahead of print.

ABSTRACT

SCN8A-developmental and epileptic encephalopathy is caused by mutations in the SCN8A gene encoding the Nav 1.6 sodium channel, and is characterized by intractable multivariate seizures and developmental regression. Fenfluramine is a repurposed drug with proven antiseizure efficacy in Dravet syndrome and Lennox-Gastaut syndrome. The effect of fenfluramine treatment was assessed in a retrospective series of three patients with intractable SCN8A epilepsy and severe neurodevelopmental comorbidity (n=2 females; age 2.8-13 years; 8-16 prior failed antiseizure medications (ASM); treatment duration: 0.75-4.2 years). In the 6 months prior to receiving fenfluramine, patients experienced multiple seizure types, including generalized tonic-clonic, focal and myoclonic seizures, and status epilepticus. Overall seizure reduction was 60%-90% in the last 3, 6, and 12 months of fenfluramine treatment. Clinically meaningful improvement was noted in ≥1 non-seizure comorbidity per patient after fenfluramine, as assessed by physician-ratings of ≥"Much Improved" on the Clinical Global Impression of Improvement scale. Improvements included ambulation in a previously non-ambulant patient and better attention, sleep, and language. One patient showed mild irritability which resolved; no other treatment-related adverse events were reported. There were no reports of valvular heart disease or pulmonary arterial hypertension. Fenfluramine may be a promising ASM for randomized clinical trials in SCN8A-related disorders.

PMID:35802036 | DOI:10.1002/epi4.12623

Sci Prog. 2022 Jul-Sep;105(3):368504221109215. doi: 10.1177/00368504221109215.

ABSTRACT

Identifying new therapeutic indications for existing drugs is a major challenge in drug repositioning. Most computational drug repositioning methods focus on known targets. Analyzing multiple aspects of various protein associations provides an opportunity to discover underlying drug-associated proteins that can be used to improve the performance of the drug repositioning approaches. In this study, machine learning models were developed based on the similarities of diversified biological features, including protein interaction, topological network, sequence alignment, and biological function to predict protein pairs associating with the same drugs. The crucial set of features was identified, and the high performances of protein pair predictions were achieved with an area under the curve (AUC) value of more than 93%. Based on drug chemical structures, the drug similarity levels of the promising protein pairs were used to quantify the inferred drug-associated proteins. Furthermore, these proteins were employed to establish an augmented drug-protein matrix to enhance the efficiency of three existing drug repositioning techniques: a similarity constrained matrix factorization for the drug-disease associations (SCMFDD), an ensemble meta-paths and singular value decomposition (EMP-SVD) model, and a topology similarity and singular value decomposition (TS-SVD) technique. The results showed that the augmented matrix helped to improve the performance up to 4% more in comparison to the original matrix for SCMFDD and EMP-SVD, and about 1% more for TS-SVD. In summary, inferring new protein pairs related to the same drugs increase the opportunity to reveal missing drug-associated proteins that are important for drug development via the drug repositioning technique.

PMID:35801312 | DOI:10.1177/00368504221109215

Antiviral Res. 2022 Jul 4:105373. doi: 10.1016/j.antiviral.2022.105373. Online ahead of print.

ABSTRACT

COVID-19 is marked by extensive damage to the respiratory system, often accompanied by systemic manifestations, due to both viral cytopathic effects and hyperinflammatory syndrome. Therefore, the development of new therapeutic strategies or drug repurposing aiming to control virus replication and inflammation are required to mitigate the impact of the disease. Hydroxypropyl-beta-cyclodextrin (HP-BCD) is a cholesterol-sequestering agent with antiviral activity that has been demonstrated against enveloped viruses in in vitro and in vivo experimental models. We also demonstrated that HP-BCD has an immunomodulatory effect, inhibiting the production of selected proinflammatory cytokines induced by microbial products. Importantly, this drug has been used in humans for decades as an excipient in drug delivery systems and as a therapeutic agent in the treatment of Niemann pick C disease. The safety profile for this compound is well established. Here, we investigated whether HP-BCD would affect SARS-CoV-2 replication and virus-induced inflammatory response, using established cell lines and primary human cells. Treating virus or cells with HP-BCD significantly inhibited SARS-CoV-2 replication with a high selective index. A broad activity against distinct SARS-CoV-2 variants was evidenced by a remarkable reduction in the release of infectious particles. The drug did not alter ACE2 surface expression, but affected cholesterol accumulation into intracellular replication complexes, lowering virus RNA and protein levels, and reducing virus-induced cytopathic effects. Virus replication was also impaired by HP-BCD in Calu-3 pulmonary cell line and human primary monocytes, in which not only the virus, but also the production of proinflammatory cytokines were significantly inhibited. Given the pathophysiology of COVID-19 disease, these data indicate that the use HP-BCD, which inhibits both SARS-CoV2 replication and production of proinflammatory cytokines, as a potential COVID-19 therapeutic warrants further investigation.

PMID:35798224 | DOI:10.1016/j.antiviral.2022.105373