Front Med (Lausanne). 2021 Nov 24;8:740087. doi: 10.3389/fmed.2021.740087. eCollection 2021.

ABSTRACT

Metabolic reprogramming is a key feature of Autosomal Dominant Polycystic Kidney Disease (ADPKD) characterized by changes in cellular pathways occurring in response to the pathological cell conditions. In ADPKD, a broad range of dysregulated pathways have been found. The studies supporting alterations in cell metabolism have shown that the metabolic preference for abnormal cystic growth is to utilize aerobic glycolysis, increasing glutamine uptake and reducing oxidative phosphorylation, consequently resulting in ADPKD cells shifting their energy to alternative energetic pathways. The mechanism behind the role of the polycystin proteins and how it leads to disease remains unclear, despite the identification of numerous signaling pathways. The integration of computational data analysis that accompanies experimental findings was pivotal in the identification of metabolic reprogramming in ADPKD. Here, we summarize the important results and argue that their exploitation may give further insights into the regulative mechanisms driving metabolic reprogramming in ADPKD. The aim of this review is to provide a comprehensive overview on metabolic focused studies and potential targets for treatment, and to propose that computational approaches could be instrumental in advancing this field of research.

PMID:34901057 | PMC:PMC8652061 | DOI:10.3389/fmed.2021.740087

F1000Res. 2021 May 7;10:Chem Inf Sci-358. doi: 10.12688/f1000research.52168.1. eCollection 2021.

ABSTRACT

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a new coronavirus discovered that appeared in Wuhan, China, in December 2019, causes COVID-19 disease which have resulted in cases similar to SARS-atypical pneumonia. As of March 1, 2021, Mexico had reached 2.11 million cases of COVID-19 and 189 thousand deaths; around 116 million cases and 2.57 million deaths are reported worldwide with new cases and increasing mortality every day. To date, there is no specific commercial treatment to control the infection. Repurpose drugs targeting the angiotensin-converting enzyme 2 (ACE2) receptor represents an alternative strategy to block the binding of SARS-CoV-2 protein S and forestall virus adhesion, internalization and replication in the host cell. Methods: Rigid molecular docking was performed using receptor binding domain of the S1 subunit of S protein (RBD S1)-ACE2 (PDB ID: 6VW1) interaction site and 1,283 drugs FDA approved and prescribed by the Mexican Public Health System. The results were analyzed by docking score, frequency of the drug in receptor site and the types of interactions at the binding site residues. Results: About 40 drugs were identified as a potential inhibitor of RBD S1-ACE2 interaction. Within the top-ranked drugs, we identified ipratropium, formoterol and fexofenadine, which stands out as they are used as therapies to treat chronic obstructive pulmonary disease, asthma and virtually any respiratory infection. Conclusions: Our results will serve as the basis for in vitro and in vivo studies to evaluate the potential use of those drugs to generate affordable and convenient therapies to treat COVID-19.

PMID:34900223 | PMC:PMC8630554 | DOI:10.12688/f1000research.52168.1

Trends Pharmacol Sci. 2021 Dec 9:S0165-6147(21)00221-2. doi: 10.1016/j.tips.2021.11.004. Online ahead of print.

ABSTRACT

For complex diseases, most drugs are highly ineffective, and the success rate of drug discovery is in constant decline. While low quality, reproducibility issues, and translational irrelevance of most basic and preclinical research have contributed to this, the current organ-centricity of medicine and the 'one disease-one target-one drug' dogma obstruct innovation in the most profound manner. Systems and network medicine and their therapeutic arm, network pharmacology, revolutionize how we define, diagnose, treat, and, ideally, cure diseases. Descriptive disease phenotypes are replaced by endotypes defined by causal, multitarget signaling modules that also explain respective comorbidities. Precise and effective therapeutic intervention is achieved by synergistic multicompound network pharmacology and drug repurposing, obviating the need for drug discovery and speeding up clinical translation.

PMID:34895945 | DOI:10.1016/j.tips.2021.11.004

Vet Res. 2021 Dec 11;52(1):143. doi: 10.1186/s13567-021-01012-x.

ABSTRACT

Haemonchus contortus is a parasitic nematode of ruminants which causes significant losses to many farmers worldwide. Since the drugs currently in use for the treatment of haemonchosis are losing their effectiveness due to the drug-resistance of this nematode, a new or repurposed drug is highly needed. As the antipsychotic drug sertraline (SRT) has been shown to be effective against the parasitic nematodes Trichuris muris, Ancylostoma caninum and Schistosoma mansoni, the aim of the present study was to evaluate the possible effect of SRT on H. contortus. The potential hepatotoxicity of SRT was tested in sheep, a common H. contortus host. In addition, the main metabolic pathways of SRT in H. contortus and the ovine liver were identified. While no effect of SRT on H. contortus egg hatching was observed, SRT was found to significantly decrease the viability of H. contortus adults in drug-sensitive and resistant strains, with its effect comparable to the commonly used anthelmintics levamisole and monepantel. Moreover, SRT in anthelmintically active concentrations showed no toxicity to the ovine liver. Biotransformation of SRT in H. contortus was weak, with most of the drug remaining unmetabolized. Production of the main metabolite hydroxy-SRT did not differ significantly between strains. Other minor metabolites such as SRT-O-glucoside, dihydroxy-SRT, and SRT-ketone were also identified in H. contorts adults. Compared to H. contortus, the ovine liver metabolized SRT more extensively, mainly via desmethylation and glucuronidation. In conclusion, the potency of SRT against H. contortus was proven, and it should be tested further toward possible repurposing.

PMID:34895342 | DOI:10.1186/s13567-021-01012-x

J Enzyme Inhib Med Chem. 2022 Dec;37(1):51-61. doi: 10.1080/14756366.2021.1991336.

ABSTRACT

Neisseria gonorrhoeae is a high-priority pathogen of concern due to the growing prevalence of resistance development against approved antibiotics. Herein, we report the anti-gonococcal activity of ethoxzolamide, the FDA-approved human carbonic anhydrase inhibitor. Ethoxzolamide displayed an MIC50, against a panel of N. gonorrhoeae isolates, of 0.125 µg/mL, 16-fold more potent than acetazolamide, although both molecules exhibited almost similar potency against the gonococcal carbonic anhydrase enzyme (NgCA) in vitro. Acetazolamide displayed an inhibition constant (Ki) versus NgCA of 74 nM, while Ethoxzolamide's Ki was estimated to 94 nM. Therefore, the increased anti-gonococcal potency of ethoxzolamide was attributed to its increased permeability in N. gonorrhoeae as compared to that of acetazolamide. Both drugs demonstrated bacteriostatic activity against N. gonorrhoeae, exhibited post-antibiotic effects up to 10 hours, and resistance was not observed against both. Taken together, these results indicate that acetazolamide and ethoxzolamide warrant further investigation for translation into effective anti-N. gonorrhoeae agents.

PMID:34894972 | DOI:10.1080/14756366.2021.1991336

Brief Bioinform. 2021 Dec 9:bbab515. doi: 10.1093/bib/bbab515. Online ahead of print.

ABSTRACT

Identifying new indications for drugs plays an essential role at many phases of drug research and development. Computational methods are regarded as an effective way to associate drugs with new indications. However, most of them complete their tasks by constructing a variety of heterogeneous networks without considering the biological knowledge of drugs and diseases, which are believed to be useful for improving the accuracy of drug repositioning. To this end, a novel heterogeneous information network (HIN) based model, namely HINGRL, is proposed to precisely identify new indications for drugs based on graph representation learning techniques. More specifically, HINGRL first constructs a HIN by integrating drug-disease, drug-protein and protein-disease biological networks with the biological knowledge of drugs and diseases. Then, different representation strategies are applied to learn the features of nodes in the HIN from the topological and biological perspectives. Finally, HINGRL adopts a Random Forest classifier to predict unknown drug-disease associations based on the integrated features of drugs and diseases obtained in the previous step. Experimental results demonstrate that HINGRL achieves the best performance on two real datasets when compared with state-of-the-art models. Besides, our case studies indicate that the simultaneous consideration of network topology and biological knowledge of drugs and diseases allows HINGRL to precisely predict drug-disease associations from a more comprehensive perspective. The promising performance of HINGRL also reveals that the utilization of rich heterogeneous information provides an alternative view for HINGRL to identify novel drug-disease associations especially for new diseases.

PMID:34891172 | DOI:10.1093/bib/bbab515

J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Dec 1;1188:123075. doi: 10.1016/j.jchromb.2021.123075. Online ahead of print.

ABSTRACT

5-fluorouracil (5-FU) and its oral formulation, capecitabine, are widely used in treating a range of malignancies, either alone or in combination with other antineoplastic drugs. Body surface area-based dosing is used for these agents, despite this approach leading to substantial variability in drug exposure and often resulting in either toxicity or treatment failure. Tailoring therapeutic regimens for individual patients using therapeutic drug monitoring (TDM) has been shown to significantly reduce toxicity and improve cancer outcomes. However, for optimum TDM, sample timing is crucial, along with the need for a venepuncture blood sample to obtain the plasma currently used for 5-FU measurement. In addition to complex blood sample handling requirements, large sample volume and frequent sampling required for pharmacokinetic analysis is another barrier to successfully implementing TDM in a healthcare setting. Microsampling is an alternative collection method to venepuncture, which, combined with the now readily available liquid chromatography mass spectrometry (LC-MS/MS) technology, overcomes the plasma-associated issues. It also has the significant advantage of enabling at home and remote sampling, thus facilitating 5-FU TDM in clinical practice. A LC-MS/MS method for simultaneous measurement of capecitabine, 5'-deoxy-5-fluorocytidine, 5'-deoxy-5-fluorouridine and 5-FU using Mitra® microsampling devices for sample collection was developed. A Shimadzu 8060 LC-MS/MS equipped with electrospray ionisation source interface, operated in positive and negative ion modes, with reversed-phase chromatographic separation was employed for sample analysis. Samples were extracted from Mitra® devices using acetonitrile containing stable isotope-labelled internal standards, sonicated, evaporated under vacuum and resuspended in 0.1 % formic acid before injection into the LC-MS/MS. Chromatographic separation was on a Luna Omega Polar C18 (100 × 2.1 mm, 1.6 µm) column with gradient elution of 0.1 % formic acid in water and acetonitrile. Total run time was 5 min, with the injection volume of 1 µL. The intra and inter-day imprecision ranged from 3.0 to 8.1 and 6.3-13.3 % respectively. Accuracy ranged from 95 -114 % for all analytes. Lower limit of quantification with imprecision of < 19 % and accuracy between 89 and 114 % was 0.05 mg/L for 5-FU and 10 µg/L for other analytes. Assays were linear from 0.05 to 50 mg/L for 5-FU and 10-10,000 µg/L for all other analytes. Analytes were stable on Mitra® devices for up to 9 months at room temperature, 2 years at -30 ℃ and 3 days at 50 ℃. The method was successfully applied for the analysis of samples from patients undergoing cancer treatment with 5-FU and capecitabine. Microsampling using volumetric absorptive microsampling proved to be as reliable as conventional blood collection for 5-FU and capecitabine. This sampling technique may lead to less invasive and better-timed sample collection for TDM, supporting dose optimization strategy.

PMID:34891049 | DOI:10.1016/j.jchromb.2021.123075

Transl Oncol. 2021 Dec 7;15(1):101302. doi: 10.1016/j.tranon.2021.101302. Online ahead of print.

ABSTRACT

Breast cancer is common worldwide, and the estrogen receptor-positive subtype accounts for approximately 70% of breast cancer in women. Tamoxifen and fulvestrant are drugs currently used for endocrinal therapy. Breast cancer exhibiting endocrine resistance can undergo metastasis and lead to the death of breast cancer patients. Drug repurposing is an active area of research in clinical medicine. We found that nafamostat mesylate, clinically used for patients with pancreatitis and disseminated intravascular coagulation, acts as an anti-cancer drug for endocrine-resistant estrogen receptor-positive breast cancer (ERPBC). Epigenetic repression of CDK4 and CDK6 by nafamostat mesylate induced apoptosis and suppressed the metastasis of ERPBC through the deacetylation of Histone 3 Lysine 27. A combination of nafamostat mesylate and CDK4/6 inhibitor synergistically overcame endocrine resistance in ERPBC. Nafamostat mesylate might be an essential adjuvant or alternative drug for the treatment of endocrine-resistant ERPBC due to the low cost-efficiency of the CDK4/6 inhibitor.

PMID:34890965 | DOI:10.1016/j.tranon.2021.101302

Molecules. 2021 Dec 5;26(23):7375. doi: 10.3390/molecules26237375.

ABSTRACT

The mechanisms underlying the antineoplastic effects of oxicams have not been fully elucidated. We aimed to assess the effect of classic and novel oxicams on the expression/secretion of macrophage-associated chemokines (RTqPCR/Luminex xMAP) in colorectal adenocarcinoma cells, and on the expression of upstream the non-steroidal anti-inflammatory drug (NSAID)-activated genes NAG1, NFKBIA, MYD88, and RELA, as well as at the chemokine profiling in colorectal tumors. Meloxicam downregulated CCL4 9.9-fold, but otherwise the classic oxicams had a negligible/non-significant effect. Novel analogues with a thiazine ring substituted with arylpiperazine and benzoyl moieties significantly modulated chemokine expression to varying degree, upregulated NAG1 and NFKBIA, and downregulated MYD88. They inhibited CCL3 and CCL4, and their effect on CCL2 and CXCL2 depended on the dose and exposure. The propylene linker between thiazine and piperazine nitrogens and one arylpiperazine fluorine substituent characterized the most effective analogue. Only CCL19 and CXCL2 were not upregulated in tumors, nor was CXCL2 in tumor-adjacent tissue compared to normal mucosa. Compared to adjacent tissue, CCL4 and CXCL2 were upregulated, while CCL2, CCL8, and CCL19 were downregulated in tumors. Tumor CCL2 and CCL7 increased along with advancing T and CCL3, and CCL4 along with the N stage. The introduction of arylpiperazine and benzoyl moieties into the oxicam scaffold yields effective modulators of chemokine expression, which act by upregulating NAG1 and interfering with NF-κB signaling.

PMID:34885960 | DOI:10.3390/molecules26237375

Molecules. 2021 Dec 2;26(23):7326. doi: 10.3390/molecules26237326.

ABSTRACT

Drug repurposing can quickly and effectively identify novel drug repurposing opportunities. The PA endonuclease catalytic site has recently become regarded as an attractive target for the screening of anti-influenza drugs. PA N-terminal (PAN) inhibitor can inhibit the entire PA endonuclease activity. In this study, we screened the effectivity of PAN inhibitors from the FDA database through in silico methods and in vitro experiments. PAN and mutant PAN-I38T were chosen as virtual screening targets for overcoming drug resistance. Gel-based PA endonuclease analysis determined that the drug lifitegrast can effectively inhibit PAN and PAN-I38T, when the IC50 is 32.82 ± 1.34 μM and 26.81 ± 1.2 μM, respectively. Molecular docking calculation showed that lifitegrast interacted with the residues around PA or PA-I38 T's active site, occupying the catalytic site pocket. Both PAN/PAN-I38T and lifitegrast can acquire good equilibrium in 100 ns molecular dynamic simulation. Because of these properties, lifitegrast, which can effectively inhibit PA endonuclease activity, was screened through in silico and in vitro research. This new research will be of significance in developing more effective and selective drugs for anti-influenza therapy.

PMID:34885905 | DOI:10.3390/molecules26237326

Cancers (Basel). 2021 Nov 29;13(23):5993. doi: 10.3390/cancers13235993.

ABSTRACT

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an important area of research, as the major obstacle to the treatment of HGSOC is the development of resistance to platinum chemotherapy. The cause of chemoresistance is still largely unknown and may be due to epigenetics modifications that are driving HGSOC metastasis and treatment resistance. The identification of epigenetic changes in chemoresistant HGSOC enables the development of epigenetic modulating drugs that may be used to improve outcomes. Several epigenetic modulating drugs have displayed promise as drug targets for HGSOC, such as demethylating agents azacitidine and decitabine. Others, such as histone deacetylase inhibitors and miRNA-targeting therapies, demonstrated promising preclinical results but resulted in off-target side effects in clinical trials. This article reviews the epigenetic modifications identified in chemoresistant HGSOC and clinical trials utilizing epigenetic therapies in HGSOC.

PMID:34885103 | DOI:10.3390/cancers13235993

Int J Mol Sci. 2021 Dec 5;22(23):13155. doi: 10.3390/ijms222313155.

ABSTRACT

Molecular mechanisms underlying the beneficial effect of sitagliptin repurposed for hepatic ischemia-reperfusion injury (IRI) are poorly understood. We aimed to evaluate the impact of IRI and sitagliptin on the hepatic profile of eicosanoids (LC-MS/MS) and expression/concentration (RTqPCR/ELISA) of GLP-1/GLP-1R, SDF-1α/CXCR4 and VIP/VPAC1, VPAC2, and PAC1 in 36 rats. Animals were divided into four groups and subjected to ischemia (60 min) and reperfusion (24 h) with or without pretreatment with sitagliptin (5 mg/kg) (IR and SIR) or sham-operated with or without sitagliptin pretreatment (controls and sitagliptin). PGI2, PGE2, and 13,14-dihydro-PGE1 were significantly upregulated in IR but not SIR, while sitagliptin upregulated PGD2 and 15-deoxy-12,14-PGJ2. IR and sitagliptin non-significantly upregulated GLP-1 while Glp1r expression was borderline detectable. VIP concentration and Vpac2 expression were downregulated in IR but not SIR, while Vpac1 was significantly downregulated solely in SIR. IRI upregulated both CXCR4 expression and concentration, and sitagliptin pretreatment abrogated receptor overexpression and downregulated Sdf1. In conclusion, hepatic IRI is accompanied by an elevation in proinflammatory prostanoids and overexpression of CXCR4, combined with downregulation of VIP/VPAC2. Beneficial effects of sitagliptin during hepatic IRI might be mediated by drug-induced normalization of proinflammatory prostanoids and upregulation of PGD2 and by concomitant downregulation of SDF-1α/CXCR4 and reinstating VIP/VCAP2 signaling.

PMID:34884960 | DOI:10.3390/ijms222313155

Int J Mol Sci. 2021 Nov 27;22(23):12829. doi: 10.3390/ijms222312829.

ABSTRACT

Diagnosis and cure for rare diseases represent a great challenge for the scientific community who often comes up against the complexity and heterogeneity of clinical picture associated to a high cost and time-consuming drug development processes. Here we show a drug repurposing strategy applied to nephropathic cystinosis, a rare inherited disorder belonging to the lysosomal storage diseases. This approach consists in combining mechanism-based and cell-based screenings, coupled with an affordable computational analysis, which could result very useful to predict therapeutic responses at both molecular and system levels. Then, we identified potential drugs and metabolic pathways relevant for the pathophysiology of nephropathic cystinosis by comparing gene-expression signature of drugs that share common mechanisms of action or that involve similar pathways with the disease gene-expression signature achieved with RNA-seq.

PMID:34884638 | DOI:10.3390/ijms222312829

J Mycol Med. 2021 Dec 1;32(1):101232. doi: 10.1016/j.mycmed.2021.101232. Online ahead of print.

ABSTRACT

Candida auris emerges as an important causative agent of fungal infections, with worrisome mortality rates, mainly in immunocompromised individuals. This scenario is worsened by the limited availability of antifungal drugs and the increasing development of resistance to them. Due to the relevance of C. auris infections to public health, several studies aimed to discover new antifungal compounds capable of overcoming this fungus. Nonetheless, these information are decentralized, precluding the understandment of the current status of the search for new anti-C. auris compounds. Thus, this integrative review aimed to summarize information regarding anti-C. auris compounds reported in literature. After using predefined selection criteria, 71 articles were included in this review, and data from a total of 101 substances were extracted. Most of the studies tested synthetic substances, including several azoles. Moreover, drug repurposing emerges as a suitable strategy to discover new anti-C. auris agents. Few studies, however, assessed the mechanism of action and the in vivo antifungal activity of the compounds. Therefore, more studies must be performed to evaluate the usefulness of these substances as anti-C. auris therapies.

PMID:34883404 | DOI:10.1016/j.mycmed.2021.101232

Emerg Top Life Sci. 2021 Dec 9:ETLS20210223. doi: 10.1042/ETLS20210223. Online ahead of print.

ABSTRACT

Drug repositioning aims to reuse existing drugs, shelved drugs, or drug candidates that failed clinical trials for other medical indications. Its attraction is sprung from the reduction in risk associated with safety testing of new medications and the time to get a known drug into the clinics. Artificial Intelligence (AI) has been recently pursued to speed up drug repositioning and discovery. The essence of AI in drug repositioning is to unify the knowledge and actions, i.e. incorporating real-world and experimental data to map out the best way forward to identify effective therapeutics against a disease. In this review, we share positive expectations for the evolution of AI and drug repositioning and summarize the role of AI in several methods of drug repositioning.

PMID:34881780 | DOI:10.1042/ETLS20210223

Emerg Top Life Sci. 2021 Dec 9:ETLS20210249. doi: 10.1042/ETLS20210249. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) remains a devastating neurodegenerative disease with few preventive or curative treatments available. Modern technology developments of high-throughput omics platforms and imaging equipment provide unprecedented opportunities to study the etiology and progression of this disease. Meanwhile, the vast amount of data from various modalities, such as genetics, proteomics, transcriptomics, and imaging, as well as clinical features impose great challenges in data integration and analysis. Machine learning (ML) methods offer novel techniques to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers. These directions have the potential to help us better manage the disease progression and develop novel treatment strategies. This mini-review paper summarizes different ML methods that have been applied to study AD using single-platform or multi-modal data. We review the current state of ML applications for five key directions of AD research: disease classification, drug repurposing, subtyping, progression prediction, and biomarker discovery. This summary provides insights about the current research status of ML-based AD research and highlights potential directions for future research.

PMID:34881778 | DOI:10.1042/ETLS20210249

Clin Cancer Res. 2021 Dec 8:clincanres.3471.2021. doi: 10.1158/1078-0432.CCR-21-3471. Online ahead of print.

ABSTRACT

While metastatic osteosarcoma is rare in humans, it is the most common bone tumor found in any breed of dog. Given the genetic similarities between canine and human osteosarcomas, canine clinical trials allow for rapid testing and drug repurposing at a speed that cannot be achieved using osteosarcoma patients.

PMID:34880110 | DOI:10.1158/1078-0432.CCR-21-3471

ACS Infect Dis. 2021 Dec 8. doi: 10.1021/acsinfecdis.1c00367. Online ahead of print.

ABSTRACT

Glycopeptides, a class of cell wall biosynthesis inhibitors, have been the antibiotics of choice against drug-resistant Gram-positive bacterial infections. Their unique mechanism of action involving binding to the substrate of cell wall biosynthesis and substantial longevity in clinics makes this class of antibiotics an attractive choice for drug repurposing and reprofiling. However, resistance to glycopeptides has been observed due to alterations in the substrate, cell wall thickening, or both. The emergence of glycopeptide resistance has resulted in the development of synthetic and semisynthetic glycopeptide analogues to target acquired resistance. Recent findings demonstrate that these derivatives, along with some of the FDA approved glycopeptides have been shown to have antimicrobial activity against Gram-negative bacteria, Mycobacteria, and viruses thus expanding their spectrum of activity across the microbial kingdom. Additional mechanisms of action and identification of novel targets have proven to be critical in broadening the spectrum of activity of glycopeptides. This review focuses on the applications of glycopeptides beyond their traditional target group of Gram-positive bacteria. This will aid in making the scientific community aware about the nontraditional activity profiles of glycopeptides, identify the existing loopholes, and further explore this antibiotic class as a potential broad-spectrum antimicrobial agent.

PMID:34878254 | DOI:10.1021/acsinfecdis.1c00367

J Biomol Struct Dyn. 2021 Dec 8:1-13. doi: 10.1080/07391102.2021.2010601. Online ahead of print.

ABSTRACT

COVID-19 is a worldwide health crisis seriously endangering the arsenal of antiviral and antibiotic drugs. It is urgent to find an effective antiviral drug against pandemic caused by the severe acute respiratory syndrome (Sars-Cov-2), which increases global health concerns. As it can be expensive and time-consuming to develop specific antiviral drugs, reuse of FDA-approved drugs that provide an opportunity to rapidly distribute effective therapeutics can allow to provide treatments with known preclinical, pharmacokinetic, pharmacodynamic and toxicity profiles that can quickly enter in clinical trials. In this study, using the structural information of molecules and proteins, a list of repurposed drug candidates was prepared again with the graph neural network-based GEFA model. The data set from the public databases DrugBank and PubChem were used for analysis. Using the Tanimoto/jaccard similarity analysis, a list of similar drugs was prepared by comparing the drugs used in the treatment of COVID-19 with the drugs used in the treatment of other diseases. The resultant drugs were compared with the drugs used in lung cancer and repurposed drugs were obtained again by calculating the binding strength between a drug and a target. The kinase inhibitors (erlotinib, lapatinib, vandetanib, pazopanib, cediranib, dasatinib, linifanib and tozasertib) obtained from the study can be used as an alternative for the treatment of COVID-19, as a combination of blocking agents (gefitinib, osimertinib, fedratinib, baricitinib, imatinib, sunitinib and ponatinib) such as ABL2, ABL1, EGFR, AAK1, FLT3 and JAK1, or antiviral therapies (ribavirin, ritonavir-lopinavir and remdesivir).Communicated by Ramaswamy H. Sarma.

PMID:34877907 | DOI:10.1080/07391102.2021.2010601

CPT Pharmacometrics Syst Pharmacol. 2021 Dec 8. doi: 10.1002/psp4.12751. Online ahead of print.

ABSTRACT

Cystic fibrosis is a lethal autosomal recessive disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The common ΔF508-CFTR mutation results in protein misfolding and proteasomal degradation. If ΔF508-CFTR trafficks to the cell surface, its anion channel function may be partially restored. Several in vitro strategies can partially correct ΔF508-CFTR trafficking and function, including low-temperature, small molecules, overexpression of miR-138, or knockdown of SIN3A. The challenge remains to translate such interventions into therapies and to understand their mechanisms. One approach for connecting such interventions to small molecule therapies that has previously succeeded for cystic fibrosis and other diseases is via mRNA expression profiling and iterative searches of small molecules with similar expression signatures. Here, we query the Library of Integrated Network-based Cellular Signatures (LINCS) using transcriptomic signatures from previously generated CF expression data, including RNAi- and low temperature-based rescue signatures. This LINCS in silico screen prioritized 135 small molecules that mimicked our rescue interventions based on their genome-wide transcriptional perturbations. Functional screens of these small molecules identified eight compounds that partially restored ΔF508-CFTR function, as assessed by cAMP-activated chloride conductance. Of these, XL147 rescued ΔF508-CFTR function in primary CF airway epithelia, while also showing cooperativity when administered with C18. Improved CF corrector therapies are greatly needed and this integrative drug prioritization approach offers a novel method to both identify small molecules that may rescue ΔF508-CFTR function and identify gene networks underlying such rescue.

PMID:34877817 | DOI:10.1002/psp4.12751