Molecules. 2021 Sep 16;26(18):5627. doi: 10.3390/molecules26185627.

ABSTRACT

Drug repositioning is a successful approach in medicinal research. It significantly simplifies the long-term process of clinical drug evaluation, since the drug being tested has already been approved for another condition. One example of drug repositioning involves cardiac glycosides (CGs), which have, for a long time, been used in heart medicine. Moreover, it has been known for decades that CGs also have great potential in cancer treatment and, thus, many clinical trials now evaluate their anticancer potential. Interestingly, heart failure and cancer are not the only conditions for which CGs could be effectively used. In recent years, the antiviral potential of CGs has been extensively studied, and with the ongoing SARS-CoV-2 pandemic, this interest in CGs has increased even more. Therefore, here, we present CGs as potent and promising antiviral compounds, which can interfere with almost any steps of the viral life cycle, except for the viral attachment to a host cell. In this review article, we summarize the reported data on this hot topic and discuss the mechanisms of antiviral action of CGs, with reference to the particular viral life cycle phase they interfere with.

PMID:34577097 | DOI:10.3390/molecules26185627

Microorganisms. 2021 Sep 15;9(9):1960. doi: 10.3390/microorganisms9091960.

ABSTRACT

Toxoplasmosis is a parasitic disease caused by the globally distributed protozoan parasite Toxoplasma gondii, which infects around one-third of the world population. This disease may result in serious complications for fetuses, newborns, and immunocompromised individuals. Current treatment options are old, limited, and possess toxic side effects. Long treatment durations are required since the current therapeutic system lacks efficiency against T. gondii tissue cysts, promoting the establishment of latent infection. This review highlights the most promising drug targets involved in anti-T. gondii drug discovery, including the mitochondrial electron transport chain, microneme secretion pathway, type II fatty acid synthesis, DNA synthesis and replication and, DNA expression as well as others. A description of some of the most promising compounds demonstrating antiparasitic activity, developed over the last decade through drug discovery and drug repurposing, is provided as a means of giving new perspectives for future research in this field.

PMID:34576854 | DOI:10.3390/microorganisms9091960

Int J Mol Sci. 2021 Sep 21;22(18):10163. doi: 10.3390/ijms221810163.

ABSTRACT

Paediatric acute myeloid leukaemia (AML) is a heterogeneous disease characterised by the malignant transformation of myeloid precursor cells with impaired differentiation. Standard therapy for paediatric AML has remained largely unchanged for over four decades and, combined with inadequate understanding of the biology of paediatric AML, has limited the progress of targeted therapies in this cohort. In recent years, the search for novel targets for the treatment of paediatric AML has accelerated in parallel with advanced genomic technologies which explore the mutational and transcriptional landscape of this disease. Exploiting the large combinatorial space of existing drugs provides an untapped resource for the identification of potential combination therapies for the treatment of paediatric AML. We have previously designed a multiplex screening strategy known as Multiplex Screening for Interacting Compounds in AML (MuSICAL); using an algorithm designed in-house, we screened all pairings of 384 FDA-approved compounds in less than 4000 wells by pooling drugs into 10 compounds per well. This approach maximised the probability of identifying new compound combinations with therapeutic potential while minimising cost, replication and redundancy. This screening strategy identified the triple combination of glimepiride, a sulfonylurea; pancuronium dibromide, a neuromuscular blocking agent; and vinblastine sulfate, a vinca alkaloid, as a potential therapy for paediatric AML. We envision that this approach can be used for a variety of disease-relevant screens allowing the efficient repurposing of drugs that can be rapidly moved into the clinic.

PMID:34576326 | DOI:10.3390/ijms221810163

J Pers Med. 2021 Sep 18;11(9):926. doi: 10.3390/jpm11090926.

ABSTRACT

BACKGROUND: COVID-2019 pandemic lead to a raised interest on the development of new treatments through Artificial Intelligence (AI).

AIM: to carry out a systematic review on the development of repurposed drugs against COVID-2019 through the application of AI.

METHODS: The Systematic Reviews and Meta-Analyses (PRISMA) checklist was applied.

KEYWORDS: ["Artificial intelligence" and (COVID or SARS) and (medicine or drug)]. Databases: PubMed®, DOAJ and SciELO. Cochrane Library was additionally screened to identify previous published reviews on the same topic.

RESULTS: From the 277 identified records [PubMed® (n = 157); DOAJ (n = 119) and SciELO (n = 1)], 27 studies were included. Among other, the selected studies on new treatments against COVID-2019 were classified, as follows: studies with in-vitro and/or clinical data; association of known drugs; and other studies related to repurposing of drugs.

CONCLUSION: Diverse potentially repurposed drugs against COVID-2019 were identified. The repurposed drugs were mainly from antivirals, antibiotics, anticancer, anti-inflammatory, and Angiotensin-converting enzyme 2 (ACE2) groups, although diverse other pharmacologic groups were covered. AI was a suitable tool to quickly analyze large amounts of data or to estimate drug repurposing against COVID-2019.

PMID:34575703 | DOI:10.3390/jpm11090926

J Pers Med. 2021 Sep 6;11(9):888. doi: 10.3390/jpm11090888.

ABSTRACT

BACKGROUND: SYK gene regulates the expression of SYK kinase (Spleen tyrosine kinase), an important non-receptor protein-tyrosine kinase for immunological receptor-mediated signaling, which is also considered a tumor growth metastasis initiator. An onco-informatics analysis was adopted to evaluate the expression and prognostic value of the SYK gene in colorectal cancer (CRC), the third most fatal cancer type; of late, it may be a biomarker as another targeted site for CRC. In addition, identify the potential phytochemicals that may inhibit the overexpression of the SYK kinase protein and minimize the human CRC.

MATERIALS & METHODS: The differential expression of the SYK gene was analyzed using several transcriptomic databases, including Oncomine, UALCAN, GENT2, and GEPIA2. The server cBioPortal was used to analyze the mutations and copy number alterations, whereas GENT2, Gene Expression Profiling Interactive Analysis (GEPIA), Onco-Lnc, and PrognoScan were used to examine the survival rate. The protein-protein interaction network of SYK kinase and its co-expressed genes was conducted via Gene-MANIA. Considering the SYK kinase may be the targeted site, the selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. Molecular interactions were also observed by following the Ligplot+ version 2.2. YASARA molecular dynamics simulator was applied for the post-validation of the selected phytochemicals.

RESULTS: Our result reveals an increased level of mRNA expression of the SYK gene in colorectal adenocarcinoma (COAD) samples compared to those in normal tissues. A significant methylation level and various genetic alterations recurrence of the SYK gene were analyzed where the fluctuation of the SYK alteration frequency was detected across different CRC studies. As a result, a lower level of SYK expression was related to higher chances of survival. This was evidenced by multiple bioinformatics platforms and web resources, which demonstrated that the SYK gene can be a potential biomarker for CRC. In this study, aromatic phytochemicals, such as kaempferol and glabridin that target the macromolecule (SYK kinase), showed higher stability than the controls, and we have estimated that these bioactive potential phytochemicals might be a useful option for CRC patients after the clinical trial.

CONCLUSIONS: Our onco-informatics investigation suggests that the SYK gene can be a potential prognostic biomarker of CRC. On the contrary, SYK kinase would be a major target, and all selected compounds were validated against the protein using in-silico drug design approaches. Here, more in vitro and in vivo analysis is required for targeting SYK protein in CRC.

PMID:34575665 | DOI:10.3390/jpm11090888

Pharmaceutics. 2021 Sep 18;13(9):1514. doi: 10.3390/pharmaceutics13091514.

ABSTRACT

Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation.

PMID:34575590 | DOI:10.3390/pharmaceutics13091514

Front Genet. 2021 Sep 10;12:735348. doi: 10.3389/fgene.2021.735348. eCollection 2021.

ABSTRACT

Despite advances in the identification and diagnosis of congenital disorders of glycosylation (CDG), treatment options remain limited and are often constrained to symptomatic management of disease manifestations. However, recent years have seen significant advances in treatment and novel therapies aimed both at the causative defect and secondary disease manifestations have been transferred from bench to bedside. In this review, we aim to give a detailed overview of the available therapies and rising concepts to treat these ultra-rare diseases.

PMID:34567084 | PMC:PMC8461064 | DOI:10.3389/fgene.2021.735348

Front Microbiol. 2021 Sep 10;12:744458. doi: 10.3389/fmicb.2021.744458. eCollection 2021.

ABSTRACT

Interfering with the ability of pathogenic bacteria to import glucose may represent a new promising antibacterial strategy, especially for the treatment of infections occurring in diabetic and other hyperglycemic patients. Such patients are particularly susceptible to infections caused by a variety of bacteria, among which opportunistic pathogens like Pseudomonas aeruginosa. In P. aeruginosa, glucose can be directly imported into the cytoplasm or after its periplasmic oxidation into gluconate and 2-ketogluconate (2-KG). We recently demonstrated that a P. aeruginosa mutant lacking the 2-KG transporter KguT is less virulent than its kguT + parental strain in an insect infection model, pointing to 2-KG branch of glucose utilization as a possible target for anti-Pseudomonas drugs. In this work, we devised an experimental protocol to find specific inhibitors of the 2-KG pathway of P. aeruginosa glucose utilization and applied it to the screening of the Prestwick Chemical Library. By exploiting mutants lacking genes involved in the transport of glucose derivatives in the primary screening and in the secondary assays, we could identify sanguinarine as an inhibitor of 2-KG utilization. We also demonstrated that sanguinarine does not prevent 2-KG formation by gluconate oxidation or its transport, suggesting that either KguD or KguK is the target of sanguinarine in P. Aeruginosa.

PMID:34566945 | PMC:PMC8461315 | DOI:10.3389/fmicb.2021.744458

Front Neurol. 2021 Sep 9;12:703970. doi: 10.3389/fneur.2021.703970. eCollection 2021.

ABSTRACT

Introduction: Among genetic paroxysmal movement disorders, variants in ion channel coding genes constitute a major subgroup. Loss-of-function (LOF) variants in KCNA1, the gene coding for KV1.1 channels, are associated with episodic ataxia type 1 (EA1), characterized by seconds to minutes-lasting attacks including gait incoordination, limb ataxia, truncal instability, dysarthria, nystagmus, tremor, and occasionally seizures, but also persistent neuromuscular symptoms like myokymia or neuromyotonia. Standard treatment has not yet been developed, and different treatment efforts need to be systematically evaluated. Objective and Methods: Personalized therapeutic regimens tailored to disease-causing pathophysiological mechanisms may offer the specificity required to overcome limitations in therapy. Toward this aim, we (i) reviewed all available clinical reports on treatment response and functional consequences of KCNA1 variants causing EA1, (ii) examined the potential effects on neuronal excitability of all variants using a single compartment conductance-based model and set out to assess the potential of two sodium channel blockers (SCBs: carbamazepine and riluzole) to restore the identified underlying pathophysiological effects of KV1.1 channels, and (iii) provide a comprehensive review of the literature considering all types of episodic ataxia. Results: Reviewing the treatment efforts of EA1 patients revealed moderate response to acetazolamide and exhibited the strength of SCBs, especially carbamazepine, in the treatment of EA1 patients. Biophysical dysfunction of KV1.1 channels is typically based on depolarizing shifts of steady-state activation, leading to an LOF of KCNA1 variant channels. Our model predicts a lowered rheobase and an increase of the firing rate on a neuronal level. The estimated concentration dependent effects of carbamazepine and riluzole could partially restore the altered gating properties of dysfunctional variant channels. Conclusion: These data strengthen the potential of SCBs to contribute to functional compensation of dysfunctional KV1.1 channels. We propose riluzole as a new drug repurposing candidate and highlight the role of personalized approaches to develop standard care for EA1 patients. These results could have implications for clinical practice in future and highlight the need for the development of individualized and targeted therapies for episodic ataxia and genetic paroxysmal disorders in general.

PMID:34566847 | PMC:PMC8459024 | DOI:10.3389/fneur.2021.703970

Methods. 2021 Sep 22:S1046-2023(21)00223-1. doi: 10.1016/j.ymeth.2021.09.009. Online ahead of print.

ABSTRACT

The coronavirus disease 2019 (COVID-19) has outbreak since early December 2019, and COVID-19 has caused over 100 million cases and 2 million deaths around the world. After one year of the COVID-19 outbreak, there is no certain and approve medicine against it. Drug repositioning has become one line of scientific research that is being pursued to develop an effective drug. However, due to the lack of COVID-19 data, there is still no specific drug repositioning targeting the COVID-19. In this paper, we propose a framework for COVID-19 drug repositioning. This framework has several advantages that can be exploited: one is that a local graph aggregating representation is used across a heterogeneous network to address the data sparsity problem; another is the multi-hop neighbors of the heterogeneous graph are aggregated to recall as many COVID-19 potential drugs as possible. Our experimental results show that our COVDR framework performs significantly better thanbaseline methods, and the docking simulation verifies that our three potential drugs have the ability to against COVID-19 disease.

PMID:34562584 | DOI:10.1016/j.ymeth.2021.09.009

Environ Sci Pollut Res Int. 2021 Sep 25. doi: 10.1007/s11356-021-16427-4. Online ahead of print.

ABSTRACT

Coronavirus disease (COVID-19) is an emerging pandemic that threatens the world since the early days of 2020. Development of vaccines or new drugs against COVID-19 comprises several stages of investigation including efficacy, safety, and approval studies. A shortcut to this delicate pathway is computational-based analysis of FDA-approved drugs against assigned molecular targets of the coronavirus. In this study, we virtually screened a library of FDA-approved drugs prescribed for different therapeutic purposes against versatile COVID-19 specific proteins which are crucial for the virus life cycle. Three antibiotics in our screening polymyxin B, bafilomycin A, and rifampicin show motivating binding stability with more than one target of the virus. Another category of tested drugs is oral antiseptics of mouth rinsing solutions that unexpectedly exhibited significant affinity to the target proteins employed by the virus for attachment and cell internalization. Other OTC drugs widely used and tested in our study are heartburn drugs and they show no significant binding. We tested also some other drugs falling under the scope of investigation regarding interference with a degree of severity of COVID-19 like angiotensin II blockers used as antihypertensive, and our study suggests a therapeutic rather than predisposing effect of these drugs against COVID-19.

PMID:34562220 | DOI:10.1007/s11356-021-16427-4

BMC Med Inform Decis Mak. 2021 Sep 24;21(Suppl 8):263. doi: 10.1186/s12911-021-01617-4.

ABSTRACT

BACKGROUND: Drug repurposing, the process of identifying additional therapeutic uses for existing drugs, has attracted increasing attention from both the pharmaceutical industry and the research community. Many existing computational drug repurposing methods rely on preclinical data (e.g., chemical structures, drug targets), resulting in translational problems for clinical trials.

RESULTS: In this study, we propose a novel framework based on clinical connectivity mapping for drug repurposing to analyze therapeutic effects of drugs on diseases. We firstly establish clinical drug effect vectors (i.e., drug-laboratory results associations) by applying a continuous self-controlled case series model on a longitudinal electronic health record data, then establish clinical disease sign vectors (i.e., disease-laboratory results associations) by applying a Wilcoxon rank sum test on a large-scale national survey data. Eventually, a repurposing possibility score for each drug-disease pair is computed by applying a dot product-based scoring function on clinical disease sign vectors and clinical drug effect vectors. During the experiment, we comprehensively evaluate 392 drugs for 6 important chronic diseases (include asthma, coronary heart disease, congestive heart failure, heart attack, type 2 diabetes, and stroke). The experiment results not only reflect known associations between diseases and drugs, but also include some hidden drug-disease associations. The code for this paper is available at: https://github.com/HoytWen/CCMDR CONCLUSIONS: The proposed clinical connectivity map framework uses laboratory results found from electronic clinical information to bridge drugs and diseases, which make their relations explainable and has better translational power than existing computational methods. Experimental results demonstrate the effectiveness of our proposed framework, further case analysis also proves our method can be used to repurposing existing drugs opportunities.

PMID:34560862 | DOI:10.1186/s12911-021-01617-4

Biomed Pharmacother. 2021 Sep 21;143:112174. doi: 10.1016/j.biopha.2021.112174. Online ahead of print.

ABSTRACT

AIM: To elucidate the potential effect of promethazine on colorectal cancer (CRC) cells and the underlying mechanism.

MATERIALS AND METHODS: Targets of the drug promethazine (PMTZ) were identified by DrugBank and comparative toxicogenomic databases (CTD), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed with STRING software. The effects of PMTZ were predicted to be associated with the PI3K/AKT pathway. Cell Counting Kit 8 (CCK-8) assays were used to evaluate the effects of different concentrations of PMTZ on the proliferation of various types of CRC cells. Flow cytometry and Western blotting analyses were used to detect the degree of CRC cell apoptosis and the expression of the apoptosis-related proteins Bcl-2, Bax and caspase-3 after PMTZ treatment. The expression levels of PI3K/AKT pathway-related proteins [PI3K, AKT, phosphorylated (P)-PI3K and p-AKT] in CRC cells treated with PMTZ were analyzed by Western blotting.

RESULTS: PMTZ inhibited the proliferation and promoted the apoptosis of CRC cells and suppressed the activation of the PI3K/AKT signaling pathway in a dose-dependent manner.

DISCUSSION AND CONCLUSIONS: PMTZ may suppress the proliferation and induce the apoptosis of CRC cells by inhibiting the PI3K/ AKT signaling pathway. This study reported, for the first time, the function of PMTZ in CRC cells and the underlying mechanism and further confirmed the potential antitumor effects of phenothiazine. The combination of bioinformatics analyses and experiments provides informative evidence for the reuse of drugs and the development of new drugs.

PMID:34560542 | DOI:10.1016/j.biopha.2021.112174

J Glob Antimicrob Resist. 2021 Sep 21:S2213-7165(21)00211-3. doi: 10.1016/j.jgar.2021.09.003. Online ahead of print.

ABSTRACT

PURPOSE: We hypothesized that one or more of the non-antibiotic candidates selected for this study would demonstrate antibiotic activity against Staphylococcus aureus.

METHODS: We determined minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations (MBCs) for non-antibiotic drugs (amlodipine, azelastine, ebselen, and sertraline) against five clinical Staphylococcus aureus isolates and one quality control strain using microplate alamar blue assays. Our research group selected clinical isolates obtained from nasal and wound swab cultures of patients with skin and soft tissue infections (SSTIs) who were seen at primary care clinics in the South Texas Ambulatory Research Network (STARNet).

RESULTS: Three of the non-antibiotic drugs had identical MICs for all isolates: amlodipine (64 µg/ml), azelastine (200 µg/ml), and sertraline (20 µg/ml). MICs for ebselen were 0.25 µg/ml (SA-29213, A1019, and J1019), 0.5 µg/ml (A32 and B60), and 1.0 µg/ml (B72). MBCs for amlodipine, azelastine, and sertraline, were within one dilution of their MICs, indicating bactericidal activity for all test isolates. Ebselen MICs were 1 to 2 dilutions higher in most isolates, also indicating bactericidal activity for all test isolates.

CONCLUSION: In summary, all four non-antibiotics demonstrated in vitro activity to varying degrees against S. aureus clinical isolates. Ebselen was the most potent of the four non-antibiotics tested.

PMID:34560306 | DOI:10.1016/j.jgar.2021.09.003

Br J Clin Pharmacol. 2021 Sep 23. doi: 10.1111/bcp.15090. Online ahead of print.

ABSTRACT

X-linked adrenoleukodystrophy (X-ALD) is an inherited, neurodegenerative rare disease that can result in devastating symptoms of blindness, gait disturbances, and spastic quadriparesis due to progressive demyelination. Typically, the disease progresses rapidly, causing death within the first decade of life. With limited treatments available, efforts to determine an effective therapy that can alter disease progression or mitigate symptoms have been undertaken for many years, particularly through drug repurposing. Repurposing has generally been guided through clinical experience and small trials. At this time, none of the drug candidates have been approved for use, which may be due, in part, to the lack of pharmacokinetic/pharmacodynamic (PK/PD) information on the repurposed medications in the target patient population. Greater consideration for the disease pathophysiology, drug pharmacology, and potential drug-target interactions, specifically at the site of action, would improve drug repurposing and facilitate drug development. Incorporating advanced translational and clinical pharmacological approaches in preclinical studies and early stages clinical trials will improve the success of repurposed drugs for X-ALD as well as other rare diseases.

PMID:34558098 | DOI:10.1111/bcp.15090

Cell Death Dis. 2021 Sep 23;12(10):864. doi: 10.1038/s41419-021-04151-3.

ABSTRACT

Rewiring of host cytokine networks is a key feature of inflammatory bowel diseases (IBD) such as Crohn's disease (CD). Th1-type cytokines-IFN-γ and TNF-α-occupy critical nodes within these networks and both are associated with disruption of gut epithelial barrier function. This may be due to their ability to synergistically trigger the death of intestinal epithelial cells (IECs) via largely unknown mechanisms. In this study, through unbiased kinome RNAi and drug repurposing screens we identified JAK1/2 kinases as the principal and nonredundant drivers of the synergistic killing of human IECs by IFN-γ/TNF-α. Sensitivity to IFN-γ/TNF-α-mediated synergistic IEC death was retained in primary patient-derived intestinal organoids. Dependence on JAK1/2 was confirmed using genetic loss-of-function studies and JAK inhibitors (JAKinibs). Despite the presence of biochemical features consistent with canonical TNFR1-mediated apoptosis and necroptosis, IFN-γ/TNF-α-induced IEC death was independent of RIPK1/3, ZBP1, MLKL or caspase activity. Instead, it involved sustained activation of JAK1/2-STAT1 signalling, which required a nonenzymatic scaffold function of caspase-8 (CASP8). Further modelling in gut mucosal biopsies revealed an intercorrelated induction of the lethal CASP8-JAK1/2-STAT1 module during ex vivo stimulation of T cells. Functional studies in CD-derived organoids using inhibitors of apoptosis, necroptosis and JAKinibs confirmed the causative role of JAK1/2-STAT1 in cytokine-induced death of primary IECs. Collectively, we demonstrate that TNF-α synergises with IFN-γ to kill IECs via the CASP8-JAK1/2-STAT1 module independently of canonical TNFR1 and cell death signalling. This non-canonical cell death pathway may underpin immunopathology driven by IFN-γ/TNF-α in diverse autoinflammatory diseases such as IBD, and its inhibition may contribute to the therapeutic efficacy of anti-TNFs and JAKinibs.

PMID:34556638 | DOI:10.1038/s41419-021-04151-3

Eur J Med Chem. 2021 Sep 14;226:113847. doi: 10.1016/j.ejmech.2021.113847. Online ahead of print.

ABSTRACT

Transthyretin (TTR) has a well-established role in neuroprotection in Alzheimer's Disease (AD). We have setup a drug discovery program of small-molecule compounds that act as chaperones enhancing TTR/Amyloid-beta peptide (Aβ) interactions. A combination of computational drug repurposing approaches and in vitro biological assays have resulted in a set of molecules which were then screened with our in-house validated high-throughput screening ternary test. A prioritized list of chaperones was obtained and corroborated with ITC studies. Small-molecule chaperones have been discovered, among them our lead compound Iododiflunisal (IDIF), a molecule in the discovery phase; one investigational drug (luteolin); and 3 marketed drugs (sulindac, olsalazine and flufenamic), which could be directly repurposed or repositioned for clinical use. Not all TTR tetramer stabilizers behave as chaperones in vitro. These chemically diverse chaperones will be used for validating TTR as a target in vivo, and to select one repurposed drug as a candidate to enter clinical trials as AD disease-modifying drug.

PMID:34555615 | DOI:10.1016/j.ejmech.2021.113847

Comput Biol Med. 2021 Sep 10;138:104856. doi: 10.1016/j.compbiomed.2021.104856. Online ahead of print.

ABSTRACT

Machine learning and data-driven approaches are currently being widely used in drug discovery and development due to their potential advantages in decision-making based on the data leveraged from existing sources. Applying these approaches to drug repurposing (DR) studies can identify new relationships between drug molecules, therapeutic targets and diseases that will eventually help in generating new insights for developing novel therapeutics. In the current study, a dataset of 1671 approved drugs is analyzed using a combined approach involving unsupervised Machine Learning (ML) techniques (Principal Component Analysis (PCA) followed by k-means clustering) and Structure-Activity Relationships (SAR) predictions for DR. PCA is applied on all the two dimensional (2D) molecular descriptors of the dataset and the first five Principal Components (PC) were subsequently used to cluster the drugs into nine well separated clusters using k-means algorithm. We further predicted the biological activities for the drug-dataset using the PASS (Predicted Activities Spectra of Substances) tool. These predicted activity values are analyzed systematically to identify repurposable drugs for various diseases. Clustering patterns obtained from k-means showed that every cluster contains subgroups of structurally similar drugs that may or may not have similar therapeutic indications. We hypothesized that such structurally similar but therapeutically different drugs can be repurposed for the native indications of other drugs of the same cluster based on their high predicted biological activities obtained from PASS analysis. In line with this, we identified 66 drugs from the nine clusters which are structurally similar but have different therapeutic uses and can therefore be repurposed for one or more native indications of other drugs of the same cluster. Some of these drugs not only share a common substructure but also bind to the same target and may have a similar mechanism of action, further supporting our hypothesis. Furthermore, based on the analysis of predicted biological activities, we identified 1423 drugs that can be repurposed for 366 new indications against several diseases. In this study, an integrated approach of unsupervised ML and SAR analysis have been used to identify new indications for approved drugs and the study provides novel insights into clustering patterns generated through descriptor level analysis of approved drugs.

PMID:34555571 | DOI:10.1016/j.compbiomed.2021.104856

Br J Haematol. 2021 Sep 23. doi: 10.1111/bjh.17851. Online ahead of print.

ABSTRACT

The anti-cancer potential of dipyridamole has been suggested from experiments, but evidence from population-based studies is still lacking. We aimed to explore if dipyridamole use was related to a lower risk of lymphoid neoplasms. We identified individuals with prescription of aspirin after diagnosis of ischaemic cerebrovascular disease since 2006 by linking several Swedish registers. In these aspirin users, those with dipyridamole prescription were further identified as the study group and patients without dipyridamole were randomly selected as reference group with 1:1 ratio using a propensity score-matching approach. After a median of 6·67 years of follow-up, a total of 46 patients with dipyridamole use developed lymphoid neoplasms with an incidence rate of 0·49 per 1 000 person-years, while the rate in the matched group was 0·74 per 1 000 person-years. As compared to non-users, dipyridamole users were associated with a significantly decreased risk of lymphoid neoplasms [hazard ratio (HR) = 0·65; 95% confidence interval (CI) = 0·43-0·98]. Specifically, the reduced risk was observed for non-Hodgkin lymphomas (HR = 0·64; 95% CI = 0·42-0·94), especially B-cell lymphomas (HR = 0·56; 95% CI = 0·35-0·88). Dipyridamole use was related to a lower risk of lymphoid neoplasms, indicating a clinical potential of dipyridamole to be an adjunct anti-tumour agent against lymphoid neoplasms.

PMID:34553368 | DOI:10.1111/bjh.17851

J Cheminform. 2021 Sep 22;13(1):71. doi: 10.1186/s13321-021-00552-w.

ABSTRACT

Drug-target interaction (DTI) prediction is a crucial step in drug discovery and repositioning as it reduces experimental validation costs if done right. Thus, developing in-silico methods to predict potential DTI has become a competitive research niche, with one of its main focuses being improving the prediction accuracy. Using machine learning (ML) models for this task, specifically network-based approaches, is effective and has shown great advantages over the other computational methods. However, ML model development involves upstream hand-crafted feature extraction and other processes that impact prediction accuracy. Thus, network-based representation learning techniques that provide automated feature extraction combined with traditional ML classifiers dealing with downstream link prediction tasks may be better-suited paradigms. Here, we present such a method, DTi2Vec, which identifies DTIs using network representation learning and ensemble learning techniques. DTi2Vec constructs the heterogeneous network, and then it automatically generates features for each drug and target using the nodes embedding technique. DTi2Vec demonstrated its ability in drug-target link prediction compared to several state-of-the-art network-based methods, using four benchmark datasets and large-scale data compiled from DrugBank. DTi2Vec showed a statistically significant increase in the prediction performances in terms of AUPR. We verified the "novel" predicted DTIs using several databases and scientific literature. DTi2Vec is a simple yet effective method that provides high DTI prediction performance while being scalable and efficient in computation, translating into a powerful drug repositioning tool.

PMID:34551818 | DOI:10.1186/s13321-021-00552-w