Browse
Submit Data
Databases
API
Help

Dataset Information

19 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identifying FAAH Inhibitors as New Therapeutic Options for the Treatment of Chronic Pain through Drug Repurposing.

ABSTRACT: Chronic pain determines a substantial burden on individuals, employers, healthcare systems, and society. Most of the affected patients report dissatisfaction with currently available treatments. There are only a few and poor therapeutic options-some therapeutic agents are an outgrowth of drugs targeting acute pain, while others have several serious side effects. One of the primary degradative enzymes for endocannabinoids, fatty acid amide hydrolase (FAAH) attracted attention as a significant molecular target for developing new therapies for neuropsychiatric and neurological diseases, including chronic pain. Using chemical graph mining, quantitative structure-activity relationship (QSAR) modeling, and molecular docking techniques we developed a multi-step screening protocol to identify repurposable drugs as FAAH inhibitors. After screening the DrugBank database using our protocol, 273 structures were selected, with five already approved drugs, montelukast, repaglinide, revefenacin, raloxifene, and buclizine emerging as the most promising repurposable agents for treating chronic pain. Molecular docking studies indicated that the selected compounds interact with the enzyme mostly non-covalently (except for revefenacin) through shape complementarity to the large substrate-binding pocket in the active site. A molecular dynamics simulation was employed for montelukast and revealed stable interactions with the enzyme. The biological activity of the selected compounds should be further confirmed by employing in vitro and in vivo studies.

SUBMITTER: Zanfirescu A

PROVIDER: S-EPMC8781999 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Drug repurposing using computational methods to identify therapeutic options for COVID-19.

Project description:PurposeRecently, the world has been dealing with a new type of coronavirus called COVID-19 that in terms of symptoms is similar to the SARS coronavirus. Unfortunately, researchers could not find a registered therapy to treat the infection related to the virus yet. Regarding the fact that drug repurposing is a good strategy for epidemic viral infection, we applied the drug repurposing strategy using virtual screening to identify therapeutic options for COVID-19. For this purpose, five proteins of COVID-19 (3-chymotrypsin-like protease (3CLpro), Papain-Like protease (PLpro), cleavage site, HR1 and RBD in Spike protein) were selected as target proteins for drug repositioning.MethodsFirst, five proteins of COVID-19 were built by homology modeling. Then FDA-approved drugs (2471 drugs) were screened against cleavage site and RBD in Spike protein via virtual screening. One hundred and twenty-eight FDA-approved drugs with the most favorable free-binding energy were attached to the cleavage site and RBD in Spike protein. Of these 128 drugs, 18 drugs have either been used currently as antiviral or have been reported to possess antiviral effects. Virtual screening was then performed for the 18 selected drugs with ACE2, 3CLpro and PLpro and HR1 and TMPRSS2.ResultsAccording to the results, glecaprevir, paritaprevir, simeprevir, ledipasvir, glycyrrhizic acid, TMC-310911, and hesperidin showed highly favorably free binding energies with all tested target proteins.ConclusionThe above-mentioned drugs can be regarded as candidates to treat COVID-19 infections, but further study on the efficiency of these drugs is also necessary.

| S-EPMC7261216 | biostudies-literature

Recent Trends in the Management of Alzheimer's Disease: Current Therapeutic Options and Drug Repurposing Approaches.

Project description:Alzheimer's disease is one of the most progressive forms of dementia, ultimately leading to death in aged populations. The major hallmarks of Alzheimer's disease include deposition of extracellular amyloid senile plaques and intracellular neurofibrillary tangles in brain neuronal cells. Although there are classical therapeutic options available for the treatment of the diseases, however, they provide only a symptomatic relief and do not modify the molecular pathophysiological course of the disease. Recent research advances in Alzheimer's disease have highlighted the potential role of anti-amyloid, anti-tau, and anti-inflammatory therapies. However, these therapies are still in different phases of pre-clinical/clinical development. In addition, drug repositioning/repurposing is another interesting and promising approach to explore rationalized options for the treatment of Alzheimer's disease. This review discusses the different aspects of the pathophysiological mechanism involved in the progression of Alzheimer's disease along with the limitations of current therapies. Furthermore, this review also highlights emerging investigational drugs along with recent drug repurposing approaches for Alzheimer's disease.

| S-EPMC7569317 | biostudies-literature

A network-biology led computational drug repurposing strategy to prioritize therapeutic options for COVID-19.

Project description:The alarming pandemic situation of novel Severe Acute Respiratory Syndrome Coronavirus 2 (nSARS-CoV-2) infection, high drug development cost and slow process of drug discovery have made repositioning of existing drugs for therapeutics a popular alternative. It involves the repurposing of existing safe compounds which results in low overall development costs and shorter development timeline. In the present study, a computational network-biology approach has been used for comparing three candidate drugs i.e. quercetin, N-acetyl cysteine (NAC), and 2-deoxy-glucose (2-DG) to be effectively repurposed against COVID-19. For this, the associations between these drugs and genes of Severe Acute Respiratory Syndrome (SARS) and the Middle East Respiratory Syndrome (MERS) diseases were retrieved and a directed drug-gene-gene-disease interaction network was constructed. Further, to quantify the associations between a target gene and a disease gene, the shortest paths from the target gene to the disease genes were identified. A vector DV was calculated to represent the extent to which a disease gene was influenced by these drugs. Quercetin was quantified as the best among the three drugs, suited for repurposing with DV of -70.19, followed by NAC with DV of -39.99 and 2-DG with DV of -13.71. The drugs were also assessed for their safety and efficacy balance (in terms of therapeutic index) using network properties. It was found that quercetin was a forerunner than other two drugs.

| S-EPMC9093055 | biostudies-literature

Identification of SARS-CoV-2 inhibitors through phylogenetics and drug repurposing.

Project description:The novel coronavirus that has affected the whole world is declared a pandemic by the World Health Organization. Since the emergence of this virus, researchers worldwide have searched for potential antivirals against it. Being an RNA virus, it shows a high rate of mutability and variability in its genome. In the present study, all the reported SARS-CoV-2 genomes isolated from diverse regions of the world available in the GISAID database have been considered for phylogenetic analysis. The strain identified at the root is subjected to phylogenetic analysis with genomes of other known human viruses obtained from NCBI for identifying the nearest viral neighbor. Furthermore, the phylogenetic relationship between various human viruses was used to repurpose the known antiviral drugs towards coronavirus using in silico docking approach. The phylogeny reveals the link of the COVID virus with adenovirus. The known drugs against adenovirus are considered in the present study for drug repurposing through molecular docking analysis. The reference inhibitors of the respective targets were also considered in the docking study. The protein targets, namely protease, endoribonuclease, methyltransferase, phosphatase, and spike protein, are considered for screening with the known drug of adenovirus. Ribavirin, known to treat adenoviral infection, shows the best docking score, suggesting its use as a repurposed drug to treat SARS-CoV-2. Furthermore, the potency of the ribavirin drug is analyzed using molecular dynamics studies.Supplementary informationThe online version contains supplementary material available at 10.1007/s11224-022-02019-6.

| S-EPMC9315090 | biostudies-literature

Coronaviruses - drug discovery and therapeutic options.

Project description:In humans, infections with the human coronavirus (HCoV) strains HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1 usually result in mild, self-limiting upper respiratory tract infections, such as the common cold. By contrast, the CoVs responsible for severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which were discovered in Hong Kong, China, in 2003, and in Saudi Arabia in 2012, respectively, have received global attention over the past 12 years owing to their ability to cause community and health-care-associated outbreaks of severe infections in human populations. These two viruses pose major challenges to clinical management because there are no specific antiviral drugs available. In this Review, we summarize the epidemiology, virology, clinical features and current treatment strategies of SARS and MERS, and discuss the discovery and development of new virus-based and host-based therapeutic options for CoV infections.

| S-EPMC7097181 | biostudies-literature

Overcoming cancer therapeutic bottleneck by drug repurposing.

Project description:Ever present hurdles for the discovery of new drugs for cancer therapy have necessitated the development of the alternative strategy of drug repurposing, the development of old drugs for new therapeutic purposes. This strategy with a cost-effective way offers a rare opportunity for the treatment of human neoplastic disease, facilitating rapid clinical translation. With an increased understanding of the hallmarks of cancer and the development of various data-driven approaches, drug repurposing further promotes the holistic productivity of drug discovery and reasonably focuses on target-defined antineoplastic compounds. The "treasure trove" of non-oncology drugs should not be ignored since they could target not only known but also hitherto unknown vulnerabilities of cancer. Indeed, different from targeted drugs, these old generic drugs, usually used in a multi-target strategy may bring benefit to patients. In this review, aiming to demonstrate the full potential of drug repurposing, we present various promising repurposed non-oncology drugs for clinical cancer management and classify these candidates into their proposed administration for either mono- or drug combination therapy. We also summarize approaches used for drug repurposing and discuss the main barriers to its uptake.

| S-EPMC7331117 | biostudies-literature

Systematic identification of risk factors and drug repurposing options for Alzheimer's disease.

Project description:IntroductionSeveral Mendelian randomization studies have been conducted that identified multiple risk factors for Alzheimer's disease (AD). However, they typically focus on a few pre-selected risk factors.MethodsA two-sample Mendelian randomization (MR) study was used to systematically examine the potential causal associations of 1037 risk factors/medical conditions and 31 drugs with the risk of late-onset AD. To correct for multiple comparisons, the false discovery rate was set at < 0.05.ResultsThere was strong evidence of a causal association between glioma risk, reduced trunk fat-free mass, lower education levels, lower intelligence and a higher risk of AD. For 31 investigated treatments (such as antihypertensive drugs), we found limited evidence for their associations.DiscussionMR found robust evidence of causal associations between glioma, trunk fat-free, and AD. Our study also confirms that higher educational attainment and higher intelligence are associated with a reduced risk of AD.

| S-EPMC7927163 | biostudies-literature

Identifying therapeutic candidates for endometriosis through a transcriptomics-based drug repositioning approach.

Project description:Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disease signatures based on endometrial gene expression data to identify potential therapeutics from existing drugs, based on expression reversal. Of 3,131 unique genes differentially expressed by at least one of six endometriosis signatures, only 308 (9.8%) were in common; however, 221 out of 299 drugs identified, (73.9%) were shared. We selected fenoprofen, an uncommonly prescribed NSAID that was the top therapeutic candidate for further investigation. When testing fenoprofen in an established rat model of endometriosis, fenoprofen successfully alleviated endometriosis-associated vaginal hyperalgesia, a surrogate marker for endometriosis-related pain. These findings validate fenoprofen as a therapeutic that could be utilized more frequently for endometriosis and suggest the utility of the aforementioned computational drug repurposing approach for endometriosis.

| S-EPMC10952035 | biostudies-literature

Drug repurposing of bromodomain inhibitors as potential novel therapeutic leads for lymphatic filariasis guided by multi-species transcriptomics

Project description:Brugia malayi, Wolbachia (wBm), and Aedes aegypti transcriptome reads from across the B. malayi FR3 life cycle

2019-11-20 | GSE139965 | GEO

Framework for identifying drug repurposing candidates from observational healthcare data.

Project description:ObjectiveObservational medical databases, such as electronic health records and insurance claims, track the healthcare trajectory of millions of individuals. These databases provide real-world longitudinal information on large cohorts of patients and their medication prescription history. We present an easy-to-customize framework that systematically analyzes such databases to identify new indications for on-market prescription drugs.Materials and methodsOur framework provides an interface for defining study design parameters and extracting patient cohorts, disease-related outcomes, and potential confounders in observational databases. It then applies causal inference methodology to emulate hundreds of randomized controlled trials (RCTs) for prescribed drugs, while adjusting for confounding and selection biases. After correcting for multiple testing, it outputs the estimated effects and their statistical significance in each database.ResultsWe demonstrate the utility of the framework in a case study of Parkinson's disease (PD) and evaluate the effect of 259 drugs on various PD progression measures in two observational medical databases, covering more than 150 million patients. The results of these emulated trials reveal remarkable agreement between the two databases for the most promising candidates.DiscussionEstimating drug effects from observational data is challenging due to data biases and noise. To tackle this challenge, we integrate causal inference methodology with domain knowledge and compare the estimated effects in two separate databases.ConclusionOur framework enables systematic search for drug repurposing candidates by emulating RCTs using observational data. The high level of agreement between separate databases strongly supports the identified effects.

| S-EPMC7886555 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data