Name: drug repurposing hypothesis generation using the "re:fine drugs" system
Uploaded: 2016-12-11T15:00:00.000+00:00
Duration: 5 min 10 s
Description: Watch this Scientific Journal Video about Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System at JoVE.com

This work was partially supported by the National Institutes of Health (NIH) Clinical and Translational Science Awards (CTSA) Grant (UL1TR001070) to the Ohio State University's Center for Clinical and Translational Science (CCTS) and the National Library Of Medicine under Award Number T15LM011270.

1. Con avvio di query da Gene, droga o malattie Termini <ol><li> Accedere alla homepage &quot;RE: Drugs sottili&quot; al seguente link: http://drug-repurposing.nationwidechildrens.org. Iniziare inserendo un termine di ricerca nella barra di ricerca da una delle seguenti tre categorie: farmaci (nome generico del farmaco), la malattia (nuova indicazione di malattia) o gene (HGNC simbolo ufficiale del gene). </li><li> Filtrare la funzione di barra di ricerca per includere solo &quot;Droga Nome&quot;, &quot;nuova malattia indicazione&quot;, &quot;Gene Simbolo&quot; o &quot;Tutte le&quot; categorie. La barra di ricerca include una funzione di auto-fill per le voci di query. </li><li> Mettere in una parola chiave, e clicca sul pulsante &quot;Cerca&quot;. Ordinare la tabella dei risultati per una delle seguenti colonne: &quot;Drug&quot;, &quot;Indicazione registrato&quot;, &quot;P-Value&quot;, &quot;P-valore regolato&quot;, &quot;Odds Ratio&quot;, &quot;Studio&quot;, &quot;nuova indicazione&quot;, &quot;Drug Indicazione banca &quot;,&quot; # di Medline Abstracts &quot;,&quot; # di CliRegistro Trial nica &quot;,&quot; potenziale &quot;,&quot; SNP &quot;,&quot; Gene &quot;o&quot; azione &quot;. </li><li> Passare l&#39;opzione di ricerca avanzata al fine di abilitare la funzione informazione sulla droga. Fare clic sull&#39;icona nella colonna &quot;Info&quot; per un particolare farmaco. Osservare una pagina che elenca il tutte le relative informazioni tra cui p-value per l&#39;associazione, Nome della malattia, nome del farmaco, i dettagli Gene (NCBI collegamento Gene) e dettagli della droga (drugbank link). </li></ol> 2. Esplorazione di opzioni avanzate <ol><li> Fare clic sul pulsante &quot;Avanzate&quot; si trova sul lato destro della pagina, e diverse opzioni per affinare ulteriormente i risultati sono forniti. Le opzioni di ricerca avanzate includono modifiche al seguente: droga, associazione, la malattia, il potenziale, gene e l&#39;azione. </li><li> Esporta risultati tabelle cliccando sul pulsante &quot;Esporta&quot; sul lato destro della pagina. Fare clic sul pulsante &quot;Semplice&quot;, al fine di abbassare la finestra di ricerca avanzata. &lt;/ Li&gt; <li> Sotto l&#39;opzione scheda &quot;droga&quot; avanzata, specificare una particolare indicazione di droga o un nome ulteriore farmaco per filtrare i risultati. </li><li> Nella scheda &quot;associazione&quot;, filtrare i risultati per il livello di significatività P-valore, rettificato P-valore con FDR, dimensione dell&#39;effetto (Odds Ratio), e / o di studio di tipo (GWAS, PheWAS o entrambi). </li><li> Nella scheda &quot;malattia&quot;, specificare una certa descrizione malattia per il nuovo uso previsto. </li><li> Nella scheda &quot;potenziale&quot;, filtrare i risultati in base a uno dei seguenti criteri: (i) se l&#39;indicazione della droga è contenuto nel database drugbank, (ii) il numero di abstract di Medline con co-occorrenza del farmaco e la malattia, ( iii) il numero di voci del database ClinicalTrials.gov con co-occorrenza del farmaco e la malattia e (iv) Repurposing potenziale. NOTA: L&#39;opzione potenziale Repurposing descrive la novità della scoperta: (i) noto: relazione esiste già nel database drugbank, (ii) Fortemente sostenuta: Un supporto sia in Registro di sperimentazione clinica e gli abstract di Medline, (iii) Probabile: un certo supporto in entrambi registro studio clinico o gli abstract di Medline e (iv) Novel: nessuna evidenza nel registro studio clinico né in abstract di Medline. </li><li> Nella scheda &quot;gene&quot;, inserire un identificativo di SNP o Gene simbolo di filtrare i risultati in base specifici geni bersaglio di droga. </li><li> Nella scheda &quot;azione&quot;, specificare il tipo di azione dei farmaci contro il bersaglio della droga (s), tra agonisti, antagonisti, altro, sconosciuto o tutti (fonte: banca dati drugbank). </li></ol>

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The authors declare that they have no competing financial interests.

The protocol described here for the RE:fine Drugs interactive dashboard can be modified in different ways according to the user's preferences. This method uniquely integrates GWAS and PheWAS data as a novel paradigm underlying drug repurposing hypothesis generation. Specifically, this system provides access to both 52,966 PheWAS associations and 7,945 GWAS associations with advanced options to filter the results by the study type, effect size and/or significance level. Another advantage of this method over existing computational drug repurposing tools is that queries may be made from drug, gene or disease perspectives. 
There are several limitations to this method. Currently, the PheWAS data is limited to primarily adult patient population from five institutions contained in the Electronic Medical Records and Genomics (eMERGE) network with a mean age of 69.5 years 12. Additionally, the "repurposing potential" feature uses co-occurrence of search terms in Medline abstracts as one of its criteria. It is well known that text mining methods using co-occurrence have limitations with respect to syntactical structure and literature bias. Thus, we recommend this feature be used as a starting point to explore the potential novelty and/or evidence supporting specific drug repurposing hypotheses and recommend additional investigation into the biomedical literature and clinical trial databases. 
Future directions for this work not described here would be to extend this database to additional sources of GWAS and PheWAS data as they become available. Similar efforts to systematically translate results from large-scale GWAS studies into drug repurposing hypotheses have been previously published 9,13-14. It may be useful to compare these different workflows to predict drug candidates from GWAS data in future studies. Additionally, several other methods exist to computationally generate drug repurposing hypotheses from different data sources, including: genomics, transcriptomics, chemical structures, drug side effect profiles, as previously summarized 6,11. Future methodological advancements could also include automating drug combination predictions and providing information on drug toxicity to guide follow up studies for drug candidates. 
Furthermore, the hypotheses generated from RE:fine Drugs may be further validated using electronic health records, before initiating clinical trials 15. Finally, future studies will be needed to compare this system to other target-based drug repurposing methods.

I processi costosi e inefficienti associati approcci scoperta di nuovi farmaci tradizionali, tra cui farmaci ad alto rendimento e lo screening composto di piombo, stanno contribuendo a ritardi nel tradurre le scoperte della ricerca in terapie per i pazienti 1,2. Una media di 1 miliardo di dollari USA e 15-20 anni è necessario per portare un nuovo farmaco da banco al capezzale 3. Inoltre, il 52% dei farmaci sicuro durante lo sviluppo nella fase 1 studi clinici, e solo il 25% di composti che entrano fase 2 procedere in piena fase 3 studi clinici 4. L&#39;obiettivo di riproposizione di droga o di riposizionamento della droga è quello di rinnovare la droga falliti e / o trovare nuovi indicazioni per farmaci approvati al fine di fornire nuove terapie per i pazienti più velocemente e con un tasso di successo più elevato. Repurposing farmaco può diminuire la timeline per rendere disponibili i farmaci per l&#39;uso in pazienti di 3-12 anni 5. applicazioni mediche importanti per riutilizzo farmaci comprendono: malattie con Prognos poveriè e bassi tassi di sopravvivenza, malattie resistenti ai farmaci, aree di ricerca di malattia sottofinanziati e popolazioni di pazienti povere e svantaggiate. Computazionale riuso farmaco è definita come il processo di progettazione e validazione flussi di lavoro automatizzati che possono generare ipotesi per nuove indicazioni di un farmaco candidato 6. Esistenti droga riproporre metodi computazionali sono stati classificati target-based,,, a base di rete basata sulla conoscenza basato su signature, e sulla base mirati meccanismo, e possono essere orientati dal gene, malattie o farmaci prospettive. Inoltre, approcci computazionali possono ulteriormente accelerare esperimenti di validazione proof-of-concept e studi clinici su piccola scala per i candidati di droga riproposto 7. Abbiamo già riferito su &quot;RE: Drugs fine&quot;, uno strumento basato sul web interattivo liberamente disponibile per il farmaco riproporre generazione di ipotesi basate sulla teoria transitiva di farmaco-gene-malattia rapporti 8. Il g complessivaOAL di questo metodo è quello di integrare sistematicamente diversi tipi di droga, genetici e clinici dati per consentire di droga riproporre per gli utenti provenienti da diverse comunità, tra clinica, l&#39;industria e le comunità normativi. I metodi fondamentali di questo sistema sono stati precedentemente segnalato per l&#39;uso di studio genome-wide Association (GWAS) ei dati di studio a livello di associazione Phenome (PheWAS) nella droga la riallocazione delle ricerche 9,10. La nuova combinazione di questi tipi di dati distingue la nostra webtool da altri metodi di obiettivi 6,11. Il RE: multa sistema di farmaci attualmente contiene 60,911 droga riproporre ipotesi che coprono 916 farmaci, 567 geni e 1.770 malattie. Il webtool fornisce un&#39;interfaccia user-friendly per i ricercatori a cercare in modo interattivo droga ipotesi riutilizzo e definire la loro priorità in base a criteri diversi. Per esempio, gli utenti possono filtrare ipotesi riproporre farmaco con supporto nella letteratura biomedica e studi clinici databaSE, significativi valori di p, odds ratio di associazione o da indicazioni specifiche. L&#39;unico requisito per questo sistema è l&#39;accesso a Internet.

<table><tbody><tr><td>Access the homepage for &amp;ldquo;RE:fine Drugs&amp;rdquo; at the following link: http://drug-repurposing.nationwidechildrens.org.&amp;nbsp;</td><td>n/a</td><td>n/a</td><td>The only requirement for this system is Internet access</td></tr></tbody></table>

drug repurposing hypothesis generation using the "re:fine drugs" system

The promise of drug repurposing is that existing drugs may be used for new disease indications in order to curb the high costs and time for approval. The goal of computational methods for drug repurposing is to enable solutions for safer, cheaper and faster drug discovery. Towards this end, we developed a novel method that integrates genetic and clinical phenotype data from large-scale GWAS and PheWAS studies with detailed drug information on the concept of transitive Drug-Gene-Disease triads. We created "RE:fine Drugs," a freely available, interactive dashboard that automates gene, disease and drug-based searches to identify drug repurposing candidates. This web-based tool supports a user-friendly interface that includes an array of advanced search and export options. Results can be prioritized in a variety of ways, including but not limited to, biomedical literature support, strength and statistical significance of GWAS and/or PheWAS associations, disease indications and molecular drug targets. Here we provide a protocol that illustrates the functionalities available in the "RE:fine Drugs" system and explores the different advanced options through a case study.

In questo esempio, il gene &quot;IL2RB&quot; è stato inserito come una query basato sui geni, ed è stato automaticamente riconosciuto come tale dalla funzione di auto-fill (Figura 1). I riallocazione ipotesi dodici droga per il gene IL2RB vengono restituiti, come mostrato nella Figura 2. Pagina di informazioni dettagliate per una particolare ipotesi repurposing di droga, &quot;daclizumab&quot; in questo caso, è fornito dalla colonna &quot;Info&quot; (Figura 3). I risultati sono stati filtrati nella scheda farmaco era di tutti i risultati corrispondenti al farmaco &quot;daclizumab&quot;, come mostrato nella figura 4. La Figura 5 mostra solo quei farmaci con un&#39;indicazione noto per il termine malattia &quot;trapianto&quot; (fonte: banca dati drugbank). La scheda associazione permette all&#39;utente di filtrare i rapporti SNP-fenotipo di significatività statistica (P-value) e le dimensioni effetto genetico (odds ratio), definito come il rapporto tra le probabilità di presence della malattia in individui con un genotipo specifico (SNP allele) sopra le probabilità di presenza della malattia in individui senza l&#39;allele SNP. La Figura 6 mostra i risultati filtrati nella scheda associazione all&#39;interno della gamma P-valore dello 0,000001 0.05. La figura 7 mostra ipotesi riproporre farmaci specifici per &quot;asma&quot; sulla base delle nuove indicazioni che abbiamo trovato in studio. Figura 8 mostra i risultati nella scheda potenziale per filtrare per un numero minimo di 5 abstracts Medline contenenti un co-occorrenza di termini droga e malattie. In questo esempio, tutti i farmaci risultati nella scheda gene sono mirati per il gene &quot;IL2RB&quot;, corrispondente al termine query originale (Figura 9). Infine, la figura 10 mostra risultati filtrati nella scheda &quot;azione&quot; per riportare tutti i farmaci che agiscono come agonisti sul gene IL2RB. <img alt="Figura 1"src = &quot;/ files / ftp_upload / 54948 / 54948fig1.jpg&quot; /&gt; Figura 1: RE: I farmaci pregiati del cruscotto interattivo homepage. Gli utenti possono iniziare una query inserendo un nome del farmaco, nuova indicazione malattia o il simbolo del gene. I collegamenti sono previste anche per i giornali di riferimento GWAS e PheWAS che descrivono le metodologie per la generazione di ipotesi riuso di droga. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig1large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <img alt="figura 2" src="/files/ftp_upload/54948/54948fig2.jpg" /> Figura 2: funzione Auto-fill per le voci di query. Come esempio, il termine di ricerca gene &quot;IL2RB&quot; è stata automaticamente riconosciuta come termine gene. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig2large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <pclass = &quot;jove_content&quot; fo: keep-together.within-page = &quot;1&quot;&gt; <img alt="Figura 3" src="/files/ftp_upload/54948/54948fig3.jpg" /> Figura 3: Drug riproporre tabella dei risultati prodotta da una query gene-based (ad esempio, IL2RB). Dodici droga riproporre ipotesi per il gene IL2RB vengono prodotte. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig3large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <img alt="Figura 4" src="/files/ftp_upload/54948/54948fig4.jpg" /> Figura 4: foglio di informazione per i singoli farmaci da pagina dei risultati. Cliccando sull&#39;icona nella colonna &quot;Info&quot; sono riportate le informazioni dettagliate per il daclizumab droga. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig4large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> Figura 5: opzione di ricerca avanzata nella scheda di droga per filtrare da un farmaco specifico. In questo esempio, tre risultati sono mostrati per il daclizumab droga. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig5large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <img alt="Figura 6" src="/files/ftp_upload/54948/54948fig6.jpg" /> Figura 6: opzione di ricerca avanzata nella scheda di droga per filtrare da un&#39;indicazione specifica malattia dal database drugbank. Tutti i farmaci a indicazione noto per la malattia termine &quot;trapianto&quot; sono mostrate. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig6large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> Figura 7: opzione di ricerca avanzata nella scheda associazione per filtrare per livello di significatività. In questo caso, sono previsti otto risultati cui associazione significato livello ricade nel campo da P-valore dello 0,000001 0.05. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig7large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <img alt="Figura 8" src="/files/ftp_upload/54948/54948fig8.jpg" /> Figura 8: opzione di ricerca avanzata nella scheda malattia per filtrare da un&#39;indicazione specifica malattia abbiamo estratto in questo studio. In questo esempio, quattro risultati sono mostrati per asma come una nuova indicazione utilizzo malattia. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig8large.jpg" target="_blank">Clicca qui per visualizzare un Versi più grandi</a>su questa figura. <img alt="Figura 9" src="/files/ftp_upload/54948/54948fig9.jpg" /> Figura 9: opzione di ricerca avanzata nella scheda potenziale per filtrare da un co-occorrenza di droga e la malattia in termini abstract di Medline. In questo esempio, quattro risultati sono mostrati supportato da un numero minimo di 5 abstracts Medline contenenti un co-occorrenza di termini droga e malattie. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig9large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a> <img alt="Figura 10" src="/files/ftp_upload/54948/54948fig10.jpg" /> Figura 10: opzione di ricerca avanzata nella scheda gene per filtrare da un simbolo specifico gene, in cui tutti i risultati corrispondono al gene IL2RB utilizzato per la query originale. In questo esempio, tutti i farmaci risultatinella scheda gene sono mirati per il gene &quot;IL2RB&quot;, corrispondente alla durata query originale. opzione di ricerca avanzata nella scheda azione per filtrare solo da farmaci agonisti. In questo esempio, sei risultati vengono restituiti per tutti i farmaci che agiscono come agonisti sul gene IL2RB. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig10large.jpg" target="_blank">Clicca qui per vedere una versione più grande di questa figura.</a>

Watch this Scientific Journal Video about Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System at JoVE.com

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Here we describe a protocol using the web-based drug repurposing hypothesis generation tool: "RE:fine Drugs." This protocol can be modified to a user's preferences at the level of the query type (gene, drug or disease) and/or the range of available advanced options.

Drug Repurposing Ipotesi Generation Con il &quot;RE: Drugs sottili&quot; Sistema

The promise of drug repurposing is that existing drugs may be used for new disease indications in order to curb the high costs and time for approval. The ...

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9.2K Views.  The Ohio State University. Here we describe a protocol using the web-based drug repurposing hypothesis generation tool: "RE:fine Drugs." This protocol can be modified to a user's preferences at the level of the query type (gene, drug or disease) and/or the range of available advanced options. 

Video: Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Method for Efficient Refolding and Purification of Chemoreceptor Ligand Binding Domain

Identification of natural ligands of chemoreceptors and structural studies aimed at elucidation of the molecular basis of the ligand specificity can be greatly facilitated by the production of milligram amounts of pure, folded ligand binding domains. Attempts to heterologously express periplasmic ligand binding domains of bacterial chemoreceptors in Escherichia coli (E. coli) often result in their targeting into inclusion bodies. Here, a method is presented for protein recovery from inclusion bodies, its refolding and purification, using the periplasmic dCACHE ligand binding domain of Campylobacter jejuni (C. jejuni) chemoreceptor Tlp3 as an example. The approach involves expression of the protein of interest with a cleavable His6-tag, isolation and urea-mediated solubilisation of inclusion bodies, protein refolding by urea depletion, and purification by means of affinity chromatography, followed by tag removal and size-exclusion chromatography. The circular dichroism spectroscopy is used to confirm the folded state of the pure protein. It has been demonstrated that this protocol is generally useful for production of milligram amounts of dCACHE periplasmic ligand binding domains of other bacterial chemoreceptors in a soluble and crystallisable form.

A procedure is presented for the refolding of the dCACHE periplasmic ligand binding domain of Campylobacter jejuni chemoreceptor Tlp3 from inclusion bodies and the purification to yield milligram quantities of protein.

Metodo per ripiegamento efficiente e purificazione del chemocettore Ligand Binding Domain

Identification of natural ligands of chemoreceptors and structural studies aimed at elucidation of the molecular basis of the ligand specificity can be ...

Ricerca

Biochimica

Facilitating Drug Discovery: An Automated High-content Inflammation Assay in Zebrafish

Zebrafish larvae are particularly amenable to whole animal small molecule screens1,2 due to their small size and relative ease of manipulation and observation, as well as the fact that compounds can simply be added to the bathing water and are readily absorbed when administered in a &lt;1% DMSO solution. Due to the optical clarity of zebrafish larvae and the availability of transgenic lines expressing fluorescent proteins in leukocytes, zebrafish offer the unique advantage of monitoring an acute inflammatory response in vivo. Consequently, utilizing the zebrafish for high-content small molecule screens aiming at the identification of immune-modulatory compounds with high throughput has been proposed3-6, suggesting inflammation induction scenarios e.g. localized nicks in fin tissue, laser damage directed to the yolk surface of embryos7 or tailfin amputation3,5,6. The major drawback of these methods however was the requirement of manual larva manipulation to induce wounding, thus preventing high-throughput screening. Introduction of the chemically induced inflammation (ChIn) assay8 eliminated these obstacles. Since wounding is inflicted chemically the number of embryos that can be treated simultaneously is virtually unlimited. Temporary treatment of zebrafish larvae with copper sulfate selectively induces cell death in hair cells of the lateral line system and results in rapid granulocyte recruitment to injured neuromasts. The inflammatory response can be followed in real-time by using compound transgenic cldnB::GFP/lysC::DsRED26,9 zebrafish larvae that express a green fluorescent protein in neuromast cells, as well as a red fluorescent protein labeling granulocytes.
In order to devise a screening strategy that would allow both high-content and high-throughput analyses we introduced robotic liquid handling and combined automated microscopy with a custom developed software script. This script enables automated quantification of the inflammatory response by scoring the percent area occupied by red fluorescent leukocytes within an empirically defined area surrounding injured green fluorescent neuromasts. Furthermore, we automated data processing, handling, visualization, and storage all based on custom developed MATLAB and Python scripts.
In brief, we introduce an automated HC/HT screen that allows testing of chemical compounds for their effect on initiation, progression or resolution of a granulocytic inflammatory response. This protocol serves a good starting point for more in-depth analyses of drug mechanisms and pathways involved in the orchestration of an innate immune response. In the future, it may help identifying intolerable toxic or off-target effects at earlier phases of drug discovery and thereby reduce procedural risks and costs for drug development.

Here we describe a novel high-content chemically induced inflammation assay aiming at the identification of immune-modulatory bioactives. We have successfully combined automated microscopy with custom developed software scripts enabling automated quantification of the inflammatory response as well as further data processing, analysis, mining, and storage.

Facilitare Drug Discovery: un sistema automatico di alta Tenore infiammazione in Zebrafish

Zebrafish larvae are particularly amenable to whole animal small molecule screens1,2 due to their small size and relative ease of manipulation and ...

Immunologia e infezioni

Using Human Induced Pluripotent Stem Cell-derived Hepatocyte-like Cells for Drug Discovery

The ability to differentiate human induced pluripotent stem cells (iPSCs) into hepatocyte-like cells (HLCs) provides new opportunities to study inborn errors in hepatic metabolism. However, to provide a platform that supports the identification of small molecules that can potentially be used to treat liver disease, the procedure requires a culture format that is compatible with screening thousands of compounds. Here, we describe a protocol using completely defined culture conditions, which allow the reproducible differentiation of human iPSCs to hepatocyte-like cells in 96-well tissue culture plates. We also provide an example of using the platform to screen compounds for their ability to lower Apolipoprotein B (APOB) produced from iPSC-derived hepatocytes generated from a familial hypercholesterolemia patient. The availability of a platform that is compatible with drug discovery should allow researchers to identify novel therapeutics for diseases that affect the liver.

The protocol presented here describes a platform for identifying small molecules for the treatment of liver disease. A step-by-step description is presented detailing how to differentiate iPSCs into cells with hepatocyte characteristics in 96-well plates, and to use the cells to screen for small molecules with potential therapeutic activity.

Utilizzando umani indotti dell'epatocita-come di derivati da cellule staminali pluripotenti per scoperta della droga

The ability to differentiate human induced pluripotent stem cells (iPSCs) into hepatocyte-like cells (HLCs) provides new opportunities to study inborn ...

Biologia dello sviluppo

NMR-Based Fragment Screening in a Minimum Sample but Maximum Automation Mode

Fragment-based screening (FBS) is a well-validated and accepted concept within the drug discovery process both in academia and industry. The greatest advantage of NMR-based fragment screening is its ability not only to detect binders over 7-8 orders of magnitude of affinity but also to monitor purity and chemical quality of the fragments and thus to produce high quality hits and minimal false positives or false negatives. A prerequisite within the FBS is to perform initial and periodic quality control of the fragment library, determining solubility and chemical integrity of the fragments in relevant buffers, and establishing multiple libraries to cover diverse scaffolds to accommodate various macromolecule target classes (proteins/RNA/DNA). Further, an extensive NMR-based screening protocol optimization with respect to sample quantities, speed of acquisition and analysis at the level of biological construct/fragment-space, in condition-space (buffer, additives, ions, pH, and temperature) and in ligand-space (ligand analogues, ligand concentration) is required. At least in academia, these screening efforts have so far been undertaken manually in a very limited fashion, leading to limited availability of screening infrastructure not only in the drug development process but also in the context of chemical probe development. In order to meet the requirements economically, advanced workflows are presented. They take advantage of the latest state-of-the-art advanced hardware, with which the liquid sample collection can be filled in a temperature-controlled fashion into the NMR-tubes in an automated manner. 1H/19F NMR ligand-based spectra are then collected at a given temperature. High-throughput sample changer (HT sample changer) can handle more than 500 samples in temperature-controlled blocks. This together with advanced software tools speeds up data acquisition and analysis. Further, application of screening routines on protein and RNA samples are described to make aware of the established protocols for a broad user base in biomacromolecular research.

Fragment-based screening by NMR is a robust method to rapidly identify small molecule binders to biomacromolecules (DNA, RNA, or proteins). Protocols describing automation-based sample preparation, NMR experiments &#38; acquisition conditions, and analysis workflows are presented. The technique allows for optimal exploitation of both 1H and 19F NMR-active nuclei for detection.

Screening dei frammenti basato su NMR in un campione minimo ma in modalità di automazione massima

Fragment-based screening (FBS) is a well-validated and accepted concept within the drug discovery process both in academia and industry. The greatest ...

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Thermal shift assays (TSAs) examine how the melting temperature (Tm) of a target protein changes in response to changes in its environment (e.g., buffer composition). The utility of TSA, and specifically of nano-Differential Scanning Fluorimetry (nano-DSF), has been established over the years, both for finding conditions that help stabilize a specific protein and for looking at ligand binding by monitoring changes in the apparent Tm. This paper presents an efficient screening of the Diamond-SGC-iNEXT Poised (DSi-Poised) fragment library (768 compounds) by the use of nano-DSF, monitoring Tm to identify potential fragment binding. The prerequisites regarding protein quality and concentration for performing nano-DSF experiments are briefly outlined followed by a step-by-step protocol that uses a nano-liter robotic dispenser commonly used in structural biology laboratories for preparing the required samples in 96-well plates. The protocol describes how the reagent mixtures are transferred to the capillaries needed for nano-DSF measurements. In addition, this paper provides protocols to measure thermal denaturation (monitoring intrinsic tryptophan fluorescence) and aggregation (monitoring light back-scattering) and the subsequent steps for data transfer and analysis. Finally, screening experiments with three different protein targets are discussed to illustrate the use of this procedure in the context of lead discovery campaigns. The overall principle of the method described can be easily transferred to other fragment libraries or adapted to other instruments.

Monitoring changes in the melting temperature of a target protein (i.e., thermal shift assay, TSA) is an efficient method for screening fragment libraries of a few hundred compounds. We present a TSA protocol implementing robotics-assisted nano-Differential Scanning Fluorimetry (nano-DSF) for monitoring intrinsic tryptophan fluorescence and light back-scattering for fragment screening.

Fluorimetria a scansione nano-differenziale per lo screening nella scoperta di piombo basata su frammenti

Thermal shift assays (TSAs) examine how the melting temperature (Tm) of a target protein changes in response to changes in its environment (e.g., buffer ...

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Although targeted therapies are initially effective, resistance inevitably emerges. Several methods, such as genetic analysis of resistant clinical specimens, have been applied to uncover these resistance mechanisms to facilitate follow-up care. Although these approaches have led to clinically relevant discoveries, difficulties in attaining the relevant patient material or in deconvoluting the genomic data collected from these specimens have severely hampered the path towards a cure. To this end, we here describe a tool for expeditious discovery that may guide improvement in first-line therapies and alternative clinical management strategies. By coupling preclinical in vitro or in vivo drug selection with next-generation sequencing, it is possible to identify genomic structural variations and/or gene expression alterations that may serve as functional drivers of resistance. This approach facilitates the spontaneous emergence of alterations, enhancing the probability that these mechanisms may be observed in the patients. In this protocol we provide guidelines to maximize the potential for uncovering single nucleotide variants that drive resistance using adherent lines.

Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

Drug resistance to targeted therapeutics is widespread and the need to identify mechanisms of resistance--prior to or following clinical onset--is critical for guiding alternative clinical management strategies. Here, we present a protocol to couple derivation of drug-resistant lines in vitro with sequencing to expedite discovery of these mechanisms.

Implementazione di<em&gt; In Vitro</em&gt; Drug Resistance saggi: massimizzare il potenziale per scoprire clinicamente rilevanti Resistenza Meccanismi

Although targeted therapies are initially effective, resistance inevitably emerges. Several methods, such as genetic analysis of resistant clinical ...

Medicina

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Receptors and enzyme proteins are important biomolecules that act as binding targets for bioactive small molecules. Thus, the rapid and global validation of the drug-protein interactions is highly desirable for not only understanding the molecular mechanisms underlying therapeutic efficacy but also for assessing drug characteristics, such as adsorption, distribution, metabolism, excretion, and toxicity (ADMET) for clinical use. Here, we present a biosensor-based high throughput strategy for the biopanning of T7 phage-displayed short peptides that can be easily displayed on the phage capsid. Subsequent analysis of the amino acid sequences of peptides containing short segments, as &#34;broken relics&#34;, of the drug-binding sites using bioinformatics programs in receptor ligand contact (RELIC) suite, is also shown. By applying this method to two clinically approved drugs, an anti-tumor irinotecan, and an anti-flu oseltamivir, the detailed process for collecting the drug-recognizing peptide sequences and highlighting the drug-binding sites of the target proteins are explained in this paper. The strategy described herein can be applied for any small molecules of interest.

This study aimed to present a strategy for identifying drug-peptide interactions. The strategy involves the biopanning of drug-recognizing short peptides based on a quartz-crystal microbalance (QCM) biosensor, followed by bioinformatics analysis for quantitatively assessing the information obtained for the drug recognition and annotation of the drug-binding sites on proteins.

Strategia di biopanning e analisi bioinformatica ad alta produttività basata su biosensore per la convalida globale delle interazioni farmaco-proteina

Receptors and enzyme proteins are important biomolecules that act as binding targets for bioactive small molecules. Thus, the rapid and global validation ...

Bioingegneria

Development of Inhibitors of Protein-protein Interactions through REPLACE: Application to the Design and Development Non-ATP Competitive CDK Inhibitors

REPLACE is a unique strategy developed to more effectively target protein-protein interactions (PPIs). It aims to expand available drug target space by providing improved methodology for the identification of inhibitors for such binding sites and which represent the majority of potential drug targets. The main goal of this paper is to provide a methodological overview of the use and application of the REPLACE strategy which involves computational and synthetic chemistry approaches. REPLACE is exemplified through its application to the development of non-ATP competitive cyclin dependent kinases (CDK) inhibitors as anti-tumor therapeutics. CDKs are frequently deregulated in cancer and hence are considered as important targets for drug development. Inhibition of CDK2/cyclin A in S phase has been reported to promote selective apoptosis of cancer cells in a p53 independent manner through the E2F1 pathway. Targeting the protein-protein interaction at the cyclin binding groove (CBG) is an approach which will allow the specific inhibition of cell cycle over transcriptional CDKs. The CBG is recognized by a consensus sequence derived from CDK substrates and tumor suppressor proteins termed the cyclin binding motif (CBM). The CBM has previously been optimized to an octapeptide from p21Waf (HAKRRIF) and then further truncated to a pentapeptide retaining sufficient activity (RRLIF). Peptides in general are not cell permeable, are metabolically unstable and therefore the REPLACE (REplacement with Partial Ligand Alternatives through Computational Enrichment) strategy has been applied in order to generate more drug-like inhibitors. The strategy begins with the design of Fragment ligated inhibitory peptides (FLIPs) that selectively inhibit cell cycle CDK/cyclin complexes. FLIPs were generated by iteratively replacing residues of HAKRRLIF/RRLIF with fragment like small molecules (capping groups), starting from the N-terminus (Ncaps), followed by replacement on the C-terminus. These compounds are starting points for the generation of non-ATP competitive CDK inhibitors as anti-tumor therapeutics.

We describe implementation of the REPLACE strategy for targeting protein-protein interactions. REPLACE is an iterative strategy involving synthetic and computational approaches for the conversion of optimized peptidic inhibitors into drug like molecules.

Sviluppo di inibitori di interazioni proteina-proteina attraverso REPLACE: Applicazione alla progettazione e allo sviluppo non ATP inibitori CDK competitivo

REPLACE is a unique strategy developed to more effectively target protein-protein interactions (PPIs). It aims to expand available drug target space by ...

Biologia

Chemogenetic Regulation in Reprogrammed Stem Cell-derived Precursor Cells in Treating Neurodegenerative Diseases

The integration of designer receptors exclusively activated by designer drugs (DREADD) with stem cell-based therapies presents an advanced strategy for precise neuronal modulation. Here, we utilized CRISPR-engineered human reprogrammed stem cells expressing excitatory (hM3Dq) or inhibitory (hM4Di) DREADD receptors to evaluate the functional integration and modulation of transplanted dopaminergic precursors in a murine model of Parkinson&#39;s disease (PD). Key steps included generating non-fusion DREADD-expressing stem cell lines, differentiating them into midbrain dopaminergic precursors, and transplanting these cells into the striatum of 6-hydroxydopamine (6-OHDA)-lesioned mice. We conducted behavioral assessments and electrophysiological recordings to analyze the effects of the transplanted cells. Behavioral tests, such as the cylinder test, demonstrated significant modulation of motor function following clozapine-N-oxide (CNO) administration. Specifically, activation of hM4Di reduced contralateral forelimb movement, whereas activation of hM3Dq was associated with enhanced motor behavior. Electrophysiological recordings revealed distinct synaptic responses. hM4Di activation increased interevent intervals and decreased peak amplitudes of spontaneous excitatory postsynaptic currents (sEPSCs), whereas hM3Dq activation decreased interevent intervals and increased peak amplitudes, reflecting enhanced excitatory signaling. In summary, the integration of behavioral and electrophysiological assessments validates the precise functional incorporation of engineered chemically reprogrammed stem cells into host neural circuits.

Here, we describe a protocol for engineering chemically reprogrammed stem cells to achieve precise neuronal modulation by differentiating these cells into dopaminergic precursor cells, transplanting them into mouse models of Parkinson's disease, and evaluating behavioral and electrophysiological outcomes to confirm the successful integration and functional effectiveness of the transplanted cells.

Regolazione chemiogenetica nelle cellule precursori derivate da cellule staminali riprogrammate nel trattamento delle malattie neurodegenerative

The integration of designer receptors exclusively activated by designer drugs (DREADD) with stem cell-based therapies presents an advanced strategy for ...

Neuroscienze

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and the pharmaceutical industry.
The process begins with drug screening, which involves various assays to evaluate the pharmacological profile and activity of the drug at different levels, such as molecular, cellular, organ system, and whole animal levels. The candidate molecule undergoes extensive testing to determine its mechanism of action, selectivity, and potential toxic effects. Animal models of human diseases are used to select compounds for further development, especially in cases where preclinical models are well-established.
The candidate compound is screened for its activity on the target protein at the molecular level using techniques like receptor binding assays. Cell function studies determine whether the drug acts as an agonist, partial agonist, inverse agonist, or antagonist at relevant receptors. Whole animal studies assess the drug&#39;s effects on organ systems and disease models.
Lead compounds with the desired pharmacological activity and selectivity are identified during the screening and lead generation processes. These lead compounds serve as the basis for further chemical modification and optimization in the lead optimization phase. Lead optimization involves a range of tests and assays to increase the potency of the compound, optimize selectivity, and evaluate other characteristics, such as pharmacokinetic properties. Animal studies assess the compound&#39;s activity in vivo, potential adverse effects, genotoxicity, and oral availability.
Only a small percentage of drug discovery projects succeed in generating a drug candidate, and the lead optimization phase can be time-consuming and challenging. Many factors can hinder progress, including the inability to optimize lead compounds or the failure to produce desired effects in animal models. Successful drug candidates proceed to the next phase, preclinical development, before entering human clinical trials.

Scoperta di farmaci: panoramica

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for ...

Drug Repurposing Ipotesi Generation Con il "RE: Drugs sottili" Sistema

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