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. Gene Sorgular başlatılması, İlaç veya Hastalık Şartları <ol><li> http://drug-repurposing.nationwidechildrens.org: aşağıdaki bağlantıdan: &quot;fine Uyuşturucu RE&quot; için ana erişin. ilaç (jenerik ilaç adı), hastalık (yeni hastalık belirtisi) ya da gen (resmi HGNC gen sembolü): Aşağıdaki üç kategoriden herhangi birinden arama çubuğuna bir sorgu terimini girerek başlayın. </li><li> Sadece &quot;İlaç Adı&quot;, &quot;Yeni Hastalığı Endikasyon&quot;, &quot;Gen Symbol&quot; veya &quot;Tümü&quot; kategorileri dahil arama çubuğu işlevi Filtre. arama çubuğu sorgusu girişleri için otomatik doldurma fonksiyonu içerir. </li><li> Bir anahtar kelime koymak ve &quot;Ara&quot; butonuna tıklayın. Sıralama aşağıdaki sütunların herhangi sonuçların tablosu: &quot;İlaç&quot;, &quot;Kayıtlı Endikasyon&quot;, &quot;P-değeri&quot;, &quot;P-Value Arındırılmış&quot;, &quot;Oran Oran&quot;, &quot;Çalışma&quot;, &quot;Yeni Endikasyon&quot;, &quot;İlaç Banka Endikasyon &quot;,&quot; Medline Abstracts içinde &quot;,&quot; Cli arasındanical Deneme Kayıt &quot;,&quot; Potansiyel &quot;,&quot; SNP &quot;,&quot; Gen &quot;veya&quot; eylem &quot;. </li><li> uyuşturucu bilgi özelliğini etkinleştirmek için gelişmiş arama seçeneğine gidin. Belirli bir ilaç için &quot;Bilgi&quot; sütunundaki simgesine tıklayın. listeleyen bir sayfa gözlemlemek tüm dernek, Hastalık adı, İlaç adı p değeri, Gen ayrıntıları (NCBI Gen bağlantısı) ve İlaç ayrıntıları (drugbank link) de dahil olmak üzere, ilgili bilgiler. </li></ol> Gelişmiş Seçenekler 2. Arama <ol><li> Sayfanın sağ tarafında bulunan &quot;Gelişmiş&quot; butonuna tıklayın ve İleriki sonuçları geliştirmek için çeşitli seçenekler sunulmaktadır. ilaç, dernek, hastalık, potansiyel, gen ve eylem: gelişmiş arama seçenekleri aşağıdaki değişiklikleri içerir. </li><li> İhracat sayfanın sağ tarafındaki &quot;Dışa Aktar&quot; butonuna tıklayarak tablolar ile sonuçlanır. gelişmiş arama penceresini aşağı katlayın için &quot;Basit&quot; butonuna tıklayın. &lt;/ Li&gt; <li> gelişmiş seçenek &quot;ilaç&quot; sekmesi altında, belirli bir ilaç gösterge ya da sonuçları filtrelemek için ek bir ilaç adı belirtin. </li><li> &quot;Dernek&quot; sekmesinin altında, anlamlılık düzeyi P değeri, FDR ile Düzeltilmiş P değeri, etki boyutu (Odds Oranı) ve / veya filtre sonuçları tipi (GWAS, PheWAS veya ikisi) inceleyin. </li><li> &quot;Hastalık&quot; sekmesinin altında, tahmin edilen yeni kullanım için belirli bir hastalık açıklamasını belirtin. </li><li> &quot;Potansiyel&quot; sekmesinin altında, aşağıdaki kriterlerden herhangi birine göre filtre sonuçları: (i) ilaç göstergesi drugbank veritabanında bulunan olup olmadığını, ilacın eş oluşum ve hastalık ile Medline özetleri (ii) numarası ( ilacın ortak oluşum ve hastalık ve (iv) Potansiyel repurposing ile ClinicalTrials.gov veritabanı girişlerinin iii) sayısı. NOT: (ii) Güçlü desteklenen ilişki zaten drugbank veritabanında var: Bilinen: (i) repurposing Potansiyel seçenek keşif yenilik açıklar: Her iki klinik çalışma kayıt defteri ve Medline özetleri bazı destek, (iii) Muhtemel: klinik çalışma kayıt defterinde veya Medline özetleri ve ya bazı destek (iv) Roman: klinik çalışma defterinde ne Medline özetleri hiçbir kanıt. </li><li> &quot;Gen&quot; sekmesi altında, bir SNP tanımlayıcı girin veya Gen Sembol belirli ilaç hedef genler tarafından sonuçları filtrelemek için. </li><li> &quot;Eylem&quot; sekmesinin altında, agonist, antagonist diğer bilinmeyen veya tüm (: drugbank veritabanı kaynağı dahil) ilaç hedef (ler), karşı ilaç eylem türünü belirtin. </li></ol>

<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.

Yüksek verimli ilaç ve kurşun bileşik taraması da dahil olmak üzere geleneksel ilaç keşfi yaklaşımları ile ilişkili masraflı ve verimsiz süreçler, hastalar 1,2 tedavilerin araştırmalar keşifler çeviri gecikmeler katkıda bulunmaktadır. 1 milyar dolar ve 15-20 yıllık bir ortalama başucunda 3 tezgah yeni bir ilaç getirmek için gereklidir. Dahası, ilaçların% 52 faz 1 klinik çalışmalarda gelişimi sırasında başarısız ve faz 2 girin bileşiklerin sadece% 25&#39;i tam faz 3 klinik çalışmalarda 4 içine geçin. ilaç repurposing veya ilaç yeniden konumlandırma hedefi başarısız ilaçları yenilemek ve / veya daha hızlı hastalara yeni tedaviler sunmak ve daha yüksek bir başarı oranı ile amacıyla onaylanan ilaçlar için yeni endikasyonlar bulmaktır. İlaç yeniden amaç 3-12 yıl 5 hastalarda kullanılmak üzere ilaçların kullanılabilir hale getirmek için zaman çizelgesini azaltabilir. İlaç repurposing için önemli tıbbi uygulamalar şunlardır: fakir Prognos ile hastalıklarıve düşük sağkalım oranları, ilaca dirençli hastalıklar, yeterince hastalık araştırma alanları ve yoksul ve yeterli hizmet alamayan hasta popülasyonları. Bilgisayar destekli ilaç yeniden amaç tasarımı ve bir ilaç adayı 6 için yeni endikasyonlar için hipotezler üretebilir otomatik iş akışları doğrulama süreci olarak tanımlanır. Mevcut hesaplama ilaç repurposing yöntemleri, hedef bazlı, bilgiye dayalı, imza tabanlı, ağ tabanlı kategorize ve hedefli bir mekanizma bazlı ve gen, hastalık veya ilaç perspektiflerden yönlendirilebilir edilmiştir. Ayrıca, hesaplamalı yaklaşımlar daha repurposed ilaç adayları 7 proof-of-concept doğrulama deneyleri ve küçük ölçekli klinik çalışmalar hızlandırabilir. Biz daha önce &quot;RE: İnce İlaçlar&quot; bildirdin, İlaç-Gen-Hastalık ilişkileri 8 geçişli teorisine dayalı ilaç repurposing hipotez üretimi için bir serbestçe kullanılabilir, etkileşimli web tabanlı bir araç. genel gBu yöntemin oal sistematik klinik, sanayi ve düzenleyici topluluklar da dahil olmak üzere çeşitli topluluklar, kullanıcılar için repurposing ilaç sağlamak için ilaç, genetik ve klinik verilerin farklı türlerini entegre etmektir. Bu sistem için temel yöntemler, daha önce genom boyu bağlantı çalışması (GWAS) ve araştırmayı 9,10 repurposing ilaç phenome çapında dernek çalışması (PheWAS) veri kullanımı için rapor edilmiştir. Veri bu tür yeni bir kombinasyonu diğer hedef bazlı yöntemler 6,11 bizim webtool ayırır. RE: İnce İlaçlar sistemi şu anda 916 ilaç, 567 gen ve 1770 hastalıkları kapsayan 60.911 ilaç repurposing hipotez içeriyor. webtool interaktif ilaç yeniden amaç hipotezler arama ve çeşitli kriterleri kullanarak bunları öncelik araştırmacılar için kullanıcı dostu bir arayüz sağlar. Örneğin, kullanıcılar biyomedikal literatürde destek ve klinik çalışmalarda databa ilaç yeniden amaç hipotez süzebilirsinizse, önemli p-değerleri, dernek odds oranları veya belirli endikasyonlar tarafından. Bu sistem için tek şart Internet erişimi.

<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.

Bu örnekte, gen &quot;IL2RB&quot; bir gen temelli sorgu olarak girildi ve otomatik otomatik doldurma fonksiyonu (Şekil 1) gibi tanındı. Şekil 2&#39;de gösterildiği gibi, IL2RB geni için on iki ilacın repurposing hipotez, döndürülür. Bu durumda belirli bir ilaç yeniden amaç hipotezi, &quot;daklizumab&quot; Ayrıntılı bilgi sayfası, &quot;Bilgi&quot; sütununda (Şekil 3) sağlanmaktadır. İlaç sekme &quot;daklizumab&quot; ilaç karşılık gelen tüm sonuçlar oldu Şekil 4&#39;te gösterildiği gibi, sonuçlar, filtre edilmiştir. Şekil 5 &quot;nakli&quot; hastalık dönemi (: drugbank veritabanı kaynağı) için bilinen bir endikasyon yalnızca bu ilaçları gösterir. Dernek sekmesi pr oran oranı olarak tanımlanan istatistiksel anlamlılık (p-değeri) ve genetik etkinin büyüklüğü (odds oranı) tarafından SNP-fenotip ilişkileri filtre kullanıcıyı tanırSNP alleli olmayan bireylerde hastalığın varlığı oran üzerinden belirli bir genotip (SNP alel) olan kişilerde hastalığın esence. Şekil 6 0.000001&#39;den içinde 0.05 P-Değeri aralığında dernek sekmesinin altında filtre sonuçlarını gösterir. Şekil 7 biz çalışmamızda bulduğumuz yeni endikasyonlar dayanan &quot;astım&quot; için özel ilaç yeniden amaç hipotezler gösterir. Potansiyel sekmesi altında Şekil 8 sonuçları ilaç ve hastalık terimleri eş oluşumunu içeren 5 Medline özetlerin asgari sayısına göre filtrelemek için. Bu örnekte, gen sekmesi altında tüm ilaçlar sonuçları özgün sorgu dönem (Şekil 9) karşılık gelen, &quot;IL2RB&quot; gen için hedeflenir. Son olarak, &quot;eylem&quot; sekmesinin altında filtre Şekil 10 sonuç IL2RB geni üzerinde agonistler olarak hareket tüm ilaçları dönün. <img alt="Şekil 1"src = &quot;/ files / ftp_upload / 54948 / 54948fig1.jpg&quot; /&gt; Şekil 1: RE: ince İlaçlar interaktif pano anasayfa. Kullanıcılar bir uyuşturucu adı, yeni bir hastalık göstergesi ya da gen sembolü girerek sorgu başlayabilir. Bağlantıları da uyuşturucu yeniden amaç hipotezler üretme için yöntemler açıklayan GWAS ve PheWAS referans kağıtları verilmektedir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig1large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <img alt="şekil 2" src="/files/ftp_upload/54948/54948fig2.jpg" /> Şekil 2: Sorgu girişleri için otomatik doldurma işlevi. Bir örnek olarak, gen sorgu terimi &quot;IL2RB&quot; otomatik bir gen terim olarak tanındı. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig2large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <pkeep-together.within sayfa = &quot;1&quot;&gt;: fo class = &quot;jove_content&quot; <img alt="Şekil 3," src="/files/ftp_upload/54948/54948fig3.jpg" /> Şekil 3: gen temelli sorgusu (örneğin, IL2RB) üretilen İlaç repurposing sonuçları tablosu. IL2RB geni için Oniki ilaç repurposing hipotezler üretilmektedir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig3large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <img alt="Şekil 4," src="/files/ftp_upload/54948/54948fig4.jpg" /> Şekil 4: sonuçları sayfasında tek tek ilaçlar için bilgi sayfası. &quot;Bilgi&quot; sütunundan simgesine tıklayarak uyuşturucu daklizumab için ayrıntılı bilgi gösterir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig4large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> Şekil 5: ilaç sekmesi altında Gelişmiş arama seçeneği belirli bir ilaca göre filtre uygulamak için. Bu örnekte, üç sonuç uyuşturucu daklizumab için gösterilmiştir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig5large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <img alt="Şekil 6," src="/files/ftp_upload/54948/54948fig6.jpg" /> Şekil 6: İlaç sekmesi altında Gelişmiş arama seçeneği drugbank veritabanından spesifik bir hastalık göstergesi göre filtre uygulamak için. Hastalık dönem &quot;nakli&quot; için bilinen bir endikasyonu tüm ilaçlar gösterilir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig6large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> Şekil 7: Dernek sekmesi altında Gelişmiş arama seçeneği anlamlılık düzeyine göre filtrelemek için. Bu durumda, sekiz sonuç olan dernek anlamlılık düzeyi 0.05 0.000001&#39;den P-Değer aralığı içinde düşer sağlanmaktadır. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig7large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <img alt="Şekil 8," src="/files/ftp_upload/54948/54948fig8.jpg" /> Şekil 8: Hastalık sekmesi altında Gelişmiş arama seçeneği bu çalışmada çıkarılan spesifik bir hastalık göstergesi göre filtre uygulamak için. Bu örnekte, dört sonuçları yeni kullanımı hastalığı gösterge olarak astım için gösterilmiştir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig8large.jpg" target="_blank">Daha büyük bir Versi görmek için buraya tıklayınız</a>bu rakamın üzerinde. <img alt="Şekil 9," src="/files/ftp_upload/54948/54948fig9.jpg" /> Şekil 9: Potansiyel sekmesi altında Gelişmiş arama seçeneği Medline özetler ilaç ve hastalık açısından bir co-oluşum göre filtre uygulamak için. Bu örnekte, dört sonuçları ilaç ve hastalık terimleri eş oluşumunu içeren 5 Medline özetlerin az sayıda tarafından desteklenen gösterilir. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig9large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</a> <img alt="Şekil 10," src="/files/ftp_upload/54948/54948fig10.jpg" /> Şekil 10: gen sekmesi altında Gelişmiş arama seçeneği tüm sonuçlar, orijinal sorgu için kullanılan IL2RB genine karşılık belirli bir gen sembolü, göre filtre uygulamak için. Bu örnekte, tüm ilaçlar sonuçlarıGen sekmesi altında özgün sorgu terimine karşılık gelen, &quot;IL2RB&quot; gen için hedeflenir. Eylem sekmesinin altında Gelişmiş arama seçeneği agonist ilaçların yalnızca göre filtre uygulamak için. Bu örnekte, altı sonuç IL2RB geni agonistler olarak hareket eden tüm ilaçlar için döndürülür. <a href="http://ecsource.jove.com/files/ftp_upload/54948/54948fig10large.jpg" target="_blank">Bu rakamın büyük halini görmek için lütfen buraya tıklayınız.</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.

&quot;RE: İnce ilaçlar kullanılması&quot; İlaç repurposing Hipotez Üretim Sistemi

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 ...

drug-repurposing-hypothesis-generation-using-the-refine-drugs-system

Research

JoVE Journal

Medicine

9.2K Görüntüleme.  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.

Verimli Refolding ve arıtma Chemoreceptor Ligand bağlayıcı etki için yöntemi

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

Biyokimya

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.

Kolaylaştırılması İlaç Keşfi: Zebra balığı An Otomatik Yüksek içeriği Enflamasyon Assay

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

İmmünoloji ve Enfeksiyon

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.

İnsan kullanarak Pluripotent kök hücre kaynaklı hepatosit benzeri hücreler indüklenen ilaç bulma için

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

Gelişim Biyolojisi

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.

Minimum numune ancak maksimum otomasyon modunda NMR tabanlı parça taraması

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.

Parça Bazlı Kurşun Keşfinde Tarama için Nano-Diferansiyel Tarama Florüretrisi

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.

Uygulanması<em&gt; İn Vitro</em&gt; İlaç Direnci Tahliller: Klinik İlgili Direnç Mekanizmaları ortaya çıkararak yönelik Potansiyeli maksimize

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

Tıp

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.

İlaç-protein Etkileşimlerinin Küresel Doğrulanması için Biyosensör Tabanlı Yüksek Verimli Biyopanning ve Biyoinformatik Analiz Stratejisi

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

Biyomühendislik

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.

Aracılığıyla DEĞİŞTİR Protein-protein etkileşimleri İnhibitörlerinin Geliştirilmesi: Tasarım ve Geliştirme Olmayan ATP Rekabetçi CDK inhibitörleri Uygulama

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

Biyoloji

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.

Nörodejeneratif Hastalıkların Tedavisinde Yeniden Programlanmış Kök Hücre Kaynaklı Öncü Hücrelerde Kemogenetik Düzenleme

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

Nörobilim

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.

İlaç Keşfi: Genel Bakış

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

"RE: İnce ilaçlar kullanılması" İlaç repurposing Hipotez Üretim Sistemi

Özet

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