scholarly journals Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets

Biomedicines ◽  
2016 ◽  
Vol 4 (4) ◽  
pp. 27 ◽  
Author(s):  
Suhas Vasaikar ◽  
Pooja Bhatia ◽  
Partap Bhatia ◽  
Koon Chu Yaiw
2017 ◽  
Vol 37 (4) ◽  
Author(s):  
Sarah K. Wooller ◽  
Graeme Benstead-Hume ◽  
Xiangrong Chen ◽  
Yusuf Ali ◽  
Frances M.G. Pearl

Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse ‘big data’ that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications.


2018 ◽  
Author(s):  
Deepali Jhamb ◽  
Michal Magid-Slav ◽  
Mark R. Hurle ◽  
Pankaj Agarwal

AbstractGenome-wide association studies (GWAS) have made considerable progress and there is emerging evidence that genetics-based targets can lead to 28% more launched drugs. However, translating the results of GWAS for drug discovery remains challenging. We analyzed 1,589 GWAS across 1,456 protein interaction pathways to translate these often, imprecise genetic loci into therapeutic hypotheses for 182 diseases. We validate these pathway-based genetic targets by testing if current drug targets are enriched in the pathway space of the same indication. Remarkably, 30% of diseases have significantly more targets in these pathways than expected by chance; the comparable number for GWAS alone (without using pathway analysis) is zero. Although pathway analysis is routine for GWAS, this study shows that the routine analysis can often enrich for drug targets, by performing a systematic global analysis to translate genetic findings into therapeutic hypotheses for new drug discovery and repositioning opportunities for current drugs.


2020 ◽  
Vol 25 (6) ◽  
pp. 634-645 ◽  
Author(s):  
Mei Ding ◽  
Christian Tyrchan ◽  
Elisabeth Bäck ◽  
Jörgen Östling ◽  
Steffen Schubert ◽  
...  

Human rhinovirus (RV) is the most common cause of acute upper respiratory tract infections and has recently been shown to play a significant role in exacerbations of asthma and chronic obstructive pulmonary disease (COPD). There is a significant unmet medical need for agents for the prevention and/or treatment of exacerbations triggered by human RV infection. Phenotypic drug discovery programs using different perturbation modalities, for example, siRNA, small-molecule compounds, and CRISPR, hold significant value for identifying novel drug targets. We have previously reported the identification of lanosterol synthase as a novel regulator of RV2 replication through a phenotypic screen of a library of siRNAs against druggable genes in normal human bronchial epithelial (NHBE) cells. Here, we describe a follow-up phenotypic screen of small-molecule compounds that are annotated to be pharmacological regulators of target genes that were identified to significantly affect RV2 replication in the siRNA primary screen of 10,500 druggable genes. Two hundred seventy small-molecule compounds selected for interacting with 122 target gene hits were screened in the primary RV2 assay in NHBE cells by quantifying viral replication via in situ hybridization followed by secondary quantitative PCR-based assays for RV2, RV14, and RV16. The described follow-up phenotypic screening allowed us to identify Fms-related tyrosine kinase 4 (FLT4) as a novel target regulating RV replication. We demonstrate that a combination of siRNA and small-molecule compound screening models is a useful phenotypic drug discovery approach for the identification of novel drug targets.


2020 ◽  
Vol 19 (5) ◽  
pp. 300-300 ◽  
Author(s):  
Sorin Avram ◽  
Liliana Halip ◽  
Ramona Curpan ◽  
Tudor I. Oprea

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Marie O. Pohl ◽  
Jessica von Recum-Knepper ◽  
Ariel Rodriguez-Frandsen ◽  
Caroline Lanz ◽  
Emilio Yángüez ◽  
...  

Author(s):  
Eamonn Morrison ◽  
Patty Wai ◽  
Andri Leonidou ◽  
Philip Bland ◽  
Saira Khalique ◽  
...  

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Christos Dimitrakopoulos ◽  
Sravanth Kumar Hindupur ◽  
Marco Colombi ◽  
Dritan Liko ◽  
Charlotte K. Y. Ng ◽  
...  

Abstract Background Genetic aberrations in hepatocellular carcinoma (HCC) are well known, but the functional consequences of such aberrations remain poorly understood. Results Here, we explored the effect of defined genetic changes on the transcriptome, proteome and phosphoproteome in twelve tumors from an mTOR-driven hepatocellular carcinoma mouse model. Using Network-based Integration of multi-omiCS data (NetICS), we detected 74 ‘mediators’ that relay via molecular interactions the effects of genetic and miRNA expression changes. The detected mediators account for the effects of oncogenic mTOR signaling on the transcriptome, proteome and phosphoproteome. We confirmed the dysregulation of the mediators YAP1, GRB2, SIRT1, HDAC4 and LIS1 in human HCC. Conclusions This study suggests that targeting pathways such as YAP1 or GRB2 signaling and pathways regulating global histone acetylation could be beneficial in treating HCC with hyperactive mTOR signaling.


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