Browsing by Subject "KINASE INHIBITORS"

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  • Ravikumar, Balaguru; Timonen, Sanna; Alam, Zaid; Parri, Elina; Wennerberg, Krister; Aittokallio, Tero (2019)
    Owing to the intrinsic polypharmacological nature of most small-molecule kinase inhibitors, there is a need for computational models that enable systematic exploration of the chemogenomic landscape underlying druggable kinome toward more efficient kinome-profiling strategies. We implemented Virtual-KinomeProfiler, an efficient computational platform that captures distinct representations of chemical similarity space of the druggable kinome for various drug discovery endeavors. By using the computational platform, we profiled approximately 37 million compound-kinase pairs and made predictions for 151,708 compounds in terms of their repositioning and lead molecule potential, against 248 kinases simultaneously. Experimental testing with biochemical assays validated 51 of the predicted interactions, identifying 19 small-molecule inhibitors of EGFR, HCK, FLT1, and MSK1 protein kinases. The prediction model led to a 1.5-fold increase in precision and 2.8-fold decrease in false-discovery rate, when compared with traditional single-dose biochemical screening, which demonstrates its potential to drastically expedite the kinome-specific drug discovery process.
  • Louhimo, Riku i; Laakso, Marko; Belitskin, Denis; Klefstrom, Juha; Lehtonen, Rainer; Hautaniemi, Sampsa (2016)
    Background: Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer therapy are selected based on molecular alterations. The selection of a precision therapy benefiting most patients is challenging but can be enhanced with integration of multiple types of molecular data. Data integration approaches for drug prioritization have successfully integrated diverse molecular data but do not take full advantage of existing data and literature. Results: We have built a knowledge-base which connects data from public databases with molecular results from over 2200 tumors, signaling pathways and drug-target databases. Moreover, we have developed a data mining algorithm to effectively utilize this heterogeneous knowledge-base. Our algorithm is designed to facilitate retargeting of existing drugs by stratifying samples and prioritizing drug targets. We analyzed 797 primary tumors from The Cancer Genome Atlas breast and ovarian cancer cohorts using our framework. FGFR, CDK and HER2 inhibitors were prioritized in breast and ovarian data sets. Estrogen receptor positive breast tumors showed potential sensitivity to targeted inhibitors of FGFR due to activation of FGFR3. Conclusions: Our results suggest that computational sample stratification selects potentially sensitive samples for targeted therapies and can aid in precision medicine drug repositioning. Source code is available from
  • Liu, Yixin; Ribeiro, Orquidea De Castro; Robinson, James; Goldman, Adrian (2020)
    The receptor tyrosine kinase RET is essential in a variety of cellular processes. RET gain-of-function is strongly associated with several cancers, notably multiple endocrine neoplasia type 2A (MEN 2A), while RET loss-of-function causes Hirschsprung's disease and Parkinson's disease. To investigate the activation mechanism of RET as well as to enable drug development, over-expressed recombinant protein is needed for in vitro functional and structural studies. By comparing insect and mammalian cells expression of the RET extracellular domain (RETECD), we showed that the expression yields of RETECD using both systems were comparable, but mammalian cells produced monomeric functional RETECD, whereas RETECD expressed in insect cells was non-functional and multimeric. This was most likely due to incorrect disulfide formation. By fusing an Fc tag to the C-terminus of RETECD, we were able to produce, in HEK293T cells, dimeric oncogenic RETECD (C634R) for the first time. The protein remained dimeric even after cleavage of the tag via the cysteine disulfide, as in full-length RET in the context of MEN 2A and related pathologies. Our work thus provides valuable tools for functional and structural studies of the RET signaling system and its oncogenic activation mechanisms. (C) 2020 Published by Elsevier B.V.