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DTSTART;TZID=Europe/Stockholm:20230927T100000
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UID:155411-1695808800-1695812400@www.scilifelab.se
SUMMARY:Blending Chemistry and Biology to Enable Systems Pharmacology
DESCRIPTION:Patrick Aloy\, Prof.\, Institute for Research in Biomedicine (IRB Barcelona) \n\n\n\n \n\n\n\nOrganizers \n\n\n\nCBCS-KI and PhenoTarget Research Community Program \n\n\n\nJoin the seminar on Zoomhttps://ki-se.zoom.us/j/64473979770 \n\n\n\nAbstract \n\n\n\nBig Data analytical techniques and AI have the potential to transform drug discovery\, as they are reshaping other areas of science and technology\, but we need to blend biology and chemistry in a format that is amenable for modern machine learning. In this talk\, I will present the Chemical Checker (CC)\, a resource that provides processed\, harmonized and integrated bioactivity data on small molecules. The CC divides data into five levels of increasing complexity\, ranging from the chemical properties of compounds to their clinical outcomes. In between\, it considers targets\, off-targets\, perturbed biological networks and several cell-based assays such as gene expression\, growth inhibition and morphological profiles. I will also present the Bioteque\, a resource of unprecedented size and scope that contains pre-calculated biomedical embeddings around 11 biological entities (e.g. genes\, cells\, tissues\, disease\, etc)\, derived from a gigantic knowledge graph\, so that each entity can be described considering different contexts (e.g. interactions\, expression\, etc). With small molecule and biological bioactivity descriptors in hand\, we now face a new scenario for chemical and biological entities where they both are translated into a common numerical format. In this computational framework\, complex connections between entities can be unveiled by means of simple arithmetic operations. Indeed\, we demonstrate and experimentally validate that these descriptors can be used to reverse and mimic biological signatures of disease models and genetic perturbations in vitro and in vivo\, options that are otherwise impossible using chemical information alone.ReferencesDuran-Frigola et al. Extending the small molecule similarity principle to all levels of biology with the Chemical Checker. 2020. Nat Biotechnol. 38: 1087-1096. \n\n\n\nBertoni et al. Bioactivity descriptors for uncharacterized chemical compounds. 2021. Nat Commun. 12: 3932. \n\n\n\nPauls et al. Identification and drug-induced reversion of molecular signatures of Alzheimer’s disease onset and progression in AppNL-G-F\, AppNL-F\, and 3xTg-AD mouse models. 2021. Genome Med. 13:168. \n\n\n\nFernández-Torras et al. Connecting chemistry and biology through molecular descriptors. 2022. Curr Opin Chem Biol\, 66: 102090. \n\n\n\nFernández-Torras et al. Integrating and formatting biomedical data in the Bioteque\, a comprehensive repository of pre-calculated knowledge graph embeddings. 2022. Nat Commun. 13: 5304.
URL:https://www.scilifelab.se/event/blending-chemistry-and-biology-to-enable-systems-pharmacology/
LOCATION:Gamma 2 Lunchroom\, SciLifeLab\, Tomtebodavägen 23\, Solna\, Sweden
CATEGORIES:Event
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