A Translator Knowledge Provider for Systems Chemical Biology

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Chemical biology and systems biology operate at different scales of molecular or cellular organization, requiring translation between the disciplines (e.g., terminology, existing evidence, new findings) to allow each to inform the other (1, 2). We propose a Biomedical Data Translator Knowledge Provider for Systems Chemical Biology to address this need. Centrally, the promise of systems chemical biology (SCB) is discovering novel therapeutics and re-purposing opportunities, avoiding toxicity and other side effects, and understanding how small molecules function (i.e., mechanism-of-action studies). Many evidence types used to solve such problems can also be used to understand functions of alterations at similar molecular scales, such as post-translational modification and protein-coding genetic variants. Currently, researchers in the field face major data access and interpretation challenges. For example, to support mechanism-of-action (MoA) studies, many experimental methods produce relevant data (gene-expression, protein-protein interactions, diverse bioactivities against pure proteins and cells, etc.) that are too numerous and heterogeneous to query for most researchers. Many web-based tools exist to share such data, but they are scattered, not always easy to find, and generally lack any communication between each other. As the field matures and increasingly embraces high-throughput experiments, these problems will only get worse (3). Our proposed SCB Knowledge Provider will mitigate these challenges by: • integrating and reconciling core molecular data (structure, name, annotated target) from multiple existing resources; • integrating and analyzing biological activity data for small molecules across multiple biological scales (binding, cellular activity, disease indication) (4); and • providing context for activities of small molecules and their targets informed by systems biology (complexes, pathways, processes). Our proposed SCB Knowledge Provider will enable answering questions such as: • what is the mechanism of action of a small molecule identified from a phenotypic screen? • which compounds are available to modulate my target of interest, and which other candidate targets might influence the activity of my target in a particular cellular context? • given my interest in a disease process or pathway, which candidate targets should I consider in relevant models, and which compounds are known to modulate those targets? We anticipate addressing gaps in data by scouting for inclusion additional sources of small-molecule bioactivity and contextual information about protein target function (see Data Milestones). We will implement existing and develop new methods to surface inconsistencies and prioritize returned results (see Methods Milestones). Finally, we propose an Advisory Committee to help prioritize content most relevant to researchers, overcome development obstacles, and keep abreast of emerging data and methods (see Outreach Milestones). We have core expertise needed to realize this SCB vision via 15+ years of experience with small-molecule bioactivity databases and portals (5-7), plus expertise in phenotypic screening, small-molecule profiling, and MoA studies (8-10), which demand integrated understanding of diverse data for hypothesis-driven science. We also made key contributions to Translator feasibility, including a workflow-centric view of data exploration by subject-matter experts, identifying and providing key datasets and methods for production of TIDBITS, and prototyping set-based (e.g., gene-list) analyses in workflows. These experiences ideally position us to realize a Systems Chemical Biology Knowledge Provider for Translator.