Digital Event Horizon
A new dataset is being developed to provide a comprehensive understanding of drug-target interactions, which could revolutionize the field of pharmacology and enable new approaches to drug discovery.
Pharmaceutical companies focus on single "target" proteins, which can be flawed as many drugs have multiple targets. The Pharmome Map is a comprehensive dataset aiming to understand how drugs interact with all possible target proteins in the human body. The dataset includes measurements of compound activity, potency, and cytotoxicity for each target protein and potential off-target effects. The dataset currently focuses on nuclear receptors, 7-transmembrane receptors, and protein kinases due to their therapeutic relevance and druggability. The Pharmome Map has the potential to revolutionize pharmacology by providing a comprehensive understanding of drug-target interactions. The dataset can be used for predicting activity patterns across targets, modeling biased signaling, and identifying potential off-target effects.
The pharmaceutical industry has long been plagued by a lack of understanding about the effects of drugs on the human body. Despite the fact that billions of prescriptions are written worldwide every year, we know relatively little about how these drugs interact with our cells and tissues. Pharmaceutical companies focus their efforts on making new drugs that are safe and effective, typically targeting a single "target" protein in the process.
However, this approach can be flawed, as many drugs have multiple targets and effects on the body that are not yet fully understood. To address this issue, researchers at EvE Bio are developing a comprehensive dataset known as the Pharmome Map. This dataset aims to provide a detailed understanding of how drugs interact with all possible target proteins in the human body.
The Pharmome Map is being developed using a two-phase quantitative screening process that involves high-throughput screening and profiling of thousands of compounds against thousands of targets. The dataset includes measurements of compound activity, potency, and cytotoxicity for each target protein, as well as data on potential off-target effects.
The dataset is currently focused on three classes of targets: nuclear receptors (NRs), 7-transmembrane receptors (7TMs), and protein kinases (PKs). These classes are selected because they are therapeutically relevant, druggable by small molecules, and addressable at scale using in vitro assays.
NRs directly regulate gene expression and control the long-term behavior of cells. They are activated by ligand binding and have evolved to bind a diverse set of small molecules, making them advantageous for drug targeting. The dataset includes measurements of NR activity in agonist and antagonist modes.
7TMs sense extracellular signals and translate them into intracellular responses, telling the cell what's happening around it. They are a large target class that has evolved to sense a diversity of molecules, making them exceptionally druggable. The dataset includes measurements of 7TM activity in agonist and antagonist modes, as well as data on potential off-target effects.
PKs are enzymes that catalyze phosphorylation, controlling many molecular "switches" within cells. They enable computational complexity inside cells via feedback loops, cascades, and signal integration. The dataset includes measurements of PK activity using biochemical competition-based ligand binding assays in a single mode (inhibition).
The Pharmome Map is the largest of its kind and is actively expanding with new data added every other month. The dataset is expected to include millions of compound-target combinations, providing a comprehensive understanding of drug-target interactions.
In 2026, the number of 7TM and PK targets in the dataset will increase approximately threefold, including the addition of G-protein and β-arrestin data for 7TMs. This will enable modeling of biased signaling via these two pathways, which is considered a key opportunity for improved drug design.
The Pharmome Map has the potential to revolutionize the field of pharmacology and enable new approaches to drug discovery. By providing a comprehensive understanding of drug-target interactions, researchers can better understand how drugs work and identify new targets for therapy.
In addition to its scientific value, the Pharmome Map also has significant practical applications. It could be used to predict activity patterns across targets for novel compounds, model biased signaling, and identify potential off-target effects. The dataset could also be used to develop models that link compound and concentration response characteristics with particular forms of interference, such as cytotoxicity or unwanted interactions.
Overall, the Pharmome Map is a significant breakthrough in the field of pharmacology and has the potential to transform our understanding of drug-target interactions. Its comprehensive nature and large scale make it an invaluable resource for researchers and clinicians alike.
Related Information:
https://www.digitaleventhorizon.com/articles/The-Pharmome-Map-A-Comprehensive-Dataset-for-Understanding-Drug-Target-Interactions-deh.shtml
https://huggingface.co/blog/hugging-science/eve-bio-mapping-the-pharmone-drug-interaction
https://evebio.org/
Published: Wed Dec 3 06:32:02 2025 by llama3.2 3B Q4_K_M
