# BindingDB: An Open Knowledgebase of Protein-Small Molecule Interactions

> **NIH NIH R24** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2023 · $603,560

## Abstract

Small, organic molecules that bind specific proteins represent one of the most effective ways
that physicians have to treat diseases and that researchers can use to probe living systems.
Such small molecules, also known as ligands, can act in many ways, such as by blocking a
protein from working, by activating a protein, or by causing the protein to be broken down by
normal cellular processes. In fact, most medications are ligands, and researchers in
universities, government labs, and pharmaceutical companies, are constantly at work seeking
new ones as drugs and biological probes. These ongoing efforts generate a continuous flow of
information about what small molecules bind what proteins, and how tightly.
This information is useful not only within the specific project that generated it, but also for many
other applications, such as helping researchers identify probe molecules to help with their
research, serving as benchmarks for computational chemists creating software designed to
predict ligand-protein binding, and training and testing machine-learning tools for drug design.
However, scientists generating this information typically release it in scientific articles or patents,
where it cannot easily be found or accessed by other researchers.
The core purpose of this project is to further develop the BindingDB Knowledgebase,
dramatically expanding the availability of protein-ligand binding information and connecting this
information to other areas of knowledge in order to make it as broadly useful as possible. This
will be accomplished by using a combination of automated and human methods to carry out
fast, accurate extraction of large volumes of data from scientific articles and patents. These data
will be rendered in machine readable format, linked with related data, such as information on
protein structure and function, and made publicly available in open source format via the
searchable BindingDB website, which also allows data to be downloaded in quantity for offline
use.
The information in BindingDB will be managed according to high community standards for
findability, accessibility, interoperability, and reusability (FAIR), and the project will achieve the
high CoreTrustSeal standards and certification for reliability and long-term preservation. In
addition, steps will be taken to maximize usability and integration of this information, such as by
making it available as a public dataset in emerging cloud resources and creating links from on-
line journal articles and patents to the data extracted from them in BindingDB.

## Key facts

- **NIH application ID:** 10706457
- **Project number:** 5R24GM144232-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** MICHAEL K. GILSON
- **Activity code:** R24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $603,560
- **Award type:** 5
- **Project period:** 2022-09-20 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10706457

## Citation

> US National Institutes of Health, RePORTER application 10706457, BindingDB: An Open Knowledgebase of Protein-Small Molecule Interactions (5R24GM144232-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10706457. Licensed CC0.

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