OKB

The Oncology Knowledgebase (OKB) is a structure-activity relationship (SAR) database developed by Eidogen-Sertanty, covering a broad range of targets relevant to oncology drug discovery. It is designed for use by computational scientists and drug discovery teams working across cancer indications including colon cancer, esophageal cancer, glioma, head and neck cancer, kidney cancer, leukemia, liver cancer, lung cancer, lymphoma, melanoma, ovarian cancer, prostate cancer, skin cancer, and stomach cancer.

The OKB contains enzymatic and cell-based biological activity data spanning multiple gene families documented in the oncological literature. These include epigenetic targets, orphan nuclear receptors, transcription factors, G protein-coupled receptors (GPCRs), matrix metalloproteinases (MMPs), proteasomes, farnesyltransferases, aromatases, and phosphodiesterases. Initial releases focus on high-priority targets with crystallographic precedence, such as acyl and methyl transferases (HDACs, HATs, HMKT), enabling integration with Eidogen-Sertanty's TIP platform. The OKB complements the company's Kinase Knowledgebase (KKB).

Database Content (Q2 2023 Release)

• Journal articles and patents: 977
• Biological activity data points: 146,206
• Molecules from patents and articles: 66,198
• Unique oncology targets with assay data: 1,158
• Annotated assay protocols: 5,614
• Disease models: 137

Data Quality and Classification

All SAR data in the OKB undergoes rigorous quality control. Every data point is associated with detailed bioassay protocols and is classified according to the following attributes:

• Standardized gene name
• Binding mode
• Assay type
• Additional in vitro data, including cellular potency and cell line information
• Efficacy data in appropriate animal models

Applications for Computational Scientists

• Provides high-quality training sets for building predictive QSAR models
• In vitro enzyme activity data, particularly IC50 values, supports development of ePotency and eSelectivity models
• Cell-based activity and toxicity data supports development of eADME and eTox models
• Supports substructure, exact structure, and similar structure searching within the database

Data Access and Integration

• Designed for use by all scientists on a drug discovery team, including those without specialist computational training
• Available in multiple data formats for direct access and integration into in-house databases
• Licensing terms and product demonstrations are available on request