Advancing Drug Discovery Through AI-Powered Solutions

Kinase Foundation ModelNew!

One model. 478 kinases. Sequence in, ranking out. Trained on the Kinase Knowledgebase, it reads the kinase’s amino-acid sequence itself — no structure, no docking, no binding-site definition — so a single model covers the whole panel instead of one model per target.

Give it a kinase sequence and two compounds and it says which binds more tightly: 78.5% correct on more than 3 million held-out compound pairs, and 90% when the two compounds differ by more than tenfold in potency. Accuracy varies by target, so it is reported kinase by kinase.

Kinase Knowledgebase (KKB)

Currently the Kinase Knowledgebase Q2 2026 Release includes the following data:

• Journal articles and patents: 10,326
• Number of Biological Activity Data Points: 3,336,903
• Number of unique kinase molecules with annotated assay data: 509,691
• Number of all unique kinase molecules from patents and articles (with or without bio-activity data): 854,437
• Number of unique kinase targets with assay data: 579
• Number of annotated assay protocols: 105,916
• Machine-learning models built from this release’s SAR: activity classifiers across 392 kinase targets, median ROC-AUC 0.91 (0.95 for well-studied kinases) – view model performance report

To show what this depth of curation supports, we build machine-learning models from the KKB SAR and report how they perform: an activity classifier for each of 392 kinase targets and a potency regressor for 319 of them. The panel at left summarises classifier accuracy — ROC curves grouped by how much data each kinase has, the spread of ROC-AUC, and how accuracy rises with the depth of measured chemistry.

Accuracy is highest for compounds chemically related to what a target already has in KKB and declines for novel scaffolds, so every prediction is reported with a similarity score against the model’s own training set. Performance is also measured against published data absent from the knowledgebase.

Oncology Knowledgebase (OKB)

Currently the Oncology Knowledgebase Q2 2023 Release includes the following data:

• Journal articles and patents: 977
• Number of Biological Activity Data Points: 146,206
• Number of molecules from patents and articles: 66,198
• Number of unique oncology targets with assay data: 1,158
• Number of annotated assay protocols: 5,614
• Number of disease models: 137

Dataset Overlap AnalysisNew

How much of a dataset do you already have? Our toolkit answers that for any two SAR datasets — any target family — without either side revealing a structure. Each party encodes its own data locally into irreversible SHA-256 fingerprints; only fingerprints are compared, and only the overlap figure is shared.

Target Informatics Platform (TIP™)

The Target Informatics Platform's content grows weekly with more than 200K high resolution protein structures, ~1.2M annotated co-complex sites, and an additional ~875K predicted sites. TIP contains more than 710K protein chains representing every major drug target family.