Xeureka and UBE Achieve Lead Identification Milestone in Joint Research
Xeureka Inc. and UBE Corporation have reached the lead identification milestone in their joint research on small-molecule drug discovery for cancer. Leveraging Xeureka's high-precision computational drug discovery technology, they successfully identified lead compounds efficiently in just five months.
📋 Article Processing Timeline
- 📰 Published: May 21, 2026 at 22:00
- 🔍 Collected: May 21, 2026 at 13:31
- 🤖 AI Analyzed: May 21, 2026 at 13:57 (26 min after Collected)
Xeureka Inc. (Minato-ku, Tokyo; President: Taisei Nagae; hereafter "Xeureka") and UBE Corporation (Minato-ku, Tokyo; President: Yuki Nishida; hereafter "UBE") announced today that they have reached the lead identification milestone stipulated in their joint research agreement on small-molecule drug discovery for cancer, which commenced in December 2025.
In this collaboration, the companies have been designing novel small-molecule compounds targeting a protein identified by UBE as promising for cancer therapy. They have utilized advanced computational drug discovery and AI technologies, including "Xeureka FEP," a Free Energy Perturbation*1 program developed by Xeureka, and the molecular generation tool "XE-Generator*2."
From the compound groups designed by the two companies, multiple compounds meeting the pre-agreed criteria for lead identification were discovered, resulting in the achievement of this milestone in just about five months since the start of the research.
This achievement demonstrates that Xeureka's computational drug discovery technology functions effectively in actual drug discovery projects and confirms the utility of a drug discovery approach that integrates AI with computational science.
With the achievement of this milestone, Xeureka will receive the prescribed milestone fee from UBE based on the joint research agreement.
At UBE, compounds were previously synthesized and screened to verify their efficacy. By utilizing computational drug discovery technology, it has now become possible to predict the efficacy of compounds in advance, allowing for the efficient identification of lead compounds with a smaller number of synthesized compounds. This result is expected to contribute to a significant improvement in the efficiency of drug discovery research and bring major innovation to UBE’s drug discovery process. UBE will continue to actively engage in the application of computational technologies to create further innovation.
Both companies will continue this joint research, aiming to create new drug candidate compounds by proceeding with the optimization of the lead compounds.
*1 Free Energy Perturbation: A method based on statistical mechanics to calculate changes in free energy associated with the binding of a ligand to a protein, serving as a means to predict activity with high precision.
*2 XE-Generator: A molecular generation tool independently developed by Xeureka. In addition to common methods such as Matched Molecular Pair (MMP)-based structure transformation, bioisostere replacement, and reaction-based molecular generation, it features over 6,000 structural transformation rules built manually based on the experience and knowledge of skilled medicinal chemists. This enables the exhaustive generation of thousands to hundreds of thousands of practical compound structures from an input structure.
In this collaboration, the companies have been designing novel small-molecule compounds targeting a protein identified by UBE as promising for cancer therapy. They have utilized advanced computational drug discovery and AI technologies, including "Xeureka FEP," a Free Energy Perturbation*1 program developed by Xeureka, and the molecular generation tool "XE-Generator*2."
From the compound groups designed by the two companies, multiple compounds meeting the pre-agreed criteria for lead identification were discovered, resulting in the achievement of this milestone in just about five months since the start of the research.
This achievement demonstrates that Xeureka's computational drug discovery technology functions effectively in actual drug discovery projects and confirms the utility of a drug discovery approach that integrates AI with computational science.
With the achievement of this milestone, Xeureka will receive the prescribed milestone fee from UBE based on the joint research agreement.
At UBE, compounds were previously synthesized and screened to verify their efficacy. By utilizing computational drug discovery technology, it has now become possible to predict the efficacy of compounds in advance, allowing for the efficient identification of lead compounds with a smaller number of synthesized compounds. This result is expected to contribute to a significant improvement in the efficiency of drug discovery research and bring major innovation to UBE’s drug discovery process. UBE will continue to actively engage in the application of computational technologies to create further innovation.
Both companies will continue this joint research, aiming to create new drug candidate compounds by proceeding with the optimization of the lead compounds.
*1 Free Energy Perturbation: A method based on statistical mechanics to calculate changes in free energy associated with the binding of a ligand to a protein, serving as a means to predict activity with high precision.
*2 XE-Generator: A molecular generation tool independently developed by Xeureka. In addition to common methods such as Matched Molecular Pair (MMP)-based structure transformation, bioisostere replacement, and reaction-based molecular generation, it features over 6,000 structural transformation rules built manually based on the experience and knowledge of skilled medicinal chemists. This enables the exhaustive generation of thousands to hundreds of thousands of practical compound structures from an input structure.
FAQ
What is the core of the Xeureka and UBE news?
They reached the lead identification milestone in five months through joint drug discovery using AI and computational science.
Why is this result significant?
It demonstrates a significant improvement in drug discovery process efficiency, shortening development timelines.
What are the key technologies?
The key is activity prediction by 'Xeureka FEP' and efficient molecular generation by 'XE-Generator'.