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Profile
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Delegates :
Masato HOSODA |
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Incorporated :
May 1 , 2001 |
Paid in Capital :
376 Million yen |
Employees :
9 人 |
Address :
I&F Umeda #704 3-10-2, Toyosaki, Kita-ku, Osaka OSAKA
〒531-0072
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TEL/FAX :
+81-6-6374-5303 / +81-6-6374-5305 |
URL：
http://www.interprotein.com/ |
Attachment :
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Mission/Background :
Interprotein Corporation is an Osaka University-originated biotech that was established as Inter Cyto Nano Science in 2001, and the name was changed into the present name in 2007. We are conducting drug discovery researches for challenging targets such as PPIs with two technologies, INTENDD for hit candidate proposal and helix-loop-helix peptide as a new modality. INTENDD was advanced to AI-guided INTENDD. Using these technologies, Interprotein contributes to raising the productivity of drug R&D. |
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Technology & Business
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Interprotein is aiming at hit identification, lead generation and optimization for challenging drug targets including PPIs in collaboration with pharmaceutical companies. Interprotein conducts identifications of new scaffolds with INTENDD (INTerprotein’s Engine for New Drug Design), a unique SBDD strategy. For lead generation and optimization, Interprotein established an AI-based activity prediction system, namely AI-guided INTENDD. Interprotein also identifies novel peptide molecules that strongly bind to the targets using helix-loop-helix peptide (HLHP) technology. These approaches make it possible to conduct drug discovery researches in situations that no ligand information has been provided and crystal structure of the target protein has not been clarified. We also conducting in-house projects that are introduced in the section of “Products and Services”.
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Products & Service
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Products & Service Name
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Stage
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Outline
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Milestone
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Proposal of hit candidates by INTENDD
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Service/Marketing
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Propose hit candidates (100-300 compounds) for new targets
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Propose strategy for small molecule hit identification under CDA
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Activity prediction by AI-guided INTENDD
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Service/Marketing
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Predict activity of small molecules and divide into 8 classes
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Propose strategy for small molecule activity prediction under CDA
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Proposal of peptide inhibitors by HLHP technology
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Service/Marketing
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Propose hit candidates (100-300 compounds) for new targets.
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Examine success probability for active HLHP identification under CDA
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Proposal of collaboration for in-house small molecule project
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Discovery
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Collaboration for small molecule inhibitors of IL-6, TNF-α, Runx1
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Negotiation for collaborative researches under CDA
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Proposal of collaboration for in-house HLHP project
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Discovery
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Collaboration for HLHP inhibotors of TIM-3、NKG2A、IL-6、C99 (Aβ precursor)
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Negotiation for collaborative researches under CDA
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Highlights
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It has been verified in the number of examinations that activities of highly active small molecules with good balances of 2 components, enthalpy and entropy of free binding energies for the target proteins, are precisely predicted. We believe these results imply that AI-guided INTENDD contributes lead generation/identification of small molecules.
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Hot news
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Details of INTENDD and AI-guided INTENDD are introduced in the following 2 papers: 1) Hirotsugu Komatsu et al., Medical Science Digest, 45, 225-231 (2019). 2) Hirotsugu Komatsu et al., J. Biol. Macromol., in press.
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Alliance strategy
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We are seeking for partners that disclose targets of interest for proposal of hit candidates by INTENDD and/or strong binder identification by HLHP technology under CDA. By using AI-guided INTENDD, Interprotein proposes candidates for highly active compounds following disclosure of compound structured and separation of those activities into 8 classes.
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