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    • Our Technology
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  • DeepPath:

    Physics Elegance Beats Brute Force

    Unlocking protein motions is the key to unlocking the next generation of medicines.

  • Where other tools stop, DeepPath starts

    Unlocking hidden binding sites through fast, physics-powered protein dynamics predictions

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    Traditional Simulations

    Take months to a year on a supercomputer to reveal only shallow binding sites and dynamic changes.

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    DeepPath

    Reveals cryptic binding sites and dynamic transitions in half a day on a single GPU.

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    AlphaFold & Other AI

    Provides only a single snapshot, missing the transient hidden sites that drive functional drug binding.

  • Pipeline

    We are actively looking for strategic partners to co-develop our assets.

     

    If you are interested, please do not hesitate to get in touch.

    Contact us

    To showcase the power of our technology, we are currently developing AI_01 and AI_02 for application in treating a wide range of inflammatory diseases.

     

     

     

     

     

     

     

     

     

     

     

  • FAQs

    Have more questions? We’ve got you covered.

    What does “physics-based” mean, and why is physics important?

    What makes DeepPath unique? Why can’t others do this?

    Do you have validation data?

    What kinds of diseases can DeepPath help address?

    How is DeepPath used in real drug discovery projects?

  • Publications

    2025

    Pang YT., Kuo KM., Yang L., Gumbart JC. DeepPath: Overcoming data scarcity for protein transition pathway prediction using physics-based deep learning. bioRxiv 2025.02.27.640693; doi: https://doi.org/10.1101/2025.02.27.640693

    2022

    Coderc de Lacam EG, Blazhynska M, Chen H, Gumbart JC, Chipot C. When the Dust Has Settled: Calculation of Binding Affinities from First Principles for SARS-CoV-2 Variants with Quantitative Accuracy. J Chem Theory Comput. 2022 Oct 11;18(10):5890-5900. doi: 10.1021/acs.jctc.2c00604. Epub 2022 Sep 15. PMID: 36108303.

    Pavlova A, Bassit L, Cox BD, Korablyov M, Chipot C, Patel D, Lynch DL, Amblard F, Schinazi RF, Gumbart JC. The Mechanism of Action of Hepatitis B Virus Capsid Assembly Modulators Can Be Predicted from Binding to Early Assembly Intermediates. J Med Chem. 2022 Mar 24;65(6):4854-4864. doi: 10.1021/acs.jmedchem.1c02040. Epub 2022 Mar 15. PMID: 35290049; PMCID: PMC9026740.

    Fu H, Chen H, Blazhynska M, Goulard Coderc de Lacam E, Szczepaniak F, Pavlova A, Shao X, Gumbart JC, Dehez F, Roux B, Cai W, Chipot C. Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations. Nat Protoc. 2022 Apr;17(4):1114-1141. doi: 10.1038/s41596-021-00676-1. Epub 2022 Mar 11. PMID: 35277695; PMCID: PMC10082674.

    2021

    Wu R, Bakelar JW, Lundquist K, Zhang Z, Kuo KM, Ryoo D, Pang YT, Sun C, White T, Klose T, Jiang W, Gumbart JC, Noinaj N. Plasticity within the barrel domain of BamA mediates a hybrid-barrel mechanism by BAM. Nat Commun. 2021 Dec 8;12(1):7131. doi: 10.1038/s41467-021-27449-4. PMID: 34880256; PMCID: PMC8655018.

    Pavlova A, Zhang Z, Acharya A, Lynch DL, Pang YT, Mou Z, Parks JM, Chipot C, Gumbart JC. Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2. J Phys Chem Lett. 2021 Jun 17;12(23):5494-5502. doi: 10.1021/acs.jpclett.1c01494. Epub 2021 Jun 4. PMID: 34086459.

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