IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-47011-2.html
   My bibliography  Save this article

3D molecular generative framework for interaction-guided drug design

Author

Listed:
  • Wonho Zhung

    (KAIST)

  • Hyeongwoo Kim

    (KAIST)

  • Woo Youn Kim

    (KAIST
    KAIST
    HITS Inc.)

Abstract

Deep generative modeling has a strong potential to accelerate drug design. However, existing generative models often face challenges in generalization due to limited data, leading to less innovative designs with often unfavorable interactions for unseen target proteins. To address these issues, we propose an interaction-aware 3D molecular generative framework that enables interaction-guided drug design inside target binding pockets. By leveraging universal patterns of protein-ligand interactions as prior knowledge, our model can achieve high generalizability with limited experimental data. Its performance has been comprehensively assessed by analyzing generated ligands for unseen targets in terms of binding pose stability, affinity, geometric patterns, diversity, and novelty. Moreover, the effective design of potential mutant-selective inhibitors demonstrates the applicability of our approach to structure-based drug design.

Suggested Citation

  • Wonho Zhung & Hyeongwoo Kim & Woo Youn Kim, 2024. "3D molecular generative framework for interaction-guided drug design," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47011-2
    DOI: 10.1038/s41467-024-47011-2
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-47011-2
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-47011-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Pablo Gainza & Sarah Wehrle & Alexandra Hall-Beauvais & Anthony Marchand & Andreas Scheck & Zander Harteveld & Stephen Buckley & Dongchun Ni & Shuguang Tan & Freyr Sverrisson & Casper Goverde & Prisci, 2023. "De novo design of protein interactions with learned surface fingerprints," Nature, Nature, vol. 617(7959), pages 176-184, May.
    2. Cristina Cornelio & Sanjeeb Dash & Vernon Austel & Tyler R. Josephson & Joao Goncalves & Kenneth L. Clarkson & Nimrod Megiddo & Bachir El Khadir & Lior Horesh, 2023. "Combining data and theory for derivable scientific discovery with AI-Descartes," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Niklas W. A. Gebauer & Michael Gastegger & Stefaan S. P. Hessmann & Klaus-Robert Müller & Kristof T. Schütt, 2022. "Inverse design of 3d molecular structures with conditional generative neural networks," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. John Jumper & Richard Evans & Alexander Pritzel & Tim Green & Michael Figurnov & Olaf Ronneberger & Kathryn Tunyasuvunakool & Russ Bates & Augustin Žídek & Anna Potapenko & Alex Bridgland & Clemens Me, 2021. "Highly accurate protein structure prediction with AlphaFold," Nature, Nature, vol. 596(7873), pages 583-589, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lucien F. Krapp & Fernando A. Meireles & Luciano A. Abriata & Jean Devillard & Sarah Vacle & Maria J. Marcaida & Matteo Dal Peraro, 2024. "Context-aware geometric deep learning for protein sequence design," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Ryan Cory-Wright & Cristina Cornelio & Sanjeeb Dash & Bachir El Khadir & Lior Horesh, 2024. "Evolving scientific discovery by unifying data and background knowledge with AI Hilbert," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    3. Pierre Azoulay & Joshua Krieger & Abhishek Nagaraj, 2024. "Old Moats for New Models: Openness, Control, and Competition in Generative AI," NBER Chapters, in: Entrepreneurship and Innovation Policy and the Economy, volume 4, National Bureau of Economic Research, Inc.
    4. Anthony C. Bishop & Glorisé Torres-Montalvo & Sravya Kotaru & Kyle Mimun & A. Joshua Wand, 2023. "Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    5. Deyun Qiu & Jinxin V. Pei & James E. O. Rosling & Vandana Thathy & Dongdi Li & Yi Xue & John D. Tanner & Jocelyn Sietsma Penington & Yi Tong Vincent Aw & Jessica Yi Han Aw & Guoyue Xu & Abhai K. Tripa, 2022. "A G358S mutation in the Plasmodium falciparum Na+ pump PfATP4 confers clinically-relevant resistance to cipargamin," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    6. Shuo-Shuo Liu & Tian-Xia Jiang & Fan Bu & Ji-Lan Zhao & Guang-Fei Wang & Guo-Heng Yang & Jie-Yan Kong & Yun-Fan Qie & Pei Wen & Li-Bin Fan & Ning-Ning Li & Ning Gao & Xiao-Bo Qiu, 2024. "Molecular mechanisms underlying the BIRC6-mediated regulation of apoptosis and autophagy," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    7. Dick Schijven & Sourena Soheili-Nezhad & Simon E. Fisher & Clyde Francks, 2024. "Exome-wide analysis implicates rare protein-altering variants in human handedness," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    8. Xiaoke Yang & Mingqi Zhu & Xue Lu & Yuxin Wang & Junyu Xiao, 2024. "Architecture and activation of human muscle phosphorylase kinase," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    9. Zheng Shen & Daxiao Sun & Adriana Savastano & Sára Joana Varga & Maria-Sol Cima-Omori & Stefan Becker & Alf Honigmann & Markus Zweckstetter, 2023. "Multivalent Tau/PSD-95 interactions arrest in vitro condensates and clusters mimicking the postsynaptic density," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    10. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    11. Efren Garcia-Maldonado & Andrew D. Huber & Sergio C. Chai & Stanley Nithianantham & Yongtao Li & Jing Wu & Shyaron Poudel & Darcie J. Miller & Jayaraman Seetharaman & Taosheng Chen, 2024. "Chemical manipulation of an activation/inhibition switch in the nuclear receptor PXR," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    12. Kristy Rochon & Brianna L. Bauer & Nathaniel A. Roethler & Yuli Buckley & Chih-Chia Su & Wei Huang & Rajesh Ramachandran & Maria S. K. Stoll & Edward W. Yu & Derek J. Taylor & Jason A. Mears, 2024. "Structural basis for regulated assembly of the mitochondrial fission GTPase Drp1," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    13. Katherine A. Ray & Joshua D. Lutgens & Ramesh Bista & Jie Zhang & Ronak R. Desai & Melissa Hirsch & Takeshi Miyazawa & Antonio Cordova & Adrian T. Keatinge-Clay, 2024. "Assessing and harnessing updated polyketide synthase modules through combinatorial engineering," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    14. Fan Lu & Liang Zhu & Thomas Bromberger & Jun Yang & Qiannan Yang & Jianmin Liu & Edward F. Plow & Markus Moser & Jun Qin, 2022. "Mechanism of integrin activation by talin and its cooperation with kindlin," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    15. Zengyu Shao & Jiuwei Lu & Nelli Khudaverdyan & Jikui Song, 2024. "Multi-layered heterochromatin interaction as a switch for DIM2-mediated DNA methylation," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    16. Yudong Gao & Daichi Shonai & Matthew Trn & Jieqing Zhao & Erik J. Soderblom & S. Alexandra Garcia-Moreno & Charles A. Gersbach & William C. Wetsel & Geraldine Dawson & Dmitry Velmeshev & Yong-hui Jian, 2024. "Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    17. Martin F. Peter & Christian Gebhardt & Rebecca Mächtel & Gabriel G. Moya Muñoz & Janin Glaenzer & Alessandra Narducci & Gavin H. Thomas & Thorben Cordes & Gregor Hagelueken, 2022. "Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    18. Lauren L. Porter & Allen K. Kim & Swechha Rimal & Loren L. Looger & Ananya Majumdar & Brett D. Mensh & Mary R. Starich & Marie-Paule Strub, 2022. "Many dissimilar NusG protein domains switch between α-helix and β-sheet folds," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    19. Jutta Diessl & Jens Berndtsson & Filomena Broeskamp & Lukas Habernig & Verena Kohler & Carmela Vazquez-Calvo & Arpita Nandy & Carlotta Peselj & Sofia Drobysheva & Ludovic Pelosi & F.-Nora Vögtle & Fab, 2022. "Manganese-driven CoQ deficiency," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    20. Alexander Kroll & Sahasra Ranjan & Martin K. M. Engqvist & Martin J. Lercher, 2023. "A general model to predict small molecule substrates of enzymes based on machine and deep learning," Nature Communications, Nature, vol. 14(1), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47011-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.