IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-61160-y.html
   My bibliography  Save this article

Merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis

Author

Listed:
  • Yash Chainani

    (Northwestern University
    Center for Synthetic Biology
    Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

  • Jacob Diaz

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

  • Margaret Guilarte-Silva

    (Northwestern University
    Center for Synthetic Biology)

  • Vincent Blay

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

  • Quan Zhang

    (Northwestern University)

  • William Sprague

    (Northwestern University)

  • Keith E. J. Tyo

    (Northwestern University
    Center for Synthetic Biology)

  • Linda J. Broadbelt

    (Northwestern University
    Center for Synthetic Biology
    Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

  • Aindrila Mukhopadhyay

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

  • Jay D. Keasling

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory
    University of California
    University of California)

  • Hector Garcia Martin

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory
    Basque Center for Applied Mathematics
    DOE Agile BioFoundry)

  • Tyler W. H. Backman

    (Joint BioEnergy Institute
    Lawrence Berkeley National Laboratory)

Abstract

Synthetic biology offers the promise of manufacturing chemicals more sustainably than petrochemistry. Yet, both the rate at which biomanufacturing can synthesize these molecules and the net chemical accessible space are limited by existing pathway discovery methods, which can often rely on arduous literature searches. Here, we introduce BioPKS pipeline, an automated retrobiosynthesis tool combining multifunctional type I polyketide synthases (PKSs) and monofunctional enzymes via two complementary tools: RetroTide and DORAnet. Monofunctional enzymes are valuable for carefully decorating a substrate’s carbon backbone while PKSs are unique in their ability to iteratively catalyze carbon-carbon bond formation reactions, thereby expanding carbon backbones in a predictable fashion. We evaluate the performance of BioPKS pipeline using a previously reported set of 155 biomanufacturing candidates, achieving exact synthetic designs for 93 compounds and generating chemically similar pathways for most remaining targets. Furthermore, BioPKS pipeline can propose pathways for the complex therapeutic natural products cryptofolione and basidalin.

Suggested Citation

  • Yash Chainani & Jacob Diaz & Margaret Guilarte-Silva & Vincent Blay & Quan Zhang & William Sprague & Keith E. J. Tyo & Linda J. Broadbelt & Aindrila Mukhopadhyay & Jay D. Keasling & Hector Garcia Mart, 2025. "Merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61160-y
    DOI: 10.1038/s41467-025-61160-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-61160-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-025-61160-y?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. Shota Atsumi & Taizo Hanai & James C. Liao, 2008. "Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels," Nature, Nature, vol. 451(7174), pages 86-89, January.
    2. 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.
    3. Michael A. Skinnider & Chad W. Johnston & Mathusan Gunabalasingam & Nishanth J. Merwin & Agata M. Kieliszek & Robyn J. MacLellan & Haoxin Li & Michael R. M. Ranieri & Andrew L. H. Webster & My P. T. C, 2020. "Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    4. Kathryn Tunyasuvunakool & Jonas Adler & Zachary Wu & Tim Green & Michal Zielinski & Augustin Žídek & Alex Bridgland & Andrew Cowie & Clemens Meyer & Agata Laydon & Sameer Velankar & Gerard J. Kleywegt, 2021. "Highly accurate protein structure prediction for the human proteome," Nature, Nature, vol. 596(7873), pages 590-596, August.
    5. Joseph L. Watson & David Juergens & Nathaniel R. Bennett & Brian L. Trippe & Jason Yim & Helen E. Eisenach & Woody Ahern & Andrew J. Borst & Robert J. Ragotte & Lukas F. Milles & Basile I. M. Wicky & , 2023. "De novo design of protein structure and function with RFdiffusion," Nature, Nature, vol. 620(7976), pages 1089-1100, August.
    6. Xixi Sun & Yujie Yuan & Qitong Chen & Shiqi Nie & Jiaxuan Guo & Zutian Ou & Min Huang & Zixin Deng & Tiangang Liu & Tian Ma, 2022. "Metabolic pathway assembly using docking domains from type I cis-AT polyketide synthases," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    7. Itai Levin & Mengjie Liu & Christopher A. Voigt & Connor W. Coley, 2022. "Merging enzymatic and synthetic chemistry with computational synthesis planning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    8. Shuangjia Zheng & Tao Zeng & Chengtao Li & Binghong Chen & Connor W. Coley & Yuedong Yang & Ruibo Wu, 2022. "Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    9. Akhil Kumar & Lin Wang & Chiam Yu Ng & Costas D. Maranas, 2018. "Pathway design using de novo steps through uncharted biochemical spaces," Nature Communications, Nature, vol. 9(1), pages 1-15, December.
    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. Enrico Orsi & Lennart Schada von Borzyskowski & Stephan Noack & Pablo I. Nikel & Steffen N. Lindner, 2024. "Automated in vivo enzyme engineering accelerates biocatalyst optimization," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Veda Sheersh Boorla & Costas D. Maranas, 2025. "CatPred: a comprehensive framework for deep learning in vitro enzyme kinetic parameters," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    3. Aika Iwama & Ryoji Kise & Hiroaki Akasaka & Fumiya K. Sano & Hidetaka S. Oshima & Asuka Inoue & Wataru Shihoya & Osamu Nureki, 2024. "Structure and dynamics of the pyroglutamylated RF-amide peptide QRFP receptor GPR103," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    4. Laura Shub & Wenjin Liu & Georgios Skiniotis & Michael J. Keiser & Michael J. Robertson, 2025. "MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    5. 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.
    6. Arne Matthys & Jan Felix & Joao Paulo Portela Catani & Kenny Roose & Wim Nerinckx & Benthe Buyten & Daria Fijalkowska & Nico Callewaert & Savvas N. Savvides & Xavier Saelens, 2025. "Single-domain antibodies directed against hemagglutinin and neuraminidase protect against influenza B viruses," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    7. Daniel R. Fox & Kazem Asadollahi & Imogen Samuels & Bradley A. Spicer & Ashleigh Kropp & Christopher J. Lupton & Kevin Lim & Chunxiao Wang & Hari Venugopal & Marija Dramicanin & Gavin J. Knott & Rhys , 2025. "Inhibiting heme piracy by pathogenic Escherichia coli using de novo-designed proteins," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    8. Wei Lu & Jixian Zhang & Weifeng Huang & Ziqiao Zhang & Xiangyu Jia & Zhenyu Wang & Leilei Shi & Chengtao Li & Peter G. Wolynes & Shuangjia Zheng, 2024. "DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    9. Meghana Kshirsagar & Artur Meller & Ian R. Humphreys & Samuel Sledzieski & Yixi Xu & Rahul Dodhia & Eric Horvitz & Bonnie Berger & Gregory R. Bowman & Juan Lavista Ferres & David Baker & Minkyung Baek, 2025. "Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    10. Chase R. Freschlin & Sarah A. Fahlberg & Pete Heinzelman & Philip A. Romero, 2024. "Neural network extrapolation to distant regions of the protein fitness landscape," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    11. Isak S. Pretorius & Thomas A. Dixon & Michael Boers & Ian T. Paulsen & Daniel L. Johnson, 2025. "The coming wave of confluent biosynthetic, bioinformational and bioengineering technologies," Nature Communications, Nature, vol. 16(1), pages 1-8, December.
    12. Simon d’Oelsnitz & Daniel J. Diaz & Wantae Kim & Daniel J. Acosta & Tyler L. Dangerfield & Mason W. Schechter & Matthew B. Minus & James R. Howard & Hannah Do & James M. Loy & Hal S. Alper & Y. Jessie, 2024. "Biosensor and machine learning-aided engineering of an amaryllidaceae enzyme," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    13. Pantelis Livanos & Choy Kriechbaum & Sophia Remers & Arvid Herrmann & Sabine Müller, 2025. "Kinesin-12 POK2 polarization is a prerequisite for a fully functional division site and aids cell plate positioning," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    14. Surabhi Kokane & Ashutosh Gulati & Pascal F. Meier & Rei Matsuoka & Tanadet Pipatpolkai & Giuseppe Albano & Tin Manh Ho & Lucie Delemotte & Daniel Fuster & David Drew, 2025. "PIP2-mediated oligomerization of the endosomal sodium/proton exchanger NHE9," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    15. Justin Riper & Arleth O. Martinez-Claros & Lie Wang & Hannah E. Schneiderman & Sweta Maheshwari & Monica C. Pillon, 2025. "CryoEM structure of the SLFN14 endoribonuclease reveals insight into RNA binding and cleavage," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    16. Pierre Azoulay & Joshua Krieger & Abhishek Nagaraj, 2024. "Old Moats for New Models: Openness, Control, and Competition in Generative Artificial Intelligence," NBER Chapters, in: Entrepreneurship and Innovation Policy and the Economy, volume 4, pages 7-46, National Bureau of Economic Research, Inc.
    17. Xin Yong & Guowen Jia & Qin Yang & Chunzhuang Zhou & Sitao Zhang & Huaqing Deng & Daniel D. Billadeau & Zhaoming Su & Da Jia, 2025. "Cryo-EM structure of the BLOC-3 complex provides insights into the pathogenesis of Hermansky-Pudlak syndrome," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    18. Jun-Yu Si & Yuan-Mei Chen & Ye-Hui Sun & Meng-Xue Gu & Mei-Ling Huang & Lu-Lu Shi & Xiao Yu & Xiao Yang & Qing Xiong & Cheng-Bao Ma & Peng Liu & Zheng-Li Shi & Huan Yan, 2024. "Sarbecovirus RBD indels and specific residues dictating multi-species ACE2 adaptiveness," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    19. 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.
    20. 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.

    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:16:y:2025:i:1:d:10.1038_s41467-025-61160-y. 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.