Robust deep learning–based protein sequence design using ProteinMPNN

Dauparas, J., Anishchenko, I., Bennett, N., Bai, H., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Courbet, A. +14 more·2022·Science

Cited by (2,090)

Items 101–200 of 2,090

  1. Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering
    Peng Cheng, Cong Mao, Jin Tang, Sen Yang, Yu Cheng, Wuke Wang, Qiuxi Gu, Wei Han, Hao Chen, Sihan Li et al. · 2024 · Cell Research
  2. From intuition to AI: evolution of small molecule representations in drug discovery
    Miles McGibbon, Steven Shave, Jie Nan Dong, Yumiao Gao, Douglas R. Houston, Jiancong Xie, Yuedong Yang, Philippe Schwaller, Vincent Blay · 2023 · Briefings in Bioinformatics
  3. How will generative AI disrupt data science in drug discovery?
    Vert, Jean-Philippe · 2023 · Nature Biotechnology
  4. De novo design of drug-binding proteins with predictable binding energy and specificity
    Lei Lü, Xuxu Gou, Sophia K. Tan, Samuel I. Mann, Hyunjun Yang, Xiaofang Zhong, Dimitris Gazgalis, Jesús Valdiviezo, Hyunil Jo, Yibing Wu et al. · 2024 · Science
  5. Computational enzyme design by catalytic motif scaffolding
    Braun, Markus, Tripp, Adrian, Chakatok, Morakot, Kaltenbrunner, Sigrid, Fischer, Celina, Stoll, David, Bijelic, Aleksandar, Elaily, Wael, Totaro, Massimo G., Moser, Melanie et al. · 2026 · Nature
  6. Strengthening nucleic acid biosecurity screening against generative protein design tools
    Bruce J. Wittmann, Tessa Alexanian, Craig M. Bartling, Jacob Beal, Adam J. Clore, James Diggans, Kevin Flyangolts, Bryan T. Gemler, Tom Mitchell, Steven T. Murphy et al. · 2025 · Science
  7. Understanding the cell: Future views of structural biology
    Martin Beck, Roberto Covino, Inga Hänelt, Michaela Müller-McNicoll · 2024 · Cell
  8. Self-play reinforcement learning guides protein engineering
    Yi Wang, Hui Tang, Lichao Huang, Lulu Pan, Lixiang Yang, Huanming Yang, Feng Mu, Meng Yang · 2023 · Nature Machine Intelligence
  9. The genetic architecture of protein stability
    André J. Faure, Aina Martí-Aranda, Cristina Hidalgo-Carcedo, Toni Beltran, Jörn M. Schmiedel, Ben Lehner · 2024 · Nature
  10. Computer-Aided Drug Discovery for Undruggable Targets
    Qi Sun, Hanping Wang, Juan Xie, Liying Wang, Junxi Mu, Junren Li, Yuhao Ren, Luhua Lai · 2025 · Chemical Reviews
  11. AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design
    Guillem Casadevall, Cristina Duran, Sílvia Osuna · 2023 · JACS Au
  12. Cross-protein transfer learning substantially improves disease variant prediction
    2023
  13. Blueprinting extendable nanomaterials with standardized protein blocks
    Timothy F. Huddy, Yang Hsia, Ryan D. Kibler, Jinwei Xu, Neville P. Bethel, Deepesh Nagarajan, Rachel L. Redler, Philip J. Y. Leung, Connor Weidle, Alexis Courbet et al. · 2024 · Nature
  14. Deep learning–guided design of dynamic proteins
    Guo, Amy B., Akpinaroglu, Deniz, Stephens, Christina A., Grabe, Michael, Smith, Colin A., Kelly, Mark J. S., Kortemme, Tanja · 2025 · Science
  15. Computational design of metallohydrolases
    Donghyo Kim, Seth M. Woodbury, Woody Ahern, Doug Tischer, Alex Kang, Emily Joyce, Asim K. Bera, Nikita Hanikel, Saman Salike, Rohith Krishna et al. · 2025 · Nature
  16. Strategies for designing biocatalysts with new functions
    Elizabeth L. Bell, Amy E. Hutton, Ashleigh J. Burke, Adam O’Connell, Amber Barry, Elaine O’Reilly, Anthony P. Green · 2024 · Chemical Society Reviews
  17. Stability Oracle: a structure-based graph-transformer framework for identifying stabilizing mutations
    Daniel J. Diaz, Chengyue Gong, Jeffrey Ouyang-Zhang, James M. Loy, Jordan Wells, David K. Yang, Andrew D. Ellington, Alexandros G. Dimakis, Adam R. Klivans · 2024 · Nature Communications
  18. Artificial intelligence in peptide-based drug design
    Silong Zhai, Tiantao Liu, Shaolong Lin, Dan Li, Huanxiang Liu, Xiaojun Yao, Tingjun Hou · 2025 · Drug Discovery Today
  19. Structure-informed Language Models Are Protein Designers
    Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei Ye, Quanquan Gu · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  20. Programmable synthetic receptors: the next-generation of cell and gene therapies
    Fei Teng, Tongtong Cui, Li Zhou, Qingqin Gao, Qi Zhou, Wei Li · 2024 · Signal Transduction and Targeted Therapy
  21. De novo design of pH-responsive self-assembling helical protein filaments
    Hao Shen, Eric M. Lynch, Susrut Akkineni, Joseph L. Watson, Justin A. Decarreau, Neville P. Bethel, Issa Benna, William Sheffler, Daniel P. Farrell, Frank DiMaio et al. · 2024 · Nature Nanotechnology
  22. Exploring new galaxies: Perspectives on the discovery of novel PET-degrading enzymes
    Jan Mičan, Da’san M. M. Jaradat, Weidong Liu, Gert Weber, Stanislav Mazurenko, Uwe T. Bornscheuer, Jiřı́ Damborský, Ren Wei, David Bednář · 2023 · Applied Catalysis B: Environmental
  23. Deep Confident Steps to New Pockets: Strategies for Docking Generalization
    Gabriele Corso, Arthur Deng, Benjamin N. Fry, Nicholas F. Polizzi, Regina Barzilay, Tommi Jaakkola · 2024 · PubMed
  24. Integration of pre-trained protein language models into geometric deep learning networks
    Fang Wu, Lirong Wu, Dragomir Radev, Jinbo Xu, Stan Ziqing Li · 2023 · Communications Biology
  25. A review of enzyme design in catalytic stability by artificial intelligence
    Yongfan Ming, Wenkang Wang, Rui Yin, Min Zeng, Li Tang, Shizhe Tang, Min Li · 2023 · Briefings in Bioinformatics
  26. Code to complex: AI-driven de novo binder design
    Daniel Fox, Cyntia Taveneau, Janik Clement, Rhys Grinter, Gavin J. Knott · 2025 · Structure
  27. Engineered natural killer cells for cancer therapy
    Alexander Biederstädt, Katayoun Rezvani · 2025 · Cancer Cell
  28. A high-level programming language for generative protein design
    Brian Hie, Salvatore Candido, Zeming Lin, Ori Kabeli, Roshan Rao, Nikita Smetanin, Tom Sercu, Alexander W. Rives · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  29. Designing Multifunctional Biomaterials via Protein Self‐Assembly
    Alexey V. Solomonov, Anna Kozell, Ulyana Shimanovich · 2024 · Angewandte Chemie International Edition
  30. Protein language models are biased by unequal sequence sampling across the tree of life
    Ding, Frances, Steinhardt, Jacob · 2024
  31. Protein Structure Prediction: Challenges, Advances, and the Shift of Research Paradigms
    Bin Huang, Lupeng Kong, Chao Wang, Fusong Ju, Qi Zhang, Jianwei Zhu, Tiansu Gong, Haicang Zhang, Chungong Yu, Wei‐Mou Zheng et al. · 2023 · Genomics Proteomics & Bioinformatics
  32. Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development
    Kwangho Nam, Yihan Shao, Dan Thomas Major, Magnus Wolf‐Watz · 2024 · ACS Omega
  33. Revolutionizing <scp>peptide‐based</scp> drug discovery: Advances in the <scp>post‐AlphaFold</scp> era
    Chang, Liwei, Mondal, Arup, Singh, Bhumika, Martínez‐Noa, Yisel, Perez, Alberto · 2024 · WIREs Computational Molecular Science
  34. ProT‐Diff: A Modularized and Efficient Strategy for De Novo Generation of Antimicrobial Peptide Sequences by Integrating Protein Language and Diffusion Models
    2024
  35. An end-to-end deep learning method for protein side-chain packing and inverse folding
    Matt McPartlon, Jinbo Xu · 2023 · Proceedings of the National Academy of Sciences
  36. Using machine learning to predict the effects and consequences of mutations in proteins
    Daniel J. Diaz, Anastasiya V. Kulikova, Andrew D. Ellington, Claus O. Wilke · 2023 · Current Opinion in Structural Biology
  37. Four-component protein nanocages designed by programmed symmetry breaking
    Sangmin Lee, Ryan D. Kibler, Green Ahn, Yang Hsia, Andrew J. Borst, Annika Philomin, Madison Arza Kennedy, Buwei Huang, Barry L. Stoddard, David A. Baker · 2024 · Nature
  38. Dual-use capabilities of concern of biological AI models
    Jaspreet Pannu, Doni Bloomfield, Robert MacKnight, Moritz S. Hanke, Alex W Zhu, Gabe Gomes, Anita J. Cicero, Thomas V. Inglesby · 2025 · PLoS Computational Biology
  39. Biomimetic Intelligent Thermal Management Materials: From Nature‐Inspired Design to Machine‐Learning‐Driven Discovery
    Heng Zhang, Qingxia He, Fei Zhang, Yanshuai Duan, Mengmeng Qin, Wei Feng · 2025 · Advanced Materials
  40. Revolutionizing protein–protein interaction prediction with deep learning
    Jing Zhang, Jesse Durham, Qian Cong · 2024 · Current Opinion in Structural Biology
  41. Target-Specific De Novo Peptide Binder Design with DiffPepBuilder
    Fanhao Wang, Y.X. Wang, Laiyi Feng, Changsheng Zhang, Luhua Lai · 2024 · Journal of Chemical Information and Modeling
  42. A trimodal protein language model enables advanced protein searches
    Jin Su, Yan He, Shiyang You, Shiyu Jason Jiang, Xibin Zhou, Xuting Zhang, Yuxuan Wang, Xining Su, Igor Tolstoy, Xing Chang et al. · 2025 · Nature Biotechnology
  43. Accelerating Biomolecular Modeling with AtomWorks and RF3
    Nathaniel Corley, Simon V. Mathis, Rohith Krishna, Magnus S. Bauer, Tuscan R. Thompson, Woody Ahern, Maxwell W. Kazman, Rafael I. Brent, Kieran Didi, Andrew Kubaney et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  44. Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence
    Duran-Frigola, Miquel, Cigler, Marko, Winter, Georg E. · 2023 · Journal of the American Chemical Society
  45. Variant effect predictor correlation with functional assays is reflective of clinical classification performance
    2025
  46. From random to rational: improving enzyme design through electric fields, second coordination sphere interactions, and conformational dynamics
    Shobhit S. Chaturvedi, Daniel Bím, Christo Z. Christov, Anastassia N. Alexandrova · 2023 · Chemical Science
  47. Peptide-based drug design using generative AI
    Srinivasan Ekambaram, Nikolay V. Dokholyan · 2025 · Chemical Communications
  48. Accelerating therapeutic protein design with computational approaches toward the clinical stage
    Zhidong Chen, Xinpei Wang, Xu Chen, Juyang Huang, Chenglin Wang, Junqing Wang, Zhe Wang · 2023 · Computational and Structural Biotechnology Journal
  49. A Top-Down Design Approach for Generating a Peptide PROTAC Drug Targeting Androgen Receptor for Androgenetic Alopecia Therapy
    Bohan Ma, Donghua Liu, Zhe Wang, Dize Zhang, Yanlin Jian, Kun Zhang, Tianyang Zhou, Yibo Gao, Yizeng Fan, Jian Ma et al. · 2024 · Journal of Medicinal Chemistry
  50. Human coronavirus HKU1 recognition of the TMPRSS2 host receptor
    Matthew McCallum, Young‐Jun Park, Cameron Stewart, Kaitlin R. Sprouse, Amin Addetia, Jack T Brown, M. Alejandra Tortorici, Cecily A. Gibson, Emily Wong, Margareta M. Ieven et al. · 2024 · Cell
  51. AI-Driven Enzyme Engineering: Emerging Models and Next-Generation Biotechnological Applications
    Mohd Faheem Khan, Mohd. Tasleem Khan · 2025 · Molecules
  52. Harnessing the power of artificial intelligence to advance cell therapy
    Sara Capponi, Kyle G. Daniels · 2023 · Immunological Reviews
  53. An end-to-end attention-based approach for learning on graphs
    David Buterez, Jon Paul Janet, Dino Oglić, Píetro Lió · 2025 · Nature Communications
  54. Large language model for knowledge synthesis and AI-enhanced biomanufacturing
    Wenyu Li, Zhitao Mao, Zhengyang Xiao, Xiaoping Liao, Mattheos A. G. Koffas, Yixin Chen, Hongwu Ma, Yinjie Tang · 2025 · Trends in biotechnology
  55. AI-generated MLH1 small binder improves prime editing efficiency
    Ju-Chan Park, Heesoo Uhm, Yong Woo Kim, Ye Eun Oh, Jeung‐Hee Lee, Jiyun Yang, Kyoungmi Kim, Sangsu Bae · 2025 · Cell
  56. Design of amyloidogenic peptide traps
    Sahtoe, Danny D., Andrzejewska, Ewa A., Han, Hannah L., Rennella, Enrico, Schneider, Matthias M., Meisl, Georg, Ahlrichs, Maggie, Decarreau, Justin, Nguyen, Hannah, Kang, Alex et al. · 2024 · Nature Chemical Biology
  57. Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design
    Xinyi Wu, Huitian Lin, Renren Bai, Hongliang Duan · 2024 · European Journal of Medicinal Chemistry
  58. De novo protein design with a denoising diffusion network independent of pretrained structure prediction models
    Yufeng Liu, Sheng Wang, Jixin Dong, Ling-Hui Chen, Xinyu Wang, Lei Wang, Fudong Li, Chenchen Wang, Jiahai Zhang, Yuzhu Wang et al. · 2024 · Nature Methods
  59. Deep Generative Models for Therapeutic Peptide Discovery: A Comprehensive Review
    Leshan Lai, Yuansheng Liu, Bosheng Song, Keqin Li, Xiangxiang Zeng · 2025 · ACM Computing Surveys
  60. AntiFold: improved structure-based antibody design using inverse folding
    Magnus Haraldson Høie, Alissa M. Hummer, Tobias Hegelund Olsen, Broncio Aguilar-Sanjuan, Morten Nielsen, Charlotte Mary Deane · 2024 · Bioinformatics Advances
  61. Physics-based modeling in the new era of enzyme engineering
    Christopher P. Jurich, Qianzhen Shao, Xinchun Ran, Zhongyue John Yang · 2025 · Nature Computational Science
  62. EquiFold: Protein Structure Prediction with a Novel Coarse-Grained Structure Representation
    Jae Hyeon Lee, Payman Yadollahpour, Andrew M. Watkins, Nathan C. Frey, Andrew Leaver‐Fay, Stephen Ra, Kyunghyun Cho, Vladimir Gligorijević, Aviv Regev, Richard Bonneau · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  63. Context-aware geometric deep learning for protein sequence design
    2024
  64. In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models
    Odessa J. Goudy, Amrita Nallathambi, Tomoaki Kinjo, Nicholas Z. Randolph, Brian A. Kuhlman · 2023 · Proceedings of the National Academy of Sciences
  65. Artificial intelligence and machine learning applications for cultured meat
    Michael E. Todhunter, Sheikh Jubair, Ruchika Verma, Rikard Saqe, Kevin Shen, Breanna Duffy · 2024 · Frontiers in Artificial Intelligence
  66. The Nobel Prize in Chemistry: past, present, and future of AI in biology
    Luciano A. Abriata · 2024 · Communications Biology
  67. Molecular basis of convergent evolution of ACE2 receptor utilization among HKU5 coronaviruses
    Young‐Jun Park, Chen Liu, Jimin Lee, Jack T Brown, Chengbao Ma, Peng Liu, Risako Gen, Qing Xiong, Samantha K. Zepeda, Cameron Stewart et al. · 2025 · Cell
  68. Scaling Unlocks Broader Generation and Deeper Functional Understanding of Proteins
    Aadyot Bhatnagar, Sarthak Jain, Joel Beazer, Samuel C. Curran, Alexander M. Hoffnagle, Kyle Ching, Michael Martyn, Stephen Nayfach, Jeffrey A. Ruffolo, Ali Madani · 2025 · neural information processing systems
  69. New Insights into the Cooperativity and Dynamics of Dimeric Enzymes
    Ke-Wei Chen, Tian‐Yu Sun, Yun‐Dong Wu · 2023 · Chemical Reviews
  70. Electrostatics as a Guiding Principle in Understanding and Designing Enzymes
    J. Javier Ruiz‐Pernía, Katarzyna Świderek, J. Bertrán, Vicent Moliner, Iñaki Tuñón · 2024 · Journal of Chemical Theory and Computation
  71. Structure-based self-supervised learning enables ultrafast protein stability prediction upon mutation
    Jinyuan Sun, Tong Zhu, Yinglu Cui, Bian Wu · 2025 · The Innovation
  72. ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model
    Bo Ni, David Lee Kaplan, Markus J. Buehler · 2024 · Science Advances
  73. De novo design of transmembrane fluorescence-activating proteins
    Jingyi Zhu, Mingfu Liang, Ke Sun, Wei Yu, Ruiying Guo, Lijing Zhang, Junhui Shi, Dan Ma, Qi Hu, Gaoxingyu Huang et al. · 2025 · Nature
  74. Efficient and selective energy transfer photoenzymes powered by visible light
    Rebecca Crawshaw, Ross Smithson, Johannes Hofer, Florence J. Hardy, George W. Roberts, Jonathan Samuel Trimble, Anna R. Kohn, Colin Levy, Deborah A. Drost, Christian Merten et al. · 2025 · Nature Chemistry
  75. AI-driven de novo enzyme design: Strategies, applications, and future prospects
    Xi-Chen Cui, Yan Zheng, Ye Liu, Zhiguang Yuchi, Ying‐Jin Yuan · 2025 · Biotechnology Advances
  76. Generative artificial intelligence for enzyme design: Recent advances in models and applications
    Shuixiu Wen, Wen Zheng, Uwe T. Bornscheuer, Shuke Wu · 2025 · Current Opinion in Green and Sustainable Chemistry
  77. Nanobodies: From Discovery to AI-Driven Design
    Haoran Zhu, Yu Ding · 2025 · Biology
  78. De novo design and structure of a peptide–centric TCR mimic binding module
    Karsten D. Householder, Xinyu Xiang, Kevin M. Jude, Arthur Deng, Matthias Obenaus, Yang Zhao, Steven C. Wilson, Xiaojing Tina Chen, Nan Wang, K. Christopher García · 2025 · Science
  79. Real-World Applications and Experiences of AI/ML Deployment for Drug Discovery
    William R. Pitt, Jonathan M. Bentley, Christophe Boldron, Lionel Colliandre, Carmen Esposito, Elizabeth Hatcher Frush, J. Kopec, Stéphanie Labouille, Jérôme Meneyrol, David A. Pardoe et al. · 2025 · Journal of Medicinal Chemistry
  80. Rapid and automated design of two-component protein nanomaterials using ProteinMPNN
    de Haas, Robbert J., Brunette, Natalie, Goodson, Alex, Dauparas, Justas, Yi, Sue Y., Yang, Erin C., Dowling, Quinton, Nguyen, Hannah, Kang, Alex, Bera, Asim K. et al. · 2024 · Proceedings of the National Academy of Sciences
  81. Antigen spacing on protein nanoparticles influences antibody responses to vaccination
    Daniel Ellis, Annie M. Dosey, Seyhan Boyoglu-Barnum, Young‐Jun Park, Rebecca A. Gillespie, Hubza Syeda, Geoffrey B. Hutchinson, Yaroslav Tsybovsky, Michael Murphy, Deleah Pettie et al. · 2023 · Cell Reports
  82. Design of linear and cyclic peptide binders from protein sequence information
    Qiuzhen Li, Efstathios Nikolaos Vlachos, Patrick Bryant · 2025 · Communications Chemistry
  83. Genome-scale annotation of protein binding sites via language model and geometric deep learning
    Yuan, Qianmu, Tian, Chong, Yang, Yuedong · 2024 · eLife
  84. Small-molecule binding and sensing with a designed protein family
    2026
  85. Structure Prediction and Computational Protein Design for Efficient Biocatalysts and Bioactive Proteins
    Rebecca Buller, Jiřı́ Damborský, Donald Hilvert, Uwe T. Bornscheuer · 2024 · Angewandte Chemie International Edition
  86. Rapid directed evolution guided by protein language models and epistatic interactions
    Vincent Q. Tran, Matthew Nemeth, Liam J. Bartie, Sita S. Chandrasekaran, Alison Fanton, Hyungseok C. Moon, Brian Hie, Silvana Konermann, Patrick D. Hsu · 2026 · Science
  87. Leveraging deep learning to improve vaccine design
    Andrew P. Hederman, Margaret E. Ackerman · 2023 · Trends in Immunology
  88. GPSFun: geometry-aware protein sequence function predictions with language models
    Qianmu Yuan, Chong Tian, Yidong Song, Peihua Ou, Mingming Zhu, Huiying Zhao, Yuedong Yang · 2024 · Nucleic Acids Research
  89. Beyond Anticoagulation: A Comprehensive Review of Non-Vitamin K Oral Anticoagulants (NOACs) in Inflammation and Protease-Activated Receptor Signaling
    Shirin Jannati, Rajashree Patnaik, Yajnavalka Banerjee · 2024 · International Journal of Molecular Sciences
  90. Advancements in protein structure prediction: A comparative overview of AlphaFold and its derivatives
    Yuktika Malhotra, Jerry John, Deepika Yadav, Deepshikha Sharma, Vanshika, Kamal Rawal, Vaibhav Mishra, Navaneet Chaturvedi · 2025 · Computers in Biology and Medicine
  91. Engineering highly active nuclease enzymes with machine learning and high-throughput screening
    Neil Thomas, David Belanger, Chenling A. Xu, Hanson Lee, Kathleen Hirano, Kosuke Iwai, Vanja Polic, Kendra Dee Nyberg, Kevin G. Hoff, Lucas Frenz et al. · 2025 · Cell Systems
  92. Systems and synthetic biology for plant natural product pathway elucidation
    Kezhen Qin, Fang Liu, Caibin Zhang, Rui Deng, Alisdair Robert Fernie, Youjun Zhang · 2025 · Cell Reports
  93. Protein design using structure-based residue preferences
    2024
  94. AI for organic and polymer synthesis
    Xin Hong, Qi Yang, Kuangbiao Liao, Jianfeng Pei, Mao Chen, Fanyang Mo, Hua Lu, Wen-Bin Zhang, Haisen Zhou, Jiaxiao Chen et al. · 2024 · Science China Chemistry
  95. Modeling protein–small molecule conformational ensembles with PLACER
    Ivan V. Anishchenko, Yakov Kipnis, Indrek Kalvet, Guangfeng Zhou, Rohith Krishna, Samuel J. Pellock, Anna Lauko, Gyu Rie Lee, Linna An, Justas Dauparas et al. · 2025 · Proceedings of the National Academy of Sciences
  96. Deep generative optimization of mRNA codon sequences for enhanced mRNA translation and therapeutic efficacy
    Li, Yupeng, Wang, Fan, Yang, Jiaqi, Han, Zirong, Chen, Linfeng, Jiang, Wenbing, Zhou, Hao, Li, Tong, Tang, Zehua, Deng, Jianxiang et al. · 2025 · Nature Communications
  97. Cytochrome P450 Enzyme Design by Constraining the Catalytic Pocket in a Diffusion Model
    Qian Wang, Xiaonan Liu, Hejian Zhang, Huanyu Chu, Chao Shi, Lei Justan Zhang, Pi Liu, Pi Liu, Xiaoxi Zhu, Yuwan Liu et al. · 2024 · Research
  98. Advances in stress-tolerance elements for microbial cell factories
    Zheyi Kuang, Xiaofang Yan, Yanfei Yuan, Ruiqi Wang, Haifan Zhu, Youyang Wang, Jianfeng Li, Jianwen Ye, Haitao Yue, Xiaofeng Yang · 2024 · Synthetic and Systems Biotechnology
  99. Protein Engineering for Industrial Biocatalysis: Principles, Approaches, and Lessons from Engineered PETases
    Konstantinos Grigorakis, Christina Ferousi, Evangelos Topakas · 2025 · Catalysts
  100. Peptide-functionalized nanoparticles for brain-targeted therapeutics
    Sophia N. Tang, Emily Laura Han, Michael J. Mitchell · 2025 · Drug Delivery and Translational Research