An evolution-based model for designing chorismate mutase enzymes

Cited by (314)

Items 301–314 of 314

1. Towards coevolution-aware ancestral sequence reconstruction
   Alya Zeinaty, Leonardo Di Bari, Saverio Rossi, Pierre Barrat-Charlaix, Francesco Zamponi, Martin Weigt · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
2. Deep Prior Framework: integrating functional specificity with general plausibility for targeted protein evolution
   Senxin Zhang, Yining Qin, H Zhu, Fei‐Long Meng, Lei Jia, Xiaoqi Zheng · 2026 · Briefings in Bioinformatics
3. Differences between protein fitness models can be used to design variants of altered specificity
   Samuel P. Berry, Rachelle Gaudet, Debora S. Marks · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
4. Steering sequence generation in protein language models through Iterative Lookback Monte Carlo Sampling
   Francesco Calvanese, Gianluca Lombardi, Martin Weigt, Jorge Fernández-de-Cossio-Díaz · 2026 · Machine Learning Science and Technology
5. Tokenization in Protein Language Models: Methods, Taxonomy, and Applications
   Abir Linoubli, Khairi Abidi, Mohamed Farah · 2026 · Communications in computer and information science
6. FireProtASR 2.0: evolution-guided Design of Protein Ancestors and Successors with phylogenetics and machine learning
   Pavel Kohout, David Lacko, Miloš Musil, Simeon Borko, Martin Stepanek, Jan Velecký, Petr Kabourek, Rayyan Tariq Khan, Monika Rosinska, Jiřı́ Damborský et al. · 2026 · Briefings in Bioinformatics
7. Pan-tumor spatial transcriptomics reveals conserved properties of tumor organization
   Vivek Behera, Alexander Guzzetta, Hannah Giba, Ue-Yu Pen, Anna Di Lello, Bipul Pandey, Benjamin A. Doran, Alessandra Esposito, Apameh Pezeshk, Aliya Husain et al. · 2026 · Cell Reports Medicine
8. EnZight: A Structure-Guided Algorithm to Identify and Prioritize Substitution Hotspots for Enzyme Engineering
   Rune Rahbek Oestergaard, Mikkel Lyskjær Jensen, Suzana Siebenhaar, Deniz Bicer, Peter Wad Sackett, Alexander Andersen, Matteo Tiberti, Elena Papaleo, Serina L. Robinson, Søren Thirup et al. · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
9. A spectral framework for measuring diversity in multiple sequence alignments
   Vaitea Opuu · 2026 · PLoS Computational Biology
10. What deep learning can and cannot (yet) do for enzyme design.
    Judith A. Ahr, Moor de Waal, Tudor-Stefan Cotet, Daniel C. Howell, H. Bunzel · 2026 · Current Opinion in Chemical Biology
11. Machine Learning Empowers Enzyme Discovery, Structure Prediction, Engineering, and Design
    王木强, Ling Jiang, Haoran Yu, Jiachen Yu, Wenlong Zheng, Jianmin Wu · 2026 · ACS Catalysis
12. SAEKP: A Site Attention Enzyme Kinetics Prediction Method to Facilitate Enzyme Engineering
    Jia-He Qiu, Zongying Lin, Ke-Wei Chen, Qiang Wang, Tian‐Yu Sun, Li Yuan, Xian Zhang, Yonghong Tian, Yun‐Dong Wu · 2026 · Journal of Chemical Information and Modeling
13. Design and experimental characterization of specificity-switching mutational paths of WW domains
    Ahmed Rehan, Eugenio Mauri, Jorge Fernández-de-Cossio-Díaz, Pierre-Guillaume Brun, Rémi Monasson, Marco Ribezzi‐Crivellari, Simona Cocco · 2026 · eLife
14. A Vast Navigable Protein Sequence Subspace
    Sinai, Sam, Gane, Andreea, Jain, Nina, Bryant, Drew, Bileschi, Max, Bashir, Ali, Church, George M., Kelsic, Eric, Colwell, Lucy · 2026