Learning the protein language: Evolution, structure, and function

Cited by (486)

Items 101–200 of 486

1. Prosit Transformer: A transformer for Prediction of MS2 Spectrum Intensities
   Markus Ekvall, Patrick Truong, Wassim Gabriel, Mathias Wilhelm, Lukas Käll · 2022 · Journal of Proteome Research
2. Machine Learning Generation of Dynamic Protein Conformational Ensembles
   Li-E Zheng, Shrishti Barethiya, Erik B. Nordquist, Jianhan Chen · 2023 · Molecules
3. Epitope-anchored contrastive transfer learning for paired CD8+ T cell receptor–antigen recognition
   Yumeng Zhang, Zhikang Wang, Yunzhe Jiang, Dene R. Littler, Mark Gerstein, Anthony Wayne Purcell, Jamie Rossjohn, Hong‐Yu Ou, Jiangning Song · 2024 · Nature Machine Intelligence
4. Learning the language of antibody hypervariability
   Rohit Singh, Chiho Im, Yu Qiu, Brian C. Mackness, Abhinav Gupta, Taylor Joren, Samuel Sledzieski, Lena Erlach, Maria Wendt, Yves Fomekong‐Nanfack et al. · 2024 · Proceedings of the National Academy of Sciences
5. Artificial Intelligence-Driven Enzyme Engineering from Structural Prediction to De Novo Design
   Hongling Shi, Xueyang Bai, Fangyuan Tian, Yangwan Li, Dandan Li, Lunguang Yao, Chuang Xue, Cun‐Duo Tang · 2026 · Journal of Agricultural and Food Chemistry
6. BEND: Benchmarking DNA Language Models on biologically meaningful tasks
   Frederikke Isa Marin, Felix Teufel, Marc Horlacher, Dennis Madsen, Dennis Pultz, Ole Winther, Wouter Boomsma · 2023 · arXiv (Cornell University)
7. Structure-informed protein language models are robust predictors for variant effects
   2024
8. ProAffinity-GNN: A Novel Approach to Structure-Based Protein–Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks
   Zhou, Zhiyuan, Yin, Yueming, Han, Hao, Jia, Yiping, Koh, Jun Hong, Kong, Adams Wai-Kin, Mu, Yuguang · 2024 · Journal of Chemical Information and Modeling
9. Medium-sized protein language models perform well at transfer learning on realistic datasets
   Vieira, Luiz C., Handojo, Morgan L., Wilke, Claus O. · 2025 · Scientific Reports
10. deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model
    Fei Zhao, Junhui Qiu, Dongyou Xiang, Pengrui Jiao, Yu Cao, Qingrui Xu, Dairong Qiao, Hui Xu, Yi Cao · 2024 · PeerJ
11. GOProFormer: A Multi-Modal Transformer Method for Gene Ontology Protein Function Prediction
    Anowarul Kabir, Amarda Shehu · 2022 · Biomolecules
12. TT3D: Leveraging precomputed protein 3D sequence models to predict protein–protein interactions
    Samuel Sledzieski, Kapil Devkota, Rohit Singh, Lenore Cowen, Bonnie Berger · 2023 · Bioinformatics
13. Seq-InSite: sequence supersedes structure for protein interaction site prediction
    Hosseini, SeyedMohsen, Golding, G Brian, Ilie, Lucian · 2024 · Bioinformatics
14. Finding functional motifs in protein sequences with deep learning and natural language models
    Castrense Savojardo, Pier Luigi Martelli, Rita Casadio · 2023 · Current Opinion in Structural Biology
15. Tree visualizations of protein sequence embedding space enable improved functional clustering of diverse protein superfamilies
    Wayland Yeung, Zhongliang Zhou, Liju Mathew, Nathan Gravel, Rahil Taujale, Brady M. O’Boyle, Mariah Victoria Salcedo, Aarya Venkat, William N. Lanzilotta, Sheng Li et al. · 2023 · Briefings in Bioinformatics
16. Ultra-fast protein structure prediction to capture effects of sequence variation in mutation movies
    Konstantin Weißenow, Michael Heinzinger, Martin Steinegger, Burkhard Rost · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
17. Protein embeddings improve phage-host interaction prediction
    Mark Edward M. Gonzales, Jennifer C. Ureta, Anish Man Singh Shrestha · 2023 · PLoS ONE
18. BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for Escherichia coli and Staphylococcus aureus
    Jianxiu Cai, Jielu Yan, Chon-Wai Un, Yapeng Wang, François‐Xavier Campbell‐Valois, Shirley W. I. Siu · 2025 · Journal of Chemical Information and Modeling
19. In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning
    Michal Vasina, David R. Kovar, Jiřı́ Damborský, Yun Ding, Tianjin Yang, Andrew J. deMello, Stanislav Mazurenko, Stavros Stavrakis, Zbyněk Prokop · 2023 · Biotechnology Advances
20. Learning the language of protein-protein interactions
    2026
21. Teaching AI to speak protein
    Michael Heinzinger, Burkhard Rost · 2025 · Current Opinion in Structural Biology
22. RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins
    Xinxin Peng, Xiaoyu Wang, Yuming Guo, Zongyuan Ge, Fuyi Li, Xin Gao, Jiangning Song · 2022 · Briefings in Bioinformatics
23. AlphaFold and what is next: bridging functional, systems and structural biology
    Kacper Szczepski, Łukasz Jaremko · 2025 · Expert Review of Proteomics
24. PTG-PLM: Predicting Post-Translational Glycosylation and Glycation Sites Using Protein Language Models and Deep Learning
    Alhasan Alkuhlani, Walaa Khaled Gad, Mohamed Ismail Roushdy, Michael Gr. Voskoglou, Abdel-Badeeh Mohamed Salem · 2022 · Axioms
25. Language model-guided anticipation and discovery of mammalian metabolites
    Hantao Qiang, Fei Wang, Wenyun Lu, Xi Xing, Hahn Kim, Sandrine A. M. Mérette, Lucas B. Ayres, Eponine Oler, Jenna E. AbuSalim, Asael Roichman et al. · 2026 · Nature
26. Deep Local Analysis deconstructs protein–protein interfaces and accurately estimates binding affinity changes upon mutation
    Mohseni Behbahani, Yasser, Laine, Elodie, Carbone, Alessandra · 2023 · Bioinformatics
27. Beyond AlphaFold2: The Impact of AI for the Further Improvement of Protein Structure Prediction
    Ahmet G Genc, Liam James McGuffin · 2024 · Methods in molecular biology
28. Hydrophilic Metal–Organic Frameworks Regulated by Biomineralized Protein for Enhanced Stability and Drug Delivery
    Sajid Ur Rehman, Shuai Kong, Jing Zhang, Haining Xia, Ruiguo Chen, Zeyong Guo, Zehua Li, Rida Ahmed, Abbas Rehman, Hossein Kazemian et al. · 2024 · Nano Letters
29. Leveraging ancestral sequence reconstruction for protein representation learning
    Dana S. Matthews, Matthew A. Spence, Adam C. Mater, James Nichols, Sacha B. Pulsford, Mahakaran Sandhu, Joe A. Kaczmarski, Charlotte M. Miton, Nobuhiko Tokuriki, Colin J. Jackson · 2024 · Nature Machine Intelligence
30. Insights into the inner workings of transformer models for protein function prediction
    Markus A. Wenzel, Erik Grüner, Nils Strodthoff · 2024 · Bioinformatics
31. Simple, Efficient, and Scalable Structure-Aware Adapter Boosts Protein Language Models
    Yang Tan, Mingchen Li, Bingxin Zhou, Bozitao Zhong, Lirong Zheng, Pan Tan, Ziyi Zhou, Huiqun Yu, Guisheng Fan, Liang Hong · 2024 · Journal of Chemical Information and Modeling
32. Assessing the role of evolutionary information for enhancing protein language model embeddings
    Kyra Erckert, Burkhard Rost · 2024 · Scientific Reports
33. Multimeric protein interaction and complex prediction: Structure, dynamics and function
    Da Lu, Shuhong Yu, Yixiang Huang, Xinqi Gong · 2025 · Computational and Structural Biotechnology Journal
34. Protein Language Models: Applications and Perspectives
    Mickaël Leclercq, Arnaud Droit · 2025 · Journal of Proteome Research
35. Protein language models trained on biophysical dynamics inform mutation effects
    Chao Hou, Haiqing Zhao, Yufeng Shen · 2026 · Proceedings of the National Academy of Sciences
36. PITHIA: Protein Interaction Site Prediction Using Multiple Sequence Alignments and Attention
    Seyedmohsen Hosseini, Lucian Ilie · 2022 · International Journal of Molecular Sciences
37. Designing and identifying β-hairpin peptide macrocycles with antibiotic potential
    Justin R. Randall, Cory D. DuPai, T. Jeffrey Cole, Gillian Davidson, Kyra E. Groover, Sabrina L. Slater, Despoina A. I. Mavridou, Claus O. Wilke, Bryan W. Davies · 2023 · Science Advances
38. Extracellular vesicles for developing targeted hearing loss therapy
    Xiaoshu Pan, Yanjun Li, Peixin Huang, Hinrich Staecker, Mei He · 2024 · Journal of Controlled Release
39. Deep learning-based codon optimization with large-scale synonymous variant datasets enables generalized tunable protein expression
    David A. Constant, Jahir M. Gutierrez, Anand V. Sastry, Rebecca Viazzo, Nicholas R. Smith, Jubair Hossain, David A. Spencer, Hayley Carter, Abigail B. Ventura, Michael T. M. Louie et al. · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
40. A-Prot: protein structure modeling using MSA transformer
    Hong, Yiyu, Lee, Juyong, Ko, Junsu · 2022 · BMC Bioinformatics
41. Safe Transfer-Reinforcement-Learning-Based Optimal Control of Nonlinear Systems
    Yujia Wang, Ming Qing Xiao, Zhe Wu · 2024 · IEEE Transactions on Cybernetics
42. A predictive language model for SARS-CoV-2 evolution
    Enhao Ma, Xuan Guo, Mingda Hu, Penghua Wang, Xin Wang, Congwen Wei, Gong Cheng · 2024 · Signal Transduction and Targeted Therapy
43. Integrating microbial GWAS and single-cell transcriptomics reveals associations between host cell populations and the gut microbiome
    Jingjing Li, Yunlong Ma, Yue Cao, Gongwei Zheng, Qing Ren, Cheng Ann CHEN, Qunyan Zhu, Yijun Zhou, Yu Lu, Yaru Zhang et al. · 2025 · Nature Microbiology
44. Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery
    Fang-Ping Wan, Marcelo Der Torossian Torres, Chang-Ge Guan, C. de la Fuente-Núñez · 2025 · Nature Protocols
45. Antibody apparent solubility prediction from sequence by transfer learning
    Jiangyan Feng, Min Jiang, James Shih, Qing Chai · 2022 · iScience
46. LambdaPP : Fast and accessible protein‐specific phenotype predictions
    2022
47. ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences
    Matteo Manfredi, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio · 2023 · Journal of Molecular Biology
48. Inferring protein fitness landscapes from laboratory evolution experiments
    Sameer D’Costa, Emily C. Hinds, Chase R. Freschlin, Hyebin Song, Philip A. Romero · 2023 · PLoS Computational Biology
49. IDP-LM: Prediction of protein intrinsic disorder and disorder functions based on language models
    Yihe Pang, Bin Liu · 2023 · PLoS Computational Biology
50. PROPERMAB: an integrative framework for in silico prediction of antibody developability using machine learning
    Bian Li, Shukun Luo, Wenhua Wang, Jiahui Xu, Dingjiang Liu, Mohammed Shameem, John Mattila, Matthew C. Franklin, Peter G. Hawkins, Gurinder S. Atwal · 2025 · mAbs
51. Evaluation of Machine Learning-Assisted Directed Evolution Across Diverse Combinatorial Landscapes
    Francesca-Zhoufan Li, Jason Yang, Kadina E. Johnston, Emre Gürsoy, Yisong Yue, Frances H. Arnold · 2024 · Cell Systems
52. Deciphering the protein landscape with ProtFlash, a lightweight language model
    Lei Wang, Hui Zhang, Wei Min Xu, Zhidong Xue, Yan Wang · 2023 · Cell Reports Physical Science
53. DeepNeuropePred: A robust and universal tool to predict cleavage sites from neuropeptide precursors by protein language model
    Lei Wang, Zilu Zeng, Zhidong Xue, Yan Wang · 2023 · Computational and Structural Biotechnology Journal
54. Learning the shape of protein microenvironments with a holographic convolutional neural network
    Michael Neal Pun, Andrew Ivanov, Quinn Bellamy, Zachary Montague, Colin LaMont, Philip H Bradley, Jakub Otwinowski, Armita Nourmohammad · 2024 · Proceedings of the National Academy of Sciences
55. SumoPred-PLM: human SUMOylation and SUMO2/3 sites Prediction using Pre-trained Protein Language Model
    Andrew Vargas Palacios, Pujan Acharya, Anthony S. Peidl, Moriah Rene Beck, Eduardo Blanco, Avdesh Mishra, Tasneem Bawa‐Khalfe, Subash Chandra Pakhrin · 2024 · NAR Genomics and Bioinformatics
56. EpiScan: accurate high-throughput mapping of antibody-specific epitopes using sequence information
    Chuan Wang, Jiangyuan Wang, Wenjun Song, Guan‐Zheng Luo, Taijiao Jiang · 2024 · npj Systems Biology and Applications
57. Foundation models of protein sequences: A brief overview
    Andreas Bjerregaard, Peter Mørch Groth, Søren Hauberg, Anders Krogh, Wouter Boomsma · 2025 · Current Opinion in Structural Biology
58. Decoding the interactions and functions of non-coding RNA with artificial intelligence
    Vincent Jung, Cédric Vincent-Cuaz, Charlotte Tumescheit, Lisa Mathilde Fournier, Marousa Darsinou, Zhi Ming Xu, Ali Saadat, Yiran Wang, Petros K. Tsantoulis, Olivier Alain Michielin et al. · 2025 · Nature Reviews Molecular Cell Biology
59. Quantifying uncertainty in protein representations across models and tasks
    R. Prabakaran, Yana Bromberg · 2026 · Nature Methods
60. Integration of protein sequence and protein–protein interaction data by hypergraph learning to identify novel protein complexes
    Simin Xia, Dianke Li, Xinru Deng, Zhongyang Liu, Huaqing Zhu, Dong Li, Dong Li · 2024 · Briefings in Bioinformatics
61. Application of Sequence Embedding in Protein Sequence-Based Predictions
    Nabil Ibtehaz, Daisuke Kihara · 2022 · WORLD SCIENTIFIC eBooks
62. ProteinCLIP: enhancing protein language models with natural language
    Kevin Wu, Howard Y. Chang, James Zou · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
63. Phytopathogen Effector Biology in the Burgeoning AI Era
    Darcy Jones, Sylvain Raffaele · 2025 · Annual Review of Phytopathology
64. Critical Assessment of Protein Intrinsic Disorder Round 3 ‐ Predicting Disorder in the Era of Protein Language Models
    Mahta Mehdiabadi, Alessio Del Conte, María Victoria Nugnes, Maria Cristina Aspromonte, Silvio C. E. Tosatto, Damiano Piovesan · 2025 · Proteins Structure Function and Bioinformatics
65. MFTrans: A multi-feature transformer network for protein secondary structure prediction
    Y Chen, Guanxing Chen, Calvin Yu‐Chian Chen · 2024 · International Journal of Biological Macromolecules
66. Aggregating residue-level protein language model embeddings with optimal transport
    Navid Naderializadeh, Rohit Singh · 2024 · Bioinformatics Advances
67. Learning the Language of Antibody Hypervariability
    Rohit Singh, Chiho Im, Yu Qiu, Brian C. Mackness, Abhinav Gupta, Taylor Sorenson, Samuel Sledzieski, Lena Erlach, Maria Wendt, Yves Fomekong‐Nanfack et al. · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
68. Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning
    Wozniak, Spencer, Janson, Giacomo, Feig, Michael · 2025 · Journal of Chemical Theory and Computation
69. In the twilight zone of protein sequence homology: do protein language models learn protein structure?
    Anowarul Kabir, Asher Moldwin, Yana Bromberg, Amarda Shehu · 2024 · Bioinformatics Advances
70. LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research
    Yintao Zhang, Lingyan Zheng, Nanxin You, Wei Hu, Wanghao Jiang, Mingkun Lu, Hangwei Xu, Haibin Dai, Tingting Fu, Ying Zhou · 2025 · Journal of Pharmaceutical Analysis
71. Advances in ligand-specific biosensing for structurally similar molecules
    Chenggang Xi, Jinjin Diao, Tae Seok Moon · 2023 · Cell Systems
72. On knowing a gene: A distributional hypothesis of gene function
    Jason J. Kwon, Joshua Pan, Guadalupe Gonzalez, William C. Hahn, Marinka Žitnik · 2024 · Cell Systems
73. Decoding functional proteome information in model organisms using protein language models
    Barrios-Núñez, Israel, Martínez-Redondo, Gemma I, Medina-Burgos, Patricia, Cases, Ildefonso, Fernández, Rosa, Rojas, Ana M · 2024 · NAR Genomics and Bioinformatics
74. Enhancing predictions of protein stability changes induced by single mutations using MSA-based language models
    Francesca Cuturello, Marco Celoria, Alessio Ansuini, Alberto Cazzaniga · 2024 · Bioinformatics
75. Current computational tools for protein lysine acylation site prediction
    Zhaohui Qin, Haoran Ren, Pei Zhao, Kaiyuan Wang, Huixia Liu, Chunbo Miao, Yanxiu Du, Junzhou Li, Liuji Wu, Zhen Chen · 2024 · Briefings in Bioinformatics
76. Paying attention to attention: High attention sites as indicators of protein family and function in language models
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77. Evaluating Pretrained Protein Language Model Embeddings as Proxies for Functional Similarity
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78. Visualizing everything, everywhere, all at once: Cryo-EM and the new field of structureomics
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79. BBLN: A bilateral-branch learning network for unknown protein–protein interaction prediction
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80. Accurate Prediction of Antifreeze Protein from Sequences through Natural Language Text Processing and Interpretable Machine Learning Approaches
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81. A systematic analysis of regression models for protein engineering
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82. Improving viral annotation with artificial intelligence
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83. Major advances in protein function assignment by remote homolog detection with protein language models – A review
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84. Intelligent host engineering for metabolic flux optimisation in biotechnology
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85. Collectively encoding protein properties enriches protein language models
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86. Do domain-specific protein language models outperform general models on immunology-related tasks?
    Nicolas Deutschmann, Aurélien Pélissier, Anna Weber, Shuaijun Gao, Jasmina Bogojeska, María Rodríguez Martínez · 2024 · ImmunoInformatics
87. ProtChat: An AI Multi-Agent for Automated Protein Analysis Leveraging GPT-4 and Protein Language Model
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88. Identifying Proteotypic Peptides via Deep Learning
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89. A large language model for predicting neurotoxic peptides and neurotoxins
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90. Predictive and therapeutic applications of protein language models
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91. Deep Extrapolation for Attribute-Enhanced Generation
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92. Machine learning for enzyme catalytic activity: current progress and future horizons
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93. Generative design of compounds with desired potency from target protein sequences using a multimodal biochemical language model
    Hengwei Chen, Jürgen Bajorath · 2024 · Journal of Cheminformatics
94. Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework
    Guoqing Zhang, Hui Wang, Zhiguo Zhang, Lu Zhang, Guibing Guo, Jian Yang, Fajie Yuan, Feng Ju · 2024 · Briefings in Bioinformatics
95. AlphaFold2 and ESMFold: A large-scale pairwise model comparison of human enzymes upon Pfam functional annotation
    Matteo Manfredi, Gabriele Vazzana, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio · 2025 · Computational and Structural Biotechnology Journal
96. In silico prediction of variant effects: promises and limitations for precision plant breeding
    Janek Sendrowski, Thomas M Bataillon, Guillaume P. Ramstein · 2025 · Theoretical and Applied Genetics
97. Benchmarking protein structure predictors to assist machine learning-guided peptide discovery
    Victor Daniel Aldas-Bulos, Fabien Plisson · 2023 · Digital Discovery
98. Linear-Scaling Kernels for Protein Sequences and Small Molecules Outperform Deep Learning While Providing Uncertainty Quantitation and Improved Interpretability
    Jonathan Parkinson, Wei Wang · 2023 · Journal of Chemical Information and Modeling
99. Deep learning-enabled design of synthetic orthologs of a signaling protein
    Xinran Lian, Niksa Praljak, Subu K. Subramanian, Sarah Wasinger, Rama Ranganathan, Andrew L. Ferguson · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
100. Multi-Modal Large Language Model Enables Protein Function Prediction
     Mingjia Huo, Han Wen Guo, Xingyi Cheng, Digvijay Singh, Hamidreza Rahmani, Shen Li, Philipp Gerlof, Trey Ideker, Danielle Ann Grotjahn, Elizabeth Villa et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)