Deep mutational scanning: a new style of protein science

Cited by (1,003)

Items 201–300 of 1,003

1. High-throughput discovery of trafficking-deficient variants in the cardiac potassium channel KV11.1
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2. Deep mutational scanning identifies SARS-CoV-2 Nucleocapsid escape mutations of currently available rapid antigen tests
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3. A comprehensive map of human glucokinase variant activity
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4. The Generation and Exploitation of Protein Mutability Landscapes for Enzyme Engineering
   Jan‐Ytzen van der Meer, Lieuwe Biewenga, Gerrit J. Poelarends · 2016 · ChemBioChem
5. Epistasis in a Fitness Landscape Defined by Antibody-Antigen Binding Free Energy
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6. Functional Constraint Profiling of a Viral Protein Reveals Discordance of Evolutionary Conservation and Functionality
   Nicholas C. Wu, C. Anders Olson, Yushen Du, Shuai Le, Kevin Tran, Roland Remenyi, Danyang Gong, Laith Q. Al‐Mawsawi, Hangfei Qi, Ting-Ting Wu et al. · 2015 · PLoS Genetics
7. Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins
   Leander, Megan, Liu, Zhuang, Cui, Qiang, Raman, Srivatsan · 2022 · eLife
8. DeMaSk: a deep mutational scanning substitution matrix and its use for variant impact prediction
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9. Linking genome variants to disease: scalable approaches to test the functional impact of human mutations
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10. Linking protein structural and functional change to mutation using amino acid networks
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11. Enzyme engineering in biomimetic compartments
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12. Engineering Stability, Viscosity, and Immunogenicity of Antibodies by Computational Design
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13. Deep mutational scan of a drug efflux pump reveals its structure–function landscape
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14. Creation of Novel Protein Variants with CRISPR/Cas9-Mediated Mutagenesis: Turning a Screening By-Product into a Discovery Tool
    Katherine F. Donovan, Mudra Hegde, Meagan E. Sullender, Emma W Vaimberg, Cory M. Johannessen, David E. Root, John G. Doench · 2017 · PLoS ONE
15. CRISPR-Cas9–mediated saturated mutagenesis screen predicts clinical drug resistance with improved accuracy
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16. Predictive constitutive modelling of arteries by deep learning
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17. Pervasive epistasis exposes intramolecular networks in adaptive enzyme evolution
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18. Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans
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19. In vivo hypermutation and continuous evolution
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20. Challenges and opportunities associated with rare-variant pharmacogenomics
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21. Interpretable and explainable predictive machine learning models for data-driven protein engineering
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22. Comprehensive Sequence-Flux Mapping of a Levoglucosan Utilization Pathway in E. coli
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23. Deep mutational scanning of SARS-CoV-2 Omicron BA.2.86 and epistatic emergence of the KP.3 variant
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24. High-Throughput Screening in Protein Engineering: Recent Advances and Future Perspectives
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25. Evolutionary history of ATP‐binding cassette proteins
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26. UMI-linked consensus sequencing enables phylogenetic analysis of directed evolution
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27. Deep mutational scanning for therapeutic antibody engineering
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28. Comprehensive interrogation of the ADAR2 deaminase domain for engineering enhanced RNA editing activity and specificity
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29. Comprehensive deletion landscape of CRISPR-Cas9 identifies minimal RNA-guided DNA-binding modules
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30. Addressing epistasis in the design of protein function
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31. Variant effect predictor correlation with functional assays is reflective of clinical classification performance
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33. alignparse: A Python package for parsing complex features from high-throughput long-read sequencing
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34. Shifting Fitness and Epistatic Landscapes Reflect Trade-offs along an Evolutionary Pathway
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35. Deep Mutational Scan of an SCN5A Voltage Sensor
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36. Lynch syndrome, molecular mechanisms and variant classification
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37. Collateral fitness effects of mutations
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38. Chance and pleiotropy dominate genetic diversity in complex bacterial environments
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39. Saturation genome editing-based clinical classification of BRCA2 variants
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40. Deep scanning lysine metabolism in Escherichia coli
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41. A Statistical Guide to the Design of Deep Mutational Scanning Experiments
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42. Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning
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43. SARS-CoV-2 E484K Mutation Narrative Review: Epidemiology, Immune Escape, Clinical Implications, and Future Considerations
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44. A combinatorially complete epistatic fitness landscape in an enzyme active site
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45. Enhancing computational enzyme design by a maximum entropy strategy
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46. Recent Advances in Machine Learning Variant Effect Prediction Tools for Protein Engineering
    Jesse Horne, Diwakar Shukla · 2022 · Industrial & Engineering Chemistry Research
47. Deep mutational scanning of essential bacterial proteins can guide antibiotic development
    Dewachter, Liselot, Brooks, Aaron N., Noon, Katherine, Cialek, Charlotte, Clark-ElSayed, Alia, Schalck, Thomas, Krishnamurthy, Nandini, Versées, Wim, Vranken, Wim, Michiels, Jan · 2023 · Nature Communications
48. SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs
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49. Deep mutational scanning and machine learning for the analysis of antimicrobial-peptide features driving membrane selectivity
    Justin R. Randall, Luiz Carlos Vieira, Claus O. Wilke, Bryan W. Davies · 2024 · Nature Biomedical Engineering
50. α-Synuclein Pathology in Synucleinopathies: Mechanisms, Biomarkers, and Therapeutic Challenges
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51. Unbiased Fitness Estimation of Pooled Barcode or Amplicon Sequencing Studies
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52. CRISPR/Cas9 recombineering‐mediated deep mutational scanning of essential genes in Escherichia coli
    Alaksh Choudhury, Jacob A. Fenster, Reilly G. Fankhauser, Joel L. Kaar, Olivier Tenaillon, Ryan T. Gill · 2020 · Molecular Systems Biology
53. Correspondence between functional scores from deep mutational scans and predicted effects on protein stability
    Gerasimavicius, Lukas, Livesey, Benjamin J., Marsh, Joseph A. · 2023 · Protein Science
54. A dual-reporter system for investigating and optimizing protein translation and folding in E. coli
    Ariane Zutz, Louise Hamborg, Lasse Ebdrup Pedersen, Maher M. Kassem, Elena Papaleo, Anna Koza, Markus J. Herrgård, Sheila Ingemann Jensen, Kaare Teilum, Kresten Lindorff‐Larsen et al. · 2021 · Nature Communications
55. An end-to-end framework for the prediction of protein structure and fitness from single sequence
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56. Helicase-assisted continuous editing for programmable mutagenesis of endogenous genomes
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57. Genetically Engineered Proteins to Improve Biomass Conversion: New Advances and Challenges for Tailoring Biocatalysts
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58. Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods
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59. Scaling Unlocks Broader Generation and Deeper Functional Understanding of Proteins
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60. A Gradient of Sitewise Diversity Promotes Evolutionary Fitness for Binder Discovery in a Three-Helix Bundle Protein Scaffold
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61. Molecular Fitness Landscapes from High-Coverage Sequence Profiling
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62. CRISPR-Cas9 human gene replacement and phenomic characterization in Caenorhabditis elegans to understand the functional conservation of human genes and decipher variants of uncertain significance
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63. Using protein engineering to understand and modulate aggregation
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64. Tools for computational design and high-throughput screening of therapeutic enzymes
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65. evSeq: Cost-Effective Amplicon Sequencing of Every Variant in a Protein Library
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66. Elucidating the Determinants of Polymerase Specificity by Microfluidic-Based Deep Mutational Scanning
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67. Optimization of the antimicrobial peptide Bac7 by deep mutational scanning
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68. Using Evolution to Guide Protein Engineering: The Devil IS in the Details
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69. High‐Throughput Assays to Assess the Functional Impact of Genetic Variants: A Road Towards Genomic‐Driven Medicine
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70. An Accessible Continuous-Culture Turbidostat for Pooled Analysis of Complex Libraries
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71. Fine Epitope Mapping of the CD19 Extracellular Domain Promotes Design
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72. CYP2C9 and CYP2C19 : Deep Mutational Scanning and Functional Characterization of Genomic Missense Variants
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75. Integrating molecular networks with genetic variant interpretation for precision medicine
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76. Deep Mutational Scanning Comprehensively Maps How Zika Envelope Protein Mutations Affect Viral Growth and Antibody Escape
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77. Mutation, Randomness, and Evolution
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80. The evolutionary potential of influenza A virus hemagglutinin is highly constrained by epistatic interactions with neuraminidase
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81. High-throughput identification of prefusion-stabilizing mutations in SARS-CoV-2 spike
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83. Functional characterization of 3D protein structures informed by human genetic diversity
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85. Simple mechanisms for the evolution of protein complexity
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86. Base editor screens for in situ mutational scanning at scale
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87. A Balance between Inhibitor Binding and Substrate Processing Confers Influenza Drug Resistance
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89. Improving the prediction of protein stability changes upon mutations by geometric learning and a pre-training strategy
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91. Elucidating the Molecular Determinants of Aβ Aggregation with Deep Mutational Scanning
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94. Protein Design and Variant Prediction Using Autoregressive Generative Models
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95. ProSTAGE: Predicting Effects of Mutations on Protein Stability by Using Protein Embeddings and Graph Convolutional Networks
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96. Network of epistatic interactions in an enzyme active site revealed by large-scale deep mutational scanning
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97. Structural and functional diversity of Resistance-Nodulation-Division (RND) efflux pump transporters with implications for antimicrobial resistance
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