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Literature DB >> 35046575

Can AlphaFold2 predict the impact of missense mutations on structure?

Gwen R Buel¹, Kylie J Walters².

Abstract

Entities: Chemical

Mesh：

Substances：
Proteins
Ubiquitin

Year: 2022 PMID： 35046575 DOI： 10.1038/s41594-021-00714-2

Source DB: PubMed Journal: Nat Struct Mol Biol ISSN： 1545-9985 Impact factor: 15.369

Keyword Cloud
Cited

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11 in total

1. Complementing machine learning-based structure predictions with native mass spectrometry.

Authors: Timothy M Allison; Matteo T Degiacomi; Erik G Marklund; Luca Jovine; Arne Elofsson; Justin L P Benesch; Michael Landreh
Journal: Protein Sci Date: 2022-06 Impact factor: 6.993

2. Proteins' Evolution upon Point Mutations.

Authors: Jorge A Vila
Journal: ACS Omega Date: 2022-04-14

3. AlphaFold2: A Role for Disordered Protein/Region Prediction?

Authors: Carter J Wilson; Wing-Yiu Choy; Mikko Karttunen
Journal: Int J Mol Sci Date: 2022-04-21 Impact factor: 6.208

4. Where to From Here?

Authors: Robert Schleif; Manuel Espinosa
Journal: Front Mol Biosci Date: 2022-03-25

Review 5. P-Loop Channels: Experimental Structures, and Physics-Based and Neural Networks-Based Models.

Authors: Denis B Tikhonov; Boris S Zhorov
Journal: Membranes (Basel) Date: 2022-02-16

Review 6. Uncertainty quantification: Can we trust artificial intelligence in drug discovery?

Authors: Jie Yu; Dingyan Wang; Mingyue Zheng
Journal: iScience Date: 2022-07-21

7. Structural Protein Effects Underpinning Cognitive Developmental Delay of the PURA p.Phe233del Mutation Modelled by Artificial Intelligence and the Hybrid Quantum Mechanics-Molecular Mechanics Framework.

Authors: Juan Javier López-Rivera; Luna Rodríguez-Salazar; Alejandro Soto-Ospina; Carlos Estrada-Serrato; David Serrano; Henry Mauricio Chaparro-Solano; Olga Londoño; Paula A Rueda; Geraldine Ardila; Andrés Villegas-Lanau; Marcela Godoy-Corredor; Mauricio Cuartas; Jorge I Vélez; Oscar M Vidal; Mario A Isaza-Ruget; Mauricio Arcos-Burgos
Journal: Brain Sci Date: 2022-06-30

Can AlphaFold2 predict the impact of missense mutations on structure?

1. Complementing machine learning-based structure predictions with native mass spectrometry.

2. Proteins' Evolution upon Point Mutations.

3. AlphaFold2: A Role for Disordered Protein/Region Prediction?

4. Where to From Here?

Review 5. P-Loop Channels: Experimental Structures, and Physics-Based and Neural Networks-Based Models.

Review 6. Uncertainty quantification: Can we trust artificial intelligence in drug discovery?

7. Structural Protein Effects Underpinning Cognitive Developmental Delay of the PURA p.Phe233del Mutation Modelled by Artificial Intelligence and the Hybrid Quantum Mechanics-Molecular Mechanics Framework.

Review 8. AlphaFold, Artificial Intelligence (AI), and Allostery.

9. PHEX^L222P Mutation Increases Phex Expression in a New ENU Mouse Model for XLH Disease.

Review 10. Big data in basic and translational cancer research.

Can AlphaFold2 predict the impact of missense mutations on structure?

1. Complementing machine learning-based structure predictions with native mass spectrometry.

2. Proteins' Evolution upon Point Mutations.

3. AlphaFold2: A Role for Disordered Protein/Region Prediction?

4. Where to From Here?

Review 5. P-Loop Channels: Experimental Structures, and Physics-Based and Neural Networks-Based Models.

Review 6. Uncertainty quantification: Can we trust artificial intelligence in drug discovery?

7. Structural Protein Effects Underpinning Cognitive Developmental Delay of the PURA p.Phe233del Mutation Modelled by Artificial Intelligence and the Hybrid Quantum Mechanics-Molecular Mechanics Framework.

Review 8. AlphaFold, Artificial Intelligence (AI), and Allostery.

9. PHEXL222P Mutation Increases Phex Expression in a New ENU Mouse Model for XLH Disease.

Review 10. Big data in basic and translational cancer research.

9. PHEX^L222P Mutation Increases Phex Expression in a New ENU Mouse Model for XLH Disease.