Linking protein structural and functional change to mutation using amino acid networks
出版年份 2022 全文链接
标题
Linking protein structural and functional change to mutation using amino acid networks
作者
关键词
Point mutation, Protein structure, Mutation detection, Structural proteins, Protein sequencing, Protein structure networks, Proteomic databases, Substitution mutation
出版物
PLoS One
Volume 17, Issue 1, Pages e0261829
出版商
Public Library of Science (PLoS)
发表日期
2022-01-22
DOI
10.1371/journal.pone.0261829
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
- (2021) Xianggen Liu et al. PLoS Computational Biology
- Improved protein structure prediction using potentials from deep learning
- (2020) Andrew W. Senior et al. NATURE
- Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding
- (2020) Tyler N. Starr et al. CELL
- Using deep mutational scanning to benchmark variant effect predictors and identify disease mutations
- (2020) Benjamin J Livesey et al. Molecular Systems Biology
- Sex Differences in Gene Expression and Regulatory Networks across 29 Human Tissues
- (2020) Camila M. Lopes-Ramos et al. Cell Reports
- Establishing a Framework of Using Residue–Residue Interactions in Protein Difference Network Analysis
- (2019) Xin-Qiu Yao et al. Journal of Chemical Information and Modeling
- Determining protein structures using deep mutagenesis
- (2019) Jörn M. Schmiedel et al. NATURE GENETICS
- Advances in protein structure prediction and design
- (2019) Brian Kuhlman et al. NATURE REVIEWS MOLECULAR CELL BIOLOGY
- Protein structure-based drug design: from docking to molecular dynamics
- (2018) Paweł Śledź et al. CURRENT OPINION IN STRUCTURAL BIOLOGY
- Application of protoplast technology to CRISPR/Cas9 mutagenesis: from single-cell mutation detection to mutant plant regeneration
- (2018) Choun-Sea Lin et al. PLANT BIOTECHNOLOGY JOURNAL
- Rationally Designed Sensing Selectivity and Sensitivity of an Aerolysin Nanopore via Site-Directed Mutagenesis
- (2018) Ya-Qian Wang et al. ACS Sensors
- In proteins, the structural responses of a position to mutation rely on the Goldilocks principle: not too many links, not too few
- (2018) Rodrigo Dorantes Gilardi et al. PHYSICAL CHEMISTRY CHEMICAL PHYSICS
- Somatic Gene Editing of GUCY2D by AAV-CRISPR/Cas9 Alters Retinal Structure and Function in Mouse and Macaque
- (2018) K. Tyler McCullough et al. HUMAN GENE THERAPY
- Protein Data Bank: the single global archive for 3D macromolecular structure data
- (2018) et al. NUCLEIC ACIDS RESEARCH
- T5 exonuclease-dependent assembly offers a low-cost method for efficient cloning and site-directed mutagenesis
- (2018) Yongzhen Xia et al. NUCLEIC ACIDS RESEARCH
- A Single Active Site Mutation in the Pikromycin Thioesterase Generates a More Effective Macrocyclization Catalyst
- (2017) Aaron A. Koch et al. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
- Structural basis of CRISPR–SpyCas9 inhibition by an anti-CRISPR protein
- (2017) De Dong et al. NATURE
- The flavivirus capsid protein: Structure, function and perspectives towards drug design
- (2017) Edson R.A. Oliveira et al. VIRUS RESEARCH
- NAPS: Network Analysis of Protein Structures
- (2016) Broto Chakrabarty et al. NUCLEIC ACIDS RESEARCH
- Protein structural robustness to mutations: an in silico investigation
- (2016) Mounia Achoch et al. PHYSICAL CHEMISTRY CHEMICAL PHYSICS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Uncovering disease-disease relationships through the incomplete interactome
- (2015) J. Menche et al. SCIENCE
- The construction of an amino acid network for understanding protein structure and function
- (2014) Wenying Yan et al. AMINO ACIDS
- Alignment-free protein interaction network comparison
- (2014) Waqar Ali et al. BIOINFORMATICS
- The robustness and innovability of protein folds
- (2014) Ágnes Tóth-Petróczy et al. CURRENT OPINION IN STRUCTURAL BIOLOGY
- Deep mutational scanning: a new style of protein science
- (2014) Douglas M Fowler et al. NATURE METHODS
- Measuring the activity of protein variants on a large scale using deep mutational scanning
- (2014) Douglas M Fowler et al. Nature Protocols
- Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era
- (2013) H. Kamisetty et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Protein Contact Networks: An Emerging Paradigm in Chemistry
- (2012) L. Di Paola et al. CHEMICAL REVIEWS
- The Protein-Folding Problem, 50 Years On
- (2012) K. A. Dill et al. SCIENCE
- A Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes
- (2012) D. G. MacArthur et al. SCIENCE
- Protein Structural Modularity and Robustness Are Associated with Evolvability
- (2011) Mary M. Rorick et al. Genome Biology and Evolution
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families
- (2011) F. Morcos et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Deep mutational scanning: assessing protein function on a massive scale
- (2011) Carlos L. Araya et al. TRENDS IN BIOTECHNOLOGY
- Biopython: freely available Python tools for computational molecular biology and bioinformatics
- (2009) P. J. A. Cock et al. BIOINFORMATICS
- Protein Sectors: Evolutionary Units of Three-Dimensional Structure
- (2009) Najeeb Halabi et al. CELL
- The sequence–structure relationship and protein function prediction
- (2009) M I Sadowski et al. CURRENT OPINION IN STRUCTURAL BIOLOGY
- Stability effects of mutations and protein evolvability
- (2009) Nobuhiko Tokuriki et al. CURRENT OPINION IN STRUCTURAL BIOLOGY
- Exploring protein fitness landscapes by directed evolution
- (2009) Philip A. Romero et al. NATURE REVIEWS MOLECULAR CELL BIOLOGY
- The Protein Folding Problem
- (2008) Ken A. Dill et al. Annual Review of Biophysics
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