4.6 Article

Mining Endonuclease Cleavage Determinants in Genomic Sequence Data

期刊

JOURNAL OF BIOLOGICAL CHEMISTRY
卷 286, 期 37, 页码 32617-32627

出版社

AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/jbc.M111.259572

关键词

-

资金

  1. National Institutes of Health [GM084433, RL1CA133832]
  2. Foundation for the National Institutes of Health through the Gates Foundation Grand Challenges in Global Health Initiative
  3. Howard Hughes Medical Institute

向作者/读者索取更多资源

Homing endonucleases have great potential as tools for targeted gene therapy and gene correction, but identifying variants of these enzymes capable of cleaving specific DNA targets of interest is necessary before the widespread use of such technologies is possible. We identified homologues of the LAGLIDADG homing endonuclease I-AniI and their putative target insertion sites by BLAST searches followed by examination of the sequences of the flanking genomic regions. Amino acid substitutions in these homologues that were located close to the target site DNA, and thus potentially conferring differences in target specificity, were grafted onto the I-AniI scaffold. Many of these grafts exhibited novel and unexpected specificities. These findings show that the information present in genomic data can be exploited for endonuclease specificity redesign.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Letter Dermatology

A survey of article types in the dermatology literature

Mindy D. Szeto, Steven M. Lada, Sameeha S. Husayn, Colby L. Presley, Michelle Militello, Robert P. Dellavalle

JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY (2021)

Article Biochemistry & Molecular Biology

Varying the Directionality of Protein Catalysts for Aldol and Retro-Aldol Reactions

Toshifumi Fujioka, Nobutaka Numoto, Hiroyuki Akama, Kola Shilpa, Michiko Oka, Prodip K. Roy, Yarkali Krishna, Nobutoshi Ito, David Baker, Masayuki Oda, Fujie Tanaka

Summary: The study found that the directionality of protein catalysts can be altered by replacing one amino acid. Additionally, protein catalysts from the same protein scaffold exhibit different efficiency in catalyzing aldol and retro-aldol reactions.

CHEMBIOCHEM (2022)

Article Chemistry, Multidisciplinary

Engineering an efficient and enantioselective enzyme for the Morita-Baylis-Hillman reaction

Rebecca Crawshaw, Amy E. Crossley, Linus Johannissen, Ashleigh J. Burke, Sam Hay, Colin Levy, David Baker, Sarah L. Lovelock, Anthony P. Green

Summary: The combination of computational design and directed evolution has shown to be effective in creating enzymes with new functions and catalytic mechanisms for challenging chemical transformations. Through evolutionary optimization of a primitive design, an efficient and enantioselective enzyme was developed for a specific reaction, demonstrating that intricate catalytic devices can be built to promote demanding multi-step processes not observed in nature.

NATURE CHEMISTRY (2022)

Editorial Material Biochemical Research Methods

Deep learning and protein structure modeling

Minkyung Baek, David Baker

NATURE METHODS (2022)

Review Multidisciplinary Sciences

The road to fully programmable protein catalysis

Sarah L. Lovelock, Rebecca Crawshaw, Sophie Basler, Colin Levy, David Baker, Donald Hilvert, Anthony P. Green

Summary: Designing efficient enzymes has a profound impact on chemistry, biotechnology, and medicine. Recent advances in protein engineering and computational methods have made it possible to optimize protein structures and generate efficient enzymes through laboratory evolution. Emerging methods like deep learning hold promise for improving the accuracy of protein design models.

NATURE (2022)

Article Multidisciplinary Sciences

Rotational dynamics and transition mechanisms of surface-adsorbed proteins

Shuai Zhang, Robbie Sadre, Benjamin A. Legg, Harley Pyles, Talita Perciano, E. Wes Bethel, David Baker, Oliver Rubel, James J. De Yoreo

Summary: This study directly observes and quantifies the rotational dynamics of protein nanorods on solid-water interfaces using high-speed atomic force microscopy and machine learning techniques. The findings reveal the characteristics of transitions between different angular states and provide insights into the self-assembly and other orientationally anisotropic outcomes of biomolecules at these interfaces.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2022)

Article Multidisciplinary Sciences

De novo design and directed folding of disulfide-bridged peptide heterodimers

Sicong Yao, Adam Moyer, Yiwu Zheng, Yang Shen, Xiaoting Meng, Chong Yuan, Yibing Zhao, Hongwei Yao, David Baker, Chuanliu Wu

Summary: Peptide heterodimers are functional macromolecules and molecular tools with wide applications in chemical and synthetic biology. In this study, the authors report the successful design, synthesis, and application of peptide heterodimers with mutual orthogonality through computational de novo designs and a directed disulfide pairing strategy. These heterodimers can be utilized as scaffolds for generating functional molecules, as well as chemical tools or building blocks for protein labeling and crosslinking hybrids.

NATURE COMMUNICATIONS (2022)

Article Biochemistry & Molecular Biology

Randomized gates eliminate bias in sort-seq assays

Brian L. Trippe, Buwei Huang, Erika A. DeBenedictis, Brian Coventry, Nicholas Bhattacharya, Kevin K. Yang, David Baker, Lorin Crawford

Summary: Sort-seq assays are commonly used in biological engineering to profile groups of cells based on their fluorescence characteristics. However, current methods introduce systematic bias. This study demonstrates that unbiased estimates can be obtained by incorporating randomness into the sorting process. The findings are validated through simulations and experiments, and extensions for estimating group level variances and using multi-bin sorters are described.

PROTEIN SCIENCE (2022)

Article Biotechnology & Applied Microbiology

Time-tagged ticker tapes for intracellular recordings

Dingchang Lin, Xiuyuan Li, Eric Moult, Pojeong Park, Benjamin Tang, Hao Shen, Jonathan B. B. Grimm, Natalie Falco, Bill Z. Z. Jia, David Baker, Luke D. D. Lavis, Adam E. E. Cohen

Summary: Recording the transcriptional histories of cells can provide a deeper understanding of their developmental trajectory and response to external stimuli. This study introduces an engineered protein fiber that incorporates fluorescent marks to create a ticker tape-like history. By utilizing a reporter gene and high-resolution imaging, the cellular histories can be accurately read and the absolute timing determined. The protein-based ticker tape design has the potential for massively parallel single-cell recordings of various physiological processes.

NATURE BIOTECHNOLOGY (2023)

Article Multidisciplinary Sciences

Sampling of structure and sequence space of small protein folds

Thomas W. Linsky, Kyle Noble, Autumn R. Tobin, Rachel Crow, Lauren Carter, Jeffrey L. Urbauer, David Baker, Eva-Maria Strauch

Summary: This study presents a computational platform for designing various small protein folds and sampling shape diversity. Through experimental validation of approximately 30,000 de novo protein designs, about 6,200 stable proteins were identified. The study also revealed protein folding rules and provided training data for machine learning.

NATURE COMMUNICATIONS (2022)

Article Biochemistry & Molecular Biology

A single-cell transcriptome atlas of the maturing zebrafish telencephalon

Shristi Pandey, Anna J. Moyer, Summer B. Thyme

Summary: The zebrafish telencephalon has different types of neuronal cells that regulate complex behaviors. This study analyzed single-cell transcriptomes of cells from different ages to identify the cell types and their development. The results showed that some neuronal subtypes emerge or expand in number later in development. This research provides important insights into the transcriptional signatures and development of zebrafish telencephalon.

GENOME RESEARCH (2023)

Article Multidisciplinary Sciences

Exploiting conformational dynamics to modulate the function of designed proteins

Enrico Rennella, Danny D. Sahtoe, David Baker, Lewis E. Kay

Summary: With recent advancements in calculating protein structures from amino acid sequences using AI algorithms, the next important step is to understand how dynamics is encoded in the primary protein sequence to improve function prediction. This study emphasizes the significance of dynamics in modulating the function of a designed protein called C34, which binds β-strands. By investigating the structural dynamics of C34 using NMR spectroscopy, the researchers show that manipulating conformations can enhance functionality in protein design.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2023)

Article Multidisciplinary Sciences

Peptide-binding specificity prediction using fine-tuned protein structure prediction networks

Amir Motmaen, Justas Dauparas, Minkyung Baek, Mohamad H. Abedi, David Baker, Philip Bradley

Summary: This study develops a model for predicting peptide-binding proteins and peptide-MHC interactions by adding a classifier on top of the AlphaFold network. The model shows strong generalization and excellent performance.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2023)

Article Biochemistry & Molecular Biology

Zero-shot mutation effect prediction on protein stability and function using RoseTTAFold

Sanaa Mansoor, Minkyung Baek, David Juergens, Joseph L. Watson, David Baker

Summary: The study evaluates the performance of the RFjoint model for mutation effect prediction and finds that it achieves comparable accuracy to other models without specific training. RFjoint demonstrates a broad understanding of protein sequence-structure landscapes, making it a useful tool for protein modeling.

PROTEIN SCIENCE (2023)

Article Biochemical Research Methods

Accurate prediction of protein-nucleic acid complexes using RoseTTAFoldNA

Minkyung Baek, Ryan Mchugh, Ivan Anishchenko, Hanlun Jiang, David Baker, Frank DiMaio

Summary: Protein-nucleic acid complexes have been a challenge in structure prediction, and this study introduces RoseTTAFoldNA as a method to predict their structures with high accuracy and practical value.

NATURE METHODS (2023)

暂无数据