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Relevant bibliographies by topics / Protein-RNA docking

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Journal articles

Academic literature on the topic 'Protein-RNA docking'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Protein-RNA docking"

1

Arnautova, Yelena A., Ruben Abagyan, and Maxim Totrov. "Protein-RNA Docking Using ICM." Journal of Chemical Theory and Computation 14, no. 9 (2018): 4971–84. http://dx.doi.org/10.1021/acs.jctc.8b00293.

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2

He, Jiahua, Huanyu Tao, and Sheng-You Huang. "Protein-ensemble–RNA docking by efficient consideration of protein flexibility through homology models." Bioinformatics 35, no. 23 (2019): 4994–5002. http://dx.doi.org/10.1093/bioinformatics/btz388.

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AbstractMotivationGiven the importance of protein–ribonucleic acid (RNA) interactions in many biological processes, a variety of docking algorithms have been developed to predict the complex structure from individual protein and RNA partners in the past decade. However, due to the impact of molecular flexibility, the performance of current methods has hit a bottleneck in realistic unbound docking. Pushing the limit, we have proposed a protein-ensemble–RNA docking strategy to explicitly consider the protein flexibility in protein–RNA docking through an ensemble of multiple protein structures, w

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3

Delgado Blanco, Javier, Leandro G. Radusky, Damiano Cianferoni, and Luis Serrano. "Protein-assisted RNA fragment docking (RnaX) for modeling RNA–protein interactions using ModelX." Proceedings of the National Academy of Sciences 116, no. 49 (2019): 24568–73. http://dx.doi.org/10.1073/pnas.1910999116.

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RNA–protein interactions are crucial for such key biological processes as regulation of transcription, splicing, translation, and gene silencing, among many others. Knowing where an RNA molecule interacts with a target protein and/or engineering an RNA molecule to specifically bind to a protein could allow for rational interference with these cellular processes and the design of novel therapies. Here we present a robust RNA–protein fragment pair-based method, termed RnaX, to predict RNA-binding sites. This methodology, which is integrated into the ModelX tool suite (http://modelx.crg.es), take

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4

Pérez-Cano, Laura, Miguel Romero-Durana, and Juan Fernández-Recio. "Structural and energy determinants in protein-RNA docking." Methods 118-119 (April 2017): 163–70. http://dx.doi.org/10.1016/j.ymeth.2016.11.001.

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5

Zhang, Zhao, Lin Lu, Yue Zhang, et al. "A combinatorial scoring function for protein-RNA docking." Proteins: Structure, Function, and Bioinformatics 85, no. 4 (2017): 741–52. http://dx.doi.org/10.1002/prot.25253.

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6

Zheng, Jinfang, Xu Hong, Juan Xie, Xiaoxue Tong, and Shiyong Liu. "P3DOCK: a protein–RNA docking webserver based on template-based and template-free docking." Bioinformatics 36, no. 1 (2019): 96–103. http://dx.doi.org/10.1093/bioinformatics/btz478.

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AbstractMotivationThe main function of protein–RNA interaction is to regulate the expression of genes. Therefore, studying protein–RNA interactions is of great significance. The information of three-dimensional (3D) structures reveals that atomic interactions are particularly important. The calculation method for modeling a 3D structure of a complex mainly includes two strategies: free docking and template-based docking. These two methods are complementary in protein–protein docking. Therefore, integrating these two methods may improve the prediction accuracy.ResultsIn this article, we compare

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7

Setny, Piotr, and Martin Zacharias. "A coarse-grained force field for Protein–RNA docking." Nucleic Acids Research 39, no. 21 (2011): 9118–29. http://dx.doi.org/10.1093/nar/gkr636.

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8

Nithin, Chandran, Sunandan Mukherjee, and Ranjit Prasad Bahadur. "A non-redundant protein-RNA docking benchmark version 2.0." Proteins: Structure, Function, and Bioinformatics 85, no. 2 (2016): 256–67. http://dx.doi.org/10.1002/prot.25211.

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9

Wicaksono, Adhityo, and Arli Aditya Parikesit. "Molecular Docking and Dynamics of SARS-CoV-2 Programmed Ribosomal Frameshifting RNA and Ligands for RNA-Targeting Alkaloids Prospecting." HAYATI Journal of Biosciences 30, no. 6 (2023): 1025–35. http://dx.doi.org/10.4308/hjb.30.6.1025-1035.

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RNA-ligand docking is a part of computational biology, which is currently lowly recognized compared to the protein-ligand docking procedure commonly applied for drug discovery. This in silico study aims to create a simplified protocol for RNA-ligand docking, which is applicable to RNA-targeting small molecular drug screening. Four alkaloids (berberine, colchicine, nicotine, and tomatine) were subjected to this study and contended against the SARS-CoV-2 genomic RNA -1 PRF component targeting control drug, merafloxacin, including two known intercalator berberine and colchicine, a small alkaloid

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10

Li, Yaozong, Jie Shen, Xianqiang Sun, Weihua Li, Guixia Liu, and Yun Tang. "Accuracy Assessment of Protein-Based Docking Programs against RNA Targets." Journal of Chemical Information and Modeling 50, no. 6 (2010): 1134–46. http://dx.doi.org/10.1021/ci9004157.

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