PRIDB: a protein–RNA interface database
· PDF 檔案PRIDB: a protein–RNA interface database Benjamin A. Lewis 1,2, *, Rasna R. Walia 1,3 , Michael Terribilini 4 , Jeff Ferguson 5 , Charles Zheng 5 , Vasant Honavar 1,3 and Drena Dobbs 1,2
Biology:Protein-RNA interface database
The Protein–RNA Interface Database (PRIDB) is a database of protein–RNA interfaces extracted from the Protein Data Bank. See also RNA-binding protein Protein Data Bank References ↑ 1.0 1.1 Lewis, Benjamin A; Walia Rasna R; Terribilini Michael; Ferguson
Assembly of an Exceptionally Stable RNA Tertiary …
Solvent accessibility mapping reveals that, in the absence of P5abc, the intron RNA maintains a nativelike fold but its active-site helices are not tightly packed. Upon binding of P5abc, the catalytic core becomes more tightly packed through indirect effects of the tertiary interface formation.
Improving protein-RNA interface prediction by …
We test Hom-PRIP on a benchmark dataset of 199 proteins and compare it with the state-of-the-art protein-RNA interface prediction methods. Our results show that HomPRIP can reliably identify protein-RNA interface residues in 71% of test proteins with at least one putative sequence homolog passing the similarity thresholds of HomPRIP.
RNA Interference (RNAi) – HOPES Huntington’s Disease …
RNA is introduced into the cell and binds to and destroys its mRNA target. Scientists can tailor make pieces of RNA that are complementary (matched up) to a specific strand of mRNA . In some organisms, the whole strand of complementary RNA can be introduced and an enzyme called dicer cuts it up into small fragments once it is inside the cell .
MLSeq: Machine Learning Interface to RNA-Seq Data
· PDF 檔案MLSeq: Machine Learning Interface to RNA-Seq Data 1Introduction With the recent developments in molecular biology, it is feasible to measure the expression levels of thousands of genes simultaneously. Using this information, one major task is the gene
How RNA-Binding Proteins Interact with RNA: Molecules …
Amino acid residue doublet propensity in the protein-RNA interface and its application to RNA interface prediction. Nucleic Acids Research 34, 6450–6460. [Europe PMC free article] [Abstract] [Google Scholar] Kljashtorny V, Nikonov S, Ovchinnikov L, Lyabin D
Identification of a Conserved RNA-dependent RNA …
Dengue virus, an ∼10.7-kb positive-sense RNA virus, is the most common arthropod-communicated pathogen in the world. Despite dengue’s clear epidemiological importance, mechanisms for its replication remain elusive. Here, we probed the entire dengue genome for interactions with viral RNA-dependent RNA polymerase (RdRp), and we identified the dominant interaction as a loop-forming ACAG motif
(PDF) Improving the State of the Art in Machine Learning …
Academia.edu is a platform for academics to share research papers. Improving the State of the Art in Machine Learning Methods for Protein-RNA Interface Prediction
Center for Molecular Biology of RNA
One notable example lies at the interface between the study of RNA structure and its biological functions. The presence of the UCSC Genomics Institute, faculty of which are represented in the RNA Center, provides a unique and powerful infrastructure for connecting experimental RNA science with computational biology.
Bioengineering
interactions of RNA with NP (RNA-nanobio interface) and how that impacts the structure, function, delivery, and activity of the RNA. Here, we attempt to summarize the state-of-the-art in this new and exciting field, and to lay out potential directions for
Elucidating the RNA Nano–Bio Interface: Mechanisms …
Understanding the RNA nano–bio interface is critical to advance RNA based therapeutics. A relevant RNA polyinosinic:cytidilic acid (poly I:C) is perhaps the best studied in clinical trials and is now considered an antimetastatic RNA targeting agent. Also, zinc oxide nanoparticle (ZnO NP) has well-known anticancer activity. In this work, we explore the RNA nano–bio interface of poly I:C
Protein-RNA Interaction Interface Prediction and Design
Protein-RNA Interaction Interface Prediction and Design HUANG Yang-Yu, YANG Xiu-Feng, LI Hao-Tian, JI Xiao-Feng, CHENG Hong-Li, ZHAO Yun-Jie, GUO Da-Chuan, LI Lin, LIU Shi-Yong Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, P. R. China