Discovery of a cryptic allosteric site in Ebola’s ‘undruggable’ VP35 protein using simulations and experiments

AbstractMany proteins are classified as ‘undruggable,’ especially those that engage in protein-protein and protein-nucleic acid interactions. Discovering ‘cryptic’ pockets that are absent in available structures but open due to protein dynamics could provide new druggable sites. Here, we integrate atomically-detailed simulations and biophysical experiments to search for cryptic pockets in viral protein 35 (VP35) from the highly lethal Ebola virus. VP35 plays multiple essential roles in Ebola’s replication cycle, including binding the viral RNA genome to block a host’s innate immunity. However, VP35 has so far proved undruggable. Using adaptive sampling simulations and allosteric network detection algorithms, we uncover a cryptic pocket that is allosterically coupled to VP35’s key RNA-binding interface. Experimental tests corroborate the predicted pocket and confirm that stabilizing the open form allosterically disrupts RNA binding. These results demonstrate simulations’ power to characterize hidden conformations and dynamics, uncovering cryptic pockets and allostery that present new therapeutic opportunities.

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Systematic comparison and prediction of the effects of missense mutations on protein-DNA and protein-RNA interactions

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008951 ◽

2021 ◽

Vol 17 (4) ◽

pp. e1008951

Author(s):

Yao Jiang ◽

Hui-Fang Liu ◽

Rong Liu

Keyword(s):

Rna Binding ◽

Rna Binding Proteins ◽

Binding Free Energy ◽

Structural Features ◽

Missense Mutations ◽

Binding Affinities ◽

Systematic Comparison ◽

Link Type ◽

Protein Nucleic Acid ◽

Nucleic Acid Interactions

The binding affinities of protein-nucleic acid interactions could be altered due to missense mutations occurring in DNA- or RNA-binding proteins, therefore resulting in various diseases. Unfortunately, a systematic comparison and prediction of the effects of mutations on protein-DNA and protein-RNA interactions (these two mutation classes are termed MPDs and MPRs, respectively) is still lacking. Here, we demonstrated that these two classes of mutations could generate similar or different tendencies for binding free energy changes in terms of the properties of mutated residues. We then developed regression algorithms separately for MPDs and MPRs by introducing novel geometric partition-based energy features and interface-based structural features. Through feature selection and ensemble learning, similar computational frameworks that integrated energy- and nonenergy-based models were established to estimate the binding affinity changes resulting from MPDs and MPRs, but the selected features for the final models were different and therefore reflected the specificity of these two mutation classes. Furthermore, the proposed methodology was extended to the identification of mutations that significantly decreased the binding affinities. Extensive validations indicated that our algorithm generally performed better than the state-of-the-art methods on both the regression and classification tasks. The webserver and software are freely available at http://liulab.hzau.edu.cn/PEMPNI and https://github.com/hzau-liulab/PEMPNI.

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Quantitative analysis of the cooperativity of protein-nucleic acid interactions by electron microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010014316x ◽

1986 ◽

Vol 44 ◽

pp. 308-309

Author(s):

Pamela S. Hicks ◽

Christopher L. Andrews ◽

David G. Bear

Keyword(s):

Nucleic Acid ◽

Rna Binding ◽

Direct Method ◽

Bacteriophage T4 ◽

Specific Protein ◽

Titration Data ◽

Protein Nucleic Acid ◽

Gene 32 ◽

Nucleic Acid Interactions ◽

T4 Gene 32 Protein

It is common for sing1e-stranded nucleic acid finding proteins to bind polynucleotides cooperatively. The parameter ω is used to describe the component of the association binding constant that is due to cooperative interactions between protein molecules on the polynucleotide lattice; ω is 1 for noncooperative binding, while ω can be as high as 103-104 for highly cooperative proteins such as bacteriophage T4 gene 32 protein. In the past, to has been determined by computer fitting of spectroscopic titration data. It has been suggested that electrom microscopy would provide a more direct method for estimation of the cooperativity parameter. An equation can be derived that relates the experimentally obtained average protein cluster size (at a specific protein/RNA saturation ratio) to ω. The only other parameter required for the calculation is the RNA binding site size obtained from stoichiometric titration measurements.

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Crystal structure of the human heterogeneous ribonucleoprotein A18 RNA-recognition motif

Acta Crystallographica Section F Structural Biology Communications ◽

10.1107/s2053230x17003454 ◽

2017 ◽

Vol 73 (4) ◽

pp. 209-214 ◽

Cited By ~ 6

Author(s):

Katherine Coburn ◽

Zephan Melville ◽

Ehson Aligholizadeh ◽

Braden M. Roth ◽

Kristen M. Varney ◽

...

Keyword(s):

Crystal Structure ◽

Rna Binding ◽

Rna Binding Proteins ◽

Rna Recognition Motif ◽

Rna Recognition ◽

Hnrnp A1 ◽

Structure Based Drug Design ◽

Recognition Motif ◽

Protein Nucleic Acid ◽

Nucleic Acid Interactions

The heterogeneous ribonucleoprotein A18 (hnRNP A18) is upregulated in hypoxic regions of various solid tumors and promotes tumor growthviathe coordination of mRNA transcripts associated with pro-survival genes. Thus, hnRNP A18 represents an important therapeutic target in tumor cells. Presented here is the first X-ray crystal structure to be reported for the RNA-recognition motif of hnRNP A18. By comparing this structure with those of homologous RNA-binding proteins (i.e.hnRNP A1), three residues on one face of an antiparallel β-sheet (Arg48, Phe50 and Phe52) and one residue in an unstructured loop (Arg41) were identified as likely to be involved in protein–nucleic acid interactions. This structure helps to serve as a foundation for biophysical studies of this RNA-binding protein and structure-based drug-design efforts for targeting hnRNP A18 in cancer, such as malignant melanoma, where hnRNP A18 levels are elevated and contribute to disease progression.

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Snapshot blotting: The transfer of nucleic acids and nucleoprotein complexes from electrophoresis gels to EM grids

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100124215 ◽

1992 ◽

Vol 50 (1) ◽

pp. 762-763

Author(s):

Stephen D. Jett

Keyword(s):

Nucleic Acid ◽

Nucleic Acids ◽

Nucleic Acid Binding ◽

Mobility Shift ◽

Carbon Coated ◽

Nucleoprotein Complexes ◽

Mobility Shift Assay ◽

Protein Nucleic Acid ◽

Gel Mobility Shift ◽

Nucleic Acid Interactions

The electrophoresis gel mobility shift assay is a popular method for the study of protein-nucleic acid interactions. The binding of proteins to DNA is characterized by a reduction in the electrophoretic mobility of the nucleic acid. Binding affinity, stoichiometry, and kinetics can be obtained from such assays; however, it is often desirable to image the various species in the gel bands using TEM. Present methods for isolation of nucleoproteins from gel bands are inefficient and often destroy the native structure of the complexes. We have developed a technique, called “snapshot blotting,” by which nucleic acids and nucleoprotein complexes in electrophoresis gels can be electrophoretically transferred directly onto carbon-coated grids for TEM imaging.

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Compendium of Methods to Uncover RNA-Protein Interactions In Vivo

Methods and Protocols ◽

10.3390/mps4010022 ◽

2021 ◽

Vol 4 (1) ◽

pp. 22

Author(s):

Mrinmoyee Majumder ◽

Viswanathan Palanisamy

Keyword(s):

Gene Expression ◽

Protein Interactions ◽

Rna Binding ◽

Rna Binding Proteins ◽

Expression Patterns ◽

Control Of Gene Expression ◽

Regulatory Pathways ◽

Advantages And Disadvantages ◽

Protein Nucleic Acid

Control of gene expression is critical in shaping the pro-and eukaryotic organisms’ genotype and phenotype. The gene expression regulatory pathways solely rely on protein–protein and protein–nucleic acid interactions, which determine the fate of the nucleic acids. RNA–protein interactions play a significant role in co- and post-transcriptional regulation to control gene expression. RNA-binding proteins (RBPs) are a diverse group of macromolecules that bind to RNA and play an essential role in RNA biology by regulating pre-mRNA processing, maturation, nuclear transport, stability, and translation. Hence, the studies aimed at investigating RNA–protein interactions are essential to advance our knowledge in gene expression patterns associated with health and disease. Here we discuss the long-established and current technologies that are widely used to study RNA–protein interactions in vivo. We also present the advantages and disadvantages of each method discussed in the review.

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