An in silico approach to identification, categorization and prediction of nucleic acid binding proteins

Abstract The interaction between proteins and nucleic acid plays an important role in many processes, such as transcription, translation and DNA repair. The mechanisms of related biological events can be understood by exploring the function of proteins in these interactions. The number of known protein sequences has increased rapidly in recent years, but the databases for describing the structure and function of protein have unfortunately grown quite slowly. Thus, improving such databases is meaningful for predicting protein–nucleic acid interactions. Furthermore, the mechanism of related biological events, such as viral infection or designing novel drug targets, can be further understood by understanding the function of proteins in these interactions. The information for each sequence, including its function and interaction sites, were collected and identified, and a database called PNIDB was built. The proteins in PNIDB were grouped into 27 classes, such as transcription, immune system, and structural protein, etc. The function of each protein was then predicted using a machine learning method. Using our method, the predictor was trained on labeled sequences, and then the function of a protein was predicted based on the trained classifier. The prediction accuracy achieved a score of 77.43% by 10-fold cross validation.

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An in silico approach to identification, categorization and prediction of nucleic acid binding proteins

10.1101/2020.05.05.078741 ◽

2020 ◽

Author(s):

Lei Xu ◽

Shanshan Jiang ◽

Quan Zou

Keyword(s):

Nucleic Acid ◽

Drug Targets ◽

Nucleic Acid Binding ◽

Structural Protein ◽

Interaction Sites ◽

Trained Classifier ◽

Nucleic Acid Binding Proteins ◽

Protein Nucleic Acid ◽

And Function ◽

Nucleic Acid Interactions

AbstractThe interaction between proteins and nucleic acid plays an important role in many processes, such as transcription, translation and DNA repair. The mechanisms of related biological events can be understood by exploring the function of proteins in these interactions. The number of known protein sequences has increased rapidly in recent years, but the databases for describing the structure and function of protein have unfortunately grown quite slowly. Thus, improving such databases is meaningful for predicting protein-nucleic acid interactions. Furthermore, the mechanism of related biological events, such as viral infection or designing novel drug targets, can be further understood by understanding the function of proteins in these interactions. The information for each sequence, including its function and interaction sites, were collected and identified, and a database called PNIDB was built. The proteins in PNIDB were grouped into 27 classes, such as transcription, immune system, and structural protein, etc. The function of each protein was then predicted using a machine learning method. Using our method, the predictor was trained on labeled sequences, and then the function of a protein was predicted based on the trained classifier. The prediction accuracy achieved a score of 77.43% by 10-fold cross validation.Availability and ImplementationPNIDB is now fully working and can be freely accessed at: http://server.malab.cn/PNIDB/index.html. All the data are publicly available for non-commercial use, distribution, and reproduction in any [email protected]

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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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Bioinformatic Analysis of Structure and Function of LIM Domains of Human Zyxin Family Proteins

International Journal of Molecular Sciences ◽

10.3390/ijms22052647 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2647

Author(s):

M. Quadir Siddiqui ◽

Maulik D. Badmalia ◽

Trushar R. Patel

Keyword(s):

Nucleic Acid ◽

Nuclear Export ◽

Consensus Sequence ◽

Nuclear Export Signal ◽

Bioinformatic Analysis ◽

Nucleic Acid Binding ◽

Protein Protein Interaction ◽

Lim Domains ◽

Protein Nucleic Acid ◽

And Function

Members of the human Zyxin family are LIM domain-containing proteins that perform critical cellular functions and are indispensable for cellular integrity. Despite their importance, not much is known about their structure, functions, interactions and dynamics. To provide insights into these, we used a set of in-silico tools and databases and analyzed their amino acid sequence, phylogeny, post-translational modifications, structure-dynamics, molecular interactions, and functions. Our analysis revealed that zyxin members are ohnologs. Presence of a conserved nuclear export signal composed of LxxLxL/LxxxLxL consensus sequence, as well as a possible nuclear localization signal, suggesting that Zyxin family members may have nuclear and cytoplasmic roles. The molecular modeling and structural analysis indicated that Zyxin family LIM domains share similarities with transcriptional regulators and have positively charged electrostatic patches, which may indicate that they have previously unanticipated nucleic acid binding properties. Intrinsic dynamics analysis of Lim domains suggest that only Lim1 has similar internal dynamics properties, unlike Lim2/3. Furthermore, we analyzed protein expression and mutational frequency in various malignancies, as well as mapped protein-protein interaction networks they are involved in. Overall, our comprehensive bioinformatic analysis suggests that these proteins may play important roles in mediating protein-protein and protein-nucleic acid interactions.

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PROTEIN-NUCLEIC ACID INTERACTIONS: INTEGRATING STRUCTURE, SEQUENCE, AND FUNCTION – Session Introduction

Biocomputing 2008 ◽

10.1142/9789812776136_0042 ◽

2007 ◽

Author(s):

MARTHA L. BULYK ◽

ALEXANDER J. HARTEMINK ◽

ERNEST FRAENKEL ◽

YAEL MANDEL-GUTFREUND

Keyword(s):

Nucleic Acid ◽

Protein Nucleic Acid ◽

And Function ◽

Nucleic Acid Interactions

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mmCSM-NA: accurately predicting effects of single and multiple mutations on protein–nucleic acid binding affinity

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab109 ◽

2021 ◽

Vol 3 (4) ◽

Author(s):

Thanh Binh Nguyen ◽

Yoochan Myung ◽

Alex G C de Sá ◽

Douglas E V Pires ◽

David B Ascher

Keyword(s):

Nucleic Acid ◽

Binding Affinity ◽

Single Point ◽

Point Mutations ◽

Multiple Point ◽

Missense Mutations ◽

Nucleic Acid Binding ◽

Single Point Mutations ◽

Protein Nucleic Acid ◽

Nucleic Acid Interactions

Abstract While protein–nucleic acid interactions are pivotal for many crucial biological processes, limited experimental data has made the development of computational approaches to characterise these interactions a challenge. Consequently, most approaches to understand the effects of missense mutations on protein-nucleic acid affinity have focused on single-point mutations and have presented a limited performance on independent data sets. To overcome this, we have curated the largest dataset of experimentally measured effects of mutations on nucleic acid binding affinity to date, encompassing 856 single-point mutations and 141 multiple-point mutations across 155 experimentally solved complexes. This was used in combination with an optimized version of our graph-based signatures to develop mmCSM-NA (http://biosig.unimelb.edu.au/mmcsm_na), the first scalable method capable of quantitatively and accurately predicting the effects of multiple-point mutations on nucleic acid binding affinities. mmCSM-NA obtained a Pearson's correlation of up to 0.67 (RMSE of 1.06 Kcal/mol) on single-point mutations under cross-validation, and up to 0.65 on independent non-redundant datasets of multiple-point mutations (RMSE of 1.12 kcal/mol), outperforming similar tools. mmCSM-NA is freely available as an easy-to-use web-server and API. We believe it will be an invaluable tool to shed light on the role of mutations affecting protein–nucleic acid interactions in diseases.

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Solution-state NMR structure of the putative morphogene protein BolA (PFE0790c) fromPlasmodium falciparum

Acta Crystallographica Section F Structural Biology Communications ◽

10.1107/s2053230x1402799x ◽

2015 ◽

Vol 71 (5) ◽

pp. 514-521 ◽

Cited By ~ 4

Author(s):

Garry W. Buchko ◽

Adelinda Yee ◽

Anthony Semesi ◽

Peter J. Myler ◽

Cheryl H. Arrowsmith ◽

...

Keyword(s):

Nucleic Acid ◽

Protein Structures ◽

Treatment Strategies ◽

Class Ii ◽

Nucleic Acid Binding ◽

Nucleic Acid Binding Proteins ◽

Signature Sequence ◽

Protein Nucleic Acid ◽

New Treatment ◽

Α Helix

Protozoa of the genusPlasmodiumare responsible for malaria, which is perhaps the most important parasitic disease to infect mankind. The emergence ofPlasmodiumstrains resistant to current therapeutics and prophylactics makes the development of new treatment strategies urgent. Among the potential targets for new antimalarial drugs is the BolA-like protein PFE0790c fromPlasmodium falciparum(Pf-BolA). While the function of BolA is unknown, it has been linked to cell morphology by regulating transcription in response to stress. Using an NMR-based method, an ensemble of 20 structures ofPf-BolA was determined and deposited in the PDB (PDB entry 2kdn). The overall topology of thePf-BolA structure, α1–β1–β2–η1–α2/η2–β3–α3, with the β-strands forming a mixed β-sheet, is similar to the fold observed in other BolA structures. A helix–turn–helix motif similar to the class II KH fold associated with nucleic acid-binding proteins is present, but contains an FXGXXXL signature sequence that differs from the GXXG signature sequence present in class II KH folds, suggesting that the BolA family of proteins may use a novel protein–nucleic acid interface. A well conserved arginine residue, Arg50, hypothesized to play a role in governing the formation of the C-terminal α-helix in the BolA family of proteins, is too distant to form polar contacts with any side chains in this α-helix inPf-BolA, suggesting that this conserved arginine may only serve a role in guiding the orientation of this C-terminal helix in some BolA proteins. A survey of BolA structures suggests that the C-terminal helix may not have a functional role and that the third helix (α2/η2) has a `kink' that appears to be conserved among the BolA protein structures. Circular dichroism spectroscopy shows thatPf-BolA is fairly robust, partially unfolding when heated to 353 K and refolding upon cooling to 298 K.

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