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

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.

scholarly journals Bioinformatic Analysis of Structure and Function of Lim Domains of Zyxin Family Proteins

2020 ◽  
Author(s):  
Mohammad Quadir Siddiqui ◽  
Maulik D. Badmalia ◽  
Trushar R. Patel
Keyword(s):  
Protein Interactions ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Bioinformatic Analysis ◽  
Elastic Network Model ◽  
Cellular Functions ◽  
Consensus Analysis ◽  
Mutational Frequency ◽  
Lim Domains ◽  
And Function

AbstractLim domains are one of the most abundant types of zinc-finger domains and are linked with diverse cellular functions ranging from cytoskeleton maintenance to gene regulation. Zyxin family Lim domains perform the critical cellular functions and are indispensable for cellular integrity. Despite having these important functions the fundamental nature of the sequence, structure, functions, and interactions of the Zyxin family Lim domains are largely unknown. Therefore, we have used a set of in-silico tools and bioinformatics databases to distill the fundamental properties of the Zyxin family proteins/Lim domains from their amino acid sequence, phylogeny, biochemical analysis, post-translational modifications, structure dynamics, molecular interactions, and functions. Consensus analysis of the nuclear export signal suggests a conserved Leucine-rich motif composed of LxxLxL/LxxxLxL. Molecular modeling and structural analysis demonstrate that Lim domains of the members of the Zyxin family proteins share similarities with transcriptional regulators, suggesting they could interact with nucleic acids as well. Normal mode, Covariance, and Elastic Network Model analysis of Zyxin family Lim domains suggest only the Lim1 region has similar internal dynamics properties, compared to Lim2/3. Protein expression/mutational frequency studies of the Zyxin family demonstrated higher expression and mutational frequency rates in various malignancies. Protein-protein interactions indicate that these proteins could facilitate metabolic rewiring and oncogenic addiction paradigm. Our comprehensive analysis of the Zyxin family proteins indicates that the Lim domains function in a variety of ways and could be implicated in rational protein engineering and might lead as a better therapeutic target for various diseases, including cancers.

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

2020 ◽  
Author(s):  
Lei Xu ◽  
Shanshan Jiang ◽  
Jin Wu ◽  
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

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.

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

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]

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

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.

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

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

Paxillin nuclear-cytoplasmic localization is regulated by phosphorylation of the LD4 motif: evidence that nuclear paxillin promotes cell proliferation

2009 ◽  
Vol 418 (1) ◽  
pp. 173-184 ◽  
Author(s):  
Jing-Ming Dong ◽  
Lei-Shong Lau ◽  
Yuen-Wai Ng ◽  
Louis Lim ◽  
Ed Manser
Keyword(s):  
Cell Proliferation ◽  
Focal Adhesion ◽  
Nuclear Export ◽  
Nuclear Export Signal ◽  
Pcr Analysis ◽  
Surface Receptors ◽  
Lim Domains ◽  
P21 Activated Kinase ◽  
Nih 3T3 ◽  
G Protein Coupled

Paxillin, a major focal-adhesion complex component belongs to the subfamily of LIM domain proteins and participates in cell adhesion-mediated signal transduction. It is implicated in cell-motility responses upon activation of cell-surface receptors and can recruit, among others, the GIT1 [GRK (G-protein-coupled-receptor kinase)-interacting ARF (ADP-ribosylation factor) GAP (GTPase-activating protein)]–PIX [PAK (p21-activated kinase)-interacting exchange factor]–PAK1 complex. Several adhesion proteins including zyxin, Hic5 and Trip6 are also nuclear and can exert transcriptional effects. In the present study we show that endogenous paxillin shuttles between the cytoplasm and nucleus, and we have used a variety of tagged paxillin constructs to map the nuclear export signal. This region overlaps an important LD4 motif that binds GIT1 and FAK1 (focal-adhesion kinase 1). We provide evidence that phosphorylation of Ser272 within LD4 blocks nuclear export, and we show that this modification also reduces GIT1, but not FAK1, binding; however, Ser272 phosphorylation does not appear to be mediated by PAK1 as previously suggested. Expression of nuclear-localized paxillin LIM domains stimulate DNA synthesis and cell proliferation. By real-time PCR analysis we have established that overexpression of either full-length paxillin or a truncated nuclear form suppresses expression of the parental imprinted gene H19, and modulation of this locus probably affects the rate of NIH-3T3 cell proliferation.

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

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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