Literature DB >> 26217814

In silico analyses of dystrophin Dp40 cellular distribution, nuclear export signals and structure modeling.

Alejandro Martínez-Herrera1, Jorge Aragón1, Rosa Ma Bermúdez-Cruz1, Ma Luisa Bazán1, Gabriela Soid-Raggi1, Víctor Ceja1, Andrea Santos Coy-Arechavaleta1, Víctor Alemán2, Francisco Depardón1, Cecilia Montañez1.   

Abstract

Dystrophin Dp40 is the shortest protein encoded by the DMD (Duchenne muscular dystrophy) gene. This protein is unique since it lacks the C-terminal end of dystrophins. In this data article, we describe the subcellular localization, nuclear export signals and the three-dimensional structure modeling of putative Dp40 proteins using bioinformatics tools. The Dp40 wild type protein was predicted as a cytoplasmic protein while the Dp40n4 was predicted to be nuclear. Changes L93P and L170P are involved in the nuclear localization of Dp40n4 protein. A close analysis of Dp40 protein scored that amino acids (93)LEQEHNNLV(101) and (168)LLLHDSIQI(176) could function as NES sequences and the scores are lost in Dp40n4. In addition, the changes L93/170P modify the tertiary structure of putative Dp40 mutants. The analysis showed that changes of residues 93 and 170 from leucine to proline allow the nuclear localization of Dp40 proteins. The data described here are related to the research article entitled "EF-hand domains are involved in the differential cellular distribution of dystrophin Dp40" (J. Aragón et al. Neurosci. Lett. 600 (2015) 115-120) [1].

Entities:  

Keywords:  Cellular distribution; Dystrophin Dp40; In silico

Year:  2015        PMID: 26217814      PMCID: PMC4510556          DOI: 10.1016/j.dib.2015.06.007

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications table Value of the data Bioinformatics tools permit to search putative dystrophin Dp40 protein domains and/or functions; PSORT II program is an alternative tool to screen for the subcellular localization of Dp40 proteins; NetNES 1.1 server allows to identify putative nuclear export signals of dystrophin Dp40; Comparative modeling analysis between Dp40 and Dp40 mutants identify differences in protein structure.

Data, experimental design, materials and methods

Prediction of the subcellular localization of putative Dp40 and mutant proteins

To predict the subcellular localization, the amino acids sequence of Dp40 protein (Protein ID: AGV74356.1) was analyzed using PSORT II software (http://www.genscript.com/psort/psort2.html) [2]. The Dp40 protein was predicted as a cytoplasmic protein while the predicted localization of Dp40n4, carrying changes L93P and L170P (L93/170P) into the EF1 and EF2 hand domains, was nuclear (Table 1). Additional changes are present in Dp40n4 (M288T and D303G); however, none of these changes modified the predictions of the subcellular localization and NES score. Interestingly, the replacement of proline to leucine residues in Dp40n4, either Dp40n4-P93L, Dp40n4-P170L or Dp40n4-P93/170L, was scored as cytoplasmic (Table 1). In addition, the replacement of leucines 93 and 170 to proline residues in Dp40 (Dp40-L93/170P), was predicted to have a nuclear localization (Table 1) which was confirmed by site-directed mutagenesis [1].
Table 1

Prediction of the subcellular localization (%) of putative Dp40 proteins.

ProteinOutside the nucleusaNuclear
Dp4069.630.4
Dp40-L93P69.630.4
Dp40-L170P69.630.4
Dp40-L93/170P39.160.9
Dp40n439.160.9
Dp40n4-P93L69.630.4
Dp40n4-P170L69.630.4
Dp40n4-P93/170L69.630.4

Includes cytoplasmic, mitochondrial and peroxisomal localization.

Identification of putative nuclear export signals in Dp40 amino acid sequence

To identify possible nuclear export signals (NES), a close analysis of Dp40 and Dp40n4 amino acid sequences was carried out using the NetNES 1.1 server (http://www.cbs.dtu.dk/services/NetNES/) [3]. Analyses of Dp40 amino acids from T87 to C106 and C110 to L230 scored that amino acids 93LEQEHNNLV101 and 168LLLHDSIQI176 could function as NES sequences (Fig. 1A and B, respectively) and the NES score was lost when Dp40n4 and Dp40-L93/170P amino acids (93PEQEHNNLV101 and 168LLPHDSIQI176; changes L93P and L170P are underlined) were analyzed (Fig. 1C and D, respectively).
Fig. 1

Prediction of putative nuclear export signals in Dp40 proteins. Analyses of Dp40 amino acids were performed using the NetNES 1.1 server [3]. (A) Analysis of Dp40 amino acids T87 to C106. (B) Analysis of Dp40 amino acids C110 to L230. (C) Analysis of Dp40n4 and Dp40-L93/170P amino acids T87 to C106. (D) Analysis of Dp40n4 and Dp40-L93/170P amino acids C110 to L230. Putative nuclear export signals (NES score), amino acids 93LEQEHNNLV101 and 168LLLHDSIQI176, were identified in Dp40 (A and B, respectively) and values of NES score were lost in Dp40n4 and Dp40-L93/170P (C and D, respectively). NN, Neural Network. HMM, Hidden Markov Model.

Comparative modeling analyses between Dp40 and mutant proteins

To identify whether mutations L93P and L170P modify the tertiary structure of Dp40 proteins, structure modeling of Dp40 and Dp40 mutants were analyzed using SWISS-MODEL and I-TASSER programs [4,5]. Fig. 2 shows the tertiary structure modeling of putative Dp40 proteins. Differences are observed between Dp40 and Dp40 mutants as well as among Dp40 mutants.
Fig. 2

Comparative modeling of Dp40, Dp40-L93P, Dp40-L170P and Dp40-L93/170P proteins. Structure modeling was carried out using SWISS-MODEL and I-TASSER programs [4,5]. Circles indicate differences between Dp40 and Dp40 mutants. Arrows indicate leucine and/or proline residues 93 and 170 (red).

Conflict of interest

The authors declare that there is no conflict of interest.
Subject areaBiology
More specific subject areaDystrophin bioinformatics analyses
Type of dataTable, image
How data was acquiredIn silico analyses: PSORT II program (http://www.genscript.com/psort/psort2.html) was used to predict the protein localizations; NetNES 1.1 server (http://www.cbs.dtu.dk/services/NetNES/) to search nuclear export signal; and SWISS-MODEL and I-TASSER programs (http://zhanglab.ccmb.med.umich.edu/I-TASSER/) for modeling protein structures. The comparative modeling was made in: http://www.pymol.org/funding.html
Data formatAnalyzed
Experimental factorsN/A
Experimental featuresN/A
Data source locationDepartamento de Genética y Biología Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, México, D. F., México.
Data accessibilityDp40 mRNA sequence, accession number: KF154977, http://www.ncbi.nlm.nih.gov/nuccore/KF154977. Dp40 protein sequence, http://www.ncbi.nlm.nih.gov/protein/543869031.
  5 in total

1.  PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization.

Authors:  K Nakai; P Horton
Journal:  Trends Biochem Sci       Date:  1999-01       Impact factor: 13.807

2.  Analysis and prediction of leucine-rich nuclear export signals.

Authors:  Tanja la Cour; Lars Kiemer; Anne Mølgaard; Ramneek Gupta; Karen Skriver; Søren Brunak
Journal:  Protein Eng Des Sel       Date:  2004-08-16       Impact factor: 1.650

3.  SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling.

Authors:  N Guex; M C Peitsch
Journal:  Electrophoresis       Date:  1997-12       Impact factor: 3.535

4.  EF-hand domains are involved in the differential cellular distribution of dystrophin Dp40.

Authors:  Jorge Aragón; Alejandro Martínez-Herrera; Rosa Ma Bermúdez-Cruz; Ma Luisa Bazán; Gabriela Soid-Raggi; Víctor Ceja; Andrea Santos Coy-Arechavaleta; Víctor Alemán; Francisco Depardón; Cecilia Montañez
Journal:  Neurosci Lett       Date:  2015-05-21       Impact factor: 3.046

5.  I-TASSER: a unified platform for automated protein structure and function prediction.

Authors:  Ambrish Roy; Alper Kucukural; Yang Zhang
Journal:  Nat Protoc       Date:  2010-03-25       Impact factor: 13.491

  5 in total
  1 in total

1.  Overexpression of the dystrophins Dp40 and Dp40L170P modifies neurite outgrowth and the protein expression profile of PC12 cells.

Authors:  César García-Cruz; Candelaria Merino-Jiménez; Jorge Aragón; Víctor Ceja; Brenda González-Assad; Juan Pablo Reyes-Grajeda; Cecilia Montanez
Journal:  Sci Rep       Date:  2022-01-26       Impact factor: 4.379

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.