• Users Online: 152
  • Print this page
  • Email this page
ORIGINAL ARTICLE
Year : 2021  |  Volume : 5  |  Issue : 3  |  Page : 320-326

In silico analysis and structural prediction of a hypothetical protein from Leishmania major


Department of Biotechnology, RV College of Engineering, Bengaluru, Karnataka, India

Correspondence Address:
Achisha Saikia
Flat No. 201, Lakhimi Apartment, Lakhimi Nagar, Hatigaon, Guwahati - 781 038, Assam
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/bbrj.bbrj_126_21

Rights and Permissions

Introduction: Leishmania major causes mucocutaneous leishmaniasis which is characterized by chronic skin sores. In L. major, some proteins are classified as hypothetical proteins (HPs). These proteins are chains of amino acids whose existence is predicted by sequencing organisms, but their functions remain unknown. They could further be analyzed, functionally annotated, and structurally predicted to open the doors to various applications. Methods: In this study, the HP AKK31191.1 from L. major was selected from the National Center for Biotechnology Information database. Various tools were used for one-dimensional (1D), 2D structural prediction followed by predicting the 3D protein structure via ab initio and homology modeling. The structure was analyzed and validated using various in silico tools. Results: A detailed information on the physicochemical analysis of the protein was achieved. It was found that this particular HP could be located in the cytoplasm. 2D structural analysis showed that the protein consisted of random coils at a higher amount succeeded by extended strands and alpha-helix. These data were validated through a Ramachandran plot. Subsequently, the 3D structure of the protein was visualized in UCSF Chimera which portrayed the random coils, extended strands, and the alpha-helix in different colors. Conclusions: This study focused on finding the characteristic features of the HP, predicting the 3D structure, functionally annotating the protein, and finding another similarity sequence. Through structural prediction, disease-associated mutations can be identified, and other functionally significant sites can be facilitated by determining the spatial positions of active sites and other critical residues.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed552    
    Printed4    
    Emailed0    
    PDF Downloaded56    
    Comments [Add]    

Recommend this journal