In silico Analysis and Structural Prediction of a Hypothetical Protein from Leishmania Major

• Published in: Biomedical and Biotechnology Research Journal Vol. 5; no. 3; pp. 320 - 326
• Main Authors: Saikia, Achisha, Palherkar, Duhita, Hiremath, Lingayya
• Format: Journal Article
• Language: English
• Published: Medknow Publications and Media Pvt. Ltd 01.07.2021; Wolters Kluwer Medknow Publications
• Subjects: Analysis; Bacterial proteins; Genetic aspects; Health aspects; hypothetical protein; in silico methods; Leishmania; leishmania major; national center for biotechnology information; Open reading frames; Physiological aspects; protein structure prediction; Proteins; sequencing; Structure; structure validation; India
• ISSN: 2588-9834
• DOI: 10.4103/bbrj.bbrj_126_21

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.