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ISSN 2410-955X - An International Biannual Journal
BIOMEDICAL LETTERS
In silico elucidation of potent drug targets of the melanocyte-stimulating hormone receptor 1 protein
Ayesha Tabassum, Muhammad Usman Ali*, Saba Ansar, Sajjad Ahmed Larra, Muhammad Afzal

Department of Bioinformatics and Biotechnology, Government College University Faisalabad, Pakistan

Abstract
Most of the genes, including melanocortin 1 receptor (MC1R) involved in melanogenesis. The black to brown eumelanin and the yellow to red phaeomelanin are the two kinds of pigment recognized in human skin. The primary cause of the dermal reaction to ultraviolet radiation (UVR) is cutaneous pigmentation, subsequently of the risk of developing skin cancer. Melanin pigmentation protects the skin against the harmful effects of ultraviolet radiation. The death rate of melanoma depends upon the type of skin cancer. Different computational approaches were utilized for 3D modeling and protein-protein docking analyses of MC1R leads to virtual screening. Comparative modeling and threading techniques were employed to predict the 3D structure of MC1R and 95.79% of quality factor was calculated. STRING database was utilized and 1Y7K was observed as interacting partner of MC1R. Protein-protein docking was performed, and potential interacting residues were observed. Virtual screening was performed against FDA library from ZINC database and molecular docking was performed by AutoDock Vina. The compound ZINC131 showed least binding energy of -10.3 kcal/mol. The suggested molecule may be used for further analyses in the drug discovery processes. In conclusion, the findings of current work may be helpful for novel therapeutic targets against MC1R.

A R T I C L E  I N F O

Received
April 01, 2020
Revised
May 06, 2020
Accepted
June 18, 2020

*Corresponding Author
Muhammad Usman Ali
E-mail
ua177960@gmail.com

Keywords
Melanocyte-Stimulating Hormone Receptor 1
Structure Prediction
Bioinformatics
Protein Docking



Research article


2020 | Volume 6 | Issue 2: Special issue articles: Computational drug designing and molecular docking analyses