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Molecular docking analysis of p53 with Toll-like receptors



Mohammad Jahoor Alam*,1, Fevzi, Bardakci1, Sadia Anjum1, Shumayla Rasheed Mir2, Irfan Ahmad3 & Mohd Saeed*,1



1Department of Biology, College of Science, University of Hail, Kingdom of Saudi Arabia, 2College of Computer Science and Engineering, University of Hail, Kingdom of Saudi Arabia, 3Department of Clinical Laboratory Science, College of Applied Medical Science, King Khalid University, Kingdom of Saudi Arabia;



*Corresponding author, Mohammad Jahoor Alam j.alam@uoh.edu.sa, Dr. Mohd Saeed - mo.saeed@uoh.edu.sa


Article Type

Research Article



Received September 1, 2021; Revised September 15, 2021; Accepted September 15, 2021, Published September 30, 2021



P53 is one of the most important proteins for its role in cellular signal transduction pathways. It regulates a wide variety of cellular processes, which includes apoptosis, senescence, cell cycle arrest, differentiation, and DNA repair and replication and cancer dynamics. It is a transcription factor for various cellular proteins. Recent report suggests that P53 is linked with transduction proteins involved in cellular immunity. Toll like receptors are needed for communication in cellular immunity. The interaction between p53 and toll like receptors is reported in various studies. Therefore, it is of interest to document the molecular docking analysis of p53 with Tolllike receptors for further consideration in therapeutic development. In the present paper we studied molecular interaction between p53 and toll like receptors using molecular docking approach. We used open-source tools for molecular docking and analyzing the data. Our molecular docking results suggest there is a promising interaction between p53 and toll like receptors. Our study will be a very useful for molecular therapeutics and drug design strategies. Further, molecular dynamics studies can be useful to determine of the stability of complex form by p53 and toll like receptors.



p53, Toll-like receptor, Interaction, Communication, Docking



Alam et al. Bioinformation 17(9): 784-789 (2021)


Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.