ISSN: 0973-7510

E-ISSN: 2581-690X

Research Article | Open Access
Yulanda Antonius1, Viol Dhea Kharisma2, Muhammad Hermawan Widyananda2,3, Arif Nur Muhammad Ansori4, Joko Pebrianto Trinugroho5, Md. Emdad Ullah6, Sin War Naw7, Vikash Jakhmola8 and Mariana Wahjudi1
1Faculty of Biotechnology, University of Surabaya, Surabaya, Indonesia.
2Division of Molecular Biology and Genetics, Generasi Biologi Indonesia Foundation, Gresik, Indonesia.
3Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia.
4Professor Nidom Foundation, Surabaya, Indonesia.
5Department of Life Sciences, Imperial College London, South Kensington Campus, London, United Kingdom.
6Department of Chemistry, Mississippi State University, Mississippi State, United States.
7Department of Chemistry, Myitkyina University, Myitkyina, Myanmar.
8Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, Uttarakhand, India.
Article Number: 7686 | © The Author(s). 2022
J Pure Appl Microbiol. 2022;16(3):1844-1854. https://doi.org/10.22207/JPAM.16.3.29
Received: 15 March 2022 | Accepted: 20 June 2022 | Published online: 03 August 2022
Issue online: September 2022
Abstract

Aflatoxin-B1 (AFB1) is a common contaminant for staple foods during the storage process. Chronic exposure to AFB1 is widely known to induce the development of hepatocellular carcinoma (HCC). However, there is a lack of understanding of AFBi role in HCC mechanism. This research aims to identify protein(s) in HCC that might interact with AFB1 and to predict the pathway effected by AFB1. Analyses were performed using bioinformatics tools. SMILES notation of AFB1 was submitted into Swiss Target Prediction. Interaction among predicted proteins were analyzed by using STRING. The 3D structure of target protein was constructed by homology modeling. Reverse docking was performed, and the result was ranked based on binding affinity score. Furthermore, protein interaction network was constructed and analyzed by using Cytoscape. Results showed that three protein groups were predicted as target of AFB1, such as kinases, phosphatases, and G protein-coupled receptor with probability of 46.7%, 20%, and 6.7%, respectively. Seven proteins of kinases were strongly related to HCC, including RAF1, MAPK1, MAPK3, AKT1, EGFR, GSK3B, and mTOR. Reverse docking considered the AKT1-AFB1 as the most potential complex with the lowest affinity score -10.2 kcal.mol-1. It has hydrophobic bonds in Trp80, Val270, Tyr272, Asp292, Thr211, Leu210, Leu264, and Lys268 residues, whereas hydrogen bond in Ser205 residues. Moreover, further analysis demonstrated that interaction of AKT1-AFB1 is related to the metastasis pathway in HCC mechanism.

Keywords

Cancer, Kinase Protein, Protein Interaction, Protein Pathway, Toxin

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© The Author(s) 2022. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.