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Computational Biology Tool Toward Studying the Interaction Between Azadirachtin Plant Compound with Cervical Cancer Proteins

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Intelligent Computing and Innovation on Data Science

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 118))

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Abstract

Cancer is noteworthy general well-being trouble in both developed and developing nations. Cervical disease is the significant reason for tumor passing in women around the world. Chemotherapy remains the main treatment method for different malignancies. Various manufactured anticancer medications are accessible now; however, the symptoms and the medication cooperations are significant disadvantages in its clinical utility. Thus, searching a cure for cancer remains the most challenging area in the medical field. Natural products play an important role in the discovery of drug. It can be a potential drug candidate for cancer treatment. In this study, three-dimensional models of cervical cancer cell lines (tumor suppressor gene (p53), mucosal addressin cell adhesion molecule 1 (MADCAM 1) and nuclear factor NF-kappa-B-p105 subunit (NFKB 1) were generated, and the lowest binding energy with azadirachtin phytocompound was determined using local docking approach. The protein models were generated using Swiss model; their physiochemical characterization and secondary structure prediction were evaluated. After that, the protein models were validated through PROCHECK, ERRAT and Verify 3D programs. Lastly, p53, MADCAM 1 and NFKB 1 were docked successfully with azadirachtin through BSP-Slim server. The tumor suppressor gene (p53) had the strongest bond with azadirachtin due to its lowest and negative value of binding energy (2.634 kcal/mol). Azadirachtin can be a potential anticancer agent. Therefore, this protein–ligand complex structure can further be validated in the laboratory for studying its cytotoxicity on cancer cells.

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Acknowledgements

I would like to thank Dr. Asita for her guidance. The authors declare no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Science and Biotechnology, Faculty of Engineering and Life Sciences, Universiti Selangor, 45600, Bestari Jaya, Selangor, Malaysia

    Givitha Raman

  2. Department of Biotechnology, Faculty of Science, Lincoln University College, 47301, Petaling Jaya, Selangor, Malaysia

    Asita Elengoe

Authors
  1. Givitha Raman
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  2. Asita Elengoe
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Editor information

Editors and Affiliations

  1. CSIE Department, National Dong Hwa University, Hualien City, Taiwan

    Sheng-Lung Peng

  2. Vietnam National University, Hanoi, Vietnam

    Le Hoang Son

  3. Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies, Pallavaram, Chennai, Tamil Nadu, India

    G. Suseendran

  4. Faculty of Computer Science and Multimedia, Lincoln University College, Petaling Jaya, Malaysia

    D. Balaganesh

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Raman, G., Elengoe, A. (2020). Computational Biology Tool Toward Studying the Interaction Between Azadirachtin Plant Compound with Cervical Cancer Proteins. In: Peng, SL., Son, L.H., Suseendran, G., Balaganesh, D. (eds) Intelligent Computing and Innovation on Data Science. Lecture Notes in Networks and Systems, vol 118. Springer, Singapore. https://doi.org/10.1007/978-981-15-3284-9_5

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