Computational Model of Trisindoline 1 Conjugate to Protein P53 and P53R2: Targets For Breast Cancer Therapy

DOI

10.2991/absr.k.220406.044How to use a DOI?

Keywords

Breast Cancer; Molecular Docking; P53; P53R2

Abstract

In 2020, there were 2.3 million women diagnosed with breast cancer with average, 7 percent to 11 percent of women with early breast cancer experience a local recurrence during this time. Resistance mechanisms in breast cancer include DNA repair mechanisms that protect cancer cells from endogenous or exogenous DNA-damaging agents. p53R2 is a potential target for cancer gene therapy like RRM2 because of its role in dNDP synthesis and DNA repair. Inhibition of p53R2 enhances the sensitivity of cancer cells in vitro. Meanwhile, the P53 protein plays a role in apoptosis and can respond to signals of DNA damage, hypoxia, oxidative stress, and oncogene activation. The common cancer therapy given is chemotherapy or radiotherapy, but it is known that cancer cell has a DNA repair mechanism pathway that resists that treatment. Due to the severity of side effects of current cancer therapy, such as resistance and non-specific target to the cancer cell, natural compound sources were believed to have multiple specific targets with minimally acceptable side-effects are now of interest to many researchers, such as a group of alkaloids, Trisindolina 1 that derived from a marine sponge. Trisindolina is a group of alkaloid compounds that showed the highest cytotoxicity activity in the next cytotoxicity test, Trisindolina 1. The cytotoxicity test was carried out on 7 cell lines, namely HepG2, HELA, T47D, WiDr, RAJI, 4T1 and Vero with IC50 values 0.183; 1,532; 1,293; 1,431; 0.392 μg / ml. Thus, we need to confirm the potency of Trisindoline 1 against the DNA repair-inducing protein, P53R2, and its capability to interact with the apoptotic-inducing protein, P53, by In-silico drug design. So, this study focused mainly on computer-aided drug design processes like structure-based pharmacophore modeling, virtual screening, ADMET, molecular docking, and dynamic simulation approaches to identify the possible natural antagonist against P53r2 protein and enhanced protein p53-apoptotic inducing protein to treat breast cancer.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Shabrina Syifa Ghaissani
AU  - Awik Puji Dyah Nurhayati
AU  - Vencka Azzahra Putri
PY  - 2022
DA  - 2022/05/02
TI  - Computational Model of Trisindoline 1 Conjugate to Protein P53 and P53R2: Targets For Breast Cancer Therapy
BT  - Proceedings of the 7th International Conference on Biological Science (ICBS 2021)
PB  - Atlantis Press
SP  - 310
EP  - 320
SN  - 2468-5747
UR  - https://doi.org/10.2991/absr.k.220406.044
DO  - 10.2991/absr.k.220406.044
ID  - Ghaissani2022
ER  -