Molecular Docking, Drug likeness Studies and ADMET Prediction of Phytochemical of plant Ipomoea Tricolor for Breast Cancer Activity

Cancer of the breast develops when abnormal cells in breast multiply and spread out of control, prominent to formation of a tumour. The cells that line the milk ducts of the breast are the usual starting point for breast cancer. Breast tumors, alterations in breast nature or size, dimpling skin, inability to milk, discharge from the nipple, nipple inversion, or reddening or scaling of the skin are all possible signs of breast cancer. Molecular docking has emerged as a powerful computational tool in the field of breast cancer research, facilitating the exploration of interactions between small molecules and target proteins implicated in disease pathways. After retrieving the protein from Protein Data Bank, Biovia Discovery Studio was used to generate its crystal structure. Advances in computational algorithms and structural biology techniques have enhanced the accuracy and applicability of docking simulations, allowing researchers to screen large compound libraries efficiently and prioritize lead compounds for further experimental validation. After obtaining the phytochemicals from the NCBI PubChem database, their molecular structures were generated using Open Babel. PyRx was used to perform molecular docking using Autodock Vina. The web servers pkCSM and SwissADME were utilized to calculate the ADMET properties of the top-performing compounds. This abstract summarizes the role of molecular docking in breast cancer research, emphasizing its utility in drug discovery, interaction prediction, and therapeutic development.