IN-SILICO MOLECULAR SCREENING OF NATURAL PLANT PRODUCTS FOR THE IDENTIFICATION OF NOVEL POTENTIAL CHEMOTHERAPEUTIC AGENTS AGAINST BREAST CANCER

In-silico computational approaches help in ascertaining drug targets via bioinformatics tools. HER2 is the most valuable therapeutic target for breast cancer therapy. The overexpression of HER2 protein plays a very critical role in the progression of breast cancer. Plant-derived natural products have received increasing attention over the past 20-30 years for their potential as novel therapeutic agents. In the future, plant products may offer more effective medicines than synthetic drugs. The main aim of the current study helps to develop new anti-cancer drug candidates from natural and dietary compounds with the help of computational approaches. In this context, the plant-derived compounds resveratrol and its related analogs were taken and docked onto the protein active site (PDB ID:1M14) via structure-based virtual screening for the prediction of novel potential inhibitors, which may be used as anticancer drugs against breast cancer. Furthermore, Molinspiration server and Data warrior software tools were used to evaluate the ADMET profiling and physicochemical parameters of the screened compounds. The best compound was identified, showing good binding affinity value, have a positive bioactivity score as well as good pharmacokinetic properties. Among all the test candidates in the study, the compound [3-hydroxy-5-[(E)-2-(4-hydroxyphenyl)ethenyl]phenyl] hydrogen sulfate (CID: 25113755) was found to be the most potent lead molecule. So the compound (CID: 25113755) could be used as novel anti-breast cancer agent.