in silico analysis and qsar of borassus flabellifer metabolite compounds that inhibit erbb4 as breast cancer drug candidates

Breast cancer is one of the most common types of cancer in women. knowing the great potential of coastal plants in indonesia, such as siwalan leaves (borassus flabellifer) attracts attention in creating more effective and safe treatments. the aim of this study is to identify compounds found in siwalan leaves and elucidate their molecular mechanism in inhibiting breast cancer cells. druglikeness and admet programs were used to determine the absorption profile and oral bioavailability. validation using molecular operating environment (moe) version 2022 with erbb4 receptor (pdb id: 3bbt). a total of 16 active compounds were identified through uplc qtof-ms/ms. druglikeness analysis showed that 6 active compounds met the physicochemical properties suitable for drug candidates. admet prediction showed that there were 10 compounds with promising pharmacokinetic profiles and no warnings related to acute toxicity. the compound o-guaiacylglycerol-hex showed higher affinity to the erbb4 receptor target than lapatinib. qsar models are essential in predicting the biological activity of compounds as they are able to relationship the chemical structure of a compound with its biological activity through statistical and computational methods. the best qsar regression equation of borassus flabellifer metabolite compounds is log a = 0.071 logp2 - 0.115logp - 0.010 bm - 3.584 (n=16; sig.=0.000; r=0.901; f=17.302; and se=0.8103). the equation can be a reference in predicting breast anticancer activity in silico. the equation can be a reference in predicting breast anticancer activity in silico. therefore, further research (in vitro and in vivo) is needed for breast anticancer activity.