Abstract

Drug discovery is a complex process with the aim of discovering efficacious molecules where their potency and selectivity are balanced against ADMET properties to set the appropriate dose and dosing interval. The link between physicochemical properties and molecular structure are well established. The subsequent connections between physicochemical properties and a drug’s biological behavior provide an indirect link back to structure, facilitating the prediction of a biological property as a consequence of a particular molecular manipulation. Due to this understanding, during early drug discovery in vitro physicochemical property assays are commonly performed to eliminate compounds with properties commensurate with high attrition risks. However, the goal is to accurately predict physicochemical properties to prevent the synthesis of high risk compounds and hence minimize wasted drug discovery efforts.It has long been considered that the most significant risks for breast cancer are gender and age but, as many other tumors, this cancer has also been undeniably linked to gene mutations. The vast majority of breast cancers in postmenopausal women are estrogen-responsive, a hormone which is biosynthesized from blood-circulating androgens through an aromatization reaction, catalyzed by aromatase (AR). Here, in Biogenea Pharmaceuticals Ltd we discovered for the first time the GENEA-Aromahibinir-4492 Quantum algorithms for topological and geometric analysis of computational methods and a metastasis perfomed thermodynamic integration approach for the discovery of a potent aromatase/collagen IV derived biomimetic dual targeted small poly-active compound with future anti-tumor inhibitory activities.

Keywords

Quantum algorithms; topological;geometric analysis; Computational methods; a metastasis; thermodynamic integration; discovery; potent; aromatase/collagen IV; biomimetic; dual targeted; small poly-active; compound; future; anti-tumor; inhibitory activities;