The Role of Computational Chemistry in Drug Design Based on Natural Products to Inhibit ABCG2 proteins in Cancer Cells

In an attempt to design new antineoplastic drugs, one of the main aspects, which is the topic of the most researches are the drug design for drug-resistant proteins. ABCG2 proteins are the transporter proteins while protecting tissues against xenobiotics; they also can wrest pharmacokinetic processes of drugs contributing to multidrug resistance [1]. These groups of protein are expressed in many cells, but it is mainly expressed in tissues; such as blood-brain barrier, kidney, liver and intestinal epithelium playing physiological roles in the human body. It should be noted that ABCG2 is also expressed in many stem cells [2,3]. ABCG2 is known as Breast cancer resistance protein [4], and this given name is due to the discovery of ABCG2 during the study of drug-resistant breast cancer cell line [5]. From the structural point of view; ABCG2 is the member of ABCG subfamily of proteins which have six transmembrane domains alongside with one nucleotide domain, besides its N-terminus and C-terminus of ABCG subfamily of proteins located at intracellular space, although ABCG2 protein has 654 residues in its structure in most of the cases, it dimerises to have a better function (Figure1) [6]. It should be noted that the Dysfunction of ABCG2 can lead to kidney disease and hypertension [7], and ABCG2's overexpression or overactivation can cause the drug resistance to chemotherapeutic medicines and their metabolites; such as methotrexate, sulfated methotrexate, topotecan, camptothecin and flavopiridol [8]. Consequently, the drug resistance effect of this protein does not limit to breast cancer disease only. Since now, many drugs have been developed to inhibit ABCG2 transporters in case of MDR (multidrug resistance); such as, FTC Which is the production of Aspergillus fumigatus [9], but it can lead to neurotoxicity [10] ABCG2 is categorised as the transmembrane protein, and, notably, inward-facing cavity to the cytoplasm of cells are the main targets of many drugs as inhibitors [1]. Recently, many studies have been developed to design the appropriate medications for this family of ABC proteins, from synthetic organic chemistry to machine learning [4] with the premise of the best fitting drug forABCG2 transporter proteins, besides being beneficial, the most of these studies centred at the modification of chemical structures, which undoubtedly are expected to have side effects. In order to design or synthesise new drugs as antagonists of ABCG2 proteins, the structures of new medicine are based on flat, polycyclic, hydrophobic compounds, still chemical compounds [11]. In this project by employing computational methods, our research group attempted to design new drugs based on natural products to inhibit ABCG2 proteins more efficiently alongside with fewer side effects compared to the old drugs.