[1] Y.T. Ngoc Nguyen, C. Duong-Dinh, H. Vu-Quang, L. T. Lan Dinh, T. Nguyen-Minh, N. Dinh Nguyen, A. Tu Nguyen, LC-ESI-QTOF-HRMS-based myxobacterial metabolite profiling for potential anti-breast cancer extracts, J. Med. Chem. Sci., 2023, 6, 2767–2777. [Crossref], [Publisher] [2] P.A. Kalvanagh, Y.A. Kalvanagh, A new therapeutic approach based on silymarin in the treatment of breast cancer, 2023, 5, 75–85. [Crossref], [Publisher], [Pdf]   [3] F. Mohajer, G.M. Ziarani, A. Badiei, New advances on modulating nanomagnetic cores as the MRI-monitored drug release in cancer, J. Appl. Organomet. Chem., 2021, 1, 141-145. [Crossref], [Google Scholar], [Publisher] [4] N. Yellasubbaiah, V. Velmurugan, QSAR modeling, molecular docking, and adme studies of novel 5-oxo-imidazoline derivatives as anti-breast cancer drug compounds against MCF-7 Cell Line, J. Med. Chem. Sci., 2023, 6, 3087–3112. [Crossref], [Publisher], [Pdf] [5] O.E. Oyeneyin, T.G. Abayomi, N. Ipinloju, E.B. Agbaffa, D.D. Akerele, O.A. Arobadade, Investigation of amino chalcone derivatives as anti-proliferative agents against MCF-7 breast cancer cell lines-DFT, molecular docking and pharmacokinetics studies, Adv. J. Chem. Sect. A, 2021, 4, 288–299. [Crossref], [Google Scholar], [Publisher] [6] Shagufta, I. Ahmad, S. Mathew, S. Rahman, Recent progress in selective estrogen receptor downregulators (SERDs) for the treatment of breast cancer, RSC Med. Chem., 2020, 11, 438–454. [Crossref], [Google Scholar], [Publisher] [7] X. Lu, Y. Teng, X. Lin, M. Xiao, C. Liu, X. Chi, Y. Zhang, G. Luo, H. Xiang, Discovery of novel 2H-chromene-3-carbonyl derivatives as selective estrogen receptor degraders (SERDs): Design, synthesis and biological evaluation, Bioorg. Chem., 2021, 109, 104714. [Crossref], [Google Scholar], [Publisher] [8] Siswandono, R. Widyowati, A. Suryadi, T. Widiandani, D. Prismawa, Molecular modeling, synthesis, and qsar of 5-O-acylpinostrobin derivatives as promising analgesic agent, Rasayan J. Chem., 2020, 13, 2559–2568. [Crossref], [Google Scholar], [Publisher] [9] M.R.F. Pratama, H. Poerwono, S. Siswandono, Design and molecular docking of novel 5-O-Benzoylpinostrobin derivatives as anti-breast cancer, Thai J. Pharm. Sci., 2019, 43, 201–212. [Crossref], [Google Scholar], [Publisher] [10] S. Asirvatham, E. Thakor, H. Jain, Morpholine and Thiomorpholine: A Privileged Scaffold Possessing Diverse Bioactivity Profile, J. Chem. Rev., 2021, 3, 247-272. [Crossref], [Google Scholar], [Publisher] [11] O. Babafakruddin, H. Abdul Ahad, H. Chinthaginjala, K. Tarun, G.A. Kumar, G.G. Reddy, The Design of Soft Drugs: Basic Principles, Energetic Metabolite Methods, Approved Compounds, and Pharmaceutical Applications, J. Chem. Rev., 2022, 4, 241-254. [Crossref], [Publisher] [12] Y. Ahmadyousefi, Bacteria-Derived Chemotherapeutic Agents for Cancer Therapy: A Brief Overview, Asian J. Green Chem., 2023, 7, 223–228. [Crossref], [Pdf], [Publisher] [13] E.N. Praditapuspa, S. Siswandono, T. Widiandani, In silico analysis of pinostrobin derivatives from boesenbergia pandurata on ErbB4 kinase target and QSPR linear models to predict drug clearance for searching anti-breast cancer drug candidates, Pharmacogn. J., 2021, 13, 1143–1149. [Crossref], [Google Scholar], [Publisher] [14] S. Siswandono, Kimia Medisinal Edisi ke-1. Airlangga University Press; Surabaya, 2016. [Publisher] [15] Lionta, G. Spyrou, D. Vassilatis, Z. Cournia, Structure-based virtual screening for drug discovery: principles, applications and recent advances, Curr. Top. Med. Chem., 2021, 14, 1923–1938. [Crossref], [Google Scholar], [Publisher] [16] P.A. Kalvanagh, Y.A. Kalvanagh, A new therapeutic approach based on silymarin in the treatment of breast cancer, Adv. J. Chem. Sect. B, 2023, 5, 75–85. [Crossref], [Publisher] [17] D.N. Illian, A.P. Widiyana, A.R. Hasana, H.A.I. Maysarah, S.S. Mustaniroh, M. Basyuni, In silico approach: prediction of ADMET, molecular docking, and QSPR of secondary metabolites in mangroves, J. Appl. Pharm. Sci., 2022, 12, 21–29. [Crossref], [Google Scholar], [Publisher] [18] S. Sharma, A short review of past, present, and future of metallocene and its derivatives as an effective therapeutic agent, J. Appl. Organomet. Chem., 2023, 3, 142-155. [Crossref], [Publisher] [19] A.B. Mezoughi, W. Abdussalam-Mohammed, A.A.A. Abdusalam, Synthesis and molecular docking studies of some thiohydantoin derivatives as potential anticancer and antimicrobial agents, Adv. J. Chem. Sect. A, 2021, 4, 327–338. [Crossref], [Google Scholar], [Publisher] [20] M.T. Ibrahim, A. Uzairu, Structure-based identification of some potential epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) with in-silico assessment of their pharmacokinetic features and qantum cemical calculations, Adv. J. Chem. Sect. A., 2022, 5, 333–334. [Crossref], [Publisher] [21] L. Frye, S. Bhat, K. Akinsanya, R. Abel, From computer-aided drug discovery to computer-driven drug discovery, Drug Discov. Today: Technol., 2021, 39, 111–117. [Crossref], [Google Scholar], [Publisher] [22] L.G. Ferreira, R.N. Dos Santos, G. Oliva, A.D. Andricopulo, Molecular docking and structure-based drug design strategies, Molecules., 2015, 20, 13384-13421. [Crossref], [Google Scholar], [Publisher] [23] N.K. Patel, G. Jaiswal, K.K. Bhutani, A review on biological sources, chemistry and pharmacological activities of pinostrobin, Nat. Prod. Res., 2016, 30, 2017–2027. [Crossref], [Google Scholar], [Publisher] [24] S. Dara, S. Dhamercherla, S.S. Jadav, C.M. Babu, M.J. Ahsan, Machine learning in drug discovery: a review. Artif. Intell. Rev., 2021, 55, 1947-1999. [Crossref], [Google Scholar], [Publisher] [25] S. Kar, J. Leszczynski, Open access in silico tools to predict the ADMET profiling of drug candidates, Expert. Opin. Drug. Discov., 2020, 15, 1473–1487. [Crossref], [Google Scholar], [Publisher] [26] A.S. Wiyono, Siswandono, N.W. Diyah, Molecular docking of 5-o-benzoylpinostrobin derivatives from Boesenbergia pandurata roxb. as anti-inflammatory, J. Public Health Africa, 2023, 14. [Crossref], [Google Scholar], [Publisher] [27] S.L. Agustin, T. Widiandani, S. Hardjono, B.T. Purwanto, QSAR of acyl pinostrobin derivatives as anti-breast cancer against HER-2 receptor and their ADMET properties based on in silico Study, RJPT, 2022, 15, 4641-4648. [Crossref], [Google Scholar], [Publisher] [28] Y. Liu, X. Yu, J. Chen, Quantitative structure–property relationship of distribution coefficients of organic compounds, SAR QSAR Environ. Res., 2020, 31, 585–596. [Crossref], [Google Scholar], [Publisher] [29] S.H. Abdullahi, A. Uzairu, G.A. Shallangwa, S. Uba, Pharmacokinetics studies of some diaryl pyrimidinamine derivatives as anti-cancer agent : in-silico drug design and molecular docking, Adv. J. Chem. Sect. A, 2022, 5, 320–332. [Crossref], [Google Scholar], [Publisher] [30] A.M. Hantosha, N.A. Rajab, F.T. Abachic, Synthesis, in silico ADMET, docking, antioxidant, antibacterial and antifungal evaluations of some pyrimidine derivatives, Eurasian Chem. Commun., 2023, 5, 216–227. [Crossref], [Publisher] [31] A.B. Umar, Exploration of aticancer potential of novel pyrrolo [2,3-b] pyridine derivatives targeting V600E-BRAF kinase : molecular docking , Pharmacokinetic and DFT Studies, Adv. J. Chem. Sect. A, 2022, 5, 271–286. [Crossref], [Publisher] [32] M. Yusuf, U. Chawla, N.H. Ansari, M. Sharma, Perspective on metal-ligand coordination complexes and improvement of current drugs for neurodegenerative diseases ( NDDs ), Adv. J. Chem. Sect. A, 2023, 6, 31–49. [Crossref], [Google Scholar], [Publisher]