Jian Zhang* and Haiting Chai Pages 1855 - 1857 ( 3 )
This editorial provides a brief overview of the thematic issue and the papers in it. The thematic issue is proposed to help chemists and biologists track the most recent advances in drug discovery and cancer diagnoses. The process of drug discovery involves the identification and validation of biological targets, the identification and optimization of lead compounds, preclinical development, and clinical trials. Cancer is a major public health problem in the world. The results of tissue diagnosis, blood tests, computed tomography scans, and cytogenetic analyses can provide informative clues about molecular changes and indicate proper prognoses. Timely detection of cancer significantly improves cancer outcomes by providing care at the earliest possible stage thus contributing greatly to the prevention and exacerbation and has become an important public health strategy in all settings. The collection of this thematic issue includes five articles. The first one reviews the current advances and limitations of deep learning in anticancer drug sensitivity prediction. The next review summarizes the most recent and high-quality research related to anticancer activities of Vitamin C. The third one reports the efficacy of two different sets of natural products (terpenoids and flavonoids) towards caspase-3 activity. The fourth one proposes a novel in silico method for predicting cancer biomarkers in human body fluids. The fifth article performs an in silico and in vitro investigation on isothymusin, which serves as a potential inhibitor of cancer cell proliferation.
Drug discovery, Cancer, Biomarkers, Molecular biochemistry, In vitro, In silico.
School of Computer and Information Technology, Xinyang Normal University, Xinyang, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow