About this Research Topic

Background

Cancer is a multifactorial disease, involving multiple pathogenetic mechanisms. Cancer onset, metastasis, invasion are mainly driven by the loss of the regulatory circuits controlling normal cell growth and homeostasis, leading to deregulated proliferation and to the subsequent appearance of mutations in the DNA. These mutations in turn contribute to genome instability and to the gain or loss of function of some genes, thus altering normal cell functions. Ultimately, a normal cell undergoes a gradual shift to a malignant phenotype and, if able to escape the immune destruction, might promote cancer initiation. Recent progress in massive sequencing, proteomics genomics, and bioinformatics greatly facilitated the dissection of the molecular basis of cancer. Such techniques brought to light genes and signaling pathways playing key roles in cancer development and progression, which have been proposed as therapeutic targets.

Several cellular signaling processes are controlled by transient phosphorylation, with abnormal phosphorylation profiles being also associated with cancer. The phosphoproteome results from the activity of both protein kinases and phosphatases, which add or remove phosphate groups, respectively. The balance between the activities of these enzymes is essential to maintain cellular homeostasis and has been explored for cancer treatment.
The modulation of molecular pathways involved in cancer, with particular regard to proteins with altered expression or function inside the cancer cells, has been the focus of intensive drug discovery efforts, also laying the foundation of personalized medicine. In this context, computational approaches have greatly supported the drug discovery process, in some cases representing the driving force behind the discovery of novel small molecule therapeutics.

In this Research Topic, we wish to focus on the design and development of anticancer agents against human malignancies, with a special emphasis on the synergies between in silico methods and drug discovery, in particular in the areas of hit identification, hit-to-lead, and lead optimization. In this frame, we would like to welcome original articles and reviews to be considered for publication in this upcoming thematic collection.

Areas of interest include, but are not limited to:
• anticancer agents acting on kinases and phosphatases relevant to cancer
• anticancer agents acting on apoptotic signaling pathways
• natural products anticancer compounds
• metabolism modulating anti-cancer agents
• epigenetic modulators

Experimental and theoretical research studies are welcome; multidisciplinary approaches are particularly encouraged.

Keywords: Drug discovery, medicinal chemistry, molecular modelling, chemoinformatics, bioinformatics, big data, machine learning, cancer

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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