Virtual screening tools have the potential to accelerate the discovery of anti-cancer drugs
Protein Engineering team at International Clinical Research Center of St. Anne’s University Hospital Brno (FNUSA-ICRC) and Faculty of Science of Masaryk University has focused on the potential of web-based screening tools in accelerating the discovery of cancer-treating drugs based on microbial products. Protein Engineering team have presented a review of web screening tools, such as molecular databases, and provided a step-by-step description of how to use them. “Our goal is to increase awareness of available virtual screening tools within the medical and scientific community, particularly among those working in experimental and clinical oncology,” explained head of the team Jiří Damborský. There are multiple methods and the use of each depends on the available information we have about the microbial products and the molecules being targeted.
At the moment, cancer can be treated by chemo, radiotherapy, surgery, RNA-binding proteins, targeted therapy, or immunotherapy which uses microbial products. Microbial products, such as cellular components or viral particles, are used to target and inhibit proteins involved in carcinogenesis and present a relatively low-cost method to treat cancer. However, there are many different microbial products that could be used and many different proteins that need to be targeted. That is why virtual screening tools are essential in making the process of finding potential anti-cancer drugs more efficient, as they predict how specific molecules will react with one another and thus show us which combinations are most promising.
Overall, the use of virtual screening tools presents an available and low-cost way to speed up the discovery and development of anti-cancer drugs while also enriching the online databases of compounds that could be tested in the future. “However, it is essential to keep in mind that using automated web tools brings challenges of its own, and, for most computational methods, the results will only be as good as the input data,” concluded the head of Bioinformatics unit David Bednář.
The full review is available here