Andrea Mae Añonuevo, Marineil Gomez, Lemmuel L Tayo
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In silico de novo drug design of a therapeutic peptide inhibitor against UBE2C in breast cancer.
The World Health Organization (WHO) declared breast cancer (BC) as the most prevalent cancer in the world. With its prevalence and severity, there have been several breakthroughs in developing treatments for the disease. Targeted therapy treatments limit the damage done to healthy tissues. These targeted therapies are especially potent for luminal and HER-2 positive type breast cancer. However, for triple negative breast cancer (TNBC), the lack of defining biomarkers makes it hard to approach with targeted therapy methods. Protein-protein interactions (PPIs) have been studied as possible targets for drug action. However, small molecule drugs are not able to cover the entirety of the PPI binding interface. Peptides were found to be more suited to the large or flat PPI surfaces, in addition to their better pharmacokinetic properties. In this study, computational methods was used in order to verify whether peptide drug inhibitors are good drug candidates against the ubiquitin protein, UBE2C by conducting docking, MD and MMPBSA analyses. Results show that while the lead peptide, T20-M shows good potential as a peptide drug, its binding affinity towards UBE2C is not enough to overcome the natural UBE2C-ANAPC2 interaction. Further studies on modification of T20-M and the analysis of other peptide leads are recommended.
期刊介绍:
The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information.
The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.