Discovery of TIGIT-Targeted Small Molecules as Cancer Therapies
Annotation
This paper will discuss the results of experiments done on the immune checkpoint TIGIT and the discovery of potential immune checkpoint inhibitors that can bind to it. First, machine learning was used to find potential binding spots on TIGIT and the requirements it needs to bind. Next came the pharmacophore test, a list filled with drugs that are able to bind to TIGIT; 15 were chosen at random. Each drug was then tested using SwissDock, which will find the site that it will best bind with TIGIT. After that, the properties of each drug were analyzed; if it passed Lipinski's Rule, it would go on to the next experiment. Last is the toxicity test, where the toxicity level and traits of each drug were analyzed, and in the end, three drugs were chosen that had the best overall results. The study turned out to be successful, as in the end, 3 drugs were found that have the potential to act as immune checkpoint inhibitors. Although this study was successful, it is not the end of the experiment, as many more drugs can be tested with the same processes
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