The phytochemicals drug discovery for diabetes by the maximal clique algorithm

Abstract

The common disease of people all around the world is diabetes which comes from consuming unproportioned and undifferentiated food. Especially in low-income countries. Nowadays, there are many reports of cellular and molecular processes that involve diabetes risk, and also the development of personalized medicines or therapeutic clinical decisions. Alternative medicine using natural sources is now increasingly being tested and used because it is not only easily found in local places but also has high efficacy with low side effects. This study aims to discover a combination of phytochemical compounds or natural drugs for treating diabetes disorder through significant protein modules of diabetes and relevant disorders such as obesity, inflammation, and Alzheimer. The network clustering algorithm named “maximal clique (Mclique)” is applied to extract notable protein interaction modules. Then phytochemical compounds are investigated on each significant protein module to discover the efficacy of a natural drug for diabetes treatment. Our evidences revealed that the combination of phytochemicals possibly used as the plant-based derived drug for diabetes to be used as complementary drugs to modern medicines. The outmost goal of this work is to find out plant-derived drugs that have effective anti-diabetes properties with minor side effects. We also set up an accessible web-based application as the url: http://sit.mfu.ac.th/integrative/Diabetes_Cluster.php. This application collects all of our research results for investigator can poses query then get more discovery result information.