Review and research analysis of computational target methods using BioRuby and in silico screening of herbal lead compounds against pancreatic cancer using R programming.

Plants and their natural components sophisticated with the cornerstone of traditional conventional medicinal system throughout the globe for many years and extend to furnish mankind with latest remedies. Natural Products act as lead molecules for the synthesis of various potent drugs. In the current research a study is conducted on herbal small molecule and their potential binding chemical affinity to the effect or molecules of major diseases such as pancreatic cancer. Clinical studies demonstrate correlation between Cyclin- Dependent Kinase 4 (CDK4) and malignant progression of Pancreatic Cancer. Using Bioruby Gem's we were able to analyze better characteristics of the target protein. VegaZZ and NAMD were used to minimize the energy of the target protein. Therefore identification of effective, well- tolerated targets was analyzed. Further the target protein was subjected to docking with the anti cancer inhibitors which represents a rational chemo preventive strategy using AutoDock Vina. Later using the dock score top ranked phytochemicals were analyzed for Toxicity Analysis. Using the BioRuby gem we were able to measure the distance between the amino acid. Various R scripting libraries were used to hunt the best leads, as in this case the phytochemicals. Phytochemicals such as Wedelolactones and Catechin were analyzed computationally. This study has presented the various effects of naturally occurring anti pancreatic cancer compounds Catechin, Wedelolactones that inhibits Cyclin Dependent Kinase 4. The study results reveal that compounds use less binding energy to CDK4 and inhibit its activity. Future investigation of other various wet lab studies such as cell line studies will confirm results of these two herbal chemical formulations potential ones for treating Pancreatic Cancer.