Proteins serve various functions in living cells. Interactions between proteins and other molecules are responsible for various biological processes. Modern drug design not only deals with discovery of a small molecule that modulate or block specific protein functions but also aims to uncover the function and ligands of yet uncharacterized proteins having impact on various diseases. During drug design process, ~96% promising molecules are not translated into effective drugs. Over ~50% of FDA approved drugs have unexpected interactions with more than five proteins called off-targets leads to adverse effects. Toxicity and off-targets are the major cause of this drug termination. Therefore, potential off-target identification is important to avoid drug side effects or to discover new targets for existing drugs or to repositioning an existing drugs for new targets to treat rare diseases. This talk will focus on how computational biology approaches can help to predict both drug targets and drug indications for systematic drug repositioning in rare diseases. In addition, some outstanding examples will be briefly introduce to show how computational based binding site comparison approach can be applied in discovery of therapeutics for rare diseases
Dr. Rajiv Gandhi is currently a postdoctoral researcher in the department of biological sciences at Louisiana State University. He has a Master's degree in Bioinformatics and a Ph.D, in Computational biology with four-years of postdoctoral research experience. His current research focuses on developing an algorithms for across-proteome modeling of protein-drug interaction networks, advance understanding of binding promiscuity of drug causing side effects and systematic drug repositioning approach to treat rare diseases.
Louisiana State University | Computational Systems Biology Group
Dept. of Biological Sciences | Center for Computation & Technology