Development and Validation of a Protein-Protein Interactions Modeling Platform for Rapid Affinity Predictions and Pharmaceutical Applications

Developing a drug for new diseases cannot only be challenging but also time consuming. From the identification of a druggable target to a compound which can improve a condition it usually takes more than 12 years. Since there is basically an infinite number of possible compounds which can be turned into a drug it is literally the problem of finding a needle in a haystack. The trial and error method of making molecules in the laboratory and testing their efficiency has been proven successful for over a century. However, with ever growing numbers of druggable molecules, diseases and classes of drugs, this traditional workflow has become too time consuming. Efficient computer models can help rationally pre-select a much smaller number of potential drug candidate compounds which can then selectively been tested. This internship aims at testing and enhancing the predictability of a computational tool capable of guiding the development of a new emerging class of drugs, stimulating the human immune system. These drugs, called antibodies, can cure the condition by finding and interacting with their target.

Faculty Supervisor:

Gilles Peslherbe

Student:

Philippe Archambault

Partner:

Chemical Computing Group

Discipline:

Biochemistry / Molecular biology

Sector:

Information and cultural industries

University:

Concordia University