Modeling molecular recognition in flexible systems
Most macromolecules interreact with other molecules in order to carry out their biological role. By understanding the structures of complexes, the different binding modes and the interactions that drive binding we can design new molecules that promote or inhibit proteins. Computational modeling has played a significant role in predicting and identifying small molecule binding through techniques such as docking and alchemical free energy calculations. However, the success rate with flexible molecules is much lower.
In this talk I will present two directions in our efforts to combine information and simulations to predict the structures of complexes involving conformational changes. In the first example, we predict the structures of intrinsically disordered peptides that fold upon binding the extra terminal domain of bromo and extra terminal domain proteins – a class of proteins involved in cancer and viral infection. In the second example I will present our work on predict protein-nucleic acid complexes using generic information and our MELD simulation framework.
Ken Dill, Host
Refreshments following the seminar in Laufer Hub 110