Principal Investigator Tomas Lozano-Perez
Current research in drug design is dependent on the accurate determination of the three-dimensional structures of molecules at atomic-resolution. However, the difficulty of accumulating this information poses considerable challenges for drug discovery. In addition, structural information on molecules is a crucial part of understanding the molecular mechanisms of biological systems. While an important part of the structure determination process involves experimental approaches, a significant computational effort is required to interpret the experimental data. Current methods rely on an iterative process of model-to-data comparisons. The procedure is akin to fitting pieces of a puzzle into place. The data generated by structural methods, such as x-ray crystallography or nuclear magnetic resonance (NMR), define a space. Computational methods then create an atomic model to fit that space. The Lozano-Peréz research group focuses on improving computational methods that allow a more accurate fitting of the models to the experimental data.
The algorithm AmbiPack, developed in collaboration with the Tidor group, uses chemically defined constraints to assign the placement of atoms within a protein structure. Using experimental data to define the constraints, the algorithm searches all possible configurations of amino acids to delineate the final molecular structure of the protein. Insuring inclusion of all possible positions, AmbiPack uses a hierarchical division of the space for searches. A branch-and-bound algorithm eliminates infeasible regions of space and permits searches to be focused on the remaining space. The addition of more constraints allows the program to more quickly reach an answer because more space is excluded from the search. This algorithm provides a systematic way of determining the packing of macromolecular structures.