Combined Computational and Experimental Approaches for the Design of Protein-Protein Interactions. Start date: Jan. 1, 2005. Expires: Dec. 31, 2009. Current year award amount: $199,015. Principal investigator: John Love. Sponsor: San Diego State University Foundation.
Project will use an inverse approach that combines computational docking methods with protein-design algorithms to drive the self-assembly of previously monomeric proteins. The proteins will be computationally docked together and then treated as one in which interfacial side chains are mutated and repacked in a manner analogous to the core of a well-folded protein. The goal is to select the specific amino acids that, upon mutation, will provide the physical chemical interactions that drive complex formation. Experimental techniques will also be used to screen combinatorial libraries of mutant candidate proteins for those that bind target proteins with high affinity.
Advancing Simulation Methods for Long Time-Scale Chemical and Biological Events. Start date: Jan. 15, 2005. Expires: Dec. 31, 2007. Current year award amount: $117,345. Principal investigator: Bin Chen Sponsor: Louisiana State University.
Supports development of an aggregation-volume-bias Monte Carlo (AVBMC) approach for research on a wide range of chemical and biological events. The AVBMC algorithm will be tailored to fit individual systems by adding histogram-reweighting and other techniques and by integrating AVBMC into an ab initio framework. The new simulation methods will be applied to the problem of protein crystallization in an effort to understand recent experimental studies.
Investigating Interactive Properties of Disordered Protein Regions. Start date: Feb. 1, 2005. Expires: Jan. 31, 2006. Awarded amount to date: $119,471. Principal investigator: Lilia Iakoucheva. Sponsor: Rockefeller University.
Project will test a hypothesis that proteins with multiple binding partners interact with their partners via natively disordered regions/domains. A combined approach using computational and experimental methods has been developed for the study. First, a computational analysis that includes disorder predictions on proteins with multiple interacting partners from the C. elegans interactome will be performed. In addition, the algorithm for predicting disorder-to-order transition mutations in these proteins will be developed. Second, prediction-guided and domain-guided approaches will be used to select the targets for experimental verification. Third, site-directed and deletion mutagenesis of predicted disordered regions followed by a high-throughput yeast two-hybrid screening using known binding partners will be carried out. Finally, a database that contains all C. elegans interaction domains together with their respective partners defined in the study will be assembled and disseminated.