Protein-protein interactions are integral to virtually all biological pathways. Predicting these interactions and the function of the protein complex in key to understanding how biological pathways function. Detailed multistage docking algorithms, which starts from the unbound structures of two proteins, can determine the structure of the protein complex. The docking server, ClusPro, strives to make these docking algorithms accessible to researchers. However, the current refinement stage is computationally too demanding for use in an online server, and hence is replaced by simple energy minimization. The ClusPro team will develop methods to perform side chain search within a traditionally rigid body docking algorithm, and to calculate escape times from each energy funnel by stochastic roadmap simulations. These methods will provide more efficient refinement and will help to identify near-native models, thereby improving the reliability and accuracy of predictions. The server will be implemented on a number of platforms, including supercomputers and multi-core desktops.
ClusPro already has over 4500 users and runs over 1000 jobs per month. In 2011, 164 papers used models generated using the server to study problems in biology, biochemistry, and biotechnology. The upgraded server, with its simple user interface, will be particularly useful to experimentalist with no extensive computational experience, who will be able use it for generating models of protein interactions to explain their data. Graduate students will be trained to optimally combine high performance structure prediction algorithms with experimental data from a variety of low-resolution or non-structural techniques. Docking methods are also being incorporated into undergraduate courses to teach the biophysical principles of molecular recognition.
