Protein design methodology seeks the lowest energy amino acid sequence given constraints specifying the problem of interest. The more accurate the force field used to calculate energies, the higher the activity and success rates of the designed proteins. IPD researchers use a combination of physical chemistry and analysis of the ~100,000 protein crystal structures to improve our description of protein energetics on the atomic scale. See Comparative Modeling with RosettaCM.
Given an accurate force field, the design problem becomes finding the lowest energy sequence for a given challenge. Since there are 20 amino acids possible at each position, this may require searching through the 20x20x20…=20Nres sequences for a new designed protein with Nres residues. Because the optimal structure to solve a given challenge is in general not known in advance, alternative backbone conformations must be searched as well—also a challenge since even with the conservative estimate of three states per residue there are ~3Nres conformations for an Nres protein. IPD researchers are developing algorithms for efficiently searching through these vast sequence and structure spaces to find very low energy solutions that solve the specified design challenge. See Sampling Algorithm Development.
Once low energy designed proteins have been identified on the computer, it is critical to test these experimentally. Since neither the design forcefield nor the sampling methods are perfect, it is desirable to experimentally manufacture and measure the activity of as many designs as possible. IPD researchers are developing methods for experimentally testing tens of thousands of different computational designs in parallel. See Optimizing Flu Binders.
A test of the accuracy of the forcefield and the thoroughness of the backbone sampling methodology that is of great importance in its own right is the protein structure determination problem. IPD researchers are developing powerful methods for solving protein structures using limited experimental data that are being used to solve naturally occurring protein structures in laboratories around the world. See Prediction of Symmetric Assemblies, Energy and Density Refinement, Structure Determination from Low-Resolution Data, and Model Building for CryoEM.
The IPD seeks to involve the general public as much as possible in its research activities both for education and research purposes. The distributed computing project Rosetta@Home and the online protein design game FoldIt have both attracted over 300,000 participants. Learn how you can Participate.
In the past, almost all protein design and engineering efforts have modified naturally occurring protein backbones. However, for most challenges there is unlikely to already exist in nature a backbone with an optimal geometry. The IPD is developing general methods for designing a wide range of exceptionally stable protein structures with tunable geometries for specific applications. See Proteins Made to Order, and vaccine design for HIV and RSV.
Like most biological entities, viruses and tumor cells have specific proteins on their surfaces. Hence, designed proteins which bind target proteins with high affinity and specificity could be broadly useful as both therapeutics and diagnostics. The IPD is developing methods for designing high affinity binding, and applying these methods to design binders to targets of biomedical interest. These efforts are providing fundamental insights into the protein-protein interactions which underlie most cellular processes. See Flu Binder, Fc Binder, and Lysozyme Inhibitor.
The IPD is developing general methods for design proteins to bind with high affinity to small molecules, and applying these methods to design binders for drugs with narrow therapeutic windows, toxic compounds and other small molecules of interest. These efforts inform our understanding of small molecule recognition in biology. See Digoxigenin Binder, Preparing Scaffold Libraries, and Metal Binder.
Self assembling protein materials play critical roles in biology. IPD researchers are developing general approaches for creating new self assembling nanostructures, and using these approaches to develop a next generation of vaccines and drug delivery vehicles. See Self-Assembling Nanomaterials and Two-Component Nanomaterials.