Efficient Distribution Analysis via Graph Contraction

Alignment and distribution of data by an optimizing compiler is a dream of both manufacturers and users of parallel computers. The distribution problem has been formulated as an NP-complete graph optimization problem. The graphs arising in applications are large, and the optimization problem does not lend itself to traditional heuristic optimization techniques. In this paper, we improve some earlier results on methods that use graph contraction to reduce the size of a distribution problem. We report on an experiment using seven example programs that show these contraction operations to be effective in practice; we obtain from 60 to 99 percent reductions in problem size, the larger number being more typical, without loss of solution quality

Modeling Disordered Regions in Proteins Using Rosetta

Protein structure prediction methods such as Rosetta search for the lowest energy conformation of the polypeptide chain. However, the experimentally observed native state is at a minimum of the free energy, rather than the energy. The neglect of the missing configurational entropy contribution to the free energy can be partially justified by the assumption that the entropies of alternative folded states, while very much less than unfolded states, are not too different from one another, and hence can be to a first approximation neglected when searching for the lowest free energy state. The shortcomings of current structure prediction methods may be due in part to the breakdown of this assumption. Particularly problematic are proteins with significant disordered regions which do not populate single low energy conformations even in the native state. We describe two approaches within the Rosetta structure modeling methodology for treating such regions. The first does not require advance knowledge of the regions likely to be disordered; instead these are identified by minimizing a simple free energy function used previously to model protein folding landscapes and transition states. In this model, residues can be either completely ordered or completely disordered; they are considered disordered if the gain in entropy outweighs the loss of favorable energetic interactions with the rest of the protein chain. The second approach requires identification in advance of the disordered regions either from sequence alone using for example the DISOPRED server or from experimental data such as NMR chemical shifts. During Rosetta structure prediction calculations the disordered regions make only unfavorable repulsive contributions to the total energy. We find that the second approach has greater practical utility and illustrate this with examples from de novo structure prediction, NMR structure calculation, and comparative modeling

Computational design of a homotrimeric metalloprotein with a trisbipyridyl core

Metal-chelating heteroaryl small molecules have found widespread use as building blocks for coordination-driven, self-assembling nanostructures. The metal-chelating noncanonical amino acid (2,2'-bipyridin-5yl)alanine (Bpy-ala) could, in principle, be used to nucleate specific metalloprotein assemblies if introduced into proteins such that one assembly had much lower free energy than all alternatives. Here we describe the use of the Rosetta computational methodology to design a self-assembling homotrimeric protein with [Fe(Bpy-ala)3]2+ complexes at the interface between monomers. X-ray crystallographic analysis of the homotrimer showed that the design process had near-atomic-level accuracy: The all-atom rmsd between the design model and crystal structure for the residues at the protein interface is ∼1.4 Å. These results demonstrate that computational protein design together with genetically encoded noncanonical amino acids can be used to drive formation of precisely specified metal-mediated protein assemblies that could find use in a wide range of photophysical applications.</p

Computational design of self-assembling cyclic protein homo-oligomers

Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein-protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model