Protein NMR chemical shifts are highly sensitive to local structure. A robust protocol is described that exploits this relation for de novo protein structure generation, using as input experimental parameters the 13 C ␣ , 13 C ␤ , 13 C , 15 N, 1 H ␣ and 1 H N NMR chemical shifts. These shifts are generally available at the early stage of the traditional NMR structure determination process, before the collection and analysis of structural restraints. The chemical shift based structure determination protocol uses an empirically optimized procedure to select protein fragments from the Protein Data Bank, in conjunction with the standard ROSETTA Monte Carlo assembly and relaxation methods. Evaluation of 16 proteins, varying in size from 56 to 129 residues, yielded full-atom models that have 0.7-1.8 Å root mean square deviations for the backbone atoms relative to the experimentally determined x-ray or NMR structures. The strategy also has been successfully applied in a blind manner to nine protein targets with molecular masses up to 15.4 kDa, whose conventional NMR structure determination was conducted in parallel by the Northeast Structural Genomics Consortium. This protocol potentially provides a new direction for high-throughput NMR structure determination. molecular fragment replacement ͉ protein structure prediction ͉ ROSETTA ͉ structural genomics

Unlike random heteropolymers, natural proteins fold into unique ordered structures. Understanding how these are encoded in amino-acid sequences is complicated by energetically unfavourable non-ideal features—for example kinked α-helices, bulged β-strands, strained loops and buried polar groups—that arise in proteins from evolutionary selection for biological function or from neutral drift. Here we describe an approach to designing ideal protein structures stabilized by completely consistent local and non-local interactions. The approach is based on a set of rules relating secondary structure patterns to protein tertiary motifs, which make possible the design of funnel-shaped protein folding energy landscapes leading into the target folded state. Guided by these rules, we designed sequences predicted to fold into ideal protein structures consisting of α-helices, β-strands and minimal loops. Designs for five different topologies were found to be monomeric and very stable and to adopt structures in solution nearly identical to the computational models. These results illuminate how the folding funnels of natural proteins arise and provide the foundation for engineering a new generation of functional proteins free from natural evolution.

Conventional protein structure determination from nuclear magnetic resonance data relies heavily on side-chain proton-proton distances. The necessary side-chain resonance assignment, however, is labor intensive and prone to error. Here we show that structures can be accurately determined without NMR information on the sidechains for proteins up to 25 kDa by incorporating backbone chemical shifts, residual dipolar couplings, and amide proton distances into the Rosetta protein structure modelling methodology. These data, which are too sparse for conventional methods, serve only to guide conformational search towards the lowest energy conformations in the folding landscape; the details of the computed models are determined by the physical chemistry implicit in the Rosetta all atom energy function. The new method is not hindered by the deuteration required to suppress nuclear relaxation processes for proteins greater than 15 kDa, and should enable routine NMR structure determination for larger proteins.The first step in protein structure determination by NMR is chemical shift assignment for the backbone atoms. In contrast to the subsequent assignment of the sidechains, this is now rapid, reliable, and largely automated (1-5). Global backbone structural information complementing the local structure information provided by backbone chemical shift assignments (6,7), can be obtained from H N -H N NOESY, residual dipolar coupling (RDC) (8), and other (9,10) experiments. For larger proteins, deuteration becomes necessary to circumvent the efficient spin relaxation properties resulting from their higher rotational correlation times (11,12), but removing protons also eliminates long range NOESY information from sidechains except for selectively protonated sidechain moieties (13). The difficulty in determining accurate structures with no or limited sidechain information is a # To whom correspondence should be addressed. Phone: (206) 543-1295, Fax: (206) Here we show that structures of proteins up to 200 residues (23 kDa) can be determined using information from backbone (H N , N, C α , C β , C') NMR data by taking advantage of the conformational sampling and all atom energy function in the Rosetta structure prediction methodology, which for small proteins in favorable cases can produce atomic accuracy models starting from sequence information alone(15). Structure prediction in Rosetta proceeds in two steps; first a low resolution exploration phase using Monte-Carlo fragment assembly and a coarse-grained energy function, and second a computationally expensive refinement phase which cycles between combinatorial sidechain optimization and gradientbased minimization of all torsional degrees of freedom in a physically-realistic all-atom forcefield(15). The primary obstacle to Rosetta structure prediction from amino acid sequence information alone is conformational sampling; native structures almost always have lower energies than non-native conformations, but are very seldom sampled in unbiased trajectories. Incorpora...

The de novo design of protein-protein interfaces is a stringent test of our understanding of the principles underlying protein-protein interactions and would enable new approaches to biological and medical challenges. Here we describe a novel motif-based method to computationally design protein-protein complexes with native-like interface composition and interaction density. Using this method we designed a pair of proteins, Prb and Pdar, that heterodimerize with a Kd of 130 nM, 1,000-fold tighter than any previously designed de novo protein-protein complex. Directed evolution identified two point mutations that improve affinity to 180 pM. Crystal structures of complexes containing designed and evolved proteins reveal binding is entirely through the designed interface, making use of specific designed interactions. Surprisingly, in the evolved complex one of the partners is rotated 180 degrees relative to the design model. This work demonstrates that current understanding of protein-protein interfaces is sufficient to rationally design interfaces de novo, and underscores remaining challenges.