The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 Å. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 Å. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein−protein complexes, design altered specificity protein−protein and protein−DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.

The G-protein activated, inward-rectifying potassium (K + ) channels, "GIRKs", are a family of ion channels (K ir 3.1-K ir 3.4) that has been the focus of intense research interest for nearly two decades. GIRKs are comprised of various homo-and heterotetrameric combinations of four different subunits. These subunits are expressed in different combinations in a variety of regions throughout the central nervous system and in the periphery. The body of GIRK research implicates GIRK in processes as diverse as controlling heart rhythm, to effects on reward/addiction, to modulation of response to analgesics. Despite years of GIRK research, very few tools exist to selectively modulate GIRK channels' activity and until now no tools existed that potently and selectively activated GIRKs. Here we report the development and characterization of the first truly potent, effective, and selective GIRK activator, ML297 (VU0456810). We further demonstrate that ML297 is active in two in vivo models of epilepsy, a disease where up to 40% of patients remain with symptoms refractory to present treatments. The development of ML297 represents a truly significant advancement in our ability to selectively probe GIRK's role in physiology as well as providing the first tool for beginning to understand GIRK's potential as a target for a diversity of therapeutic indications.

To identify potential determinants of substrate selectivity in serotonin (5-HT) transporters (SERT), models of human and Drosophila serotonin transporters (hSERT, dSERT) were built based on the leucine transporter (LeuT Aa ) structure reported by Yamashita et al. (Nature 2005;437:215-223), PBDID 2A65. Although the overall amino acid identity between SERTs and the LeuT Aa is only 17%, it increases to above 50% in the first shell of the putative 5-HT binding site, allowing de novo computational docking of tryptamine derivatives in atomic detail. Comparison of hSERT and dSERT complexed with substrates pinpoints likely structural determinants for substrate binding. Forgoing the use of experimental transport and binding data of tryptamine derivatives for construction of these models enables us to cHitically assess and validate their predictive power: A single 5-HT binding mode was identified that retains the amine placement observed in the LeuT Aa structure, matches sitedirected mutagenesis and substituted cysteine accessibility method (SCAM) data, complies with support vector machine derived relations activity relations, and predicts computational binding energies for 5-HT analogs with a significant correlation coefficient (R = 0.72). This binding mode places 5-HT deep in the binding pocket of the SERT with the 5-position near residue hSERT A169/ dSERT D164 in transmembrane helix 3, the indole nitrogen next to residue Y176/Y171, and the ethylamine tail under residues F335/F327 and S336/S328 within 4 Å of residue D98. Our studies identify a number of potential contacts whose contribution to substrate binding and transport was previously unsuspected.★Correspondence to: Jens Meiler,

Computational small molecule docking into comparative models of proteins is widely used to query protein function and in the development of small molecule therapeutics. We benchmark RosettaLigand docking into comparative models for nine proteins built during CASP8 that contain ligands. We supplement the study with 21 additional protein/ligand complexes to cover a wider space of chemotypes. During a full docking run in 21 of the 30 cases, RosettaLigand successfully found a native-like binding mode among the top ten scoring binding modes. From the benchmark cases we find that careful template selection based on ligand occupancy provides the best chance of success while overall sequence identity between template and target do not appear to improve results. We also find that binding energy normalized by atom number is often less than −0.4 in native-like binding modes.

An increasingly used parameter in structural biology is the measurement of distances between spin labels bound to a protein. One limitation to these measurements is the unknown position of the spin label relative to the protein backbone. To overcome this drawback, we introduce a rotamer library of the methanethiosulfonate spin label (MTSSL) into the protein modeling program Rosetta. Spin label rotamers were derived from conformations observed in crystal structures of spin labeled T4 lysozyme and previously published molecular dynamics simulations. Rosetta’s ability to accurately recover spin label conformations and EPR measured distance distributions was evaluated against 19 experimentally determined MTSSL labeled structures of T4 lysozyme and the membrane protein LeuT and 73 distance distributions from T4 lysozyme and the membrane protein MsbA. For a site in the core of T4 lysozyme, the correct spin label conformation (Χ1 and Χ2) is recovered in 99.8% of trials. In surface positions 53% of the trajectories agree with crystallized conformations in Χ1 and Χ2. This level of recovery is on par with Rosetta performance for the 20 natural amino acids. In addition, Rosetta predicts the distance between two spin labels with a mean error of 4.4 Å. The width of the experimental distance distribution, which reflects the flexibility of the two spin labels, is predicted with a mean error of 1.3 Å. RosettaEPR makes full-atom spin label modeling available to a wide scientific community in conjunction with the powerful suite of modeling methods within Rosetta.

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Background:The Y 4 R is involved in regulation of food intake and gastrointestinal transport. Results: Mutagenesis studies revealed several residues displaying a significant loss of potency for hPP. Conclusion: Tops of TM2, TM6, and TM7 interact with the hY 4 R native agonist hPP. Significance: Characterizing the structure of the Y 4 R binding pocket is crucial for the development of new anti-obesity drugs.

This letter describes a multi-dimensional SAR campaign based on a potent, efficacious and selective GIRK1/2 activator (~10-fold versus GIRK1/4 and inactive on nonGIRK 1-containing GIRKs, GIRK 2 or GIRK2/3). Further chemical optimization through an iterative parallel synthesis effort identified multiple ‘molecular switches’ that modulated the mode of pharmacology from activator to inhibitor, as well as engendering varying selectivity profiles for GIRK1/2 and GIRK1/4. Importantly, these compounds were all inactive on nonGIRK1 containing GIRK channels. However, SAR was challenging as subtle structural modifications had large effects on both mode of pharmacology and GIRK1/2 and GIRK1/4 channel selectivity.