Hox2 Genes Are Required for Tonotopic Map Precision and Sound Discrimination in the Mouse Auditory Brainstem

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Toward better refinement of comparative models: predicting loops in inexact environments

Achieving atomic-level accuracy in comparative protein models is limited by our ability to refine the initial, homolog-derived model closer to the native state. Despite considerable effort, progress in developing a generalized refinement method has been limited. In contrast, methods have been described that can accurately reconstruct loop conformations in native protein structures. We hypothesize that loop refinement in homology models is much more difficult than loop reconstruction in crystal structures, in part, because side-chain, backbone, and other structural inaccuracies surrounding the loop create a challenging sampling problem; the loop cannot be refined without simultaneously refining adjacent portions. In this work, we single out one sampling issue in an artificial but useful test set and examine how loop refinement accuracy is affected by errors in surrounding side-chains. In 80 high-resolution crystal structures, we first perturbed 6-12 residue loops away from the crystal conformation, and placed all protein side chains in non-native but low energy conformations. Even these relatively small perturbations in the surroundings made the loop prediction problem much more challenging. Using a previously published loop prediction method, median backbone (N-Calpha-C-O) RMSD's for groups of 6, 8, 10, and 12 residue loops are 0.3/0.6/0.4/0.6 A, respectively, on native structures and increase to 1.1/2.2/1.5/2.3 A on the perturbed cases. We then augmented our previous loop prediction method to simultaneously optimize the rotamer states of side chains surrounding the loop. Our results show that this augmented loop prediction method can recover the native state in many perturbed structures where the previous method failed; the median RMSD's for the 6, 8, 10, and 12 residue perturbed loops improve to 0.4/0.8/1.1/1.2 A. Finally, we highlight three comparative models from blind tests, in which our new method predicted loops closer to the native conformation than first modeled using the homolog template, a task generally understood to be difficult. Although many challenges remain in refining full comparative models to high accuracy, this work offers a methodical step toward that goal.     

Expanding GPCR homology model binding sites via a balloon potential: A molecular dynamics refinement approach

Homology modeling of G protein-coupled receptors is becoming a widely used tool in drug discovery. However, unrefined models built using the bovine rhodopsin crystal structure as the template, often have binding sites that are too small to accommodate known ligands. Here, we present a novel systematic method to refine model active sites based on a pressure-guided molecular dynamics simulation. A distinct advantage of this approach is the ability to introduce systematic perturbations in model backbone atoms in addition to side chain adjustments. The method is validated on two test cases: (1) docking of retinal into an MD-relaxed structure of opsin and (2) docking of known ligands into a homology model of the CCR2 receptor. In both cases, we show that the MD expansion algorithm makes it possible to dock the ligands in poses that agree with the crystal structure or mutagenesis data.     

Protein-protein docking by simulating the process of association subject to biochemical constraints

We present a computational procedure for modeling protein-protein association and predicting the structures of protein-protein complexes. The initial sampling stage is based on an efficient Brownian dynamics algorithm that mimics the physical process of diffusional association. Relevant biochemical data can be directly incorporated as distance constraints at this stage. The docked configurations are then grouped with a hierarchical clustering algorithm into ensembles that represent potential protein-protein encounter complexes. Flexible refinement of selected representative structures is done by molecular dynamics simulation. The protein-protein docking procedure was thoroughly tested on 10 structurally and functionally diverse protein-protein complexes. Starting from X-ray crystal structures of the unbound proteins, in 9 out of 10 cases it yields structures of protein-protein complexes close to those determined experimentally with the percentage of correct contacts >30% and interface backbone RMSD <4 A. Detailed examination of all the docking cases gives insights into important determinants of the performance of the computational approach in modeling protein-protein association and predicting of protein-protein complex structures.     

A novel method for predicting and using distance constraints of high accuracy for refining protein structure prediction

The principal bottleneck in protein structure prediction is the refinement of models from lower accuracies to the resolution observed by experiment. We developed a novel constraints‐based refinement method that identifies a high number of accurate input constraints from initial models and rebuilds them using restrained torsion angle dynamics (rTAD). We previously created a Bayesian statistics‐based residue‐specific all‐atom probability discriminatory function (RAPDF) to discriminate native‐like models by measuring the probability of accuracy for atom type distances within a given model. Here, we exploit RAPDF to score (i.e., filter) constraints from initial predictions that may or may not be close to a native‐like state, obtain consensus of top scoring constraints amongst five initial models, and compile sets with no redundant residue pair constraints. We find that this method consistently produces a large and highly accurate set of distance constraints from which to build refinement models. We further optimize the balance between accuracy and coverage of constraints by producing multiple structure sets using different constraint distance cutoffs, and note that the cutoff governs spatially near versus distant effects in model generation. This complete procedure of deriving distance constraints for rTAD simulations improves the quality of initial predictions significantly in all cases evaluated by us. Our procedure represents a significant step in solving the protein structure prediction and refinement problem, by enabling the use of consensus constraints, RAPDF, and rTAD for protein structure modeling and refinement. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Template‐free protein structure prediction and quality assessment with an all‐atom free‐energy model

Biophysical forcefields have contributed less than originally anticipated to recent progress in protein structure prediction. Here, we have investigated the selectivity of a recently developed all‐atom free‐energy forcefield for protein structure prediction and quality assessment (QA). Using a heuristic method, but excluding homology, we generated decoy‐sets for all targets of the CASP7 protein structure prediction assessment with <150 amino acids. The decoys in each set were then ranked by energy in short relaxation simulations and the best low‐energy cluster was submitted as a prediction. For four of nine template‐free targets, this approach generated high‐ranking predictions within the top 10 models submitted in CASP7 for the respective targets. For these targets, our de‐novo predictions had an average GDT_S score of 42.81, significantly above the average of all groups. The refinement protocol has difficulty for oligomeric targets and when no near‐native decoys are generated in the decoy library. For targets with high‐quality decoy sets the refinement approach was highly selective. Motivated by this observation, we rescored all server submissions up to 200 amino acids using a similar refinement protocol, but using no clustering, in a QA exercise. We found an excellent correlation between the best server models and those with the lowest energy in the forcefield. The free‐energy refinement protocol may thus be an efficient tool for relative QA and protein structure prediction. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Structure of Hepatitis B Surface Antigen from Subviral Tubes Determined by Electron Cryomicroscopy

Hepatitis B virus consists of an icosahedral core containing the double-stranded DNA genome, enveloped by a membrane with embedded surface proteins. The crystal structure of the core protein has been solved but little information about the structure of the surface proteins has so far been available. There are three sizes of surface protein, small (S), medium (M) and large (L), which form disulfide-bonded homo- and heterodimers. The three proteins, expressed from different start sites in the coding sequence, share the common C-terminal S region; the M protein contains an additional preS2 sequence N-terminal to S, and the L protein a further preS1 sequence N-terminal to M. In infected individuals, the surface proteins are produced in huge excess over the amount needed for viral envelopment and are secreted as a heterogeneous mixture of isometric and tubular subviral particles. We have used electron cryomicroscopy to study tubular particles extracted from human serum. Helical Fourier-Bessel analysis was used to calculate a low-resolution map, although it showed that the tubes were quite disordered. From the symmetry derived from this analysis, we used single-particle methods to improve the resolution. We found that the tubes had a diameter of approximately 250 Å, with spike-like features projecting from the membrane. In the plane of the membrane the proteins appear to be close packed. We propose a model for the packing arrangement of surface protein dimers in the tubes.     

Behavioral tests as indicator for pain and distress in a primate endometriosis model

Background As common marmosets (Callithrix jacchus) are frequently used experimental animals, sensitive test systems are needed to evaluate impairment and pain caused by procedures and diseases. Methods A diurnal profile of healthy animals was obtained by videotaping. Differences in social behavior and cognitive skills between marmosets with established endometriosis and healthy monkeys were investigated using the videotaping, the Wisconsin General Test Apparatus (WGTA), and a food tree. Results The marmosets showed a mostly trimodal course of activity. Social grooming and activity were significantly decreased in animals with endometriosis; furthermore, the diseased monkeys habituated significantly worse to the cognitive test settings. The food tree experiments offered no differences between diseased and control animals. Conclusion The videotaping and the WGTA are suitable methods to detect disease‐related impairments in common marmosets, which is essential for the refinement of experiments.     

Identifying roles for neurotransmission in circuit assembly: insights gained from multiple model systems and experimental approaches

In the adult nervous system, chemical neurotransmission between neurons is essential for information processing. However, neurotransmission is also important for patterning circuits during development, but its precise roles have yet to be identified, and some remain highly debated. Here, we highlight viewpoints that have come to be widely accepted or still challenged. We discuss how distinct techniques and model systems employed to probe the developmental role of neurotransmission may reconcile disparate ideas. We underscore how the effects of perturbing neurotransmission during development vary with model systems, the stage of development when transmission is altered, the nature of the perturbation, and how connectivity is assessed. Based on findings in circuits with connectivity arranged in layers, we raise the possibility that there exist constraints in neuronal network design that limit the role of neurotransmission. We propose that activity-dependent mechanisms are effective in refining connectivity patterns only when inputs from different cells are close enough, spatially, to influence each other's outcome.