Heritable disorder resembling neuronal storage disease in mice expressing prion protein with deletion of an alpha-helix.

Mice were constructed carrying prion protein (PrP) transgenes with individual regions of putative secondary structure deleted. Transgenic mice with amino-terminal regions deleted remained healthy at >400 days of age, whereas those with either of carboxy-terminal alpha-helices deleted spontaneously developed fatal CNS illnesses similar to neuronal storage diseases. Deletion of either C-terminal helix resulted in PrP accumulation within cytoplasmic inclusions in enlarged neurons. Deletion of the penultimate C-terminal helix resulted in proliferation of rough endoplasmic reticulum. Mice with the C-terminal helix deleted were affected with nerve cell loss in the hippocampus and proliferation of smooth endoplasmic reticulum. Whether children with the human counterpart of this malady will be found remains to be determined.

Eight prion strains have PrP(Sc) molecules with different conformations.

Variations in prions, which cause different incubation times and deposition patterns of the prion protein isoform called PrP(Sc), are often referred to as 'strains'. We report here a highly sensitive, conformation-dependent immunoassay that discriminates PrP(Sc) molecules among eight different prion strains propagated in Syrian hamsters. This immunoassay quantifies PrP isoforms by simultaneously following antibody binding to the denatured and native forms of a protein. In a plot of the ratio of antibody binding to denatured/native PrP graphed as a function of the concentration of PrP(Sc), each strain occupies a unique position, indicative of a particular PrP(Sc) conformation. This conclusion is supported by a unique pattern of equilibrium unfolding of PrP(Sc) found with each strain. Our findings indicate that each of the eight prion strains has a PrP(Sc) molecule with a unique conformation and, in accordance with earlier results, indicate the biological properties of prion strains are 'enciphered' in the conformation of PrP(Sc) and that the variation in incubation times is related to the relative protease sensitivity of PrP(Sc) in each strain.

Mutational and secondary structural analysis of the basolateral sorting signal of the polymeric immunoglobulin receptor.

The 17-juxtamembrane cytoplasmic residues of the polymeric immunoglobulin receptor contain an autonomous basolateral targeting signal that does not mediate rapid endocytosis (Casanova, J. E., G. Apodaca, and K. E. Mostov. Cell. 66:65-75). Alanine-scanning mutagenesis identifies three residues in this region, His656, Arg657, and Val660, that are most essential for basolateral sorting and two residues, Arg655 and Tyr668, that play a lesser role in this process. Progressive truncations suggested that Ser664 and Ile665 might also play a role in basolateral sorting. However, mutation of these residues to Ala or internal deletions of these residues did not affect basolateral sorting, indicating that these residues are probably not required for basolateral sorting. Two-dimensional NMR spectroscopy of a peptide corresponding to the 17-mer signal indicates that the sequence Arg658-Asn-Val-Asp661 has a propensity to adopt a beta-turn in solution. Residues COOH-terminal to the beta-turn (Arg662 to Arg669) seem to take up a nascent helix structure in solution. Substitution of Val660 with Ala destabilizes the turn, while mutation of Arg657 to Ala does not appear to affect the turn structure. Neither mutation detectably altered the stability of the nascent helix in the COOH-terminal portion of the peptide.

Structure-activity studies of interleukin-2.

The critical role of interleukin-2 (IL-2) in immune response heightens the need to know its structure in order to understand its activity. New computer-assisted predictive methods for the assignment of secondary structure together with a method to predict the tertiary structure of a protein from data on its primary sequence and secondary structure were applied to IL-2. This method generated four topological families of structures, of which the most plausible is a right-handed fourfold alpha-helical bundle. Members of this family were shown to be compatible with existing structural data on disulfide bridges and monoclonal antibody binding for IL-2. Experimental estimates of secondary structure from circular dichroism and site-directed mutagenesis data support the model. A region likely to be important in IL-2 binding to its receptor was identified as residues Leu36, Met38, Leu40, Phe42, Phe44, and Met46.

Exploiting the basis of proline recognition by SH3 and WW domains: design of N-substituted inhibitors.

Src homology 3 (SH3) and WW protein interaction domains bind specific proline-rich sequences. However, instead of recognizing critical prolines on the basis of side chain shape or rigidity, these domains broadly accepted amide N-substituted residues. Proline is apparently specifically selected in vivo, despite low complementarity, because it is the only endogenous N-substituted amino acid. This discriminatory mechanism explains how these domains achieve specific but low-affinity recognition, a property that is necessary for transient signaling interactions. The mechanism can be exploited: screening a series of ligands in which key prolines were replaced by nonnatural N-substituted residues yielded a ligand that selectively bound the Grb2 SH3 domain with 100 times greater affinity.

Selective neuronal targeting in prion disease.

The pattern of scrapie prion protein (PrP(Sc)) accumulation in the brain is different for each prion strain. We tested whether the PrP(Sc) deposition pattern is influenced by the Asn-linked oligosaccharides of PrP(C) in transgenic mice. Deletion of the first oligosaccharide altered PrP(C) trafficking and prevented infection with two prion strains. Deletion of the second did not alter PrP(C) trafficking, permitted infection with one prion strain, and had a profound effect on the PrP(Sc) deposition pattern. Our data raise the possibility that glycosylation can modify the conformation of PrP(C). Glycosylation could affect the affinity of PrP(C) for a particular conformer of PrP(Sc), thereby determining the rate of nascent PrP(Sc) formation and the specific patterns of PrP(Sc) deposition.

A protease-resistant 61-residue prion peptide causes neurodegeneration in transgenic mice.

An abridged prion protein (PrP) molecule of 106 amino acids, designated PrP106, is capable of forming infectious miniprions in transgenic mice (S. Supattapone, P. Bosque, T. Muramoto, H. Wille, C. Aagaard, D. Peretz, H.-O. B. Nguyen, C. Heinrich, M. Torchia, J. Safar, F. E. Cohen, S. J. DeArmond, S. B. Prusiner, and M. Scott, Cell 96:869-878, 1999). We removed additional sequences from PrP106 and identified a 61-residue peptide, designated PrP61, that spontaneously adopted a protease-resistant conformation in neuroblastoma cells. Synthetic PrP61 bearing a carboxy-terminal lipid moiety polymerized into protease-resistant, beta-sheet-enriched amyloid fibrils at a physiological salt concentration. Transgenic mice expressing low levels of PrP61 died spontaneously with ataxia. Neuropathological examination revealed accumulation of protease-resistant PrP61 within neuronal dendrites and cell bodies, apparently causing apoptosis. PrP61 may be a useful model for deciphering the mechanism by which PrP molecules acquire protease resistance and become neurotoxic.

Modeling protein-ligand complexes.

Increasing the rate at which new biologically active compounds are found is a major goal in pharmaceutical chemistry. Recently, several computational methods have been proposed with this intent. For some time, algorithms have been used to direct ligand evolution on the basis of complementarity to the three-dimensional structure of a selected protein. Current research focuses on enhancements to methods for searching chemical databases, proposing sensible modifications to known active compounds, and construction of novel ligands from theoretical principles.

The prion folding problem.

Prion diseases are neurodegenerative disorders in which dramatic conformational change in the structure of the prion protein is the fundamental event. This structural transition involves the loss of substantial alpha-helical content and the acquisition of beta-sheet structure. A convergence of recent biological and structural studies argues that the mechanism underlying the prion diseases is truly unprecedented.

Collecting and harvesting biological data: the GPCRDB and NucleaRDB information systems.

The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.

Protein misfolding and prion diseases.

The prion diseases provide an intriguing connection between protein folding and neurodegenerative disease. In this review, I explore that importance of protein folding and misfolding in the prion diseases. Thermodynamic and kinetic models are examined in an effort to understand infectious, inherited and sporadic forms of these diseases. These concepts can be generalized to gain insight into other disorders of protein aggregation and deposition such as Alzheimer's disease.

Beta-breakers: an aperiodic secondary structure.

We have studied the architecture of parallel beta-sheets in proteins and focused on the residues that initiate and terminate the beta-strands. These beta-breaker residues are at the origin of the kink between the beta-strand and the turn that precedes or follows it. beta-Breakers can be located automatically using a consensus approach based on algorithmic secondary structure assignment, solvent accessibility and backbone dihedral angles. These beta-breakers are conformationally homogeneous with respect to side-chain solvent accessibility and backbone dihedral angle profile. A sequence-structure correlation is noted: a restricted subset of amino acids is observed at these positions. Analysis of homologous protein sequences shows that these residues are more highly conserved than other residues in the loop. We conclude that beta-breakers are the structural analogs of the N and C-terminal caps of alpha-helices. The identification of this aperiodic substructure suggests a strategy for improving secondary structure prediction and may guide site-directed mutagenesis experiments.

Protein folding. Effect of packing density on chain conformation.

Recent lattice polymer simulations by Chan & Dill suggest that compactness may be a significant driving force in the formation of secondary structure. We have addressed the robustness of this conclusion for non-lattice polymers using a rotational isomeric model of proteins. Boundary conditions are used to enforce compactness and excluded volume effects are explicitly incorporated. As in the cubic lattice studies, compactness is seen to influence secondary structure content. This effect is modest for densities comparable to native proteins but dramatic for chains that are approximately 30% more dense than native proteins. alpha-Helical structure is common but beta-sheet structure is rare. It appears that lattices impart to compact chains an organizational bias that favors beta-sheet structure. The strengths and weakness of various simplified representations of polypeptide chains are also discussed.

Multiple sequence information for threading algorithms.

Threading algorithms attempt to solve the inverse protein folding problem: given a group of structures and a sequence, identify the structure that is most compatible with this sequence. A recent study of this class of algorithms by S. J. Wodak and colleagues suggests that while threading algorithms are capable of recognizing many folding motifs, their performance in truly blind predictions is disappointing, and the underlying alignments upon which the selections are based are frequently errant. To help overcome this problem we have developed a Test of Optimal Mutagenesis algorithm (TOM) that exploits information inherent in the variation between several homologues in a multiple sequence alignment. This information is used to help select the correct structural motif for the sequence from a database of known structures. A total of 305 high-resolution structures were selected to represent the set of known folds; 56 proteins were chosen that had at least one close structural match in this set. To test TOM, we attempted to determine which of the 305 folds was a match to each of the 56 protein sequences. TOM correctly predicts a close structural match for 45% of these proteins. THREADER, an algorithm chosen as a literature standard, correctly matched 20% of the test set. By comparing the performance of TOM, THREADER, and TOM NOVAR (a version of TOM without variability information), we conclude that the tendency of an amino acid to be buried or exposed is the dominant determinant of the success of threading algorithms. In addition, the structural alignments produced by TOM suggest that the exact alignment of just 30 to 50% of the residues in a sequence with the correct fold is necessary to select it as the highest scoring match in a set of folds.

A surface of minimum area metric for the structural comparison of proteins.

A new method for comparing protein structures, based on a minimal surface metric, is developed. A virtual polypeptide backbone is created by joining consecutive C alpha atoms in a protein structure. The minimal surface between the virtual backbones of two proteins (the Area Functional) is determined numerically using an iterative triangulation strategy. The first protein is then rotated and translated in space until the smallest minimal surface is obtained. Such a technique yields the optimal structural superposition between two protein segments. It requires no initial sequence alignment, is relatively insensitive to insertions and deletions, and obviates the need to select a gap penalty. The optimal minimal area can then be converted to the Area-C alpha distance, measured in angstroms, to determine the structural similarity. This technique has been applied to a large class of proteins and is able to detect not only small-scale differences between closely related proteins but also large-scale topological similarities between evolutionary unrelated proteins that lack any obvious sequence homology. To measure the similarity between structurally dissimilar proteins, an additional measure (the Fit Comparison) is developed. This is a scale-invariant measure of a structural similarity that is useful for determining topological similarities between dissimilar proteins with unrelated sequences.

Novel method for the rapid evaluation of packing in protein structures.

There has been considerable effort to predict the structure of proteins from their amino acid sequences. A major problem in all prediction efforts has been that, short of a direct comparison with crystallographic co-ordinates, it is often difficult to evaluate the merit of a model, or "proposed" protein structure. Here, we present a method for evaluating proposed protein structures that does not require a structural model of complete atomic detail. Our method evaluates residue-residue packing density using a simplified model of the polypeptide chain where amino acids are represented as one, two (histidine, tyrosine and phenylalanine), or three (tryptophan) spheres. This method also gives a measure of the appropriateness of residue-residue contacts, thus giving a measure of the amino acid distribution throughout the protein. Amino acid packing and amino acid distribution, as evaluated by this technique, are consistent with the accuracy of model-built structures. We have been able to select the best structures from a set of combinatorially generated models using this method, and we anticipate that it will be useful as a general tool for model-building.

Pairwise sequence alignment below the twilight zone.

Improved sequence alignment at low pairwise identity is important for identifying potential remote homologues in database searches and for obtaining accurate alignments as a prelude to modeling structures by homology. Our work is motivated by two observations: structural data provide superior training examples for developing techniques to improve the alignment of remote homologues; and general substitution patterns for remote homologues differ from those of closely related proteins. We introduce a new set of amino acid residue interchange matrices built from structural superposition data. These matrices exploit known structural homology as a means of characterizing the effect evolution has on residue-substitution profiles. Given their origin, it is not surprising that the individual residue-residue interchange frequencies are chemically sensible. The structural interchange matrices show a significant increase both in pairwise alignment accuracy and in functional annotation/fold recognition accuracy across distantly related sequences. We demonstrate improved pairwise alignment by using superpositions of homologous domains extracted from a structural database as a gold standard and go on to show an increase in fold recognition accuracy using a database of homologous fold families. This was applied to the unassigned open reading frames from the genome of Helicobacter pylori to identify five matches, two of which are not represented by new annotations in the sequence databases. In addition, we describe a new cyclic permutation strategy to identify distant homologues that experienced gene duplication and subsequent deletions. Using this method, we have identified a potential homologue to one additional previously unassigned open reading frame from the H. pylori genome.

An evolutionary trace method defines binding surfaces common to protein families.

X-ray or NMR structures of proteins are often derived without their ligands, and even when the structure of a full complex is available, the area of contact that is functionally and energetically significant may be a specialized subset of the geometric interface deduced from the spatial proximity between ligands. Thus, even after a structure is solved, it remains a major theoretical and experimental goal to localize protein functional interfaces and understand the role of their constituent residues. The evolutionary trace method is a systematic, transparent and novel predictive technique that identifies active sites and functional interfaces in proteins with known structure. It is based on the extraction of functionally important residues from sequence conservation patterns in homologous proteins, and on their mapping onto the protein surface to generate clusters identifying functional interfaces. The SH2 and SH3 modular signaling domains and the DNA binding domain of the nuclear hormone receptors provide tests for the accuracy and validity of our method. In each case, the evolutionary trace delineates the functional epitope and identifies residues critical to binding specificity. Based on mutational evolutionary analysis and on the structural homology of protein families, this simple and versatile approach should help focus site-directed mutagenesis studies of structure-function relationships in macromolecules, as well as studies of specificity in molecular recognition. More generally, it provides an evolutionary perspective for judging the functional or structural role of each residue in protein structure.

Improvements in protein secondary structure prediction by an enhanced neural network.

Computational neural networks have recently been used to predict the mapping between protein sequence and secondary structure. They have proven adequate for determining the first-order dependence between these two sets, but have, until now, been unable to garner higher-order information that helps determine secondary structure. By adding neural network units that detect periodicities in the input sequence, we have modestly increased the secondary structure prediction accuracy. The use of tertiary structural class causes a marked increase in accuracy. The best case prediction was 79% for the class of all-alpha proteins. A scheme for employing neural networks to validate and refine structural hypotheses is proposed. The operational difficulties of applying a learning algorithm to a dataset where sequence heterogeneity is under-represented and where local and global effects are inadequately partitioned are discussed.

Identification of functional surfaces of the zinc binding domains of intracellular receptors.

Transcriptional regulatory factor complexes assemble on genomic response elements to control gene expression. To gain insights on the surfaces that determine this assembly in the zinc binding domains from intracellular receptors, we systematically analyzed the variations in sequence and function of those domains in the context of their invariant fold. Taking the intracellular receptor superfamily as a whole revealed a hierarchy of amino acid residues along the DNA interface that correlated with response element binding specificity. When only steroid receptors were considered, two additional sites appeared: the known dimer interface, and a novel putative interface suitably located to contact regulatory factors bound to the free face of palindromic response elements commonly used by steroid receptors. Surprisingly, retinoic acid receptors, not known to bind palindromic response elements, contain both of these surfaces, implying that they may dimerize at palindromic elements under some circumstances. This work extends Evolutionary Trace analysis of functional surfaces to protein-DNA interactions, suggests how coordinated exchange of trace residues may predictably switch binding specificity, and demonstrates how to detect functional surfaces that are not apparent from sequence comparison alone.