INCIDENTAL INTRAOSSEOUS CALCANEAL LIPOMA IN A PATIENT SUFFERING FROM PLANTARFASZIITIS.

Intraosseous calcaneal lipoma is a rare benign bone tumor. The incidence of intraosseous lipoma involving the calcaneus has been noted to account for fewer than 8-15% of all intraosseous lipoma. The etiology of the lesion is unknown. A post-traumatic secondary bone reaction, healing bone infarct, and benign neoplasm have been discussed. The symptoms can be nonspecific, varying from dull, intermittent pain to activity-related plantar pain. This pain can predictably be misdiagnosed as plantar fasciitis. We present the case of a 49-year-old male patient suffering from plantar fasciitis for three months and incidental asymptomatic intraosseous calcaneal lipoma, which was diagnosed by x-ray and CT scan. As the patient was out of complaints, the typical CT findings we saw no indication for biopsy but recommended regular CT and MRI controls.;

INTRAMUSCULAR MYXOMA OF THE BUTTOCK- A CASE REPORT.

Intramuscular myxoma (IM) is a benign, soft tissue neoplasm of mesenchymal origin. IM is rare, with an incidence of between 0.1 and 0.13 in every 100,000 individuals. Onset is usually between the fourth and seventh decades of life, predominantly in women (70%). The thigh is the common site of involvement seen in 51% patients, followed by upper arm (9%), calf (7%), and rarely in buttocks. We present the case of a 63-year-old female patient with a 6-month history of a growing IM of the right buttock. Due to rapid tumor growth resection of the tumor was indicated to obtain histopathological examination and to rule out malignancy. Marginal surgical removal was performed. Histopathological examination brought the diagnosis of a big intramuscular myxoma. There is no recurrence at latest follow-up.

Protein structure similarities.

Comparison of protein structures can reveal distant evolutionary relationships that would not be detected by sequence information alone. This helps to infer functional properties. In recent years, many methods for pairwise protein structure alignment have been proposed and are now available on the World Wide Web. Although these methods have made it possible to compare all available protein structures, they also highlight the remaining difficulties in defining a reliable score for protein structure similarities.

Mean-field minimization methods for biological macromolecules.

Simulations of macromolecular structures involve the minimization of a potential-energy function that presents many local minima. Mean-field theory provides a tool that enables us to escape these minima, by enhancing sampling in conformational space. The number of applications of this technique has increased significantly over the past year, enabling problems with protein-homology modelling and inverted protein structure prediction to be solved.

Application of a self-consistent mean field theory to predict protein side-chains conformation and estimate their conformational entropy.

Understanding the relations between the conformation of the side-chains and the backbone geometry is crucial for structure prediction as well as for homology modelling. To attempt to unravel these rules, we have developed a method which allows us to predict the position of the side-chains from the co-ordinates of the main-chain atoms. This method is based on a rotamer library and refines iteratively a conformational matrix of the side-chains of a protein, CM, such that its current element at each cycle CM (ij) gives the probability that side-chain i of the protein adopts the conformation of its possible rotamer j. Each residue feels the average of all possible environments, weighted by their respective probabilities. The method converges in only a few cycles, thereby deserving the name of self consistent mean field method. Using the rotamer with the highest probability in the optimized conformational matrix to define the conformation of the side-chain leads to the result that on average 72% of chi 1, 75% of chi 2 and 62% of chi 1 + 2 are correctly predicted for a set of 30 proteins. Tests with six pairs of homologous proteins have shown that the method is quite successful even when the protein backbone deviates from the correct conformation. The second application of the optimized conformational matrix was to provide estimates of the conformational entropy of the side-chains in the folded state of the protein. The relevance of this entropy is discussed.

Atomic environment energies in proteins defined from statistics of accessible and contact surface areas.

Atomic contact potentials are derived by statistical analysis of atomic surface contact areas versus atom type in a database of non-homologous protein structures. The atomic environment is characterized by the surface area accessible to solvent and the surface of contacts with polar and non-polar atoms. Four types of atoms are considered, namely neutral polar atoms from protein backbones and from protein side-chains, non-polar atoms and charged atoms. Potential energies delta Ej(E) are defined from the preference for an atom of type j to be in a given environment E compared to the expected value if everything was random; Boltzmann's law is then used to transform these preferences into energies. These new potentials very clearly discriminate misfolded from correct structural models. The performance of these potentials are critically assessed by monitoring the recognition of the native fold among a large number of alternative structural folding types (the hide-and-seek procedure), as well as by testing if the native sequence can be recovered from a large number of randomly shuffled sequences for a given 3D fold (a procedure similar to the inverse folding problem). We suggest that these potentials reflect the atomic short range non-local interactions in proteins. To characterise atomic solvation alone, similar potentials were derived as a function of the percentage of solvent-accessible area alone. These energies were found to agree reasonably well with the solvation formalism of Eisenberg and McLachlan.

De novo protein design. I. In search of stability and specificity.

We have developed a fully automated protein design strategy that works on the entire sequence of the protein and uses a full atom representation. At each step of the procedure, an all-atom model of the protein is built using the template protein structure and the current designed sequence. The energy of the model is used to drive a Monte Carlo optimization in sequence space: random moves are either accepted or rejected based on the Metropolis criterion. We rely on the physical forces that stabilize native protein structures to choose the optimum sequence. Our energy function includes van der Waals interactions, electrostatics and an environment free energy. Successful protein design should be specific and generate a sequence compatible with the template fold and incompatible with competing folds. We impose specificity by maintaining the amino acid composition constant, based on the random energy model. The specificity of the optimized sequence is tested by fold recognition techniques. Successful sequence designs for the B1 domain of protein G, for the lambda repressor and for sperm whale myoglobin are presented. We show that each additional term of the energy function improves the performance of our design procedure: the van der Waals term ensures correct packing, the electrostatics term increases the specificity for the correct native fold, and the environment solvation term ensures a correct pattern of buried hydrophobic and exposed hydrophilic residues. For the globin family, we show that we can design a protein sequence that is stable in the myoglobin fold, yet incompatible with the very similar hemoglobin fold.

De novo protein design. II. Plasticity in sequence space.

It is generally accepted that many different protein sequences have similar folded structures, and that there is a relatively high probability that a new sequence possesses a previously observed fold. An indirect consequence of this is that protein design should define the sequence space accessible to a given structure, rather than providing a single optimized sequence. We have recently developed a new approach for protein sequence design, which optimizes the complete sequence of a protein based on the knowledge of its backbone structure, its amino acid composition and a physical energy function including van der Waals interactions, electrostatics, and environment free energy. The specificity of the designed sequence for its template backbone is imposed by keeping the amino acid composition fixed. Here, we show that our procedure converges in sequence space, albeit not to the native sequence of the protein. We observe that while polar residues are well conserved in our designed sequences, non-polar amino acids at the surface of a protein are often replaced by polar residues. The designed sequences provide a multiple alignment of sequences that all adopt the same three-dimensional fold. This alignment is used to derive a profile matrix for chicken triose phosphate isomerase, TIM. The matrix is found to recognize significantly the native sequence for TIM, as well as closely related sequences. Possible application of this approach to protein fold recognition is discussed.

Construction of plasmids containing a unique acetylaminofluorene adduct located within a mutation hot spot. A new probe for frameshift mutagenesis.

N-2-acetylaminofluorene (AAF), a potent rat liver carcinogen, binds primarily to the C-8 position of guanine residues. In a bacterial forward mutation assay, more than 90% of the mutations induced by -AAF adducts are frameshift mutations located at specific sites: the so-called mutation hot spots. We are particularly interested in a class of -2 frameshift mutations occurring within a specific sequence, the NarI sequence. The NarI site, GGCGCC, contains three guanine residues that are approximately equally reactive toward -AAF substitution. To study further the mechanism by which mutations are induced by -AAF adducts at this site, we designed a new plasmid probe. In this paper we describe the construction and the effectiveness of this probe, pSM14, which provides a simple phenotypic test for detecting frameshift mutations within the NarI site. The construction and the characterization of plasmids with a single -AAF adduct in each of the three positions of the NarI site are also described. The strategy of construction that was used involves the ligation of oligonucleotides containing a single adduct in a NarI site into a gapped-duplex pSM14 plasmid. Plasmids that have successfully integrated the oligonucleotides by ligation at both the 5' and the 3' ends were purified by centrifugation on CsCl gradients. These constructs have been used in single adduct mutation studies.

Computing the geometry of a molecule in dihedral angle space using n.m.r.-derived constraints. A new algorithm based on optimal filtering.

We have developed a method based on optimal filtering to determine the three-dimensional structure of a protein from n.m.r.-derived constraints, using the dihedral angle internal representation of the molecule. It differs from currently proposed methods in that it directly produces estimates of errors on the parameters that are refined, hence providing an image of the minimum that has been found. A similar algorithm had already been proposed using cartesian co-ordinates as independent parameters, encoded in PROTEAN2. We found that using dihedral angles significantly reduces the computational burden of the technique, and provides better control over a priori informations that can be used, such as geometric restrictions for proline residues and informations from vicinal coupling constants. Performance of the method, encoded in FILMAN, is demonstrated by application to the folding of a ten-residue alanine polypeptide, to the geometric cyclization of an 11-residue peptide, as well as on the folding of a medium size protein, i.e. tendamistat. The validity of the error estimates on the dihedral angles produced by FILMAN is discussed.

Refined crystallographic structure of Pseudomonas aeruginosa exotoxin A and its implications for the molecular mechanism of toxicity.

Exotoxin A of Pseudomonas aeruginosa asserts its cellular toxicity through ADP-ribosylation of translation elongation factor 2, predicated on binding to specific cell surface receptors and intracellular trafficking via a complex pathway that ultimately results in translocation of an enzymatic activity into the cytoplasm. In early work, the crystallographic structure of exotoxin A was determined to 3.0 A resolution, revealing a tertiary fold having three distinct structural domains; subsequent work has shown that the domains are individually responsible for the receptor binding (domain I), transmembrane targeting (domain II), and ADP-ribosyl transferase (domain III) activities, respectively. Here, we report the structures of wild-type and W281A mutant toxin proteins at pH 8.0, refined with data to 1.62 A and 1.45 A resolution, respectively. The refined models clarify several ionic interactions within structural domains I and II that may modulate an obligatory conformational change that is induced by low pH. Proteolytic cleavage by furin is also obligatory for toxicity; the W281A mutant protein is substantially more susceptible to cleavage than the wild-type toxin. The tertiary structures of the furin cleavage sites of the wild-type and W281 mutant toxins are similar; however, the mutant toxin has significantly higher B-factors around the cleavage site, suggesting that the greater susceptibility to furin cleavage is due to increased local disorder/flexibility at the site, rather than to differences in static tertiary structure. Comparison of the refined structures of full-length toxin, which lacks ADP-ribosyl transferase activity, to that of the enzymatic domain alone reveals a salt bridge between Arg467 of the catalytic domain and Glu348 of domain II that restrains the substrate binding cleft in a conformation that precludes NAD+ binding. The refined structures of exotoxin A provide precise models for the design and interpretation of further studies of the mechanism of intoxication.

Modelling the dynamics of an antigenic peptide using NMR relaxation data.

The internal dynamics of a cyclic peptide which was designed to mimic an antigenic loop of the haemagglutinin, is studied through heteronuclear relaxation along the 13C alpha-1H alpha vectors and through homonuclear relaxation along the 1H alpha-1HN and 1H beta-1H beta' vectors. Order parameters are extracted from the longitudinal and cross-relaxation data. Molecular dynamics simulations are performed and the order parameters are calculated in different ways from the trajectories. The simulation, which is performed in vacuo, gives smaller order parameters (vector motions of larger amplitude) than the experimental results. However, the general features of the experimental order parameters are reproduced by the molecular dynamics simulation. The flexibility of the molecule can then be investigated from the results of the molecular dynamics. It shows that the mobility observed through the order parameters is due to motions in flanking regions, remote from the observed vectors.

Theoretical consideration of the chemical pathways for radiation-induced strand breaks.

A theoretical approach to the understanding of the biochemical mechanisms of indirect action of ionizing radiation on SV40 DNA in aqueous solution is presented. The extent of OH attack on the sugar moiety and bases has been calculated. A realistic model for the DNA (in B form) based on available X-ray diffraction data is used and specific reaction sites for the OH radicals are obtained. A Monte Carlo scheme is used to follow the diffusion and reaction of the OH radicals. Effects of track structure have been considered and the single strand break D37 values for 14 MeV electrons (low-LET) and 670 MeV/u and 40 MeV/u neon particles are presented. Calculated results are in agreement with available experimental data. It has been found that regardless of the qualities of radiation, 80% of the OH attack on DNA is on the bases and 20% is on the deoxyribose. From probability considerations only, it appears that the number of double strand breaks varies linearly with dose.

Polar and nonpolar atomic environments in the protein core: implications for folding and binding.

Hydrophobic interactions are believed to play an important role in protein folding and stability. Semi-empirical attempts to estimate these interactions are usually based on a model of solvation, whose contribution to the stability of proteins is assumed to be proportional to the surface area buried upon folding. Here we propose an extension of this idea by defining an environment free energy that characterizes the environment of each atom of the protein, including solvent, polar or nonpolar atoms of the same protein or of another molecule that interacts with the protein. In our model, the difference of this environment free energy between the folded state and the unfolded (extended) state of a protein is shown to be proportional to the area buried by nonpolar atoms upon folding. General properties of this environment free energy are derived from statistical studies on a database of 82 well-refined protein structures. This free energy is shown to be able to discriminate misfolded from correct structural models, to provide an estimate of the stabilization due to oligomerization, and to predict the stability of mutants in which hydrophobic residues have been substituted by site-directed mutagenesis, provided that no large structural modifications occur.

A self consistent mean field approach to simultaneous gap closure and side-chain positioning in homology modelling.

A new computational procedure which simultaneously provides gap closure and side-chain positioning in homology modelling is described. It uses a database search scheme to generate fragments to model gaps, a rotamer library to define side-chain conformations, and iteratively refines a conformational matrix CM, such that its elements CM(i,j,o) and CM(i,j,k) give the probabilities that the backbone of residue i adopts the conformation described by fragment j and that its side-chain adopts the conformation of its possible rotamer k. Each residue experiences the average of all possible environments, weighted by their respective probabilities. The method converges, thereby deserving the name of 'self consistent mean field' approach.

Influence of protein structure databases on the predictive power of statistical pair potentials.

A long standing goal in protein structure studies is the development of reliable energy functions that can be used both to verify protein models derived from experimental constraints as well as for theoretical protein folding and inverse folding computer experiments. In that respect, knowledge-based statistical pair potentials have attracted considerable interests recently mainly because they include the essential features of protein structures as well as solvent effects at a low computing cost. However, the basis on which statistical potentials are derived have been questioned. In this paper, we investigate statistical pair potentials derived from protein three-dimensional structures, addressing in particular questions related to the form of these potentials, as well as to the content of the database from which they are derived. We have shown that statistical pair potentials depend on the size of the proteins included in the database, and that this dependence can be reduced by considering only pairs of residue close in space (i.e., with a cutoff of 8 A). We have shown also that statistical potentials carry a memory of the quality of the database in terms of the amount and diversity of secondary structure it contains. We find, for example, that potentials derived from a database containing alpha-proteins will only perform best on alpha-proteins in fold recognition computer experiments. We believe that this is an overall weakness of these potentials, which must be kept in mind when constructing a database.

The inverse protein folding problem: self consistent mean field optimisation of a structure specific mutation matrix.

The goal of the inverse folding problem is to supply a list of sequences compatible with a known protein structure. If two-body interactions are taken into account in energy calculations, an exhaustive exploration of the energy landscape in sequence space cannot be achieved because of the huge number of possible combinations. To circumvent this problem, we propose a method in which multiple copies corresponding to every possible side-chain type are attached to each C alpha position in the protein. The weights of each copy (stored in the sequence matrix SM) are refined using mean field theory: each side-chain copy interacts with the mean field generated by all possible side-chain copies at neighbouring positions, weighted by their respective probabilities. The potential energy is simply taken to be amino acid pair potentials of mean force. The method converges in a few cycles to a self-consistent solution. The refined matrix does not depend on the starting point; therefore the method succeeds in removing memory effects. Starting solely from the backbone of the known structure, and without information from the initial sequence, the final sequence matrix SM is shown to be able to retrieve significant sequence information, as observed through a series of structure-recognizes-sequence(s) computer experiments. The issue of specificity is discussed in detail.

The native sequence determines sidechain packing in a protein, but does optimal sidechain packing determine the native sequence?

Globular proteins have highly compact structures and the corresponding packing interactions are widely considered as the principal determinant of the native structure. It is therefore important that theoretical approaches to protein design explicitly take in account packing, which requires that a full atomic representation of the designed protein is maintained. As a first step towards this goal, we have developed in this report an inverse folding algorithm with the aim of specifically designing amino acid sequences which optimise sidechain packing for a given protein fold. The design is performed by a global Monte Carlo optimisation in sequence space, with constant amino acid composition and a full-atom representation of the various protein models. Packing is defined by a Lennard-Jones potential. The program was tested by designing stable sequence variants for the chymotrypsin inhibitor fold. The final protein models showed an increase in intramolecular atomic contacts and a decrease in the overall volume compared to the native structure. Starting from the backbone only of the target structure, the algorithm did gradually retrieve reliable though limited sequence information. Higher compatibility might be achieved by improving the potential, however our results suggest that packing interactions are an essential element of a yet-to-be-defined successful energy function for protein design.