Feto-maternal interface of human placenta inhibits angiogenesis in the chick chorioallantoic membrane (CAM) assay.

The rapidly growing chorionic villi of the human placenta characteristically show constant blood vessel growth and differentiation. In contrast, the underlying decidua reveals tissue remodeling without apparent angiogenesis. Using the chick chorioallantoic membrane (CAM) assay, we found marked inhibition of angiogenesis by the feto-maternal interface tissue derived from nine human placentas obtained minutes after delivery. Inhibition was prevented by the addition of monensin, which blocks the release of synthesized cell products, and was markedly reduced by drying or freezing the tissue before the assay. Histology, combined with statistical analysis of the constituent cell types, correlated inhibition of angiogenesis with the number of fetally-derived extravillous trophoblasts in the feto-maternal interface tissue. Electron microscopy revealed endothelial cell damage in preexisting small (but not large) CAM vessels. We conclude that decidual tissue inhibited angiogenesis by releasing a water soluble factor which was under apparent constant production by vaible trophoblast on the CAM. The extravillous trophoblast population resembles tumor cells in its migratory and invasive properties but, in contrast to tumor induced angiogenesis, it is angiostatic, perhaps to counteract angiogenic proteins leaking from the intervillous space which could be detrimental to the maternal organism if active.

Structure comparison of human glioma pathogenesis-related protein GliPR and the plant pathogenesis-related protein P14a indicates a functional link between the human immune system and a plant defense system.

The human glioma pathogenesis-related protein (GliPR) is highly expressed in the brain tumor glioblastoma multiforme and exhibits 35% amino acid sequence identity with the tomato pathogenesis-related (PR) protein P14a, which has an important role for the plant defense system. A molecular model of GliPR was computed with the distance geometry program DIANA on the basis of a P14a-GliPR sequence alignment and a set of 1,200 experimental NMR conformational constraints collected with P14a. The GliPR structure is represented by a group of 20 conformers with small residual DIANA target function values, low AMBER-energies after restrained energy-minimization with the program OPAL, and an average rms deviation relative to the mean of 1.6 A for the backbone heavy atoms. Comparison of the GliPR model with the P14a structure lead to the identification of a common partially solvent-exposed spatial cluster of four amino acid residues, His-69, Glu-88, Glu-110, and His-127 in the GliPR numeration. This cluster is conserved in all known plant PR proteins of class 1, indicating a common putative active site for GliPR and PR-1 proteins and thus a functional link between the human immune system and a plant defense system.

Torsion angle dynamics for NMR structure calculation with the new program DYANA.

The new program DYANA (DYnamics Algorithm for Nmr Applications) for efficient calculation of three-dimensional protein and nucleic acid structures from distance constraints and torsion angle constraints collected by nuclear magnetic resonance (NMR) experiments performs simulated annealing by molecular dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than molecular dynamics in Cartesian coordinate space because of the reduced number of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temperatures in the structure calculation. It also represents a significant advance over the variable target function method in torsion angle space with the REDAC strategy used by the predecessor program DIANA. DYANA computation times per accepted conformer in the "bundle" used to represent the NMR structure compare favorably with those of other presently available structure calculation algorithms, and are of the order of 160 seconds for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test calculations starting from conformers with random torsion angle values further showed that DYANA is capable of efficient calculation of high-quality protein structures with up to 400 amino acid residues, and of nucleic acid structures.

Mapping of the primary binding site of measles virus to its receptor CD46.

The measles virus (MV) hemagglutinin binds to the complement control protein (CCP) CD46 primarily through the two external modules, CCP-I and -II. To define the residues involved in binding, 40 amino acids predicted to be solvent-exposed on the CCP-I-II module surface were changed to either alanine or serine. Altered proteins were expressed on the cell surface, and their abilities to bind purified MV particles, a soluble form of hemagglutinin (sH) and nine CD46-specific antibodies competing to different levels with sH attachment, were measured. All proteins retained, at least in part, MV and sH binding, but some completely lost binding to certain antibodies. Amino acids essential for binding of antibodies weakly or moderately competing with sH attachment are situated in the membrane-distal tip of CCP-I, whereas residues involved in binding of strongly sH competing antibodies cluster in the center of CCP-I (Arg-25, Asp-27) or in CCP-II (Arg-69, Asp-70). Both clusters face the same side of CCP-I-II and map close to amino acid exchanges impairing sH binding (E11A, R29A, P39A, and D70A) or MV binding (D70A and E84A) and to a six-amino acid loop, previously shown to be necessary for sH binding.

A 3D model for the measles virus receptor CD46 based on homology modeling, Monte Carlo simulations, and hemagglutinin binding studies.

The two terminal complement control protein (CCP) modules of the CD46 glycoprotein mediate measles virus binding. Three-dimensional models for these two domains were derived based on the NMR structures of two CCP modules of factor H. Both CD46 modules are about 35 A long, and form a five-stranded antiparallel beta-barrel structure. Monte Carlo simulations, sampling the backbone torsion angles of the linker peptide and selecting possible orientations on the basis of minimal solvent-exposed hydrophobic area, were used to predict the orientation of CCP-I relative to CCP-II. We tested this procedure successfully for factor H. For CD46, three clusters of structures differing in the tilt angle of the two domains were obtained. To test these models, we mutagenized the CCP modules. Four proteins, two without an oligosaccharide chain and two with mutated short amino acid segments, reached the cell surface efficiently. Only the protein without the CCP-I oligosaccharide chain maintained binding to the viral attachment protein hemagglutinin. These results are consistent with one of our models and suggest that the viral hemagglutinin does not bind at the membrane-distal tip of CD46, but near the concave CCP-II interface region.

Automated combined assignment of NOESY spectra and three-dimensional protein structure determination.

A procedure for automated protein structure determination is presented that is based on an iterative procedure during which the NOESY peak list assignment and the structure calculation are performed simultaneously. The input consists of a list of NOESY peak positions and a list of chemical shifts as obtained from sequence-specific resonance assignment. For the present applications of this approach the previously introduced NOAH routine was implemented in the distance geometry program DIANA. As an illustration, experimental 2D and 3D NOESY cross-peak lists of six proteins have been analyzed, for which complete sequence-specific 1H assignments are available for the polypeptide backbone and the amino acid side chains. The automated method assigned 70-90% of all NOESY cross peaks, which is on average 10% less than with the interactive approach, and only between 0.8% and 2.4% of the automatically assigned peaks had a different assignment than in the corresponding manually assigned peak lists. The structures obtained with NOAH/DIANA are in close agreement with those from manually assigned peak lists, and with both approaches the residual constraint violations correspond to high-quality NMR structure determinations. Systematic comparisons of the bundles of conformers that represent corresponding automatically and interactively determined structures document the absence of significant bias in either approach, indicating that an important step has been made towards automation of structure determination from NMR spectra.

Automated assignment of simulated and experimental NOESY spectra of proteins by feedback filtering and self-correcting distance geometry.

A new method for automatically assigning proton-proton NOESY spectra is described and demonstrated for simulated and experimental spectra of the proteins dendrotoxin K, alpha-amylase inhibitor tendamistat and the DNA-binding domain of the 434 repressor protein. The method assigns the NOESY spectrum and calculates three-dimensional protein structures simultaneously, using a list of proton chemical shifts and 3JNH alpha coupling constants. An ensemble of structures is iteratively calculated by self-correcting distance geometry from unambiguous and selected ambiguous NOESY cross peaks. New structure based filters recognize the correct constraints from the ambiguous cross peak list. For the first round of assignment neither a preliminary initial structure nor a sufficient set of unambiguous NOESY cross peaks is needed. The method can also be applied to cross peak lists containing hundreds of noise peaks. For an assumed tolerance of +/- 0.01 ppm in the chemical shifts of the peak positions, only about 10% of the NOESY cross peaks can be unambiguously assigned based on their chemical shifts alone. Our automated method assigned about 80% of all cross peaks with this chemical shift tolerance, and 95 to 99% of the assignments were correct. The average pairwise RMSD for the backbone atoms of the ten best final structures is about 1.5 A in all three proteins and the previously determined NMR solution structures are always embedded in this structure bundle. We regard our method as a highly practical tool for automatic calculation of three-dimensional protein structures from NMR spectra with minimal human interference.

Predicting the helix packing of globular proteins by self-correcting distance geometry.

A new self-correcting distance geometry method for predicting the three-dimensional structure of small globular proteins was assessed with a test set of 8 helical proteins. With the knowledge of the amino acid sequence and the helical segments, our completely automated method calculated the correct backbone topology of six proteins. The accuracy of the predicted structures ranged from 2.3 A to 3.1 A for the helical segments compared to the experimentally determined structures. For two proteins, the predicted constraints were not restrictive enough to yield a conclusive prediction. The method can be applied to all small globular proteins, provided the secondary structure is known from NMR analysis or can be predicted with high reliability.