Using evolutionary information contained in multiple sequence alignments as input to neural networks, secondary structure can be predicted at significantly increased accuracy. Here, we extend our previous three-level system of neural networks by using additional input information derived from multiple alignments. Using a position-specific conservation weight as part of the input increases performance. Using the number of insertions and deletions reduces the tendency for overprediction and increases overall accuracy. Addition of the global amino acid content yields a further improvement, mainly in predicting structural class. The final network system has sustained overall accuracy of 71.6% in a multiple cross-validation test on 126 unique protein chains. A test on a new set of 124 recently solved protein structures that have no significant sequence similarity to the learning set confirms the high level of accuracy. The average cross-validated accuracy for all 250 sequence-unique chains is above 72%. Using various data sets, the method is compared to alternative prediction methods, some of which also use multiple alignments: the performance advantage of the network system is at least 6 percentage points in three-state accuracy. In addition, the network estimates secondary structure content from multiple sequence alignments about as well as circular dichroism spectroscopy on a single protein and classifies 75% of the 250 proteins correctly into one of four protein structural classes. Of particular practical importance is the definition of a position-specific reliability index. For 40% of all residues the method has a sustained three-state accuracy of 88%, as high as the overall average for homology modelling. A further strength of the method is greatly increased accuracy in predicting the placement of secondary structure segments.

/pdf/combining-evolutionary-information-and-neural-networks-to-1erh7f9bkj.pdf

Combining evolutionary information and neural networks to predict protein secondary structure.

The structure

Supported lipid bilayers (SLBs) are popular models of cell membranes with potential bio-technological applications. A qualitative understanding of the process of SLB formation after exposure of small lipid vesicles to a hydrophilic support is now emerging. Recent studies have revealed a stunning variety of effects that can take place during this self-organization process. The ensemble of results in our group has revealed unprecedented insight into intermediates of the SLB-formation process and has helped to identify a number of parameters that are determinant for the lipid deposition on solid supports. The pathway of lipid deposition can be tuned by electrostatic interactions and by the presence of calcium. We emphasize the importance of the solid support in the SLB-formation process. Our results suggest that the molecular-level interaction between lipids and the solid support needs to be considered explicitly, to understand the rupture of vesicles and the formation of SLBs as well as to predict the properties of the resulting SLB. The impact of the SLB-formation process on the quality and the physical properties of the resulting SLB as well as implications for other types of surface-confined lipid bilayers are discussed.

Formation of solid-supported lipid bilayers: an integrated view.

A protein is usually classified into one of the following five struc- tural classes: a!, j3, a! +j3, a!/j3, and ( (irregular). The structural class of aprotein is correlated with its amino acid composition. However, given the amino acid composition of aprotein, how may one predict its structural class? Various efforts have been made in addressing this problem. This review addresses the progress in this field, with the focus on the state of the art, which is featured by a novel prediction algorithm and a recently developed database. The novel algorithm is characterized by a covariance matrix that takes into account the coupling effect among different amino acid components of a protein. The new database was established based on the requirement that the classes should have (1) as many nonhomologous structures as possible, (2) good quality structure, and (3) typical or distinguishable features for each of the structural classes concerned. The very high success rate for both the training-set proteins and the testing-set proteins, which has been further validated by a simulated analysis and a jackknife analysis, indicates that it is possible to predict the structural class of a protein according to its amino acid composition if an ideal and complete database can be established. It also suggests that the overall fold of a protein is basically determined by its amino acid composition.

Prediction of protein structural classes.

Interaction of membrane proteins and lipids with solubilizing detergents.

Mammalian GPI proteins: sorting, membrane residence and functions.

Several cell surface eukaryotic proteins have a glycosylphosphatidylinositol (GPI) modification at the C-terminal end that serves as an anchor to the plasma membrane and could be responsible for the presence of GPI proteins in rafts, a type of functionally important membrane microdomain enriched in sphingolipids and cholesterol In order to understand better how GPI proteins partition into rafts, the insertion of the GPI-anchored alkaline phosphatase (AP) was studied in real-time using atomic force microscopy Supported phospholipid bilayers made of a mixture of sphingomyelin-dioleoylphosphatidylcholine containing cholesterol (Chl+) or not (Chl-) were used to mimic the fluid-ordered lipid phase separation in biological membranes Spontaneous insertion of AP through its GPI anchor was observed inside both Chl+ and Chl- lipid ordered domains, but AP insertion was markedly increased by the presence of cholesterol

/pdf/spontaneous-insertion-and-partitioning-of-alkaline-27vwbc8rs2.pdf

Spontaneous insertion and partitioning of alkaline phosphatase into model lipid rafts

The lattice location of three rare‐earth ions (Pr3+, Ho3+, Yb3+) in LiNbO3 is investigated using Rutherford backscattering spectrometry/channeling techniques. All of them are found to occupy the Li+ octahedron but shifted from the Li+ regular position by different amounts (−0.45 A for Pr3+, −0.38 A for Ho3+, and −0.3 A for Yb3+) as previously reported for other rare‐earth ions. The amount of displacement is directly related to the variation of the ionic radius of the rare‐earth ion, oppositely to transition metal ions which are not shifted. A simple model based on electronic configuration is given to account for this behavior.

Lattice location of rare‐earth ions in LiNbO3

To investigate the possible role(s) of glycans in human tissue non-specific alkaline phosphatase (TNAP) activity, the iso-enzymes were purified and treated with various exo- and endo-glycosidases. Catalytic activity, oligomerization, conformation and immunoreactivity of the modified TNAPs were evaluated. All TNAPs proved to be N-glycosylated, and only the liver isoform (LAP) is not O-glycosylated. Usually, the kidney (KAP) and bone (BAP) isoenzymes are similar and cannot be clearly discriminated. Differences between the immunoreactivity of KAP/BAP and LAP with a BAP antibody were mainly attributed to the N-glycosylated moieties of the TNAPs. In addition, elimination of O-glycosylations moderately affects the TNAP reactivity. Interestingly, N-glycosylation is absolutely essential for TNAP activity, but not for that of the placental or intestinal enzymes. According to the deduced amino acid sequence of TNAP cDNA, Asn-213 is a possible N-glycosylation site, and our present findings suggest that this sugar chain plays a key role in enzyme regulation. With regard to the oligomeric state of alkaline phosphatase (AP) isoforms, the dimer/tetramer equilibrium is dependent on the deglycosylation of glycosyl-phosphatidylinositol(GPI)-free APs, but not GPI-linked APs. This equilibrium does not affect the AP conformation as observed with CD. With regard to TNAPs, no data were available on the gene expression or nature of the 5'-non-translated leader exon of human KAP, as opposed to BAP and LAP genes. cDNA sequencing revealed that cortex/medulla KAP is genetically related to BAP, and medulla KAP to LAP.

/pdf/human-tissue-non-specific-alkaline-phosphatases-sugar-moiety-1oqg99ahct.pdf

Human tissue non-specific alkaline phosphatases: sugar-moiety-induced enzymic and antigenic modulations and genetic aspects.

The influence of thermocapillary forces on buoyancy-driven convection is numerically simulated for shallow open cavities with differentially heated endwalls and filled with low-Prandtl-number fluid. Calculations are carried out by solving two-dimensional Navier-Stokes equations coupled to the energy equation, for three aspects ratios A = (length/height) = 4, 12.5 and 25, and several values of the Grashof number (up to 6 × 104) and Reynolds number (|Re| ≤ 1.67 × 104). Thermocapillarity can have a quite significant effect on the stability of a primarily buoyancy-driven flow. The result of the combination of the two basic mechanisms (thermo-capillarity) and buoyancy) depends on whether their effects are additive (positive Re) or opposing (negative Re); counter-acting mechanisms yield more complex flow patterns. The critical Grashof number Grc for the onset of the unsteady regime is found to decrease substantially within a small range of negative Re, and to increase for positive Re (and also for large negative Re). For Gr = 4 × 104, A = 4 and small negative Reynolds numbers, −2.4 × 103 ≤ Re < 0, mono-periodic and bi- or quasi-periodic regimes are shown to exist successively, followed by a reverse transition. The development of the instabilities from an initial steady-state regime has been investigated by varying Re for Gr = 1.5 × 104 (below Grc at Re = 0); the onset of buoyant instabilities is enhanced in a narrow range of Re only (-1200 < Re < -200). It is also noteworthy that for small enough Grashof numbers (e.g. Gr = 3 × 103), a steady-state solution prevails over the whole range of Reynolds numbers investigated. This means that a critical Grashof number exists below which the effect of the thermocapillary forces is no longer destabilizing.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022112092001009

Bernard Roux

Papers

Mammalian GPI proteins: sorting, membrane residence and functions.

Spontaneous insertion and partitioning of alkaline phosphatase into model lipid rafts

Lattice location of rare‐earth ions in LiNbO3

Human tissue non-specific alkaline phosphatases: sugar-moiety-induced enzymic and antigenic modulations and genetic aspects.

Buoyancy- and thermocapillary-driven flows in differentially heated cavities for low-Prandtl-number fluids