Shear-induced α → γ transformation in nanoscale Fe-C composite

High-resolution transmission electron microscopy and three-dimensional atom probe observations show clearly that a reverse transformation of body-centred cubic ferrite to face-centred cubic austenite occurs during severe plastic deformation of a pearlitic steel resulting in a nanocrystalline structure, something that never occurs in conventional deformation of coarse-grained iron and steels. The driving force and the mechanisms of this reverse transformation are discussed. It is shown that nanostructure and shear stresses are essential for this process, and the results confirm molecular dynamics predictions of such transformations in nanocrystalline iron

Tailoring the microstructure and tribological properties in commercially pure aluminium processed by High Pressure Torsion Extrusion

High Pressure Torsion Extrusion (HPTE) as a novel approach in mechanical nanostructuring of metallic materials and alloys has the potential to be utilized in industrial applications due to its unique features in fabricating bulk-nanostructured materials with enhanced mechanical and functional properties. Three different HPTE regimes based on the extrusion speed of the punch (v, mm/min) and rotational speed of the die (ω, rpm) were used in this work: v7w1, v1w1, and v1w3. The grain refinement obtained by this technique was outstanding since the initial grain size of 120 μm in annealed conditions was reduced to the final grain size of 0.7 μm in v1w3 in merely one pass of extrusion; however, each regime showed a different level of grain refinement depending on the imposed strain. Examination of the tribological properties by reciprocal wear testing in dry conditions revealed no significant change in the coefficient of friction; nevertheless, the mechanism of the wear from adhesion shifted to abrasion and the amount of displaced volume decreased. This modification is associated with the improvement of hardness and the reduction of plasticity in materials that confined the plastic shearing. Increasing the induced strain by changing the HPTE regimes decreased the overall displaced volume and reduced the built-up edge around the wear track

Formation and thermal stability of ω-Ti(Fe) in α-phase-based Ti(Fe) alloys

In this work, the formation and thermal stability of the ω-Ti(Fe) phase that were produced by the high-pressure torsion (HPT) were studied in two-phase α-Ti + TiFe alloys containing 2 wt.%, 4 wt.% and 10 wt.% iron. The two-phase microstructure was achieved by annealing the alloys at 470 °C for 4000 h and then quenching them in water. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) were utilized to characterize the samples. The thermal stability of the ω-Ti(Fe) phase was investigated using differential scanning calorimetry (DSC) and in situ high-temperature XRD. In the HPT process, the high-pressure ω-Ti(Fe) phase mainly formed from α-Ti. It started to decompose by a cascade of exothermic reactions already at temperatures of 130 °C. The decomposition was finished above ~320 °C. Upon further heating, the phase transformation proceeded via the formation of a supersaturated α-Ti(Fe) phase. Finally, the equilibrium phase assemblage was established at high temperatures. The eutectoid temperature and the phase transition temperatures measured in deformed and heat-treated samples are compared for the samples with different iron concentrations and for samples with different phase compositions prior to the HPT process. Thermodynamic calculations were carried out to predict stable and metastable phase assemblages after heat-treatments at low (α-Ti + TiFe) and high temperatures (α-Ti + β-(Ti,Fe), β-(Ti,Fe))

Degradation of structure and properties of rail surface layer at long-term operation

The microstructure evolution and properties variation of the surface layer of rail steel after passed 500 and 1000 million tons of gross weight (MTGW) have been investigated. The wear rate increases to 3 and 3.4 times after passed 500 and 1000 MTGW, respectively. The corresponding friction coefficient decreases by 1.4 and 1.1 times. The cementite plates were destroyed and formed the cementite particles of around 10-50 nm in size after passed 500 MTGW. The early stage dynamical recrystallization was observed after passed 1000 MTGW. The mechanisms for these have been suggested. The large number of bend extinction contours is revealed in the surface layer. The internal stress field is evaluated

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

SMAP-WS: a parallel web service for structural proteome-wide ligand-binding site comparison

The proteome-wide characterization and analysis of protein ligand-binding sites and their interactions with ligands can provide pivotal information in understanding the structure, function and evolution of proteins and for designing safe and efficient therapeutics. The SMAP web service (SMAP-WS) meets this need through parallel computations designed for 3D ligand-binding site comparison and similarity searching on a structural proteome scale. SMAP-WS implements a shape descriptor (the Geometric Potential) that characterizes both local and global topological properties of the protein structure and which can be used to predict the likely ligand-binding pocket [Xie,L. and Bourne,P.E. (2007) A robust and efficient algorithm for the shape description of protein structures and its application in predicting ligand-binding sites. BMC bioinformatics, 8 (Suppl. 4.), S9.]. Subsequently a sequence order independent profile–profile alignment (SOIPPA) algorithm is used to detect and align similar pockets thereby finding protein functional and evolutionary relationships across fold space [Xie, L. and Bourne, P.E. (2008) Detecting evolutionary relationships across existing fold space, using sequence order-independent profile-profile alignments. Proc. Natl Acad. Sci. USA, 105, 5441–5446]. An extreme value distribution model estimates the statistical significance of the match [Xie, L., Xie, L. and Bourne, P.E. (2009) A unified statistical model to support local sequence order independent similarity searching for ligand-binding sites and its application to genome-based drug discovery. Bioinformatics, 25, i305–i312.]. These algorithms have been extensively benchmarked and shown to outperform most existing algorithms. Moreover, several predictions resulting from SMAP-WS have been validated experimentally. Thus far SMAP-WS has been applied to predict drug side effects, and to repurpose existing drugs for new indications. SMAP-WS provides both a user-friendly web interface and programming API for scientists to address a wide range of compute intense questions in biology and drug discovery

LigASite—a database of biologically relevant binding sites in proteins with known apo-structures

Better characterization of binding sites in proteins and the ability to accurately predict their location and energetic properties are major challenges which, if addressed, would have many valuable practical applications. Unfortunately, reliable benchmark datasets of binding sites in proteins are still sorely lacking. Here, we present LigASite (‘LIGand Attachment SITE’), a gold-standard dataset of binding sites in 550 proteins of known structures. LigASite consists exclusively of biologically relevant binding sites in proteins for which at least one apo- and one holo-structure are available. In defining the binding sites for each protein, information from all holo-structures is combined, considering in each case the quaternary structure defined by the PQS server. LigASite is built using simple criteria and is automatically updated as new structures become available in the PDB, thereby guaranteeing optimal data coverage over time. Both a redundant and a culled non-redundant version of the dataset is available at http://www.scmbb.ulb.ac.be/Users/benoit/LigASite. The website interface allows users to search the dataset by PDB identifiers, ligand identifiers, protein names or sequence, and to look for structural matches as defined by the CATH homologous superfamilies. The datasets can be downloaded from the website as Schema-validated XML files or comma-separated flat files

Binding MOAD, a high-quality protein–ligand database

Binding MOAD (Mother of All Databases) is a database of 9836 protein–ligand crystal structures. All biologically relevant ligands are annotated, and experimental binding-affinity data is reported when available. Binding MOAD has almost doubled in size since it was originally introduced in 2004, demonstrating steady growth with each annual update. Several technologies, such as natural language processing, help drive this constant expansion. Along with increasing data, Binding MOAD has improved usability. The website now showcases a faster, more featured viewer to examine the protein–ligand structures. Ligands have additional chemical data, allowing for cheminformatics mining. Lastly, logins are no longer necessary, and Binding MOAD is freely available to all at http://www.BindingMOAD.org

Beauty Is in the Eye of the Beholder: Proteins Can Recognize Binding Sites of Homologous Proteins in More than One Way

Understanding the mechanisms of protein–protein interaction is a fundamental problem with many practical applications. The fact that different proteins can bind similar partners suggests that convergently evolved binding interfaces are reused in different complexes. A set of protein complexes composed of non-homologous domains interacting with homologous partners at equivalent binding sites was collected in 2006, offering an opportunity to investigate this point. We considered 433 pairs of protein–protein complexes from the ABAC database (AB and AC binary protein complexes sharing a homologous partner A) and analyzed the extent of physico-chemical similarity at the atomic and residue level at the protein–protein interface. Homologous partners of the complexes were superimposed using Multiprot, and similar atoms at the interface were quantified using a five class grouping scheme and a distance cut-off. We found that the number of interfacial atoms with similar properties is systematically lower in the non-homologous proteins than in the homologous ones. We assessed the significance of the similarity by bootstrapping the atomic properties at the interfaces. We found that the similarity of binding sites is very significant between homologous proteins, as expected, but generally insignificant between the non-homologous proteins that bind to homologous partners. Furthermore, evolutionarily conserved residues are not colocalized within the binding sites of non-homologous proteins. We could only identify a limited number of cases of structural mimicry at the interface, suggesting that this property is less generic than previously thought. Our results support the hypothesis that different proteins can interact with similar partners using alternate strategies, but do not support convergent evolution