A hydrophobic platform as a mechanistically relevant transition state stabilising factor appears to be present in the active centre of all glycoside hydrolases

AbstractAn in silico survey of the −1 subsite of all known 3D-structures of O-glycoside hydrolases containing a suitably positioned ligand has led to the recognition – apparently without exceptions – of a transition state stabilising hydrophobic platform which is complementary to a crucial hydrophobic patch of the ligand. This platform is family-specific and highly conserved. A comprehensive list is given with examples of enzymes belonging to 33 different families. Several typical constellations of platform – protein residues are described

Extending the functionalities of shear-driven chromatography nano-channels using high aspect ratio etching

An new injection system is presented for shear-driven chromatography. The device has been fabricated by high aspect ratio etching of silicon. The performance of the injection slit is studied through the aid of computational fluid dynamics, and the first experimental results are presented

Finite element analysis enhanced with subdivision surface boundary representations

In this work we develop a design-through-analysis methodology by extending the concept of the NURBS-enhanced finite element method (NEFEM) to volumes bounded by Catmull-Clark subdivision surfaces. The representation of the boundary as a single watertight manifold facilitates the generation of an external curved triangular mesh, which is subsequently used to generate the interior volumetric mesh. Following the NEFEM framework, the basis functions are defined in the physical space and the numerical integration is realized with a special mapping which takes into account the exact definition of the boundary. Furthermore, an appropriate quadrature strategy is proposed to deal with the integration of elements adjacent to extraordinary vertices (EVs). Both theoretical and practical aspects of the implementation are discussed and are supported with numerical examples.</p

An Exact Algorithm for Side-Chain Placement in Protein Design

Computational protein design aims at constructing novel or improved functions on the structure of a given protein backbone and has important applications in the pharmaceutical and biotechnical industry. The underlying combinatorial side-chain placement problem consists of choosing a side-chain placement for each residue position such that the resulting overall energy is minimum. The choice of the side-chain then also determines the amino acid for this position. Many algorithms for this NP-hard problem have been proposed in the context of homology modeling, which, however, reach their limits when faced with large protein design instances. In this paper, we propose a new exact method for the side-chain placement problem that works well even for large instance sizes as they appear in protein design. Our main contribution is a dedicated branch-and-bound algorithm that combines tight upper and lower bounds resulting from a novel Lagrangian relaxation approach for side-chain placement. Our experimental results show that our method outperforms alternative state-of-the art exact approaches and makes it possible to optimally solve large protein design instances routinely

Micro-scale finite element simulation of the viscoelastic damping in unidirectional fiber reinforced composites

A micro-scale finite element method is proposed to study the damping behavior of composite materials. The study focuses on the unidirectional fiber reinforced composites including viscoelastic constituents. The proposed method is demonstrated with the simulations performed on periodic Representative Volume Elements (RVEs) composed of idealistic square packed glass fibers in an epoxy polymer. The boundary problem is solved for a cyclic loading and thereby the different loss factors are computed through the homogenized stress and strain values. The results are compared to the strain energy method which is often used in the damping study of micro-scale composites. Finally, influence of fibers distribution and fiber volume fraction on the damping behavior of a unidirectional fiber reinforced composite is investigated

VITO combineert sensorplatformen met aardobservatie voor een betere monitoring van water

De huidige systemen om de toestand van het water op te volgen, voldoen vaak niet aan de noden van waterbeheerders, baggeraars, waterbedrijven, havenbeheerders, enzovoort. De data schieten tekort in kwaliteit en kwantiteit. Daarom ontwikkelt VITO een monitoringssysteem dat geautomatiseerde sensoren op onbemande vaartuigen combineert met aardobservatie: SAVEWATER. Ook het beschikbaar stellen van de data maakt deel uit van dit systeem. Het project wordt samen met de Europese ruimtevaartorganisatie ESA uitgewerkt

Automatic and Sampling-Free Parametric Model Order Reduction of Vibro-Acoustic Systems

Recently, a novel parametric model order reduction formulation has been derived for vibroacoustic systems that allows for the reduction of systems with low-rank parametric changes [1]. This scheme does not require sampling of the parameter space, in contrast to conventional parametric model reduction techniques. This means that a single reduction basis, obtained with conventional non-parametric model order reduction schemes, can be used for a wide range of parameter values. This is done by rewriting the system in a non-parametric form, in which the low-rank contributions act as inputs. A disadvantage of this scheme is that the size of the input matrix scales with the amount of chosen parameters, leading to a potentially large reduced basis when many parameters are considered. Therefore, in [2] an automatic Krylov reduction scheme has been proposed that utilizes the similarity in the reduced bases for inputs which are spaced closely together to still get a small reduced basis with a large number of inputs. This is done by using a combination of block second order Arnoldi with a singular value decomposition acting on the resulting basis. The algorithm includes an error estimator that uses a complementary approximation to calculate the error. The main advantages of this algorithm as compared to the commonly used iterative rational Krylov approach [3] are that only a small amount of system inversions are required and that the final reduced order model has the desired predefined relative error in the specified frequency band. In this paper the automatic Krylov reduction scheme and low-rank parametric model order reduction approach are combined and a suitable error estimator is derived, to arrive at compact but accurate parametric reduced order models. The effectiveness is shown with several examples