Search results for "RECOGNITION"

Formation of protein multilayers and their competitive replacement based on self-assembled biotinylated phospholipids.

1994

Based on specific recognition processes the build-up of protein multilayers was achieved using streptavidin layers as a docking matrix. For this purpose, streptavidin was organized at biotin-containing monolayers, liposomes, and self-assembled layers on gold. Thus, mixed double and triple layers of streptavidin, Con A, Fab fragments, and hormones were prepared and characterized by fluorescence microscopy and plasmon spectroscopy. Using biotin analogues with lower binding constants several cycles of multilayer formation followed by competitive replacement could be achieved.

Surface functionalization and surface recognition: Plasmon optical detection of molecular recognition at self assembled monolayers

1991

The synthesis of biotin- functionalized organic mercaptans and their chemisorption on gold surfaces is described. Biotin bound covalently to self assembled monolayers is recognized by streptavidin from aqueous buffer solutions. Spacer length and packing density of the biotin labels on the organic surface determine the docking kinetics. With a flexible and hydrophilic spacer very fast -diffusion controlled-docking is observed. As an alternative method of self assembly the spreading of organic mercaptans on water surfaces is established. Pressure-area diagrams of different functionalized mercaptans and disulfides are shown and their monolayer properties are discussed.

Molecular recognition in biotin-streptavidin systems and analogues at the air-water interface

1992

Abstract Specific interaction between biotin and the protein streptavidin in monolayers of synthetic lipids with biotin headgroups has been shown to lead to formation of highly ordered two-dimensional streptavidin crystals. The same behaviour is observed when using desthiobiotin as lipid headgroup which exhibits a significantly lower binding constant compared with biotin (5 × 10 13 M -1 compared with 10 15 M -1 ). This offers the possibility of detaching competetively the 2D crystalline streptavidin layer by addition of free biotin to the aqueous phase. Use of lipoic acid as lipid headgroup ( K a = 7 × 10 7 M −1 ) leads to formation of small snisotropic protein domains indicating a crystall…

Molecular Recognition of Biotinyl Hydrophobic Helical Peptides with Streptavidin at the Air/Water Interface

1994

Functionalized lipid tubules as tools for helical crystallization of proteins

1997

The development of functional supramolecular devices built by self-assembly of elementary molecules and with bioactive properties arouses considerable interest in the field of nanotechnology and new materials. We report here the formation of a new class of lipid tubules exhibiting both properties of molecular recognition and crystal formation for the protein streptavidin. These lipid tubules, made of biotin-containing dioctadecylamine molecules, are straight hollow cylinders with a constant diameter of 27 nm and variable length up to several micrometers. They are unilamellar with an inner diameter of about 16 nm, as shown by cryoelectron microscopy. Streptavidin binds to the biotinylated tu…

A convolutional neural network for virtual screening of molecular fingerprints

2019

In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…

"Towards a "fingerprint" of paper network; separating forgeries from genuine by the properties of fibre structure"

2014

A novel method is introduced for distinguishing counterfeit banknotes from genuine samples. The method is based on analyzing differences in the networks of paper fibers. The main tool is a curvelet-based algorithm for measuring the distribution of overall fiber orientation and quantifying its anisotropy. The use of a couple or more appropriate parameters makes it possible to distinguish forgeries from genuine samples as concentrated point clouds in a two- or three-dimensional parameter space. Furthermore, the techniques of making watermarks is investigated by comparing genuine and counterfeit €50 banknotes. In addition, the so-called wire markings are shown to differ significantly from each…

The Neural Basis of Idea Density During Natural Spoken Language

2019

Idea density (ID) evolved as a quantification of propositional base structure. Besides its function as a measure of linguistic complexity, ID has also been used as an index of general linguistic ability. In order to find the neural basis for the processing of high or low ID during spontaneous speech, a sample of healthy adults was assessed using the functional resonance imaging (fMRI) technique; participants described pictures presented to them while in the scanner. Differential patterns of activation were observed for the low- and high-ID conditions, providing new insights into the processing correlates of ID.

Explorations of familiarity produced by words with specific combinations of letters

2010

We explore familiarity-based recognition using a paradigm devised by Parkin et al. (2001). The task consists of the creation of two lists of words written with one of two different subsets of letters of the alphabet. We manipulated study time (50, 100, 200, 500 ms per word) of words with different letter probabilistic structure to those originally used by Parkin et al. Letter-based familiarity responding was robust and present even at rates producing otherwise chance performance. A second experi- ment and structural equation modelling led us to interpret the results from the point of view of a theory that takes into account the processing of similarities and differences (Hunt & MacDaniel, (…

Preventing Overlaps in Agglomerative Hierarchical Conceptual Clustering

2020

Hierarchical Clustering is an unsupervised learning task, whi-ch seeks to build a set of clusters ordered by the inclusion relation. It is usually assumed that the result is a tree-like structure with no overlapping clusters, i.e., where clusters are either disjoint or nested. In Hierarchical Conceptual Clustering (HCC), each cluster is provided with a conceptual description which belongs to a predefined set called the pattern language. Depending on the application domain, the elements in the pattern language can be of different nature: logical formulas, graphs, tests on the attributes, etc. In this paper, we tackle the issue of overlapping concepts in the agglomerative approach of HCC. We …