24 research outputs found
ProteinsPlus: a web portal for structure analysis of macromolecules
With currently more than 126 000 publicly available structures and an
increasing growth rate, the Protein Data Bank constitutes a rich data source
for structure-driven research in fields like drug discovery, crop science and
biotechnology in general. Typical workflows in these areas involve manifold
computational tools for the analysis and prediction of molecular functions.
Here, we present the ProteinsPlus web server that offers a unified easy-to-use
interface to a broad range of tools for the early phase of structure-based
molecular modeling. This includes solutions for commonly required pre-
processing tasks like structure quality assessment (EDIA), hydrogen placement
(Protoss) and the search for alternative conformations (SIENA). Beyond that,
it also addresses frequent problems as the generation of 2D-interaction
diagrams (PoseView), protein–protein interface classification (HyPPI) as well
as automatic pocket detection and druggablity assessment (DoGSiteScorer). The
unified ProteinsPlus interface covering all featured approaches provides
various facilities for intuitive input and result visualization, case-specific
parameterization and download options for further processing. Moreover, its
generalized workflow allows the user a quick familiarization with the
different tools. ProteinsPlus also stores the calculated results temporarily
for future request and thus facilitates convenient result communication and
re-access. The server is freely available at http://proteins.plus
Fosmidomycin Uptake into Plasmodium and Babesia-Infected Erythrocytes Is Facilitated by Parasite-Induced New Permeability Pathways
., a mouse malaria parasite. and related parasites. Our data provide further evidence that parasite-induced new permeability pathways may be exploited as routes for drug delivery
ASCONA: Rapid Detection and Alignment of Protein Binding Site Conformations
The
usage of conformational ensembles constitutes a widespread
technique for the consideration of protein flexibility in computational
biology. When experimental structures are applied for this purpose,
alignment techniques are usually required in dealing with structural
deviations and annotation inconsistencies. Moreover, many application
scenarios focus on protein ligand binding sites. Here, we introduce
our new alignment algorithm ASCONA that has been specially geared
to the problem of aligning multiple conformations of sequentially
similar binding sites. Intense efforts have been directed to an accurate
detection of highly flexible backbone deviations, multiple binding
site matches within a single structure, and a reliable, but at the
same time highly efficient, search algorithm. In contrast, most available
alignment methods rather target other issues, e.g., the global alignment
of distantly related proteins that share structurally conserved regions.
For conformational ensembles, this might not only result in an overhead
of computation time but could also affect the achieved accuracy, especially
for more complicated cases as highly flexible proteins. ASCONA was
evaluated on a test set containing 1107 structures of 65 diverse proteins.
In all cases, ASCONA was able to correctly align the binding site
at an average alignment computation time of 4 ms per target. Furthermore,
no false positive matches were observed when searching the same query
sites in the structures of other proteins. ASCONA proved to cope with
highly deviating backbone structures and to tolerate structural gaps
and moderate mutation rates. ASCONA is available free of charge for
academic use at http://www.zbh.uni-hamburg.de/ascona
SIENA: Efficient Compilation of Selective Protein Binding Site Ensembles
Structural
flexibility of proteins has an important influence on
molecular recognition and enzymatic function. In modeling, structure
ensembles are therefore often applied as a valuable source of alternative
protein conformations. However, their usage is often complicated by
structural artifacts and inconsistent data annotation. Here, we present
SIENA, a new computational approach for the automated assembly and
preprocessing of protein binding site ensembles. Starting with an
arbitrarily defined binding site in a single protein structure, SIENA
searches for alternative conformations of the same or sequentially
closely related binding sites. The method is based on an indexed database
for identifying perfect <i>k</i>-mer matches and a recently
published algorithm for the alignment of protein binding site conformations.
Furthermore, SIENA provides a new algorithm for the interaction-based
selection of binding site conformations which aims at covering all
known ligand-binding geometries. Various experiments highlight that
SIENA is able to generate comprehensive and well selected binding
site ensembles improving the compatibility to both known and unconsidered
ligand molecules. Starting with the whole PDB as data source, the
computation time of the whole ensemble generation takes only a few
seconds. SIENA is available via a Web service at www.zbh.uni-hamburg.de/siena
Chemical activation of a high-affinity glutamate transporter in human erythrocytes and its implications for malaria-parasite-induced glutamate uptake
Human erythrocytes have a low basal permeability to L-glutamate and are not known to have a functional glutamate transporter. Here, treatment of human erythrocytes with arsenite was shown to induce the uptake of L-glutamate and D-aspartate, but not that of D-glutamate or L-alanine. The majority of the arsenite-induced L-glutamate influx was via a high-affinity, Na+-dependent system showing characteristics of members of the "excitatory amino acid transporter" (EAAT) family. Western blots and immunofluorescence assays revealed the presence of a member of this family, EAAT3, on the erythrocyte membrane. Erythrocytes infected with the malaria parasite Plasmodium falciparum take up glutamate from the extracellular environment. Although the majority of uptake is via a low-affinity Na+-independent pathway there is, in addition, a high-affinity uptake component, raising the possibility that the parasite activates the host cell glutamate transporter
Discriminative Chemical Patterns: Automatic and Interactive Design
The
classification of molecules with respect to their inhibiting,
activating, or toxicological potential constitutes a central aspect
in the field of cheminformatics. Often, a discriminative feature is
needed to distinguish two different molecule sets. Besides physicochemical
properties, substructures and chemical patterns belong to the descriptors
most frequently applied for this purpose. As a commonly used example
of this descriptor class, SMARTS strings represent a powerful concept
for the representation and processing of abstract chemical patterns.
While their usage facilitates a convenient way to apply previously
derived classification rules on new molecule sets, the manual generation
of useful SMARTS patterns remains a complex and time-consuming process.
Here, we introduce SMARTSminer, a new algorithm for the automatic
derivation of discriminative SMARTS patterns from preclassified molecule
sets. Based on a specially adapted subgraph mining algorithm, SMARTSminer
identifies structural features that are frequent in only one of the
given molecule classes. In comparison to elemental substructures,
it also supports the consideration of general and specific SMARTS
features. Furthermore, SMARTSminer is integrated into an interactive
pattern editor named SMARTSeditor. This allows for an intuitive visualization
on the basis of the SMARTSviewer concept as well as interactive adaption
and further improvement of the generated patterns. Additionally, a
new molecular matching feature provides an immediate feedback on a
pattern’s matching behavior across the molecule sets. We demonstrate
the utility of the SMARTSminer functionality and its integration into
the SMARTSeditor software in several different classification scenarios
Index-Based Searching of Interaction Patterns in Large Collections of Protein–Ligand Interfaces
Comparison of three-dimensional
interaction patterns in large collections
of protein–ligand interfaces is a key element for understanding
protein–ligand interactions and supports various steps in the
structure-based drug design process. Different methods exist that
provide query systems to search for geometrical patterns in protein–ligand
complexes. However, these tools do not meet all of the requirements,
which are high query variability, an adjustable search set, and high
retrieval speed. Here we present a new tool named PELIKAN that is
able to search for a variety of geometrical queries in large protein
structure collections in a reasonably short time. The data are stored
in an SQLite database that can easily be constructed from any set
of protein–ligand complexes. We present different test queries
demonstrating the performance of the PELIKAN approach. Furthermore,
two application scenarios show the usefulness of PELIKAN in structure-based
design endeavors