540 Chemie und zugeordnete Wissenschaften
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Recent experimental evidence suggest that mebendazole, a popular antiparasitic drug, binds to heat shock protein 90 (Hsp90) and inhibit acute myeloid leukemia cell growth. In this study we use quantum mechanics (QM), molecular similarity and molecular dynamics (MD) calculations to predict possible binding poses of mebendazole to the adenosine triphosphate (ATP) binding site of Hsp90. Extensive conformational searches and minimization of the five tautomers of mebendazole using MP2/aug-cc-pVTZ theory level resulting in 152 minima being identified. Mebendazole-Hsp90 complex models were created using the QM optimized conformations and protein coordinates obtained from experimental crystal structures that were chosen through similarity calculations. Nine different poses were identified from a total of 600 ns of explicit solvent, all-atom MD simulations using two different force fields. All simulations support the hypothesis that mebendazole is able to bind to the ATP binding site of Hsp90.
In an effort to assist researchers in choosing basis sets for quantum mechanical modeling of molecules (i.e. balancing calculation cost versus desired accuracy), we present a systematic study on the accuracy of computed conformational relative energies and their geometries in comparison to MP2/CBS and MP2/AV5Z data, respectively. In order to do so, we introduce a new nomenclature to unambiguously indicate how a CBS extrapolation was computed. Nineteen minima and transition states of buta-1,3-diene, propan-2-ol and the water dimer were optimized using forty-five different basis sets. Specifically, this includes one Pople (i.e. 6-31G(d)), eight Dunning (i.e. VXZ and AVXZ, X=2-5), twenty-five Jensen (i.e. pc-n, pcseg-n, aug-pcseg-n, pcSseg-n and aug-pcSseg-n, n=0-4) and nine Karlsruhe (e.g. def2-SV(P), def2-QZVPPD) basis sets. The molecules were chosen to represent both common and electronically diverse molecular systems. In comparison to MP2/CBS relative energies computed using the largest Jensen basis sets (i.e. n=2,3,4), the use of smaller sizes (n=0,1,2 and n=1,2,3) provides results that are within 0.11--0.24 and 0.09-0.16 kcal/mol. To practically guide researchers in their basis set choice, an equation is introduced that ranks basis sets based on a user-defined balance between their accuracy and calculation cost. Furthermore, we explain why the aug-pcseg-2, def2-TZVPPD and def2-TZVP basis sets are very suitable choices to balance speed and accuracy.
The application of Raman and infrared (IR) microspectroscopy is leading to hyperspectral data containing complementary information concerning the molecular composition of a sample. The classification of hyperspectral data from the individual spectroscopic approaches is already state-of-the-art in several fields of research. However, more complex structured samples and difficult measuring conditions might affect the accuracy of classification results negatively and could make a successful classification of the sample components challenging. This contribution presents a comprehensive comparison in supervised pixel classification of hyperspectral microscopic images, proving that a combined approach of Raman and IR microspectroscopy has a high potential to improve classification rates by a meaningful extension of the feature space. It shows that the complementary information in spatially co-registered hyperspectral images of polymer samples can be accessed using different feature extraction methods and, once fused on the feature-level, is in general more accurately classifiable in a pattern recognition task than the corresponding classification results for data derived from the individual spectroscopic approaches.
The elucidation of conformations and relative potential energies (rPEs) of small molecules has a long history across a diverse range of fields. Periodically, it is helpful to revisit what conformations have been investigated and to provide a consistent theoretical framework for which clear comparisons can be made. In this paper, we compute the minima, first- and second-order saddle points, and torsion-coupled surfaces for methanol, ethanol, propan-2-ol, and propanol using consistent high-level MP2 and CCSD(T) methods. While for certain molecules more rigorous methods were employed, the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pV5Z theory level was used throughout to provide relative energies of all minima and first-order saddle points. The rPE surfaces were uniformly computed at the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ level. To the best of our knowledge, this represents the most extensive study for alcohols of this kind, revealing some new aspects. Especially for propanol, we report several new conformations that were previously not investigated. Moreover, two metrics are included in our analysis that quantify how the selected surfaces are similar to one another and hence improve our understanding of the relationship between these alcohols.
Human butyrylcholinesterase (BChE) is a glycoprotein capable of bioscavenging toxic compounds such as organophosphorus (OP) nerve agents. For commercial production of BChE, it is practical to synthesize BChE in non-human expression systems, such as plants or animals. However, the glycosylation profile in these systems is significantly different from the human glycosylation profile, which could result in changes in BChE's structure and function. From our investigation, we found that the glycan attached to ASN241 is both structurally and functionally important due to its close proximity to the BChE tetramerization domain and the active site gorge. To investigate the effects of populating glycosylation site ASN241, monomeric human BChE glycoforms were simulated with and without site ASN241 glycosylated. Our simulations indicate that the structure and function of human BChE are significantly affected by the absence of glycan 241.
In der vorliegenden Arbeit wurde ein Verfahren zur Analyse von Molekülen auf Grundlage ihrer molekularen Oberfläche und lokalen Werte für physiko-chemische und topografische Eigenschaften entwickelt. Der als Kernkomponente der Analyse entwickelte Fuzzy-Controller kombiniert molekulare Eigenschaften und selektiert die für Wechselwirkungen relevanten Merkmale auf der Oberfläche. Die Ergebnisse des Fuzzy-Controllers werden für die Berechnung von 3D-Deskriptoren und für die Visualisierung der ermittelten Domänen auf der Oberfläche herangezogen. Es werden zwei Arten von Deskriptoren berechnet. Deskriptoren, welche Flächeninhalte und Zugehörigkeiten zu den spezifizierten Bindungsmerkmalen der Domänen darstellen, und Deskriptoren, welche die räumliche Anordnung der Domänen zueinander beschreiben. Die vom Fuzzy-Controller überarbeitete Oberfläche wird im VRML-Format zur Visualisierung und weiteren Bearbeitung zur Verfügung gestellt. Die berechneten Deskriptoren werden zur Ähnlichkeitsanalyse von Liganden und zur Suche von komplementären Bereichen an der Bindungsstelle einesRezeptors eingesetzt. MTX in protonierter Form und DHF, die an das Enzym DHF-Reduktase binden, und die Inhibitoren Sildenafil, Tadalafil und Vardenafil des Enzyms PDE-5A wurden unter Ähnlichkeitsaspekten analysiert. Bei der Bestimmung von komplementären Bindungsmerkmalen wird ausgehend von den Bindungsmerkmalen eines Liganden nach komplementären Bereichen in der Bindungstasche des Rezeptors gesucht. Als Anwendungsbeispiele werden die Bindungsstelle des Enzyms DHF-Reduktase aus den Komplexen mit MTX und DHF und des Enzyms PDE-5A aus den Komplexen mit Sildenafil, Vardenafil und Tadalafil betrachtet. Insgesamt haben die Anwendungsbeispiele gezeigt, dass der vorgestellte Fuzzy-Controller Bindungsmerkmale auf der molekularen Oberfläche identifiziert unddie darauf basierenden, rotations- und translationsinvarianten Deskriptoren zur Ähnlichkeitsanalyse und zur Suche von komplementären Bereichen angewendet werden können.