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Christian Mumenthaler

Researcher at ETH Zurich

Publications -  9
Citations -  3214

Christian Mumenthaler is an academic researcher from ETH Zurich. The author has contributed to research in topics: Globular protein & Prejudice (legal term). The author has an hindex of 7, co-authored 7 publications receiving 3149 citations.

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Torsion angle dynamics for nmr structure calculation with the new program dyana

TL;DR: Test calculations starting from conformers with random torsion angle values showed that DYANA is capable of efficient calculation of high-quality protein structures with up to 400 amino acid residues, and of nucleic acid structures.
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Automated combined assignment of NOESY spectra and three-dimensional protein structure determination

TL;DR: Systematic comparisons of the bundles of conformers that represent corresponding automatically and interactively determined structures document the absence of significant bias in either approach, indicating that an important step has been made towards automation of structure determination from NMR spectra.
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Structure comparison of human glioma pathogenesis-related protein GliPR and the plant pathogenesis-related protein P14a indicates a functional link between the human immune system and a plant defense system

TL;DR: A common partially solvent-exposed spatial cluster of four amino acid residues is identified that is conserved in all known plant PR proteins of class 1, indicating a common putative active site for GliPR and PR-1 proteins and thus a functional link between the human immune system and a plant defense system.
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Mapping of the primary binding site of measles virus to its receptor cd46

TL;DR: The measles virus (MV) hemagglutinin binds to the complement control protein (CCP) CD46 primarily through the two external modules, CCP-I and -II, and amino acids essential for binding of antibodies weakly or moderately competing with sH attachment are situated in the membrane-distal tip of CCP- I.
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Predicting the helix packing of globular proteins by self-correcting distance geometry.

TL;DR: A new self‐correcting distance geometry method for predicting the three‐dimensional structure of small globular proteins was assessed with a test set of 8 helical proteins, with the knowledge of the amino acid sequence and the helical segments.