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Michael Levitt

Researcher at Stanford University

Publications -  422
Citations -  43139

Michael Levitt is an academic researcher from Stanford University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 99, co-authored 349 publications receiving 41423 citations. Previous affiliations of Michael Levitt include Laboratory of Molecular Biology & Bar-Ilan University.

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Super-resolution biomolecular crystallography with low-resolution data

TL;DR: This work introduces a method that adds specific information from known homologous structures but allows global and local deformations of these homology models, and gives significant improvements over conventional refinement in the model as monitored by coordinate accuracy, the definition of secondary structure and the quality of electron density maps.
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Use of pulmonary hydrogen (H 2 ) measurements to quantitate carbohydrate absorption: Study of partially gastrectomized patients

TL;DR: A technique was developed to quantitate the absorption of ingested carbohydrate by means of continuous measurements of pulmonary H(2) excretion, which appears to provide quantitative information on carbohydrate malabsorption not readily obtained by presently available techniques.
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The Volume of Atoms on the Protein Surface: Calculated from Simulation, using Voronoi Polyhedra

TL;DR: The volume of atoms on the protein surface during a molecular-dynamics simulation of a small protein (pancreatic trypsin inhibitor) is analyzed using a particular geometric construction, called Voronoi polyhedra, that divides the total volume of the simulation box amongst the atoms, rendering them relatively larger or smaller depending on how tightly they are packed.
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Stabilization of phage T4 lysozyme by engineered disulfide bonds

TL;DR: The results suggest that stabilization due to the effect of the crosslink on the entropy of the unfolded polypeptide is offset by the strain energy associated with formation of the disulfide bond in the folded protein.
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Comprehensive assessment of automatic structural alignment against a manual standard, the scop classification of proteins

TL;DR: A simple method for aligning protein sequences on the basis of a 3D structure, on a large scale, to the proteins in the scop classification of fold families is applied, with good agreement and detailed comparison highlights how particular protein structural features are problematical to align.